The growing emphasis on electrification has heightened the importance of reliable electricity supply. In South Korea, the government is advancing market reforms, including the introduction of capacity and ancillary service markets, to enhance electricity system reliability. Within this context, this study aims to estimate the willingness to pay (WTP) of residential electricity consumers to avoid power outages using the contingent valuation method (CVM). The resulting WTP values are used to derive the value of lost load, which serves as a key indicator for reliability investment. Based on a dataset of 1000 South Korean households, we employed both CVM and choice experiments as empirical approaches. The results indicate a WTP of 8.16% and a willingness to accept of 18.08% of the monthly electricity bill, which correspond to outage costs of USD 2.76 and USD 6.11 per kWh, respectively. Choice experiment results show that WTP varies from 0% to 26.6% depending on outage scenarios, highlighting the significant seasonal sensitivity of residential outage costs. These findings provide critical insights for policymakers seeking to design a more reliable electricity market aligned with net-zero objectives. By incorporating residential Value of Lost Load into electricity market planning, governments can better incentivize investments in flexibility and resilience, thereby mitigating outage risks in future low-carbon power systems.
TrudenCWankmüllerCZehetnerD,et al.Location and capacity allocation for emergency contact points in large-scale power outages. Cent Eur J Oper Res2025; 33: 241–276.
2.
Bajo-BuenestadoR. The effect of blackouts on household electrification status: evidence from Kenya. Energy Econ2021; 94: 105067.
3.
OseniMOPollittMG. A firm-level analysis of outage loss differentials and self-generation: evidence from African business enterprises. Energy Econ2015; 52: 277–286.
4.
PerilloFda SilvaPPCerqueiraPA. Decoupling efficiency from electricity intensity: an empirical assessment in the EU. Energy Policy2022; 169: 113171.
5.
SternNValeroA. Innovation, growth and the transition to net-zero emissions. Res Policy2021; 50: 104293.
6.
NamEJinT. Mitigating carbon emissions by energy transition, energy efficiency, and electrification: difference between regulation indicators and empirical data. J Clean Prod2021; 300: 126962.
7.
KhalidM. Smart grids and renewable energy systems: perspectives and grid integration challenges. Energy Strategy Reviews2024; 51: 101299.
8.
MacmillanMWilsonKBaikS, et al.Shedding light on the economic costs of long-duration power outages: a review of resilience assessment methods and strategies. Energy Res Soc Sci2023; 99: 103055.
9.
SinselSRRiemkeRLHoffmannVH. Challenges and solution technologies for the integration of variable renewable energy sources—a review. Renew Energy2020; 145: 2271–2285.
10.
RaniPParkashVSharmaNK. Technological aspects, utilization and impact on power system for distributed generation: a comprehensive survey. Renewable Sustainable Energy Rev2024; 192: 114257.
11.
YangXWangXLuZ, et al.Distribution network tariff design: facilitate flexible resource under uncertain future energy scenarios. Energy Policy2024; 188: 114075.
12.
LüthAWernerYEgging-BratsethR,et al.Electrolysis as a flexibility resource on energy islands: the case of the North Sea. Energy Policy2024; 185: 113921.
13.
AnwarMBGuoNSunY,et al.Can wholesale electricity markets achieve resource adequacy and high clean energy generation targets in the presence of self-interested actors?Appl Energy2024; 359: 122774.
14.
JinTLeeTEKimD. Value of lost load estimation for the South Korea’s manufacturing sector—finding the gap between the supply and demand side. Renewable Sustainable Energy Rev2023; 187: 113753.
15.
JinTLeeTEKimD. Valuing flexible resources in the Korean electricity market based on stated preference methods. Util Policy2024; 88: 101733.
16.
KimKChoY. Estimation of power outage costs in the industrial sector of South Korea. Energy Policy2017; 101: 236–245.
17.
YooSHKimHJParkS, et al.Economic Valuation of Industrial Electricity in South Korea. Seoul National University of Science and Technology. 2017.
18.
SchröderTKuckshinrichsW. Value of lost load: an efficient economic indicator for power supply security? A literature review. Front Energy Res2015; 3: 55.
19.
GrowitschCMalischekRNickS,et al.The costs of power interruptions in Germany-an Assessment in the light of the Energiewende. EWI working paper. 2013.
20.
GormanW. The quest to quantify the value of lost load: a critical review of the economics of power outages. Electricity J2022; 35: 107187.
21.
