TY - JOUR
T1 - Enhancing photovoltaic hosting capacity—A stochastic approach to optimal planning of static var compensator devices in distribution networks
AU - Xu, Xu
AU - Li, Jiayong
AU - Xu, Zhao
AU - Zhao, Jian
AU - Lai, Chun Sing
N1 - Publisher Copyright:
© 2019
PY - 2019/3/15
Y1 - 2019/3/15
N2 - To improve photovoltaic hosting capacity of distribution networks, this paper proposes a novel optimal static var compensator planning model which is formulated as a two-stage stochastic programming problem. Specifically, the first stage of our model determines the static var compensator planning decisions and the corresponding photovoltaic hosting capacity. In the second stage, the feasibility of the first stage results is evaluated under different uncertainty scenarios of load demand and photovoltaic output to ensure no constraint violations, especially no voltage constraint violations. In addition, we simultaneously consider the minimization of static var compensator planning cost and the maximization of photovoltaic hosting capacity by formulating a multi-objective function. To improve the computational efficiency, a solution method based on Benders decomposition is developed by decomposing the two-stage problem into a master problem and multiple subproblems. The effectiveness of the proposed model and solution method is validated on modified IEEE 37-node and 123-node distribution systems. Last, our results show that the proposed model can significantly improve the photovoltaic hosting capacity. The case studies also demonstrate that the PV hosting capacity becomes insensitive to the additional SVC planning cost when the total cost exceeds about $175,000.
AB - To improve photovoltaic hosting capacity of distribution networks, this paper proposes a novel optimal static var compensator planning model which is formulated as a two-stage stochastic programming problem. Specifically, the first stage of our model determines the static var compensator planning decisions and the corresponding photovoltaic hosting capacity. In the second stage, the feasibility of the first stage results is evaluated under different uncertainty scenarios of load demand and photovoltaic output to ensure no constraint violations, especially no voltage constraint violations. In addition, we simultaneously consider the minimization of static var compensator planning cost and the maximization of photovoltaic hosting capacity by formulating a multi-objective function. To improve the computational efficiency, a solution method based on Benders decomposition is developed by decomposing the two-stage problem into a master problem and multiple subproblems. The effectiveness of the proposed model and solution method is validated on modified IEEE 37-node and 123-node distribution systems. Last, our results show that the proposed model can significantly improve the photovoltaic hosting capacity. The case studies also demonstrate that the PV hosting capacity becomes insensitive to the additional SVC planning cost when the total cost exceeds about $175,000.
KW - Benders decomposition
KW - Photovoltaic hosting capacity
KW - Static var compensator planning model
KW - Two-stage stochastic programming
KW - Uncertainty scenarios
UR - http://www.scopus.com/inward/record.url?scp=85060484108&partnerID=8YFLogxK
U2 - 10.1016/j.apenergy.2019.01.135
DO - 10.1016/j.apenergy.2019.01.135
M3 - Article
AN - SCOPUS:85060484108
SN - 0306-2619
VL - 238
SP - 952
EP - 962
JO - Applied Energy
JF - Applied Energy
ER -