With the continuous progress of science and technology, the development of integrated agent technology is also changing with each passing day. In order to provide corresponding data support and thinking for the integrated energy agent technology, the concept of integrated energy agent technology is expounded, and the framework of distributed, hierarchical, and hybrid multi-agent system is analyzed. At the same time, the application status and future development trend of integrated energy agent technology are expounded. From the current application status, the application status of comprehensive energy agent technology is good, but there are always technical problems faced by reliability operation, including the coupling and modeling of multi-energy, the applicability of control equipment to multi-energy system, and the multi-energy fault processing of comprehensive energy system. In general, the overall architecture of the research can provide thinking and ideas for the development and field expansion of integrated energy agent technology.
PanGGuWLuY, et al.Optimal planning for electricity-hydrogen integrated energy system considering power to hydrogen and heat and seasonal storage. IEEE Trans Sustain Energy2020; 11(4): 2662–2676.
2.
ChenBChenYLiB, et al.An optimal dispatching model for integrated energy microgrid considering the reliability principal–agent contract. Sustainability2022; 14(13): 7645–7670.
3.
LiuHLiJGeS. Research on hierarchical control and optimisation learning method of multi‐energy microgrid considering multi‐agent game. IET Smart Grid2020; 3(4): 479–489.
4.
HuangBLiYZhanF, et al.A distributed robust economic dispatch strategy for integrated energy system considering cyber-attacks. IEEE Trans Ind Inf2021; 18(2): 880–890.
5.
SadeeqMAMZeebareeS. Energy management for internet of things via distributed systems. J Appl Science Technol Trends2021; 2(2): 80–92.
6.
AlsbouiTQinYHillR, et al.An energy efficient multi-mobile agent itinerary planning approach in wireless sensor networks. Computing2021; 103(9): 2093–2113.
7.
KeppoIButnarIBauerN, et al.Exploring the possibility space: taking stock of the diverse capabilities and gaps in integrated assessment models. Environ Res Lett2021; 16(5): 053006–053032.
8.
WayRIvesMCMealyP, et al.Empirically grounded technology forecasts and the energy transition. Joule2022; 6(9): 2057–2082.
9.
AftabWUsmanAShiJ, et al.Phase change material-integrated latent heat storage systems for sustainable energy solutions. Energy Environ Sci2021; 14(8): 4268–4291.
10.
ZhangNSunQYangL, et al.Event-triggered distributed hybrid control scheme for the integrated energy system. IEEE Trans Ind Inf2021; 18(2): 835–846.
11.
GeLLiuHYanJ, et al.Optimal integrated energy system planning with DG uncertainty affine model and carbon emissions charges. IEEE Trans Sustain Energy2021; 13(2): 905–918.
12.
ArsadAZHannanMAAl-ShetwiAQ, et al.Hydrogen energy storage integrated hybrid renewable energy systems: a review analysis for future research directions. Int J Hydrogen Energy2022; 47(39): 17285–17312.
13.
JadidbonabMMohammadi-IvatlooBMarzbandM, et al.Short-term self-scheduling of virtual energy hub plant within thermal energy market. IEEE Trans Ind Electron2020; 68(4): 3124–3136.
14.
YuLQinSZhangM, et al.A review of deep reinforcement learning for smart building energy management. IEEE Internet Things J2021; 8(15): 12046–12063.
15.
EdelenboschOYMiuLSachsJ, et al.Translating observed household energy behavior to agent-based technology choices in an integrated modeling framework. iScience2022; 25(3): 103905–103928.
16.
ShenYHuXWangX, et al.Integrated framework for space- and energy-efficient retrofitting in multifunctional buildings: A synergy of agent-based modeling and performance-based modeling. Build Simulat2024; 17(9): 1579–1600.
17.
HashmiSAAliCFZafarS. Internet of things and cloud computing‐based energy management system for demand side management in smart grid. Int J Energy Res2021; 45(1): 1007–1022.
18.
YueZLiuHLiY. Tri-layer low-carbon distributed optimization of integrated energy systems based on hybrid games under stochastic scenarios. IET Gener Transm Distrib2023; 17: 5323–5339.
19.
SharmaABahlSBaghaAK, et al.Multi-agent system applications to fight COVID-19 pandemic. Apollo Medicine2020; 17(1): 41–43.
20.
HernesMKorczakJDlK, et al.Multi-agent platform to support trading decisions in the FOREX market. Appl Intell2024; 54(22): 11690–11708.
21.
LiuYLiuJHeZ, et al.A survey of multi-agent systems on distributed formation control. Unmanned Syst2024; 12(05): 913–926.
