Sage Journals: Discover world-class research

Abstract

The urgency for China to attain carbon neutrality has driven the world’s largest carbon-emitting nation to seek more effective climate and energy policies. The adoption of smart grid (SG) technologies, aimed at enabling and accelerating the shift from fossil fuel-dependent energy systems to more sustainable ones, has garnered mounting policy interest in China. However, the full potential of SG development has yet to be realised amidst the ongoing electricity market reforms in the country. A key but largely unanswered question pertains to how and the extent to which the evolving dynamics between the government and the market have influenced SG advancements. This paper aims to develop and apply an integrated framework of policy mixes and functional dynamics for smart energy transitions, and apply it to reanalyse a case study of SG policy developments in China. Our study entails a synthesis of primary research findings, shedding light on how electricity market reforms create institutional contexts within which new government-market dynamics emerge and condition the progress of SGs in China. Our study reveals that the Chinese government has adopted a controlled dynamic approach to modulate the relationships between the government and the market within the power sector. This approach has both facilitated the creation of an enabling policy environment and imposed certain barriers to SG developments. The dominance of state-owned incumbents have on the one hand created state-driven market demand, reduction in technology costs and the influence of utility-led policy networks, but on the other hand, placing constraints on the growth of SG technologies. Our policy recommendations: China needs to formulate and implement SG policies which can effectively overcome key barriers which include under-developed regulatory frameworks, utilities’ disincentives to invest in renewable energy, and insufficiency in end-user engagements.

Keywords

SGs government-market dynamics policy mixes energy transitions China

Introduction

Around the world, the growing urgency to achieve ambitious mid-century net-zero targets has led to increased policy focus on the importance of smart grid (SG) technologies. The widespread adoption of smart technologies, coupled with the utilisation of big data analytics, is playing an increasingly pivotal role in tackling some of the most pressing urban socio-environmental challenges. Specifically, the transformation of electricity systems is underway, driven by the integration of smart technologies. Leveraging sophisticated artificial intelligence and cloud technology, SG technologies encompass a broad spectrum of energy technologies. SG can facilitate the incorporation of renewable energy sources, enhance energy efficiency, introduce innovative price-based demand response programmes, improve control and automation, and elevate overall reliability of energy system (Levenda, 2020). SGs have therefore be regarded as an enabling technology of both supply-side and demand-side energy solutions (Hamidi et al., 2010; Parvin et al., 2022).

Worldwide, national and city governments have increasingly recognised that demand reduction is an important climate mitigation strategy to complement supply-side approaches, and SG is an enabling technology which can support the integration of supply-side and demand-side energy solutions. SG policies are thus not only to produce renewable energy but to tackle peak electricity demand and increasing the on-site self-consumption of electricity generated (Hossain et al., 2016; Tuballa and Abundo, 2016). Given the integral nature of SG technologies, this study focuses on the deployment of renewable energy and smart meter-enabled energy saving initiatives, to represent key supply-side and demand-side energy solutions respectively.

In recent years, many countries have elevated SG deployment to a major national economic and energy strategy. The US government launched “Building a Better Grid” initiative in 2022, which aims to upgrade power grids to achieve 100 percent clean energy. In the US, there were over 111 million advanced meters installed in 2021 (Statista, 2023b). In Europe, SG projects are identified as Projects of Common Interest (PCI) in European Union, and member states have committed to rolling out close to 200 million smart meters by 2020 (EC, 2023). In Asia, Japan and South Korea have also launched major SG initiatives (Mah, 2020; Mah et al., 2012).

In the global context of SG developments, China, as the world’s largest energy consumer and greenhouse gas emitter, has strong motivations to develop SGs. In 2020, President Xi Jinping announced the ambitious goal of achieving carbon peaking by 2030 and carbon neutrality by 2060 (CPCnews, 2020). The 14th Five-Year Plan on Modern Energy System published by the National Development and Reform Commission in 2022 have already included SGs as key components of the national energy plan (NDRC, 2022).

In recent years, China has made important progress in SGs. In 2020, the SG industry in China reached nearly 80 billion yuan in market value (Statista, 2023a), with the State Grid Corporation of China (SGCC) ranking 26th among 94 utilities across 39 countries/markets accordingly to a SG benchmarking index (SP Group, 2022). However, there exist three notable knowledge gaps. First, there has been limited progress in reducing electricity consumption and mainstreaming renewable energy, suggesting we have a limited understanding of SG policy effectiveness. Second, despite mounting interest in SG policies, there are few studies that provide insights with their implementation both theoretically and empirically. Third, amid ongoing electricity market reforms, the intricate dynamics between the government and the market, and their subsequent impacts on SG developments in China, have remained under-studied. There is a lack of an integrated framework that can capture and offer a good understanding of the complex interactions between the government and market.

This paper therefore aims to fill these knowledge gaps by bridging two major analytical perspectives related to the topic in question: The first is the policy mix perspective which sheds important lights on different types of policy instruments and their synergistic interactions at various administrative levels (from multi-national to national and to city and local levels), across different temporal scales and with different policy stakeholders (Rosenow et al., 2017). Another perspective is the functional dynamics of energy transitions which focuses on the essential functions of transitions processes that directly determine the development and diffusion of new energy technologies, including SGs (Bergek et al., 2008; Jacobsson and Bergek, 2011). We attempt to answer research questions as follows:

(1) To what extent have ongoing electricity market reforms in China affected the realisation of the full potential of SG development?

(2) What are the specific government-market dynamics that have emerged within the power sector in China regarding SG advancements, and how have these dynamics influenced the progress of SG technologies?

(3) What policy recommendations can be formulated to address the barriers hindering the growth of SG technologies in China?

The research is a case study of China. China presents a good case to examine government-market relationships. It is a country that has been going through an on-going electricity market reforms since 1980s. It thus allows us to examine the dynamics between the government and market, and policy issues associated with the developments of SGs. Empirical research on energy transitions in China can provide important reflection on existing theoretical perspectives on energy transitions which mostly originated in the West. Our research in China has also policy implications because our analysis can inform the further optimisation of the use of different policy instruments to foster SG developments. Policy learning can go beyond China to other major economies.

This paper proceeds as follows. We begin by discussing an integrated conceptual framework which draws together different perspectives on policy mixes and functional dynamics perspectives on energy transitions. Our integrated framework is then applied to examine the emerging government-market dynamics and the associated impacts on SG developments in China. We conclude by providing policy recommendations of which the Chinese policymakers may adopt in order to foster the further digitalisation of the power system.

Theoretical background

A growing body of the energy transitions literature shed lights on the critical roles of policy interventions in fostering technological innovation and multi-actor engagement in energy transitions processes (Li and Taeihagh, 2020; Lindberg et al., 2019; Long et al., 2022; Rind et al., 2023; Song et al., 2023). This study draws linkages between two major theoretical perspectives: the policy mix theory and the function dynamics perspectives, in order to offer a better understanding of how government-market relationships affect the formulation and implementation of SG policies in China.

SG policies from a policy mix perspectives

The policy mix literature from the established disciplines of public policies contributes to our understanding of SG policies from at least three important aspects, including policy contexts, types of policy instruments, and forms of policy mixes.

One theme of the policy mix literature focuses on the importance of policy context to the holistic instrument mixes for energy transitions. Studies, most notably by (Rosenow et al., 2017), considers that the wider policy context is essential for the need for comprehensive and well targeted instrument mixes to scale up energy transitions (Rosenow et al., 2017). Rosenow introduced two concepts, technological specificity and sector specificity, which distinguish two critical dimensions of low-carbon technology-related policy contexts. The concept of technological specificity emphasises that policies need to be responsive to the massive complexity of new SG technology (e.g., microgrid, energy storage, smart meter) and the massive technological costs associated with new low-carbon technologies. The concept of sector specificity, on the other hand, argues that energy transitions involve engagement with diversity of sectors, such as institution sector, industry sector and residential sector.

Another theme of the policy mix literature makes important distinction of four main types of policy instruments: command-and-control instruments, economic instruments, market-based instruments, and voluntary instruments. Empirical studies on SGs show that all these four types of policy instruments have been deployed to foster the development of SGs. In terms of command-and-control measures , rules and regulations such as renewable portfolio standards (RPS) which mandates electricity suppliers to supply an agreed portion of production from renewable energy sources is a good example. In terms of economic measures , feed-in tariff (FiT) policies is a commonly adopted policy around the world. FiT policies are commonly regarded as an effective policy that uses economic incentives to encourage the adoption of renewable energy technologies (Ndiritu and Engola, 2020). In terms of market-based policy instruments , Renewable Energy Certificates (RECs) is most often used as a market-based instrument in SG. It helps with promoting renewable energy by trading and providing marketable value on the production of renewable energy (Gao et al., 2021). Voluntary instruments (e.g., information disclosure) can provide consumers with more choices and information to force utilities to adhere social standards (Matisoff, 2013).

The third theme of the policy mix literature distinguishes five forms of policy mixes that have relevance to SG developments as outlined as follows: (i) Policy instrument mixes : emphases the interaction of different type of policy instruments (Kanger et al., 2020; Rogge and Schleich, 2018) to achieve goals of promoting technologies and investments in renewable energy sources, such as the combined utilisation of feed-in tariff policies, renewable portfolio standards and auctions (Kwon, 2020); (ii) horizontal policy mixes: single-level policy alignment horizontally (Magro and Wilson, 2019) within the same administration level (Hu et al., 2023b) across multiple sectors (e.g., technology innovation, renewable energy sources, consumer engagement); (iii) multi-level/vertical policy mixes : across different spatial scales (such as individual, neighbourhood, city, national and regional levels (Del Río, 2014; Magro and Wilson, 2019). Householders, for instance, can be engaged in all levels, from engaging in demand-side solutions to SG pilots, and to regional renewable energy trading (D’Adamo et al., 2022; Kotilainen et al., 2021).

