Pricing Strategy of Multi-Energy Provider Considering Integrated Demand Response

被引:23
|
作者
Yang, Zhihao [1 ]
Ni, Ming [1 ,2 ]
Liu, Haoming [1 ]
机构
[1] Hohai Univ, Coll Energy & Elect Engn, Nanjing 211100, Peoples R China
[2] NARI Grp Corp, State Key Lab Smart Grid Protect & Control, Nanjing 210003, Peoples R China
来源
IEEE ACCESS | 2020年 / 8卷
基金
中国国家自然科学基金;
关键词
Water heating; Pricing; Load modeling; Resistance heating; Thermal loading; Natural gas; Cooling; Integrated demand response (IDR); residential user (RU); multi-energy provider (MEP); Stackelberg game; pricing strategy; bi-level programing; ENERGY; ELECTRICITY; MANAGEMENT; MODEL; MARKET;
D O I
10.1109/ACCESS.2020.3016005
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Residential users (RUs) are the vital component of terminal energy consumption. The development and application of integrated energy system (IES) and smart homes has promoted RUs to actively take part in the trading with multi-energy provider (MEP) for its preferential energy prices and services. This paper proposes a pricing strategy of MEP by using a Stackelberg game-based bi-level programming model. In the upper level model, the adjustment coefficient of electric power price is optimized by MEP to increase the trading probability with RUs. In the lower level model, an integrated demand response (IDR) program is proposed for RUs to optimize the flexible loads in home energy management system (HEMS). Specially, a HEMS is composed of a smart interactive terminal, a micro combined cooling, heating, and power (mCCHP) system and multi-energy loads. Case study shows that, on one hand, the energy optimization based on IDR can help RUs manage their multi-energy loads and reduce the expected energy cost. On the other hand, the proposed price strategy of MEP can increase the trading probability, which promote more RUs to trade with MEP, thus increasing the MEP's benefit by 12.29%. The research proves that the proposed strategy is a win-win strategy and it is efficient in the pre-decision-making progress for MEP in the energy trading market.
引用
收藏
页码:149041 / 149051
页数:11
相关论文
共 50 条
  • [31] Information gap-based scheduling strategy of a multi-energy retailer with integrated demand response program
    Liu, Yishu
    Zhang, Qi
    Huang, Lihua
    SUSTAINABLE CITIES AND SOCIETY, 2022, 78
  • [32] Joint Optimization of Planning and Operation in Multi-Region Integrated Energy Systems Considering Flexible Demand Response
    Gao, Shan
    Song, Tiancheng E.
    Liu, Sai
    Zhou, Cheng
    Xu, Chenkai
    Guo, Haomin
    Li, Xiaogang
    Li, Zheng
    Liu, Yu
    Jiang, Weiyi
    Wang, Juncheng
    Wang, Sicheng
    IEEE ACCESS, 2021, 9 : 75840 - 75863
  • [33] Transmission expansion planning for multi-energy system with integrated demand response
    Huang, Yichao
    Cong, Hao
    Yang, Jianlin
    Pang, Aili
    Lan, Li
    Wang, Xu
    2018 2ND IEEE CONFERENCE ON ENERGY INTERNET AND ENERGY SYSTEM INTEGRATION (EI2), 2018, : 141 - 146
  • [34] A Reliability Model for Integrated Energy System Considering Multi-energy Correlation
    Yan, Chao
    Bie, Zhaohong
    Liu, Shiyu
    Urgun, Dogan
    Singh, Chanan
    Xie, Le
    JOURNAL OF MODERN POWER SYSTEMS AND CLEAN ENERGY, 2021, 9 (04) : 811 - 825
  • [35] A multi-energy pricing strategy for port integrated energy system based on Bayesian Stackelberg game
    Yang, Jie
    Wang, Jinqiu
    Ma, Kai
    Liu, Hongru
    Dai, Yachao
    Li, Conghui
    SUSTAINABLE ENERGY GRIDS & NETWORKS, 2024, 38
  • [36] Customised Multi-Energy Pricing: Model and Solutions
    Hong, Qiuyi
    Meng, Fanlin
    Liu, Jian
    ENERGIES, 2023, 16 (04)
  • [37] Optimal Expansion Planning Model for Integrated Energy System Considering Integrated Demand Response and Bidirectional Energy Exchange
    Dong, Wenkai
    Lu, Zhigang
    He, Liangce
    Zhang, Jiangfeng
    Ma, Tao
    Cao, Xiaobo
    CSEE JOURNAL OF POWER AND ENERGY SYSTEMS, 2023, 9 (04): : 1449 - 1459
  • [38] Multi-Objective Optimization for Smart Integrated Energy System Considering Demand Responses and Dynamic Prices
    Zhang, Dongdong
    Zhu, Hongyu
    Zhang, Hongcai
    Goh, Hui Hwang
    Liu, Hui
    Wu, Thomas
    IEEE TRANSACTIONS ON SMART GRID, 2022, 13 (02) : 1100 - 1112
  • [39] A Hybrid Stochastic-Interval Operation Strategy for Multi-Energy Microgrids
    Jiang, Yibao
    Wan, Can
    Chen, Chen
    Shahidehpour, Mohammad
    Song, Yonghua
    IEEE TRANSACTIONS ON SMART GRID, 2020, 11 (01) : 440 - 456
  • [40] Natural gas demand response strategy considering user satisfaction and load volatility under dynamic pricing
    Zeng, Huibin
    Shao, Bilin
    Dai, Hongbin
    Yan, Yichuan
    Tian, Ning
    ENERGY, 2023, 277