Application Conditions of Bounded Rationality and a Microgrid Energy Management Control Strategy Combining Real-Time Power Price and Demand-Side Response

被引:16
|
作者
Wu, Nan [1 ,2 ]
Wang, Honglei [1 ]
Yin, Linfei [3 ]
Yuan, Xufeng [4 ]
Leng, Xiaoxia [1 ]
机构
[1] Guizhou Univ, Sch Management, Guiyang 550025, Peoples R China
[2] Guizhou Normal Univ, Sch Mech & Elect Engn, Guiyang 550025, Peoples R China
[3] Guangxi Univ, Coll Elect Engn, Nanning 530004, Peoples R China
[4] Guizhou Univ, Coll Elect Engn, Guiyang 550025, Peoples R China
来源
IEEE ACCESS | 2020年 / 8卷
关键词
Microgrids; Optimization; Energy management; Real-time systems; Power supplies; Supply and demand; Heuristic algorithms; Microgrid; real-time power price; demand-side response; deep adaptive dynamic programming optimization algorithm; energy management; bounded rationality; RENEWABLE INTEGRATION; STORAGE MANAGEMENT; SYSTEM; OPTIMIZATION; OPERATION; COST; UNIT;
D O I
10.1109/ACCESS.2020.3045754
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Microgrid energy management is a typical discrete non-linear optimization problem that is usually solved by off-line optimization, day-ahead demand-side management, and long-term dynamic optimization scheduling strategy. However, due to the intermittent distributed generation and time-varying load in microgrids, more attention should be paid to the real-time optimal scheduling of the overall operation of energy to ensure the dynamic balance of supply and demand in microgrids. Combining demand-side response with real-time power price, this paper applies the strategy to microgrid energy management and proposes a distributed energy real-time management model of microgrid based on demand-side response function. A deep adaptive dynamic programming optimization algorithm is also proposed for the model. The real-time interaction between microgrid operators and users is realized. The closed-loop feedback control structure of the proposed model ensures the real-time optimization control strategy. Therefore, the proposed energy management model and control strategy can realize intra-day dispatching in microgrids. The real-time performance and effectiveness of the proposed energy management model and control strategy are also verified by numerical simulation. Finally, since the proposed model is approximate, whether the solution obtained by the algorithm is the optimal or satisfactory solution of the optimization strategy set is a lack of theoretical support. Therefore, according to the approximation theorem of bounded rationality, the application conditions of the model in power markets are proposed. It is proved that the proposed model meets the application conditions, and is a specific application of bounded rationality approaching complete rationality in the power market. It is also proved that the best solution is involved in the satisfactory solution set of the model. Thus, the control strategy is a rational and feasible optimal management control strategy, which provides a theoretical basis for its further implementation.
引用
收藏
页码:227327 / 227339
页数:13
相关论文
共 50 条
  • [31] Demand-side response power control strategy considering load production sequence requirements
    Wang, Xi
    Chen, Zhen
    Xie, Haocong
    Liao, Siyang
    Ye, Xi
    Chen, Gang
    FRONTIERS IN ENERGY RESEARCH, 2024, 12
  • [32] A Novel Demand Side Management Strategy Implementation Utilizing Real-Time Pricing Schemes
    Panapakidis, Ioannis P.
    Christoforidis, Georgios C.
    Asimopoulos, Nikolaos
    Dagoumas, Athanasios S.
    2017 1ST IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2017 17TH IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC / I&CPS EUROPE), 2017,
  • [33] A Grid-Connected Microgrid Model and Optimal Scheduling Strategy Based on Hybrid Energy Storage System and Demand-Side Response
    Jing, Yaqian
    Wang, Honglei
    Hu, Yujie
    Li, Chengjiang
    ENERGIES, 2022, 15 (03)
  • [34] Data-driven real-time price-based demand response for industrial facilities energy management
    Lu, Renzhi
    Bai, Ruichang
    Huang, Yuan
    Li, Yuting
    Jiang, Junhui
    Ding, Yuemin
    APPLIED ENERGY, 2021, 283
  • [35] Distributed real-time power management for virtual energy storage systems using dynamic price
    Kang, Wenfa
    Chen, Minyou
    Lai, Wei
    Luo, Yanyu
    ENERGY, 2021, 216
  • [36] Real-Time Energy Management Strategy for Fuel Cell Range Extender Vehicles Based on Nonlinear Control
    Zhang, Yuanzhi
    Zhang, Caizhi
    Huang, Zhiyu
    Xu, Liangfei
    Liu, Zhitao
    Liu, Mingchun
    IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION, 2019, 5 (04): : 1294 - 1305
  • [37] Comprehensive Real-Time Microgrid Power Management and Control With Distributed Agents
    Colson, C. M.
    Nehrir, M. Hashem
    IEEE TRANSACTIONS ON SMART GRID, 2013, 4 (01) : 617 - 627
  • [38] Real-time resilient microgrid power management based on multi-agent systems with price forecast
    Victorio, Marcos Eduardo Cruz
    Kazemtabrizi, Behzad
    Shahbazi, Mahmoud
    IET SMART GRID, 2023, 6 (02) : 190 - 204
  • [39] Scenario-Based Real-Time Demand Response Considering Wind Power and Price Uncertainty
    Wei, Ming
    Zhong, Jin
    2015 12TH INTERNATIONAL CONFERENCE ON THE EUROPEAN ENERGY MARKET (EEM), 2015,
  • [40] A modified model-free-adaptive-control-based real-time energy management strategy for plug-in hybrid electric vehicle
    Liu, Xiaodong
    Guo, Hongqiang
    Du, Juan
    Zhao, Xuan
    ENERGY SCIENCE & ENGINEERING, 2022, 10 (10) : 4007 - 4024