SG policies from a functional dynamics perspectives

Moving beyond the policy mix framework which is relatively static in nature, innovation system scholars introduced the functional dynamic approach to capture and conceptualise the dynamics of a number of key processes of system transformations, in order words, the key “functions” of energy system transitions. These functions are critical to the development and diffusion of new energy technologies. These functional frameworks have been applied various sub-fields of energy transitions, including SGs. Work on functional dynamics perspectives has conceptualised five key functions which include:

(1) Market formation: Governments can spur the formation of new markets to support transformative policy of SGs (Boon et al., 2022) through developing SG development roadmaps, setting clear policy objectives, providing pricing signals, and driving down costs by exercising bulk purchasing power (Bradshaw and de Martino Jannuzzi, 2019; ECLAC, 2021; Panori et al., 2022);

(2) Market regulation: Governments can establish market rules to regulate player behavior, attract new market entrants, and create standards for scaling up deployment of smart meter, for instance, at both city and regional scale.

(3) Managing public goods: Governments need to intervene when market failure jeopardises public goods such as energy security and decarbonisation (Hall and Foxon, 2014), reliability of energy systems (Kowli et al., 2010), standardization (Mah et al., 2017), R&D activities (Dantas et al., 2018), and information sharing (Helmholt and Broenink, 2011).

(4) Networking and resource mobilisation: Governments collaborate with network to share common interests to influence policy processes and outcomes (Li et al., 2019). Key networks include policy communities, professional networks, intergovernmental networks, producer networks, and issue networks (Mah et al., 2017).

(5) Policy learning: Governments and policy stakeholders need to engage in a policymaking process in which policy-makers interact through dialogues and deliberation in order to adjust goals, rules and policy instruments of a given policy (Boon and Bakker, 2016; Hall, 1993) . This engaging approach for policy-making is required to ensure policy legitimacy that are required to support wide-scale adoption of low-carbon energy technologies (Bergek et al., 2008; Chou et al., 2015).

The government-market dynamics and electricity market reforms

In addition to research focusing on functional dynamics perspectives, another emerging theme of energy transitions studies shed lights on the crucial roles of government and market (Akrofi and Antwi, 2020; Droste et al., 2016; He et al., 2021; Zhang and Andrews-Speed, 2020). The literature suggests that, on the one hand, governments, or public interventions, are required to overcome market failure and limits of market forces (Cui and Wei, 2017; De Almeida, 1998). On the other hand, market forces are perceived as the most cost-effective way to address energy problems.

Extending from these works, a sub-theme of the functional dynamics perspectives on energy transitions focuses on institutions. Some recent studies have found that electricity market reforms are critical government interventions that redefine the environment within which governments and market actors (including both incumbents and new market players, interact and influence energy transitions processes (Gao et al., 2018; Greenacre et al., 2012). These reforms play a crucial role in reshaping market rules, structures, and the dynamics between governments and markets. As early as in the 1980s, market-oriented reforms in the electricity industry had already become a global trend as a major approach to enhance competitiveness and improve efficiency. Over recent years, policy attention on electricity market liberalisation has intensified, particularly in the context of the global development of SGs. Electricity market reforms have been regarded as essential to drive systemic changes in the power sector which are needed to realise the full potential of demand-side and renewable developments that can be enabled by SGs (Cooke, 2011). A recurring theme in this literature advocates for a shift in government functions from direct administrative measures to government regulation in increasingly market-driven power sectors (Droste et al., 2016; Wu et al., 2021). How, then, should such co-evolution of the role of government and market occurs, and the impacts on established regime actors and emerging market actors (Martiskainen et al., 2021), remained relatively unexplored.

Studies on SGs in China

Whilst a large body of the studies on SG developments in China focuses on the technological and economic aspects of these energy technologies (Yüksel et al., 2014), a rapidly growing body of governance literature on SGs argues that if China were to fully utilise the potential that SGs may offer, many technological, economical, as well as institutional and policy challenges have to be overcome (Mah, 2016; Yuan and Zhang, 2014). Some studies have characterised the Chinese SG development as an incumbent-led model (Mah, 2016; Mah et al., 2017), or grid company-led approach (Yuan and Zhang, 2014), suggesting the dominance of incumbent utilities as a regime actor in driving the deployment of SG technologies in China without a strong presence of new market actors.

However, a growing number of studies have argued that smart energy transitions being driven by SG technological developments demands a rapid and profound transformation of the electricity sector in China (IEA, 2021a). SGs are transformational because they coordinate and orchestra the needs and capabilities of all generators, grid operators, end-users, and electricity market stakeholders (for instance, aggregators, new energy suppliers) in highly digitalised and integrated energy systems (IEA, 2023). This increasingly dynamic stakeholder landscape has heightened the tensions among stakeholders. How to address governance challenges as a result of changing government-market relationships are particularly important for Chinese policy-makers.

It is in this context that the market environment of China’s power sector has been largely reshaped by the ongoing electricity market reforms, which have been introduced since 1980s. Before the reforms, traditional energy systems in China were characterised by the centralised, coal-based power systems with the presence of a vertically state-owned monopolised power industry. To date, in the wake of a series of major changes which have been introduced into the power sector, which include primarily the separation of electricity grid and power generation, the liberalisation of the power generation segment, and the introduction of dynamic pricing policies, China’s power sector looks very differently.

There are two streams of research trying to estimate the effect of government-market dynamics under electricity market reform. The first strand of literature emphasises regulatory mechanisms from the government. The second strand focuses on the important role of market, including market pricing mechanism and market efficiency. By conducting two case studies that under electricity market experimentation, Yu (2020) evaluates how government and market complementarities can effectively play the role in China’s electricity market reform, and it also indicated incomplete regulation and political resistance are the major challenges for the market participants. However, how, and the extent to which, such changing government-market relationships have facilitated or limited the developments of SGs in China are however under-studied.

Towards an integrated framework

To address the knowledge gaps, we present the integrated functional dynamic framework that examine the government-market relationship in supporting smart energy transitions (Figure 1).

Figure 1.

An integrated framework of policy mix and functional dynamics for smart energy transitions.

We adapted the integrated framework by (Mah et al., 2021) and further developed it in SG context. Our framework suggests that the government-market relationships in supporting smart energy transitions relates to five dimensions as follows: (1) policy contexts; (2) policy instruments; (3) policy roles; (4) forms of policy mixes; and (5) functional dynamics. Each concept is coded to facilitate a more systematic analysis (pls refer to a more detailed discussion in the methodology section). Our framework suggests the following propositions:

(1) Technological and Sectorial Influence: Policy contexts of SGs are significantly shaped by two factors: the technological specificity of the SG technologies [Code A1] and the sector specificity which is shaped by electricity market reforms and related sectors such as building and industry sectors [Code A2];

(2) Government Policy Roles: Governments play four essential roles of policies, which range from setting clear policy objectives to facilitating cost reductions [Codes: C1–C4], and deploy a diverse range of policy instruments (i.e., economic instrument, market instrument, command-and-control instrument, voluntary instrument) [Codes B1–B4]. These various instruments are integrated into various forms of policy mixes to foster the transitions to smart energy systems.

(3) Functional dynamics: The interactions of the government and market in the policymaking process within the policy contexts gives rise to five critical types of functional dynamics, which include market formation, market regulation, managing public goods, networking and resource mobilisation and policy learning [Codes E1–E5). These functional dynamics collectively influence the diffusion of SG technologies and, consequently, the overall performance of the SG-related innovation system.

Methodology

This study conducts a reanalysis of an empirical case study in China and develops an integrated conceptual framework to elucidate the intricate interplay between government and market dynamics within the context of smart energy transition. It synthesises findings from prior research and employs an integrated framework to enable robust analysis of empirical data. This methodological approach can support policy-relevant research through deeper exploitation of existing data resources, and have been increasingly adopted in energy transitions studies resulting in high-impact research (see, for instance, (Vigurs et al., 2021)).

We provided a systemic review of existing SG policies, major developments of the on-going electricity market reforms, and the impacts of the government-market dynamics on the developments of SG in China. Important empirical data collected from existing literature, official policy documents, reports and news were coded according to a coding system which is guided by our integrated framework.

Specifically, we have developed a coding system which is guided by our integrated framework for analysing data which was collected from existing literature and official policy documents, reports and news. Our framework, and the associated coding system, including five dimensions, and 20 sub-codes, (as presented in Figure 1). Our codes are linked to five key conceptual components of our integrating conceptual framework.

Our analysis focuses on how government adopted different types of policy instruments and employed policy mixes in an increasingly marketised environment, and the extent to which, and how the interactions between government and market drove or constrained the developments of SGs in China.

Case context

China’s energy basic

China’s economy is coal-dependent. Being the world’s largest developing country and the second-largest economy by GDP (World Bank, 2022), China is currently the largest energy consumers and greenhouse gas emitting country. In 2021, coal-fired power generation accounted for 55% of China’s total installed capacity (NBSC, 2021) (Table 1), and coal generated 67% of the country’s electricity (China Energy Portal, 2022) (Figure 2). While coal’s share has decreased from 72% in 2011, it remains the dominant energy source. However, non-hydro renewables, including solar and wind, have grown significantly from 4% in 2011 to 27% in 2021. Nuclear power increased modestly from 1% to 2%, while hydropower decreased from 22% to 16% during this period (NBSC, 2022).

