TY - JOUR
T1 - A Two-stage game-Theoretic method for residential pv panels planning considering energy sharing mechanism
AU - Xu, Xu
AU - Li, Jiayong
AU - Xu, Yan
AU - Xu, Zhao
AU - Lai, Chun Sing
N1 - Funding Information:
Manuscript received June 10, 2019; revised November 4, 2019 and January 18, 2020; accepted March 21, 2020. Date of publication April 14, 2020; date of current version August 24, 2020. This work was supported in part by the National Natural Science Foundation of China under Grant 71971183. The work of J. Li was supported by the National Natural Science Foundation of China under Grant 51907056. The work of Y. Xu’s work was supported by Nanyang Assistant Professorship from Nanyang Technological University, Singapore. Paper no. TPWRS-00819-2019. (Corresponding author: Zhao Xu.) Xu Xu is with the Department of Electrical Engineering, The Hong Kong Polytechnic University, Hung Hom, Hong Kong, and also with the School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, Singapore (e-mail: benxx.xu@connect.polyu.hk).
Publisher Copyright:
© 1969-2012 IEEE.
PY - 2020/9
Y1 - 2020/9
N2 - 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.
AB - 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.
KW - descend search algorithm
KW - energy sharing mechanism
KW - optimal power flow problem
KW - Residential photovoltaic panels planning
KW - Stackelberg game
UR - http://www.scopus.com/inward/record.url?scp=85088362931&partnerID=8YFLogxK
U2 - 10.1109/TPWRS.2020.2985765
DO - 10.1109/TPWRS.2020.2985765
M3 - Journal article
AN - SCOPUS:85088362931
SN - 0885-8950
VL - 35
SP - 3562
EP - 3573
JO - IEEE Transactions on Power Systems
JF - IEEE Transactions on Power Systems
IS - 5
M1 - 9067013
ER -