22.
ZiabinaYKwilinskiALyulyovO, et al.Convergence of energy policies between the EU and Ukraine under the green deal policy. Energies2023; 16(2): 998–1035.
23.
LiJZhouT. Evolutionary multi-agent deep meta reinforcement learning method for swarm intelligence energy management of isolated multi-area microgrid with internet of things. IEEE Internet Things J2023; 10(14): 12923–12937.
24.
LazarevaGGPopovVAOkishevVA, et al.Mathematical model of thermocurrents based on calculation of electrical resistance and thermopower as an integral over electron energy. Dokl Math2024; 109(3): 238–245.
25.
HarrisonAAlombahNHde Dieu Nguimfack NdongmoJ. A new hybrid MPPT based on incremental conductance-integral backstep** controller applied to a PV system under fast-changing operating conditions. Int J Photoenergy2023; 2023(1): 9931481–9931500.
26.
TongXMaDWangR, et al.Dynamic event-triggered-based integral reinforcement learning algorithm for frequency control of microgrid with stochastic uncertainty. IEEE Trans Consum Electron2023; 69(3): 321–330.
27.
IrudayarajAXRWahabNIAVeerasamyV, et al.Decentralized frequency control of restructured energy system using hybrid intelligent algorithm and non‐linear fractional order proportional integral derivative controller. IET Renew Power Gener2023; 17(8): 2009–2037.
28.
WenLYuSZhaoY, et al.Finite-time dynamic event-triggered consensus of multi-agent systems with disturbances via integral sliding mode. Int J Control2023; 96(2): 272–281.
29.
AryaYKumarNDahiyaP, et al.Cascade‐IλDμN controller design for AGC of thermal and hydro‐thermal power systems integrated with renewable energy sources. IET Renew Power Gener2021; 15(3): 504–520.
30.
LiPLiuDBaldiS. Adaptive integral sliding mode control in the presence of state-dependent uncertainty. IEEE ASME Trans Mechatron2022; 27(5): 3885–3895.
31.
LeeDJeongJChaeYT. Application of deep reinforcement learning for proportional–integral–derivative controller tuning on air handling unit system in existing commercial building. Buildings2023; 14(1): 66–90.
32.
ApresyanLAVlasovaTVKrasovskiiVI. On local and integral forms of energy conservation laws in the scattering theory. Phys Wave Phenom2024; 32(1): 19–26.
33.
ChenLLiuNLiC, et al.Peer-to-peer energy sharing with social attributes: a stochastic leader–follower game approach. IEEE Trans Ind Inf2020; 17(4): 2545–2556.
34.
WangJZhangYLiX, et al.Finite-time consensus for nonholonomic multi-agent systems with disturbances via event-triggered integral sliding mode controller. J Franklin Inst2020; 357(12): 7779–7795.
35.
XiJWangLZhengJ, et al.Energy-constraint formation for multiagent systems with switching interaction topologies. IEEE Trans Circ Syst I2020; 67(7): 2442–2454.
36.
BagaskaraMAzizahANi’mahAF, et al.New route for synthesis and characterization sulfonated chitosan using acetyl sulfate as a sulfonating agent. J Phys: Conf Ser2022; 2190(1): 0120231–0120259.
37.
LiLMaZFanL, et al.ChatGPT in education: A discourse analysis of worries and concerns on social media. Educ Inf Technol2024; 29(9): 10729–10762.
38.
OortwijnWJansenMBaltussenR. Use of evidence-informed deliberative processes by health technology assessment agencies around the globe. Int J Health Pol Manag2020; 9(1): 27–53.
39.
ZhengTArdolinoMBacchettiA, et al.The applications of Industry 4.0 technologies in manufacturing context: a systematic literature review. Int J Prod Res2021; 59(6): 1922–1954.
40.
O’RourkeBOortwijnWSchullerT, et al.The new definition of health technology assessment: A milestone in international collaboration. Int J Technol Assess Health Care2020; 36(3): 187–190.
41.
ChenWSuYZuoJ. Agentverse: Facilitating multi-agent collaboration and exploring emergent behaviors in agents. Arxiv Preprint Arxiv:2308.108482023; 2(4): 6–34.
42.
FuXWuTLiH, et al.Study on the preparation conditions and degradation performance of an efficient immobilized microbial agent for marine oil pollution. Environ Technol2022; 43(15): 2352–2358.
43.
WuTZhouPLiuK, et al.Multi-agent deep reinforcement learning for urban traffic light control in vehicular networks. IEEE Trans Veh Technol2020; 69(8): 8243–8256.