Table 1.

Energy mix of China’s power sector (in terms of installed capacity) (2011-2021).(10,000 kW).

Year	Installed Capacity of Power Generation	Thermal Power¹	%	Hydro-power	%	Nuclear Power	%	Wind Power	%	Solar Power	%	Others
2011	106253	76834	72%	23298	22%	1257	1%	4623	4%	212	0%	19
2012	114676	81968	71%	24947	22%	1257	1%	6142	5%	341	0%	20
2013	125768	87009	69%	28044	22%	1466	1%	7652	6%	1589	1%	8
2014	137887	93232	68%	30486	22%	2008	1%	9657	7%	2486	2%	19
2015	152527	100554	66%	31954	21%	2717	2%	13075	9%	4218	3%	9
2016	165051	106094	64%	33207	20%	3364	2%	14747	9%	7631	5%	7
2017	177708	110495	62%	34359	19%	3582	2%	16325	9%	12942	7%	7
2018	190012	114408	60%	35259	19%	4466	2%	18427	10%	17433	9%	20
2019	201006	118957	59%	35804	18%	4874	2%	20915	10%	20418	10%	37
2020	220204	124624	57%	37028	17%	4989	2%	28165	13%	25356	12%	41
2021	237777	129739	55%	39094	16%	5326	2%	32871	14%	30654	13%	94

Source: NBSC (2022); compiled by authors.

Thermal power comes mostly from burning coal, but also include burning oil, gas, and biomass for power generation.

Figure 2.

Electricity mix in China in 2021 (in terms of power generation (kWh)).

China’s coal-based energy system has had profound adverse effects on the economy, environment and society (Tai et al., 2020). These adverse impacts encompass climate impacts (Peng et al., 2018; Wang et al., 2021), concerns about energy security (Wang et al., 2020), cost-related issues (Zhou et al., 2022), and social instability (Shi et al., 2018). Against this national energy context that President Xi announced in 2020 a coal peaking target by 2030 and a carbon-neutral goal by 2060 (IEA, 2021a).

China’s ongoing electricity market reforms: five stages and the associated government-market relationships

As early as in the 1980s, market-oriented reforms in the electricity industry had already become a global trend as a major approach to enhancing competitiveness and improve efficiency of the power sectors (Byrne and Mun, 2003; Pollitt, 2012).

In China, electricity market reforms commenced in 1985, driven by three primary objectives: alleviating financial hardship of the power sector, attracting foreign investment, and fostering competition (Wang and Chen, 2012). Over these years, two major rounds of electricity market reforms were introduced in 2002 and 2015, significantly reshaping the power sector in terms of market structure, market players, and regulatory framework. Our review identifies five distinct phases of development within the power sector, each characterised by unique government-market dynamics, as outlined in Table 2.

Table 2.

Five stages of China’s electricity market reforms and features of government-market relationships.

Phases	Features of government-market relationships	Key features and/or major developments
Phase 1: 1949-1985	Centrally planned and administered electricity sector	• Government agencies plan, finance, manage, and operate the power system • Vertical integrated power system
Phase 2: 1985-1997	Decentralisation through opening up to market	• Opening up of the power sector to provincial government, private, and foreign investment
Phase 3: 1997-2002	Institutionalised market actors through corporatisation	• Separation of government and business • Corporatisation of the sector through the creation of the State Power Corporation (SPC) • Ministry of Electric Power was dissolved, functions transferred to the State Economic and Trade Commission and the State Development and Planning Commission, later merged into the National Development and Reform Commission
Phase 4: 2002-2014	Escalating market competition through Separation of generation from grid companies	• Dismantling of the SPC into 2 state-owned grid companies, and 5 national state-owned generating companies (the Big Five) • Creation of the State Electricity Regulatory Commission in 2003 (which was dissolved in 2013)
Phase 5: 2015-present	Extending liberalisation to retail markets	• State Council issued Document No. 9 in 2015 to initiate a new round of electricity market reforms • Through regulating the distribution and transmission, and opening up the generation and retail • Key areas of reforms: electricity pricing systems, electricity trading mechanism, and the opening up of the electricity retail market

Source: IEA (2017); Lin et al. (2019); Mah (2018); Mah et al. (2017); Zhang et al. (2018).

Phase 1 , prior to 1985, witnessed the power sector functioning as a centrally planned and administered system. Government agencies were responsible for planning, financing, managing, and operating the vertically integrated power system. In Phase 2 , spanning from 1985 to 1997, the Chinese central government initiated decentralisation and liberalised the power generation sector. This involved diversifying investments to include provincial governments, as well as private and foreign investors. In Phase 3 , spanning from 1997 to 2002, the power sector underwent significant changes, primarily through corporatization and market-oriented restructuring. During this period, the State Power Corporation was established, leading to the separation of government and business functions. The Ministry of Electric Power was dissolved, and its responsibilities were transferred to the State Economic and Trade Commission and the State Development and Planning Commission, which later merged into the National Development and Reform Commission.

In Phase 4 , from 2002 to 2014, the 2002 electricity market reforms introduced significant changes, particularly by separating generation from grid companies to enhance market competition. This reform dismantled the State Power Corporation (SPC), which held 90% of China’s grid assets and 46% of power generation assets, replacing it with two state-owned power grid companies (the State Grid Corporation of China, SGCC, and China South Power Grid, CGS) and five major generation companies. Furthermore, major regulatory changes were implemented with the creation of the State Electricity Regulatory Commission in 2003, although it was subsequently dissolved in 2013.

Despite the successful competition and efficiency improvements in power generation following the 2002 unbundling reform, state-owned grid companies had maintained a monopoly over electricity transmission, distribution, and sales (She et al., 2020). In Phase 5 , beginning in 2015, the central government initiated further market-oriented reforms to the retail markets. Document No. 9 from the State Council, titled “Some Opinions on Deepening Reform of Electricity Sector,” introduced changes to electricity pricing systems, electricity trading mechanisms, and the opening of the electricity retail market, all of which supported further SG developments (IEA, 2017).

Major developments of SGs in China

China is a later-comer of SG developments when compared with its counterparts in the West. In contrast to other economies, China’s SG initiatives have largely focused on high-voltage transmission networks while the U.S. emphasising energy system resilience and the Japanese model is based on consumer participation enabled by smart technologies (Jensterle and Venjakob, 2019; Mah et al., 2017).

China’s SG development began with the SGCC’s 2009 announcement of a three-stage SG plan. Since then, major SG policies have been introduced by the Chinese national government (Table 3). Major progress has been made in these five areas:

(1) Grid Strengthening: China plans to invest USD 350 billion (2021–2025) to bolster grids, enabling cross-provincial renewable energy integration (REN21, 2022);

(2) Renewable Integration: China led global renewable power capacity (including hydropower, solar PV, and wind power) with renewable energy attributed to a total installed capacity of about 905,490 GW in China in 2020. Renewable energy contributed to about 43% of total electricity installed capacity and 27% of total electricity generation in 2021 (China Energy Portal, 2022; NEA, 2022);

(3) Smart Meters: Both state-owned grid companies introduced smart meter rollout plans, with 109 million tenders in 2020 (Statista, 2023c);

(4) SG Technology Pilots: SG technologies like home energy management systems (HEMSs) and energy storage systems have been promoted through various pilot projects (Han et al., 2017; Zhang et al., 2019); and

(5) Time-of-Use Tariffs and Demand Response: Since 2012, China implemented tiered-based tariffs for residential sectors to replace the traditional flat-rate pricing system. One year later, in 2013, China introduced time-of-use tariff, promoting energy use shifts through smart meters and real-time pricing (Mah, 2018; Wang and Yu, 2021).

Table 3.

Major SG-related policies in China in recent years (2021-2022).

Policies	Year of enactment	SG-related policy contents
The 12th Five-Year Plan for National Economic and Social Development (NDRC, 2011)	2011	Advancing SG
The Special Planning of 12^th Five-Year Plan (2011-2015) in Smart Grid Major Science and Technology Industrialisation Projects (NEA, 2012)	2012	SG major science and technology industrialisation projects
The Guiding Opinion on Promoting the Development of Smart Grids (NDRC and NEA, 2015)	2015	SG development
13^th Energy Five-Year Plan (NEA, 2016)	2016	Commercialisation of SGs
"Opinions on the complete, accurate and comprehensive implementation of the new development concept to fulfill carbon peaking and carbon neutral (State Council, 2021a)	2021	Power grid system reform
Issuance of the Peak Carbon Action Program by 2030” (State Council, 2021b)	2021	Strong SG construction
14th Five-Year Plan for Modern Energy System(NDRC, 2022)	2022	Renewable energy generation
14th Five-Year Plan for Renewable Energy Development (NDRC and NEA, 2022b)	2022	Renewable energy; SG infrastructure construction
Opinions on Improving Institutional Mechanisms and Policies for Green and Low-Carbon Energy Transition (NDRC and NEA, 2022a)	2022	Renewable energy; smart energy systems and microgrids construction
Implementation Program for the14th Five-Year Plan for Development of New Energy Storage (NDRC and NEA, 2021)	2022	New market-oriented demand response mechanism

Findings and discussions: Controlled dynamism in China’s smart energy transitions

Guided by our integrated framework, this study examines the development of SG policies in China, and we conceptualise China’s government-market relationships in the context of smart energy transitions as a controlled dynamic approach. This approach distinguishes certain key features of the government-market dynamics in China’s smart energy transitions: there existed a strong presence of the national government and SOEs while some extent of fragmentation (across sectors) and diversity (in the stakeholder landscape) in an increasingly marketised power sector was evident. The features and logics of this controlled dynamic approach, and an assessments of the emerging government-market relationships in fulfilling transition functions are discussed in more details as follows:

The features and logics of a controlled dynamic approach in a controlled dynamic setting

Informed by our integrated framework, we found that the technological and sector-specific factors amidst the on-going electricity market reforms in China have shaped the policy contexts of SGs within an increasingly dynamic stakeholder landscape [Codes: A1, A2]. It is important to note three observations:

Firstly, there existed a strong persisting presence of the national government and SOEs despite the electricity sector has been gradually opened up. Under China’s controlled dynamic approach of modulating the interactions of the government and the market within the power sector, our research found that the two grid companies were motivated by the combined effects of national policy low-carbon commitments, political obligations and economic incentives in an increasingly marketised power sector to mobilise resources to develop and implement plans to finance the deployment of SGs.