ChoS. A Study on the Improvement of the Preliminary Feasibility Study System for Public Utilities in the Electric Power Sector. Ulsan. 2024.
22.
JinTLeeTE. A study on value of lost load (VoLL) to secure flexible resources required to the net-zero of electricity market (2/3) (in Korean). Ulsan. 2023.
23.
BliemM. Economic valuation of electrical service reliability in Austria-a choice experiment approach. Institute for Advanced Studies Carinthia, Working Paper 1. 2009.
24.
ReichlJSchmidthalerMSchneiderF. The value of supply security: the costs of power outages to Austrian households, firms and the public sector. Energy Econ2013; 36: 256–261.
25.
WolfAWenzelL. Regional diversity in the costs of electricity outages: results for German counties. Util Policy2016; 43: 195–205.
26.
KhannaSRoweK. The long-run value of electricity reliability in India. Resour Energy Econ2024; 77: 101425.
27.
BlassAALachSManskiCF. Using elicited choice probabilities to estimate random utility models: preferences for electricity reliability. Int Econ Rev (Philadelphia)2010; 51: 421–440.
28.
PwC. Estimating the Value of Lost Load in New Zealand. Wellington2018.
29.
OseniMO. Self-generation and households’ willingness to pay for reliable electricity service in Nigeria. Energy J2017; 38: 165–194.
30.
KjølleGHSamdalKSinghB,et al.Customer costs related to interruptions and voltage problems: methodology and results. IEEE Trans Power Syst2008; 23: 1030–1038.
31.
YooSHHuhSYKimHJ, et al.Economic Valuation of Residential Electricity in South Korea. Seoul National University of Science and Technology. 2019.
32.
MotzA. Security of supply and the energy transition: the households’ perspective investigated through a discrete choice model with latent classes. Energy Econ2021; 97: 105179.
33.
BaikSDavisALParkJW, et al.Estimating what US residential customers are willing to pay for resilience to large electricity outages of long duration. Nat Energy2020; 5: 250–258.
34.
GormanWCallawayD. Do notifications affect households’ willingness to pay to avoid power outages? Evidence from an experimental stated-preference survey in California. Electricity J2024; 37: 107385.
35.
KüfeoğluSLehtonenM. Comparison of different models for estimating the residential sector customer interruption costs. Electr Power Syst Res2015; 122: 50–55.
36.
PraktiknjoAJ. Stated preferences based estimation of power interruption costs in private households: an example from Germany. Energy2014; 76: 82–90.
37.
AbrateGBrunoCErbettaF, et al.A choice experiment on the willingness of households to accept power outages. Util Policy2016; 43: 151–164.
38.
BertazziAFumagalliESchiavoL. The use of customer outage cost surveys in policy decision-making: the Italian experience in regulating quality of electricity supply. In: CIRED 2005-18th International conference and exhibition on electricity distribution. Turin, Italy: IET, 2005, pp.1–5.
39.
BaarsmaBEHopJP. Pricing power outages in The Netherlands. Energy2009; 34: 1378–1386.
40.
HensherDAShoreNTrainK. Willingness to pay for residential electricity supply quality and reliability. Appl Energy2014; 115: 280–292.
41.
PepermansG. The value of continuous power supply for Flemish households. Energy Policy2011; 39: 7853–7864.
42.
MelesTH. Impact of power outages on households in developing countries: evidence from Ethiopia. Energy Econ2020; 91: 104882.
43.
AwekeATNavrudS. Valuing energy poverty costs: household welfare loss from electricity blackouts in developing countries. Energy Econ2022; 109: 105943.
44.
AmoahAFerriniSSchaafsmaM. Electricity outages in Ghana: are contingent valuation estimates valid?Energy Policy2019; 135: 110996.
45.
WooCKHoTShiuA, et al.Residential outage cost estimation: Hong Kong. Energy Policy2014; 72: 204–210.
46.
BigernaSChoudharyPJainNK, et al.An empirical investigation of the Indian households’ willingness to pay to avoid power outages. Energy Policy2024; 184: 113883.
47.
HashemiM. The economic value of unsupplied electricity: evidence from Nepal. Energy Econ2021; 95: 105124.
48.
OzbafliAJenkinsGP. The willingness to pay by households for improved reliability of electricity service in North Cyprus. Energy Policy2015; 87: 359–369.
49.
VennemoHRosnesOSkulstadA. The cost to households of a large electricity outage. Energy Econ2022; 116: 106394.
50.