44.
SamyMMElkhoulyHIBarakatS. Multi‐objective optimization of hybrid renewable energy system based on biomass and fuel cells. Int J Energy Res2021; 45(6): 8214–8230.
45.
GasserPLustenbergerPCinelliM, et al.A review on resilience assessment of energy systems. Sustain Resilient Infrastruct2021; 6(5): 273–299.
46.
IramRAnserMKAwanRU, et al.Prioritization of renewable solar energy to prevent energy insecurity: an integrated role. Singapore Econ Rev2021; 66(02): 391–412.
47.
GernaatDEHJde BoerHSDaioglouV, et al.Climate change impacts on renewable energy supply. Nat Clim Change2021; 11(2): 119–125.
48.
SalamehTAbdelkareemMAOlabiAG, et al.Integrated standalone hybrid solar PV, fuel cell and diesel generator power system for battery or supercapacitor storage systems in Khorfakkan, United Arab Emirates. Int J Hydrogen Energy2021; 46(8): 6014–6027.
49.
LiuQSunSRongB, et al.Intelligent reflective surface based 6G communications for sustainable energy infrastructure. IEEE Wireless Commun2021; 28(6): 49–55.
50.
AlSkaifTCrespo-VazquezJLSekuloskiM, et al.Blockchain-based fully peer-to-peer energy trading strategies for residential energy systems. IEEE Trans Ind Inf2021; 18(1): 231–241.
51.
HeGMichalekJKarS, et al.Utility-scale portable energy storage systems. Joule2021; 5(2): 379–392.
52.
AinouFZAliMSadiqM. Green energy security assessment in Morocco: green finance as a step toward sustainable energy transition. Environ Sci Pollut Res Int2023; 30(22): 61411–61429.
53.
OdukomaiyaAWoodsJJamesN, et al.Addressing energy storage needs at lower cost via on-site thermal energy storage in buildings. Energy Environ Sci2021; 14(10): 5315–5329.
54.
LudererGMadedduSMerfortL, et al.Impact of declining renewable energy costs on electrification in low-emission scenarios. Nat Energy2022; 7(1): 32–42.
55.
JiangYWanCBotterudA, et al.Efficient robust scheduling of integrated electricity and heat systems: A direct constraint tightening approach. IEEE Trans Smart Grid2021; 12(4): 3016–3029.
56.
WangYXuPZhangZ, et al.Control optimization for heat source temperature of vacuum belt drying system based on fuzzy control and integral control. Energies2024; 17(15): 3824–3851.
57.
El HajYSoodVK. Linear quadratic Gaussian controller for single-ended primary inductor converter via integral linear quadratic regulator merged with an Offline Kalman Filter. Energies2024; 17(14): 3385–3402.
58.
AidSEBoukabchaHBentridiSE. Path integral solution for a Dirac particle in a generalized inverse quadratic Yukawa potential. Phys Scripta2024; 99(9): 095408–095431.
59.
FrabouletKEbranJP. Addressing energy density functionals in the language of path-integrals II: comparative study of functional renormalization group techniques applied to the (0+ 0)-DO (N)-symmetric φ 4-theory. Eur Phys J A2024; 60(2): 45–73.
60.
DiakonovDV. Is the Euclidean path integral always equal to the thermal partition function. J High Energy Phys2024; 2024(4): 1–32.
61.
LiBChenYWeiW, et al.Online coordination of LNG tube trailer dispatch and resilience restoration of integrated power-gas distribution systems. IEEE Trans Smart Grid2022; 13(3): 1938–1951.
62.
KermaniMShirdareEPariseG, et al.A comprehensive technoeconomic solution for demand control in ports: energy storage systems integration. IEEE Trans Ind Appl2022; 58(2): 1592–1601.
63.
LiuJAlexanderSMarcianòA, et al.A path integral formula of quantum gravity emergent from entangled local structures. J High Energy Phys2024; 2024(7): 1–33.
64.
DuhirwePNHwangJKNgarambeJ, et al.A novel deep learning‐based integrated photovoltaic, energy storage system and electric heat pump system: optimising energy usage and costs. Int J Energy Res2021; 45(6): 9306–9325.
65.
ShenYGuCXiangY, et al.Dynamic service restoration for integrated energy systems under seismic stress. IEEE Trans Sustain Energy2022; 13(1): 527–536.
66.
WangCWeiWXieY, et al.Capacity sizing of the integrated wind-solar-storage system: A nested game approach. IET Gener Transm Distrib2022; 16(14): 2852–2863.