Previous studies have documented that because the electricity market has only been partially liberalised, the central government has retained a commanding position in the power sector through exercising ownership of the state-owned enterprises and through appointing and removing senior executives of state-owned enterprises (Chen, 2018).

The technological specificity of SG developments in China can explain the dominance of the government and SOEs [Code: A1]. SG technologies are complex and integral in nature. It entails an integration of a broad range of advanced technologies for transmission, distribution, storage, and retailing, which include smart metering, distributed system of power generation, energy storage systems, and home energy management systems. In response to these technological challenges, the Chinese government has emphasised the priorities of research and development of SG technologies in national strategic policies such as in The 12th Five-Year Plan (NDRC, 2011) and Opinions on Accelerating the Development of Energy Digitalization and Intelligence (NEA, 2023). Additionally, the complexity of SG technology is closely related to the high technology cost. Energy Foundation estimated that the amount of investment in national SG development can reached RMB 365.9 billion during the period of 2011–2030 (Energy Foundation, 2011). The high-cost nature of SG technologies also provided the two state-owned monopolised grid operators: the State Grid Corporation of China (SGCC) and China Southern Power Grid Co. Ltd. (CSG) an important role to play in this area of green investment. These two incumbents account for 83% and 17% of the national power consumption respectively, and have been pivotal in mobilising massive investments for grid enhancement and smart meter rollouts (Mah et al., 2017). SGCC and CSG have planned to contribute investments in power grid with a total of USD 442 billion over the period of 14th Five-Year Plan (2021–2025) (IEA, 2023). In 2022 alone, SGCC already invested over RMB500 billion ultra-high-voltage projects while the Chinese government played more roles on reducing technology costs through the large-scale deployment of SG technologies and achieved economies of scale (NEA and MIIT, 2022).

Additionally to the technological specificity, the sector specificity has given rise to a dynamic stakeholder landscape of SGs. Chinese policy instruments have covered a wide range of SG-related sector which include the industrial, residential and commercial sectors with the aim to enhance policy effectiveness through optimising the instrument mix in multi-sectoral policy settings [Codes: A2, D1 & D2]. It is however important to note that the policy attention given to different sectors was uneven and has been titled towards the industrial sector. The Guiding Opinion on Promoting the Development of Smart Grids (NDRC and NEA, 2015) set clear targets for increasing SG investments in industrial sector while giving insufficient attention to offering national policy support to engaging residential consumers.

Chinese provinces play a key role in the implementation of SG-related climate and energy policies at sub-national levels [Code: D3]. Under China’s “target responsibility system,” many of the central government’s key climate and energy targets are allocated to individual provinces, with provincial leaders responsible for fulfilling them. Each province has its own Leading Group on Climate Change, chaired by top provincial leaders (Sandalow et al., 2022).

Assessing the Achievements and Limitations of Government-Market Relationships in Fulfilling Transition Functions

Guided by our conceptual framework, our study has assessed the performance of China’s controlled dynamic approach in governing the government-market relationship. We found that China’s approach can perform critical functions which are required to support SG developments. However, some other functions haver remained under-performed as we discuss as follows:

Market Formation

The interplay between government and market in China’s power sector has provided critical conditions to support the market formation of SG technologies. Clear national visions and policy objectives have been delivered to policy stakeholders through the setting of the 2060 national net-carbon goal and the promulgation of the 14^th Five-Year Plan on Modern Energy System (NDRC, 2022) [Code: E1].

It is evident that the government has deployed a mix of administrative measures and market forces to mobilise multi-sectoral policy stakeholders at national, provincial and city levels to deliver the vision and policy objectives. The Chinese government has recognised that the energy system requires not only the phasing out of fossil fuels and using more renewable energy on the supply side, but also behavioral changes regarding the individual energy consumption on the demand side. The introduction of the Renewable Portfolio Standards (which mandate state-owned grid companies a minimal purchase of renewable energy) (Hove, 2023) [Code: B1], the feed-in tariff policies [Code: B2], and the green electricity trading market [Code: B3] demonstrated the use of a mix of policy instruments. The introduction of demand-side pilots in Foshan and other Chinese cities, on the other hand, is a good example of city-level demand-side policy initiatives using market forces (Mah, 2016). These policies have created a conducive market environment for supporting SG technologies (Code: E1), through introducing these supply-side and demand-side initiatives across not only the power sector, but all electricity end-uses and subsectors including the building, transport, and had sectors (Sandalow et al., 2022; Hu et al., 2023a) [Codes: D2, D5].

These observed SG-related policies have, however, major limitations in introducing pricing signals. In general, the low electricity prices in China has failed to create strong market signals to motivate energy efficiency across all sub-sectors of electricity end-users (Mah, 2016). Although recent technological breakthroughs in SGs have led to greater interest in demand-side-management activities in the residential sector, Chinese householders had limited engagement in demand response programmes, and in generally did not respond actively to time-of-use dynamic pricing systems which are linked with the use of smart meters and visualisation of real-time electricity consumption data (Mah, 2018; Yang et al., 2018). The impacts of SG policies were therefore undermined. China underperformed its energy efficiency target in the 13th Five-year Plan (2016–2020), achieving a reduction of energy intensity during the 13th FYP at 13.2% - which was less than the initiate target of 15% (Sandalow et al., 2022) [Code: E1].

Market regulation

The ongoing electricity market reforms in China are expected to liberalise and regulate the power market in new ways in order to introduce market competition, economic incentives and pricing signals to scale up the deployment of renewable energy and demand-side measures.

It is important to note that, following the 2015 electricity market reforms, the Chinese government has made important progress in establishing and regulating its electricity markets. Power exchange centres have been set up in all provinces and autonomous regions to support electricity market transactions, encompassing not only traditional electricity but also renewable [. In 2022, China reached 20TWh of cumulative transactions volumes in green electricity trading market (GIZ, 2022). At provincial level, on the launch day of the electricity trading market in Guangdong [Code: D3], four renewable developers sold 10,480 MWh to seven retailers and power users through annual contracts [Code: D1], providing empirical evidence that new market actors have become more active in China’s increasingly dynamic stakeholder landscape [Code: D5]. Importantly, the Chinese government has played important roles in establishing new renewable trading rules that govern the operation of these new electricity trading platforms (Dong and Cao, 2021) [Code: E2].

Market regulation, however, appeared to remain one of the weakest functional areas in the current government-market relationships. Overseas experiences in, for example, Germany, Spain, and the US, have clearly shown that a variety of electricity markets (such as spot markets and cross-border electricity trading) can provide numerous options of energy supply to meet market demand, and thus enabling the mainstreaming of renewable energy (Szeberényi and Bakó, 2023; Zhang et al., 2018).

In contrast, there is a lack of a comprehensive regulatory framework for governing SG-related energy markets in China. To date, no single national legislative ordinance is dedicated to promoting SGs. Instead, the Chinese government has relied on a loose regulatory framework, primarily from the National Development and Reform Commission, to regulate SG developments. It is evident that regulating the SG industry through optimising government-market dynamics is challenging. The development of the renewable energy market is dominated by state-owned enterprises (SOEs). Retail competition involving renewable energy suppliers is lacking. A large-scale integration of renewable energy has remained a major challenge. Solar PV accounts for only 3% of domestic electricity generation, whereas countries like Italy, Germany, and Japan have higher percentages. Solar PV contributed to Italy, Germany, and Japan, solar PV contributed to 8%, 7.6% and 6.6.% of Italy’s, German, and Japan’s their national electricity generation respectively in 2021 (IEA, 2021b, 2021c).

Specifically, bottlenecks in transmission networks have been a major institutional constrain that hindered the major uptake of renewable energy. The partial electricity market reforms have not yet fully addressed curtailments of renewable energy. State-owned utilities, with their established positions, lack incentives to incorporate renewable energy which is intermittent in nature. This issue is compounded by a mismatch between transmission capacity and wind and solar farm outputs and a lack of energy storage systems (Luo et al., 2018). Large-scale wind curtailment first emerged in the late 2000s in the northwest regions in China, spreading nationwide in 2010. The total solar energy abandoned was 14.19TWh between 2013 and 2016, attributed to around 15% national average curtailment rate of solar PV during that period of time (Zhang et al., 2018). In recent years, even though curtailment has continued to improve due to the commissioning of additional interprovincial transmission capacity and improved market operations, wind and solar PV generation curtailment still reached approximately 15 TWh in 2020 (IEA, 2021d) [Code: E2].

