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Energy Pricing and Management for the Integrated Energy Service Provider: A Stochastic Stackelberg Game Approach
被引:6
|作者:
Wang, Haibing
[1
]
Wang, Chengmin
[2
]
Sun, Weiqing
[1
]
Khan, Muhammad Qasim
[2
]
机构:
[1] Univ Shanghai Sci & Technol, Dept Elect Engn, 516 Jungong Rd, Shanghai 200093, Peoples R China
[2] Minist Educ, Key Lab Control Power Transmiss & Convers SJTU, 800 Dongchuan Rd, Shanghai 200240, Peoples R China
来源:
基金:
中国国家自然科学基金;
关键词:
integrated energy service provider;
stochastic programing;
Stackelberg game;
demand response;
interactive operation;
RETAIL COMPETITION;
SYSTEMS;
MODEL;
SECURITY;
MARKET;
POWER;
GAS;
D O I:
10.3390/en15197326
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:
As a retailer between the energy suppliers and end users, the integrated energy service provider (IESP) can effectively coordinate the energy supply end and the energy use end by setting energy prices and energy management. Because most of the current research focuses on the pricing of electricity retailers, there are few studies on IESP energy pricing and management, which are still at the initial stage. At the same time, the existing research often does not consider the impact of demand response (DR) and uncertainties, such as natural gas and electricity wholesale prices, on the pricing of IESP. It is necessary to model the DR and uncertainties in the integrated energy system. Aiming at the inadequacy of the existing research and to address the energy pricing and management of IESP, this paper develops a two-stage stochastic hierarchical framework, which comprehensively considers the DR strategy of the user end, characteristics of the electricity/gas/heat storage and the uncertainties of electricity and gas wholesale prices. The proposed hierarchical model for energy pricing and management is a two-layer model: the upper layer is the problem of maximizing the benefits of IESP, and the lower layer is the problem of minimizing the energy cost of user agents. Through the complementary transformation, the linearization method and the strong duality principle in the optimization theory, the model is transformed into a mixed-integer linear programing (MILP) problem, which can be easily solved by the off-shelf commercial solver. Finally, the simulation results are provided to demonstrate the interactive operation between the IESP and user agent through energy prices setting, DR strategy and energy management.
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页数:15
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