KimKNamHChoY. Estimation of the inconvenience cost of a rolling blackout in the residential sector: the case of South Korea. Energy Policy2015; 76: 76–86.
51.
KimJHLimKKYooSH. Evaluating residential consumers’ willingness to pay to avoid power outages in South Korea. Sustainability2019; 11: 1258.
52.
KimCSJoMKooY. Ex-ante evaluation of economic costs from power grid blackout in South Korea. J Electrical Eng Technol2014; 9: 796–802.
53.
CarlssonFMartinssonP. Does it matter when a power outage occurs?—A choice experiment study on the willingness to pay to avoid power outages. Energy Econ2008; 30: 1232–1245.
54.
CarlssonFKatariaMLampiE,et al.Past and present outage costs–A follow-up study of households’ willingness to pay to avoid power outages. Resour Energy Econ2021; 64: 101216.
55.
MorrisseyKPlaterADeanM. The cost of electric power outages in the residential sector: a willingness to pay approach. Appl Energy2018; 212: 141–150.
56.
CohenJJMoeltnerKReichlJ,et al.Linking the value of energy reliability to the acceptance of energy infrastructure: evidence from the EU. Resour Energy Econ2016; 45: 124–143.
57.
CohenJMoeltnerKReichlJ,et al.Effect of global warming on willingness to pay for uninterrupted electricity supply in European nations. Nat Energy2018; 3: 37–45.
58.
LebeauAPetitetMQueminS,et al.Long-term issues with the energy-only market design in the context of deep decarbonization. Energy Econ2024; 132: 107418.
59.
LiuYWangLDengY. Electricity generation and economic performance: on the 2021 Texas power crisis. Electricity J2024; 37: 107367.
60.
CarlssonFMartinssonPAkayA. The effect of power outages and cheap talk on willingness to pay to reduce outages. Energy Econ2011; 33: 790–798.
61.
WooCKTishlerAZarnikauJ,et al.Average residential outage cost estimates for the lower 48 states in the US. Energy Econ2021; 98: 105270.
62.
ArrowKSolowRPortneyPR, et al.Report of the NOAA panel on contingent valuation. Fed Regist1993; 58: 4601–4614.
63.
HanemannWM. Welfare evaluations in contingent valuation experiments with discrete responses. Am J Agric Econ1984; 66: 332–341.
64.
KrutillaJV. Conservation reconsidered. Am Econ Rev1967; 57: 777–786.
65.
JohnstonRJBoyleKJAdamowiczW, et al.Contemporary guidance for stated preference studies. J Assoc Environ Resour Econ2017; 4: 319–405.
66.
BishopRCHeberleinTA. Measuring values of extramarket goods: are indirect measures biased?Am J Agric Econ1979; 61: 926–930.
67.
HanemannWM. Willingness to pay and willingness to accept: how much can they differ?Am Econ Rev1991; 81: 635–647.
68.
KriströmB. Spike models in contingent valuation. Am J Agric Econ1997; 79: 1013–1023.
HaabTCMcConnellKE. Valuing environmental and natural resources: the econometrics of non-market valuation. Edward Elgar Publishing, 2002.
71.
KrinskyIRobbAL. On approximating the statistical properties of elasticities. Rev Econ Stat1986; 68: 715–719.
72.
JamilFIslamTU. Outage-induced power backup choice in Pakistan. Util Policy2023; 82: 101589.
73.
TrainKE. Discrete choice methods with simulation. Cambridge university press, 2009.
74.
BirolEKarousakisKKoundouriP. Using a choice experiment to account for preference heterogeneity in wetland attributes: the case of Cheimaditida wetland in Greece. Ecol Econ2006; 60: 145–156.
75.
MeyerhoffJLiebeUHartjeV. Benefits of biodiversity enhancement of nature-oriented silviculture: evidence from two choice experiments in Germany. J For Econ2009; 15: 37–58.
76.
Korea Electric Power Corporation (KEPCO). Statistics of Electric Power in KOREA. Naju. 2023; 92.
77.
World Bank. World Development Indicators [WWW Document]2024.
78.
BusbyJWBakerKBazilianMD, et al.Cascading risks: understanding the 2021 winter blackout in Texas. Energy Res Soc Sci2021; 77: 102106.
79.
DrichoutisACLuskJLPappaV. Elicitation formats and the WTA/WTP gap: a study of climate neutral foods. Food Policy2016; 61: 141–155.
80.
London Economics. The value of lost load (VoLL) for electricity in Great Britain. Final report for OFGEM and DECC2013.