The regulatory weakness has also hindered the effectiveness of SG policies in fostering consumer engagement. The electricity market reforms are expected to create new market conditions that enable competitive electricity prices, and more consumer choices – which are pre-requisite for the Chinese government to mobilise market forces and flexibility in engaging the public in demand response initiatives. However, following decades of reforms, retail market liberalisation and customer choices have remained limited in China’s power sector. Besides, demand response pilot city programmes were only launched in 10 cities as of 2019, most of these programmes were only applicable for industrial and business sector. The existence of limited customer engagement and the weak interactions between the two grid operators and residential end-users has constrained electricity consumers in participating actively in distributed energy markets and demand responses programmes (Liu et al., 2013; Mah, 2018).

Managing public goods

Many aspects of SG developments are public goods in nature which requires large amounts of investments with low return rates. Over these years, the Chinese government and two monopolised power grid companies have undertaken significant roles on accelerating SG development in China in terms of investments, R&D, diffusions, and international cooperations [Code: E3].

In terms of green investment, SGCC was the largest SG investor with its investment accounting for 99.2% of grid investment in China in 2021 (e.g., investments in the world’s first VSC-HVDC grid project in Zhangbei) (Sina Finance, 2021).

In relation to R&D, SGCC planned to increase R&D investments of RMB 58 billion from 2021 to 2025 to achieve breakthroughs in key technologies for new power systems. CSG, another state-owned grid company, has also undertaken major R&D projects such as a database power system (Sina Finance, 2021). Political obligations coupled with social responsibility appear to be the primary motivation to drive the two state-owned grid companies to develop SGs technologies. [Code: A1] The synthesis of data management, integration of renewable energy, resilience and repair (KPMG, 2023) has increased the complexity of SG development. SGCC and CSG believed that they had the responsibility to take the lead in developing SG technologies to avoid losing the global market competitiveness of the Chinese SG industries in this worldwide trend (Mah et al., 2017).

In addition, these SOEs also plays an active role in international cooperation on SGs. One notable examples is the UHVDC transmission lines which were built by SGCC in Brazil (KPMG, 2023).

Networking and resource mobilisation

It is evident that the Chinese government has been actively engaged with market actors within multi-types of policy networks in relation to SG development as follows [Code: E4].

(1) Domestic policy community: Under China’s authoritarian yet decentralised governance system (Lo, 2020), the administration structure and policy-making systems of the energy sector have remained hierarchical despite decentralisation has been introduced since the late 1970s. With the National Development and Reform Commission (NDRC) and its division National Energy Administration as the central government agencies responsible for energy policy planning and implementation, the hierarchical structure of Chinese domestic policy community has the strength in deploying administrative measures to mobilising state-owned utilities to implement policies (Xu, 2017). Provincial and city governments are also key actors in the policy community as they can exercise discretions in introducing local policies, for instance, local feed-in policies in Foshan (Mah, 2020).

(2) Global intergovernment networks: China had actively engaged in UN Framework Convention on Climate Change (UNFCCC) since 1993 and has become major players international climate negotiations such as adopted the Paris Climate Change Agreement (Paris Agreement) in 2015. China has also participated in international collaborations of SG development, with for instance, the New Energy and Industrial Technology Development (NEDO) which is the national research and development agency in Japan. Under the Belt and Road Initiative (BRI), China invested 12.04 GW of installed capacity in wind and solar power in 64 countries (Greenpeace, 2021).

(3) Domestic and global supply-chain networks: Domestically, the two state-owned monopolised grid utilities and the five major state-owned power generation companies have formed a strong supply-chain networks that span the entire upstream and downstream segments of the SG industry, involving market actors of various sizes and business nature (Mah, 2020).

(4) Multi-stakeholder networks: public (e.g., government), private (e.g., electricity utilities and consumers, smart meter users), civil (e.g., not-for-profit organisations such as China Electricity Council), as well as hybrid actors in the forms of .g., public–private partnerships (such as the Research and Development Partnerships) in developing SG technologies (Sattler et al., 2023).

There is however under-development and under-utilisation of policy networks in several important aspects. First, although industrial associations exist and have served as important intermediaries to transfer knowledge across the SG industry, many of them such as Beijing Electric Power Industry Association (2019), are managed and supervised by electricity authorities and have limited degree of independence and autonomy (Wang and Wang, 2018) [Code: E4].

SGCC and CSG have founded in-house research institutions (e.g., such as State Grid Energy Research Institute (SGERI) and CSG Electric Power Research Institute (CSG EPRI)) to provide standards, expertise, knowledge, and techniques to support SG development. However, the majority of databases from these research institutions do not open to the public, which limited the effects of knowledge sharing in research networks. [Code: E4].

Policy learning

Issue networks can play an important role in policy learning. Issue network in associated with SG developments in China involves with different industrial associations. For example, China Electricity Council (CEC). However, these kinds of government-affiliated industry association lack of independence and autonomy, and they are under the guidance and supervision of NEA. Another limitations of China’s issue network is that there are no national-scale SG industrial associations in China except the National Smart Grid Standardization Promotion Group (NSGSP) (NEA, 2011) established under the joint leadership of the NEA and the Standardization Administration of China (SAC) [Code: E5].

Another limitations of policy learning in China is the lack of an inclusive approach in SG policy developments. SG developments are a people-centered approach. Householders, or residential consumers of electricity, can be engaged in energy systems in various levels, from participating in demand-side energy solutions to investing in rooftop solar installations, and even stimulating market demand within regional renewable energy markets (Parag, 2015). However, realising the potential of consumer engagement necessitates significant departures from the traditional top-down and closed policy-making processes. Instead, it requires a shift towards a policy learning approach, through which end-users and other policy stakeholders collectively offer feedback and collaboratively adjust the goals, institutions, and policy instruments of SG policies (Lo, 2015; Mah, 2020).

Empirical studies on SG developments in China however have revealed that residential end-users exhibited a limited level of engagement in adopting energy saving practices in response to time-of-use pricing. Some studies found that consumers perceived little incentives to alter their daily energy practices because of the low electricity prices and a lack of clear differentiation between peak- and off-peak prices, there was little incentive for them to change the status quo in their daily energy practices. The Chinese government, on the other hand, was not active in making major adjustment in the electricity pricing reforms due to public opposition to tariff increase (Zhang and Qin, 2015).

Conclusions

This study developed an extended integrated framework of policy mix and functional dynamics for smart energy transitions to provide a systematic understanding of energy transitions, with a reference of an important sub-field of SG technologies in China. Our framework integrates policy mixes and functional dynamics perspectives, and guided us in our empirical analysis. It allowed us to provide a more holistic and critical analysis of SG development in China. Our analysis has illustrated that the on-going electricity market reforms have created institutional conditions (and the associated government-market dynamics) which have shaped and determined the developments of SG in China. We have advanced the theoretical developments of the energy transitions literature by conceptualising these Chinese features as a controlled dynamic approach.

In addition to theoretical contribution, this study has also made empirical contribution. In our methodology section, we explain that our reanalysis of an empirical case study through synthesising findings from prior research is guided by our conceptual framework. We also adopted a coding system to systematically map out the interactions of the government and the market. This systemic research approach enables us to conduct policy-relevant research through deeper exploitation of existing data resources. Our analysis is thus able to go beyond being desciptive. We are able to provide a much more in-depth discussion on how government adopted different types of policy instruments and employed policy mixes in an increasingly marketised environment, and the extent to which, and how the interactions between government and market can deliver critical functional dynamics that drove or constrained the developments of SGs in China. We found that changes to market rules, policy objectives and regulatory frameworks have contributed to the increasingly dynamic government-market relationships with more and more market actors interacting. However, there exist at least three significant functional weaknesses in China’s smart energy policies. These include the over-reliance on SOEs, ineffectiveness in engaging households in demand-side management, and the under-utilisation of an intelligent mix of policy instruments which are required to fully realised the potential benefits of SG.

Our findings have policy implications. We suggest that SG policies in China need to give sufficient attention to the limitations of the existing government-market relationships in fulfilling the key functions of market formation, market regulation, managing public goods, networking, and policy learning. As guided by our integrated framework, we recommend the Chinese government in assuming a more active role in optimising the policy mixes in order to improve the policy performance in delivering those “gap” functions. Our specific policy recommendations are as follows:

First, SG policies should better leverage the advantages of both the administrative policy measures and the market mechanisms to optimise the government-market relationships. Particular attention should be given to how to design and implement more effective market-based policy instruments in order to create sufficient market signals to mobilise residential end-users to take part in both supply-side and demand-side energy measures.

Secondly, the roles of the government in regulating different sub-types of energy markets, including green electricity markets, are critical and yet under-performed. SG technologies are highly integral in nature and yet there is a lack of a comprehensive regulatory framework for SGs in China. The Chinese government needs to introduce a national “smarter” regulatory framework which can foster cross-departmental policy coordination at the national level, as well as vertically across national, provincial, and city levels.

Thirdly, policy-making of SGs needs to adopt a more inclusive approach in order to encourage active engagement with the government, energy utilities, SMEs and other market actors, and endusers to gather feedback on policy-making matters.

This study applied the framework in the case study and illustrate the explanatory power of the framework. Future research directions can focus on conducting empirical research to collect primary data on explaining the policy impact of can be explained, and the scaling up mechanisms.

