A Two-Stage Game-Theoretic Method for Residential PV Panels Planning Considering Energy Sharing Mechanism

被引:36
|
作者
Xu, Xu [1 ,2 ]
Li, Jiayong [3 ]
Xu, Yan [2 ]
Xu, Zhao [4 ,5 ]
Lai, Chun Sing [6 ,7 ]
机构
[1] Hong Kong Polytech Univ, Dept Elect Engn, Hung Hom, Hong Kong, Peoples R China
[2] Nanyang Technol Univ, Sch Elect & Elect Engn, Singapore 639798, Singapore
[3] Hunan Univ, Coll Elect & Informat Engn, Changsha, Peoples R China
[4] Hong Kong Polytech Univ, Shenzhen Res Inst, Hong Kong, Peoples R China
[5] Hong Kong Polytech Univ, Dept Elect Engn, Hong Kong, Peoples R China
[6] Brunel Univ London, Dept Elect & Comp Engn, London UB8 3PH, England
[7] Guangdong Univ Technol, Dept Elect Engn, Guangzhou 510006, Peoples R China
基金
中国国家自然科学基金;
关键词
Planning; Load flow; Numerical models; Load modeling; Stochastic processes; Search problems; Electronic mail; Residential photovoltaic panels planning; energy sharing mechanism; Stackelberg game; descend search algorithm; optimal power flow problem; RENEWABLE ENERGY; ELECTRICITY PRICES; TRADING FRAMEWORK; OPTIMAL PLACEMENT; SOLAR PV; BUILDINGS; BARRIERS; REDUCTION; NETWORKS; CAPACITY;
D O I
10.1109/TPWRS.2020.2985765
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper proposes a novel two-stage game-theoretic residential photovoltaic (PV) panels planning framework for distribution grids with potential PV prosumers. One innovative contribution is that a residential PV panels location-allocation model is integrated with the energy sharing mechanism to increase economic benefits to PV prosumers and meanwhile facilitate the reasonable installation of residential PV panels. The optimization of residential PV panels planning decisions is formulated as a two-stage model. In the first stage, we develop a Stackelberg game based stochastic bi-level energy sharing model to determine the optimal sizing of PV panels with uncertain PV energy output, load demand, and electricity price. Instead of directly solving the proposed bi-level energy sharing problem by using commercial solvers, we develop an efficient descend search algorithm-based solution method which can significantly improve the computation efficiency. In the second stage, we propose a stochastic programming based residential PV panels deployment model for all PV prosumers. This model is formulated as an optimal power flow (OPF) problem to minimize active power loss. Finally, simulations on an IEEE 33-node and 123-node test systems demonstrate the effectiveness of the proposed method.
引用
收藏
页码:3562 / 3573
页数:12
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