Optimal Configuration of Electricity-Heat Integrated Energy Storage Supplier and Multi-Microgrid System Scheduling Strategy Considering Demand Response

被引:1
作者
Liu, Yuchen [1 ]
Dou, Zhenhai [1 ]
Wang, Zheng [1 ]
Guo, Jiaming [1 ]
Zhao, Jingwei [2 ]
Yin, Wenliang [1 ]
机构
[1] Shandong Univ Technol, Sch Elect & Elect Engn, Zibo 255000, Peoples R China
[2] State Power Investment Corp Haiyang Offshore Wind, Guangzhou 510710, Peoples R China
基金
中国国家自然科学基金;
关键词
multi-microgrid system; electricity-heat integrated energy storage supplier; demand response; bi-level optimization model; OPTIMIZATION;
D O I
10.3390/en17215436
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Shared energy storage system provides an attractive solution to the high configuration cost and low utilization rate of multi-microgrid energy storage system. In this paper, an electricity-heat integrated energy storage supplier (EHIESS) containing electricity and heat storage devices is proposed to provide shared energy storage services for multi-microgrid system in order to realize mutual profits for different subjects. To this end, electric boiler (EB) is introduced into EHIESS to realize the electricity-heat coupling of EHIESS and improve the energy utilization rate of electricity and heat storage equipment. Secondly, due to the problem of the uncertainty in user-side operation of multi-microgrid system, a price-based demand response (DR) mechanism is proposed to further optimize the resource allocation of shared electricity and heat energy storage devices. On this basis, a bi-level optimization model considering the capacity configuration of EHIESS and the optimal scheduling of multi-microgrid system is proposed, with the objectives of maximizing the profits of energy storage suppliers in upper-level and minimizing the operation costs of the multi-microgrid system in lower-level, and solved based on the Karush-Kuhn-Tucker (KKT) condition and Big-M method. The simulation results show that in case of demand response, the total operation cost of multi-microgrid system and the total operation profit of EHIESS are 51,687.73 and 11,983.88 CNY, respectively; and the corresponding electricity storage unit capacity is 9730.80 kWh. The proposed model realizes the mutual profits of EHIESS and multi-microgrid system.
引用
收藏
页数:23
相关论文
共 50 条
  • [31] Two-stage optimal scheduling of community integrated energy system considering demand response
    Liu R.
    Li Y.
    Yang X.
    Li Y.
    Sun G.
    Shi S.
    Taiyangneng Xuebao/Acta Energiae Solaris Sinica, 2021, 42 (09): : 46 - 54
  • [32] An Optimal Scheduling Strategy for Integrated Energy Systems Using Demand Response
    Lin, Shunfu
    Lin, Mengchen
    Shen, Yunwei
    Li, Dongdong
    FRONTIERS IN ENERGY RESEARCH, 2022, 10
  • [33] Economic-environmental risk-averse optimal heat and power energy management of a grid-connected multi microgrid system considering demand response and bidding strategy
    Rezaei, Navid
    Pezhmani, Yasin
    Khazali, Amirhossein
    ENERGY, 2022, 240
  • [34] Bi-level stochastic modeling of multi-microgrid transactive energy system via coalition formation considering battery storage and demand response programs
    Norouzi, Fahimeh
    Jadid, Shahram
    JOURNAL OF ENERGY STORAGE, 2025, 111
  • [35] 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)
  • [36] Optimal Planning of Multi-Microgrid System With Shared Energy Storage Based on Capacity Leasing and Energy Sharing
    Han, Jianpei
    Fang, Yuchen
    Li, Yaowang
    Du, Ershun
    Zhang, Ning
    IEEE TRANSACTIONS ON SMART GRID, 2025, 16 (01) : 16 - 31
  • [37] Optimal Scheduling of Regional Integrated Energy Systems Considering Hybrid Demand Response
    Lyu, Ganyun
    Cao, Bin
    Jia, Dexiang
    Wang, Nan
    Li, Jun
    Chen, Guangyu
    CSEE JOURNAL OF POWER AND ENERGY SYSTEMS, 2024, 10 (03): : 1208 - 1219
  • [38] Renewable hybrid energy system scheduling strategy considering demand response
    Guo, Minghao
    Wang, Wei
    Chen, Renhui
    SUSTAINABLE ENERGY TECHNOLOGIES AND ASSESSMENTS, 2022, 52
  • [39] Integrated Optimal Energy Management of Multi-Microgrid Network Considering Energy Performance Index: Global Chance-Constrained Programming Framework
    Hemmati, Mohammad
    Bayati, Navid
    Ebel, Thomas
    ENERGIES, 2024, 17 (17)
  • [40] Optimal Multi-Objective Power Scheduling of a Residential Microgrid Considering Renewable Sources and Demand Response Technique
    Gamil, Mahmoud M.
    Ueda, Soichirou
    Nakadomari, Akito
    Konneh, Keifa Vamba
    Senjyu, Tomonobu
    Hemeida, Ashraf M.
    Lotfy, Mohammed Elsayed
    SUSTAINABILITY, 2022, 14 (21)