Footnotes

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) received no financial support for the research, authorship, and/or publication of this article.

Author biographies

Daphne Ngar-yin Mah is the Associate Professor at Department of Geography, Hong Kong Baptist University and Director of Asian Energy Studies Centre. She was named the World’s Top 2% Scientist by Stanford University (2022). Her research interests include smart energy transitions and comparative energy governance in Asia and Europe.

Aijia Wang is Ph.D. Student at the Department of Geography, Hong Kong Baptist University. Her research interests include electricity market reform, energy transition, and energy policy.

Andy Wai-hei Siu is an MPhil student at the Department of Geography at the Hong Kong Baptist University. He received a bachelor’s degree in China Studies (geography concentration) from Hong Kong Baptist University. His research interests are carbon neutrality, carbon market, energy policy, and regional cooperation.

References

Akrofi

Antwi

(2020) COVID-19 energy sector responses in Africa: A review of preliminary government interventions. Energy Research & Social Science 68: 101681.

Beijing Electric Power Industry Association (2019) Beijing Electric Power Industry Association - About Us. Beijing. Available at: http://www.bjepea.com/m/list.php?tid=36 (accessed 30 October 2023).

Bergek

Jacobsson

Carlsson

, et al. (2008) Analyzing the functional dynamics of technological innovation systems: A scheme of analysis. Research Policy 37(3): 407–429.

Boon

Bakker

(2016) Learning to shield–Policy learning in socio-technical transitions. Environmental Innovation and Societal Transitions 18: 181–200.

Boon

Edler

Robinson

DKR

(2022) Conceptualizing market formation for transformative policy. Environmental Innovation and Societal Transitions 42: 152–169.

Bradshaw

de Martino Jannuzzi

(2019) Governing energy transitions and regional economic development: Evidence from three Brazilian states. Energy Policy 126: 1–11.

Byrne

Mun

Y-M

(2003) Rethinking reform in the electricity sector: Power liberalisation or energy transformation. In: Wamukonya

(ed.) Electricity Reform: Social and Environmental Challenges. Roskilde, Denmark: United Nations Environment Programme (UNEP) Risoe Centre, 48–76.

Chen

(2018) Governing through the market: SASAC and the resurgence of central state-owned enterprises in China. PhD Thesis, University of Birmingham, Birmingham.

China Energy Portal (2022) 2021 electricity & other energy statistics. Available at: https://chinaenergyportal.org/2021-electricity-other-energy-statistics-preliminary/ (accessed 2 January 2023).

10.

Chou

J-S

Kim

Ung

T-K

, et al. (2015) Cross-country review of smart grid adoption in residential buildings. Renewable and Sustainable Energy Reviews 48: 192–213.

11.

Cooke

(2011) Empowering customer choice in electricity markets. Information Paper. Paris: International Energy Agency. Available at: www.iea.org/reports/empowering-customer-choice-in-electricity-markets (accessed 1 December 2023).

12.

CPCnews (2020) 习近平在第七十五届联合国大会一般性辩论上发表重要讲话 [Xi Jinping delivers an important speech at the general debate of the 75th session of the United Nations General Assembly]. Available at: http://cpc.people.com.cn/n1/2020/0923/c64094-31871240.html (accessed 1 September 2023).

13.

Cui

Wei

(2017) Analysis of thermal coal pricing and the coal price distortion in China from the perspective of market forces. Energy Policy 106: 148–154.

14.

D’Adamo

Gastaldi

Morone

(2022) Solar collective self-consumption: Economic analysis of a policy mix. Ecological Economics 199: 107480.

15.

Dantas

GDA

de Castro

Dias

, et al. (2018) Public policies for smart grids in Brazil. Renewable and Sustainable Energy Reviews 92: 501–512.

16.

De Almeida

ELF

(1998) Energy efficiency and the limits of market forces: The example of the electric motor market in France. Energy Policy 26(8): 643–653.

17.

Del Río

(2014) On evaluating success in complex policy mixes: The case of renewable energy support schemes. Policy Sciences 47: 267–287.

18.

Dong

Cao

(2021) New renewable trading rules released in China: How to procure renewables in Guangdong and Zhejiang. Available at: www.spglobal.com/commodityinsights/en/ci/research-analysis/new-renewable-trading-rules-released-in-china-how-to-procure.html (accessed 2 December 2023).

19.

Droste

Hansjürgens

Kuikman

, et al. (2016) Steering innovations towards a green economy: Understanding government intervention. Journal of Cleaner Production 135: 426–434.

20.

EC (2023) Smart Metering deployment in the European Union. Available at: https://ses.jrc.ec.europa.eu/smart-metering-deployment-european-union (accessed 30 October 2023).

21.

ECLAC (2021) Digital technologies for a new future. Economic Affairs Officer of the Economic Commission for Latin America and the Caribbean (ECLAC), United Nations. Available at: www.cepal.org/sites/default/files/publication/files/46817/S2000960_en.pdf (accessed 1 December 2023).

22.

Energy Foundation (2011) 智能电网效益分析方法深化研究 [Deepening research on smart grid benefit analysis methods]. Available at: www.efchina.org/Reports-zh/reports-20110909-zh (accessed 1 December 2023).

23.

Gao

AM-Z

Fan

C-T

Liao

C-N

(2018) Application of German energy transition in Taiwan: A critical review of unique electricity liberalisation as a core strategy to achieve renewable energy growth. Energy Policy 120: 644–654.

24.

Gao

Ren

, et al. (2021) A renewable energy certificate trading system based on blockchain. In: IEEE 20th international conference on trust, security and privacy in computing and communications (TrustCom), Shenyang, China. New York, NY: IEEE.

25.

GIZ (2022) Energy in China Newsletter. Issue No. 63. Bonn, Germany: Sino-German Energy Partnership. Available at: https://login.mailingwork.de/-viewonline2/1593/12357/67/dJVhrbsz/8mm8glQhvj/1 (accessed 1 December 2023).

26.

Greenacre

Gross

Speirs

(2012) Innovation Theory: A review of the literature. London: Imperial College Centre for Energy Policy and Technology.

27.

Greenpeace (2021) 中国在“一带一路”沿线国家可再生能源投资协同效益研究报告 [China’s One-belt-one-road Initiative: Synergy of Renewable Energy Investment from Countries]. Available at: www.greenpeace.org.cn/wp-content/uploads/2021/12/coei_cobenefit_report.pdf (accessed 1 December 2023).

28.

Hall

(1993) Policy paradigms, social learning, and the state: The case of economic policymaking in Britain. Comparative Politics 25(3): 275–296.

29.

Hall

Foxon

(2014) Values in the Smart Grid: The co-evolving political economy of smart distribution. Energy Policy 74: 600–609.

30.

Hamidi

Smith

Wilson

(2010) Smart grid technology review within the transmission and distribution sector. In: IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe), Gothenburg, Sweden. New York, NY: IEEE.

31.

Han

Chen

Zhuang

Shen

(2017) A review on development practice of smart grid technology in China. IOP Conference Series: Materials Science and Engineering. IOP Publishing.

32.

Xue

Zhao

Wand

(2021) Renewable energy technological innovation, market forces, and carbon emission efficiency. Science of The Total Environment 796: 148908.

33.

Helmholt

Broenink

(2011) Degrees of freedom in information sharing on a greener and smarter grid. Energy: 22–27.

34.

Hossain

Madlool

Rahim

, et al. (2016) Role of smart grid in renewable energy: An overview. Renewable and Sustainable Energy Reviews 60(C): 1168–1184.

35.

Hove

(2023) China publishes new rules for green power trading. Bonn, Germany: Sino-German Energy Partnership. Available at: www.energypartnership.cn/home/china-publishes-new-rules-for-green-power-trading/ (accessed 1 December 2023).

36.

Xue

Liu

, et al. (2023a) Green building policies in China: A policy review and analysis. Energy and Buildings 276: 112641.

37.

Xiong

Yan

, et al. (2023b) The horizontal and vertical coordination of policy mixes for industrial upgrading in China: An ambidexterity perspective. Regional Studies 57(6): 1011–1028.

38.

IEA (2017) Prospects for Distributed Energy Systems in China. Paris: International Energy Agency. Available at: https://iea.blob.core.windows.net/assets/aa7ab168-91db-4528-aefe-82ba76654950/ProspectsforDistributedEnergySystemsinChina.pdf (accessed 1 December 2023).

39.

IEA (2021a) An Energy Sector Roadmap to Carbon Neutrality in China. Paris: International Energy Agency. Available at:https://iea.blob.core.windows.net/assets/9448bd6e-670e-4cfd-953c-32e822a80f77/AnenergysectorroadmaptocarbonneutralityinChina.pdf (accessed 1 December 2023).

40.

IEA (2021b) Renewable Energy Market Update: Outlook for 2021 and 2022. Paris: International Energy Agency. Available at: https://iea.blob.core.windows.net/assets/18a6041d-bf13-4667-a4c2-8fc008974008/RenewableEnergyMarketUpdate-Outlookfor2021and2022.pdf (accessed 1 December 2023).

41.

IEA (2021c) Renewable Information. Paris: International Energy Agency. Available at: www.iea.org/reports/renewables-information-overview (accessed 1 December 2023).

42.

IEA (2021d) Renewables 2021 - Analysis and Forecast to 2026. Paris: International Energy Agency. Available at: https://iea.blob.core.windows.net/assets/5ae32253-7409-4f9a-a91d-1493ffb9777a/Renewables2021-Analysisandforecastto2026.pdf (accessed 1 December 2023).

43.

IEA (2023) Smart Grids. Paris. Available at: https://www.iea.org/energy-system/electricity/smart-grids (accessed 14 October 2023).

44.

Jacobsson

Bergek

(2011) Innovation system analyses and sustainability transitions: Contributions and suggestions for research. Environmental Innovation and Societal Transitions 1(1): 41–57.

45.

Jensterle

Venjakob

(2019) Smart power grids and integration of renewables in Japan: Status and activities concerning smart grids implementation and integration of renewable energy sources in Japan; background study. Berlin: adelphi. Available at: https://epub.wupperinst.org/frontdoor/deliver/index/docId/7425/file/7425_Smart_Power_Grids.pdf (accessed 1 December 2023).

46.

Kanger

Savacool

Noorkõiv

(2020) Six policy intervention points for sustainability transitions: A conceptual framework and a systematic literature review. Research Policy 49(7): 104072.

47.

Kotilainen

Valta

Saari

, et al. (2021) From energy consumers to prosumers—how do policies influence the transition? In: Aalto

(ed.) Electrification. Amsterdam: Elsevier, 197–215.

48.

Kowli

Negrete-Pincetic

Gross

(2010) A successful implementation with the Smart Grid: Demand response resources. In: IEEE PES general meeting, Minneapolis, MN. New York, NY: IEEE.

49.

KPMG (2023) Smarter Grids—Powering decarbonisation through technology investment. Available at: https://assets.kpmg.com/content/dam/kpmg/cn/pdf/en/2023/05/smarter-grids.pdf (accessed 1 December 2023).

50.

Kwon

T-h

(2020) Policy mix of renewable portfolio standards, feed-in tariffs, and auctions in South Korea: Are three better than one? Utilities Policy 64: 101056.

51.

Levenda

(2020) Thinking critically about smart city experimentation: Entrepreneurialism and responsibilization in urban living labs. In: Evans

Karvonen

Martin

, et al. (eds) Smart and Sustainable Cities? London: Routledge, 9–23.

52.

Taeihagh

(2020) An in-depth analysis of the evolution of the policy mix for the sustainable energy transition in China from 1981 to 2020. Applied Energy 263: 114611.

53.

Zhang

Yuan

(2019) Research on China’s renewable portfolio standards from the perspective of policy networks. Journal of Cleaner Production 222: 986–997.

54.

Lin

Kahrl

Yuan

, et al. (2019) Challenges and strategies for electricity market transition in China. Energy Policy 133: 110899.

55.

Lindberg

Markand

Andersen

(2019) Policies, actors and sustainability transition pathways: A study of the EU’s energy policy mix. Research Policy 48(10): 103668.

56.

Liu

Wang

Sun

, et al. (2013) A barrier analysis for the development of distributed energy in China: A case study in Fujian province. Energy Policy 60: 262–271.

57.

(2015) How authoritarian is the environmental governance of China? Environmental Science & Policy 54: 152–159.

58.

(2020) Governing energy consumption in China: A comprehensive assessment of the energy conservation target responsibility system. Energy Transitions 4(1): 57–67.

59.

Long

Mokhtar

Ahmed

Lim

(2022) Enhancing sustainable development via low carbon energy transition approaches. Journal of Cleaner Production 379: 134678.

60.

Luo

Dan

Zhang

Guo

(2018) Why the wind curtailment of northwest China remains high. Sustainability 10(2): 570.

61.

Magro

Wilson

(2019) Policy-mix evaluation: Governance challenges from new place-based innovation policies. Research Policy 48(10): 103612.

62.

Mah

DN-Y

(2016) Understanding the role of incumbent utilities in sustainable energy transitions: A case study of the smart grid development in China. Asian Energy Studies Centre’s Working Paper No. 15. Hong Kong: Asian Energy Studies Centre, Hong Kong Baptist University. Available at: http://aesc.hkbu.edu.hk/wp-content/uploads/2016/03/WP15.pdf (accessed 1 December 2023).

63.

Mah

DN-Y

(2018) Understanding undergraduate students’ perceptions of dynamic pricing policies: An exploratory study of two pilot deliberative pollings (DPs) in Guangzhou, China and Kyoto, Japan. Journal of Cleaner Production 202: 160–173.

64.

Mah

DN-Y

(2020) Conceptualising government-market dynamics in socio-technical energy transitions: A comparative case study of smart grid developments in China and Japan. Geoforum 108: 148–168.

65.

Mah

DN-Y

van der Vleuten

JC-M

Ronald Hills

(2012) Governing the transition of socio-technical systems: A case study of the development of smart grids in Korea. Energy Policy 45: 133–141.

66.

Mah

DN-Y

Ronald Hills

(2017) Explaining the role of incumbent utilities in sustainable energy transitions: A case study of the smart grid development in China. Energy Policy 109: 794–806.

67.

Mah

DN-Y

Leung

MKH

Cheung

, et al. (2021) Policy mixes and the policy learning process of energy transitions: Insights from the feed-in tariff policy and urban community solar in Hong Kong. Energy Policy 157: 112214.

68.

Martiskainen

Schot

Sovacool

(2021) User innovation, niche construction and regime destabilization in heat pump transitions. Environmental Innovation and Societal Transitions 39: 119–140.

69.

Matisoff

(2013) Different rays of sunlight: Understanding information disclosure and carbon transparency. Energy Policy 55: 579–592.

70.

NBSC (2021) China Statistical Yearbook 2021. Available at: http://www.stats.gov.cn/tjsj/ndsj/2021/indexeh.htm (accessed 1 December 2023).

71.

NBSC (2022) China Statistical Yearbook 2022. Available at: http://www.stats.gov.cn/sj/ndsj/2022/indexeh.htm (accessed 6 September 2023).

72.

Ndiritu

Engola

(2020) The effectiveness of feed-in-tariff policy in promoting power generation from renewable energy in Kenya. Renewable Energy 161: 593–605.

73.

NDRC (2011) 国民经济和社会发展第十二个五年规划纲要 [The 12th Five-Year Plan for National Economic and Social Development]. Available at https://www.gov.cn/2011lh/content_1825838.htm (accessed 16 September 2023).

74.

NDRC (2022) 14th Five-Year Plan for Modern Energy System [“十四五”现代能源体系规划]. Beijing. Available at: www.nea.gov.cn/1310524241_16479412513081n.pdf (accessed 1 November 2023).

75.

NDRC and NEA (2015) 关于促进智能电网发展的指导意见 [The Guiding Opinion on Promoting the Development of Smart Grids]. Available at: https://www.ndrc.gov.cn/xxgk/zcfb/tz/201507/t20150706_963380.html (accessed 18 September 2023).

76.

NDRC and NEA (2021) “十四五”新型储能发展实施方案 [Implementation Program for the14th Five-Year Plan for Development of New Energy Storage]. Available at: www.gov.cn/zhengce/zhengceku/2022-03/22/content_5680417.htm (accessed 1 December 2023).

77.

NDRC and NEA (2022a) 关于完善能源绿色低碳转型体制机制和政策措施的意见 [Opinions on Improving Institutional Mechanisms and Policies for Green and Low-Carbon Energy Transition]. Available at www.gov.cn/zhengce/zhengceku/2022-02/11/content_5673015.htm (accessed 1 November 2023).

78.

NDRC and NEA (2022b) “十四五”可再生能源发展规划 [14th Five-Year Plan for Renewable Energy Development]. Available at: www.ndrc.gov.cn/xwdt/tzgg/202206/P020220601502009073293.pdf (accessed 1 December 2023).

79.

NEA (2011) 国家能源局关于成立国家智能电网标准化总体工作推进组的通知 [Notice of the National Energy Administration on the Establishment of the National Smart Grid Standardization Promotion Group]. Available at www.nea.gov.cn/2011-10/12/c_131187554.htm (accessed 1 November 2023).

80.

NEA (2012) 关于印发智能电网重大科技产业化工程’十二五’专项规划的通知 [The special Planning of 12th Five-Year Plan (2011-2015) in Smart Grid Major Science and Technology Industrialisation Projects]. Available at: http://www.nea.gov.cn/2012-05/07/c_131571608.htm (accessed 18 September 2023).

81.

NEA (2016) 能源发展“十三五”规划 [13th Energy Five-Year Plan (2016-2020)]. Available at: www.nea.gov.cn/135989417_14846217874961n.pdf (accessed 1 December 2023).

82.

NEA (2022) 国家能源局关于2021年可再生能源电力消纳责任权重完成情况的通报 [Notice on the Completion of Responsibility Weights for Renewable Energy Electricity Consumption in 2021]. Available at: http://zfxxgk.nea.gov.cn/2022-04/21/c_1310587748.htm#:~:text=%E6%88%AA%E8%87%B32021%E5%B9%B412%E6%9C%88%E5%BA%95,%E5%8F%91%E7%94%B5%E8%A3%85%E6%9C%BA3798%E4%B8%87%E5%8D%83%E7%93%A6%E3%80%82 (accessed 27 September 2023).

83.

NEA (2023) 国家能源局关于加快推进能源数字化智能化发展的若干意见 [Opinions on Accelerating the Development of Energy Digitalization and Intelligence]. Available at: www.gov.cn/zhengce/zhengceku/2023-04/02/content_5749758.htm (accessed 1 December 2023).

84.

NEA and MIIT (2022) Typical Cases of 5G applications in the energy sector in 2022. Available at: www.nea.gov.cn/download/nylydxalhb.pdf (accessed 1 December 2023).

85.

Panori

Kastopoulos

Karampinis

Altsitsiadis

(2022) New path creation in energy transition: Exploring the interplay between resource formation and social acceptance of biomass adoption in Europe. Energy Research & Social Science 86: 102400.

86.

Parag

(2015) Beyond energy efficiency: A ‘prosumer market’ as an integrated platform for consumer engagement with the energy system. In: ECEEE 2015 Summer Study on Energy Efficiency, Hyères, France. ECEEE, 15–23.

87.

Parvin

Hannan

Mun

, et al. (2022) The future energy internet for utility energy service and demand-side management in smart grid: Current practices, challenges and future directions. Sustainable Energy Technologies and Assessments 53: 102648.

88.

Peng

Wagner

Ramana

, et al. (2018) Managing China’s coal power plants to address multiple environmental objectives. Nature Sustainability 1(11): 693–701.

89.

Pollitt

(2012) The role of policy in energy transitions: Lessons from the energy liberalisation era. Energy Policy 50: 128–137.

90.

REN21 (2022) Renewables 2022: Global status report - China Factsheet. France: REN21. Available at: www.ren21.net/wp-content/uploads/2019/05/GSR2022_Fact_Sheet_China.pdf (accessed 1 December 2023).

91.

Rind

Raza

Zubair

, et al. (2023) Smart energy meters for smart grids, an internet of things perspective. Energies 16(4): 1974.

92.

Rogge

Schleich

(2018) Do policy mix characteristics matter for low-carbon innovation? A survey-based exploration of renewable power generation technologies in Germany. Research Policy 47(9): 1639–1654.

93.

Rosenow

Kern

Rogge

(2017) The need for comprehensive and well targeted instrument mixes to stimulate energy transitions: The case of energy efficiency policy. Energy Research & Social Science 33: 95–104.

94.

Sandalow

Meidan

Andrews-Speed

, et al. (2022) Guide To Chinese Climate Policy 2022. Oxford: The Oxford Institue for Energy Studies. Available at: https://chineseclimatepolicy.oxfordenergy.org/wp-content/uploads/2022/11/Guide-to-Chinese-Climate-Policy-2022.pdf (accessed 1 December 2023).

95.

Sattler

Barghusen

Bredemeier

, et al. (2023) Institutional analysis of actors involved in the governance of innovative contracts for agri-environmental and climate schemes. Global Environmental Change 80: 102668.

96.

She

Z-Y

Meng

Xie

B-C

O’Neill

(2020) The effectiveness of the unbundling reform in China’s power system from a dynamic efficiency perspective. Applied Energy 264: 114717.

97.

Shi

Rioux

Galkin

(2018) Unintended consequences of China’s coal capacity cut policy. Energy Policy 113: 478–486.

98.

Sina Finance (2021) SGCC invested over 2 trillion yuan in the transformation and upgrading of the power grid, what signals have been released? Available at: https://finance.sina.com.cn/roll/2021-09-13/doc-iktzqtyt5630273.shtml (accessed 26 October 2023).

99.

Song

Rogge

Ely

(2023) Mapping the governing entities and their interactions in designing policy mixes for sustainability transitions: The case of electric vehicles in China. Environmental Innovation and Societal Transitions 46: 100691.

100.

SP Group (2022) The Smart Grid Index: 2022 benchmarking result. Available at: https://www.spgroup.com.sg/our-services/network/overview/smart-grid-index (accessed 30 October 2023).

101.

State Council (2021a) 关于完整准确全面贯彻新发展理念做好碳达峰碳中和工作的意见[Opinions on the complete, accurate and comprehensive implementation of the new development concept to fullfill carbon peaking and carbon neutral]. Available at https://www.gov.cn/zhengce/2021-10/24/content_5644613.htm (accessed 30 August 2023).

102.

State Council (2021b) 国务院关于印发2030年前碳达峰行动方案的通知[Issuance of the Peak Carbon Action Program by 2030]. Available at https://www.gov.cn/zhengce/zhengceku/2021-10/26/content_5644984.htm (accessed 30 October 2023).

103.

Statista (2023a) Market size of smart grid in China from 2016 to 2020, with a forecast for 2021 (in billion yuan). Available at: https://www.statista.com/statistics/1292160/china-smart-grid-market-size/ (accessed 30 October 2023).

104.

Statista (2023b) Number of advanced meters installed in the United States from 2008 to 2022 (in millions). Available at: https://www.statista.com/statistics/446964/number-of-advanced-meters-installed-in-the-united-states/ (accessed 30 October 2023).

105.

Statista (2023c) Number of smart electricity meter tenders in China from 2016 to 2020 with an estimate for 2021 (in millions). Available at: https://www.statista.com/statistics/1277814/china-number-of-smart-electricity-meter-tenders/ (accessed 30 October 2023).

106.

Szeberényi

Bakó

(2023) Electricity market dynamics and regional interdependence in the face of pandemic restrictions and the Russian–Ukrainian conflict. Energies 16(18): 6515.

107.

Tai

Xiao

Tang

(2020) A quantitative assessment of vulnerability using social-economic-natural compound ecosystem framework in coal mining cities. Journal of Cleaner Production 258: 120969.

108.

Tuballa

Abundo

(2016) A review of the development of Smart Grid technologies. Renewable and Sustainable Energy Reviews 59: 710–725.

109.

Vigurs

Maidment

Fell

Shipworth

(2021) Customer privacy concerns as a barrier to sharing data about energy use in smart local energy systems: A rapid realist review. Energies 14(5): 1285.

110.

Wang

(2018) Social autonomy and political integration: Two policy approaches to the government-nonprofit relationship since the 18th National Congress of the Communist Party of China. Nonprofit Policy Forum 9(1): 20170029.

111.

Wang

(2021) Impact of tiered pricing reform on China’s residential electricity use. China Economic Quarterly International 1(3): 177–190.

112.

Wang

Lin

C-K

Wang

, et al. (2021) Location-specific co-benefits of carbon emissions reduction from coal-fired power plants in China. Nature Communications 12(1): 6948.

113.

Wang

Chen

(2012) China’s electricity market-oriented reform: From an absolute to a relative monopoly. Energy Policy 51: 143–148.

114.

Wang

Liu

Chen

, et al. (2020) Impact of coal sector’s de-capacity policy on coal price. Applied Energy 265: 114802.

115.

World Bank (2022) GDP (current US$). Available at: https://data.worldbank.org/indicator/NY.GDP.MKTP.CD?end=2021&start=1960&view=chart (accessed 30 October 2023).

116.

Shan

Choguill

(2021) Combining behavioral interventions with market forces in the implementation of land use planning in China: A theoretical framework embedded with nudge. Land Use Policy 108: 105569.

117.

Y-C

(2017) Sinews of Power: The Politics of the State Grid Corporation of China. New York, NY: Oxford University Press.

118.

Yang

Meng

Zhou

(2018) Residential electricity pricing in China: The context of price-based demand response. Renewable and Sustainable Energy Reviews 81: 2870–2878.

119.

(2020) Beyond the state/market dichotomy: Institutional innovations in China’s electricity industry reform. Journal of Environmental Management 264: 110306.

120.

Yuan

Zhang

(2014) An analysis of development mechanism of China’s smart grid. International Journal of Energy Economics and Policy 4(2): 198–207.

121.

Yüksel

Nielson

, et al. (2014) Quantitative modelling and analysis of a Chinese smart grid: A stochastic model checking case study. International Journal on Software Tools for Technology Transfer 16(4): 421–435.

122.

Zhang

Andrews-Speed

(2020) State versus market in China’s low-carbon energy transition: An institutional perspective. Energy Research & Social Science 66: 101503.

123.

Zhang

Qin

(2015) Lessons learned from China’s residential tiered electricity pricing reform. Manitoba: The International Institute for Sustainable Development. Available at: www.iisd.org/gsi/sites/default/files/ffsr_china_lessons_learned_may_2015.pdf (accessed 1 December 2023).

124.

Zhang

Andrews-Speed

(2018) To what extent will China’s ongoing electricity market reforms assist the integration of renewable energy? Energy Policy 114: 165–172.

125.

Zhang

Shen

Yang

, et al. (2019) Smart meter and in-home display for energy savings in residential buildings: A pilot investigation in Shanghai, China. Intelligent Buildings International 11(1): 4–26.

126.

Zhou

Liu

Peng

, et al. (2022) Environmental benefits and household costs of clean heating options in northern China. Nature Sustainability 5(4): 329–338.

A functional dynamic framework for understanding new government-market relationships of smart energy transitions in China

Abstract

Keywords

Introduction

Theoretical background

SG policies from a policy mix perspectives

SG policies from a functional dynamics perspectives

The government-market dynamics and electricity market reforms

Studies on SGs in China

Towards an integrated framework

Methodology

Case context

China’s energy basic

China’s ongoing electricity market reforms: five stages and the associated government-market relationships

Major developments of SGs in China

Findings and discussions: Controlled dynamism in China’s smart energy transitions

The features and logics of a controlled dynamic approach in a controlled dynamic setting

Assessing the Achievements and Limitations of Government-Market Relationships in Fulfilling Transition Functions

Market Formation

Market regulation

Managing public goods

Networking and resource mobilisation

Policy learning

Conclusions

Footnotes

Declaration of conflicting interests

Funding

Author biographies

References