A Two-stage Robust Optimal Allocation Model of Distributed Generation Considering Capacity Curve and Real-time Price Based Demand Response

Shuaijia He; Hongjun Gao; Hao Tian; Lingfeng Wang; Youbo Liu; Junyong Liu

DOI:10.35833/MPCE.2019.000174


A Two-stage Robust Optimal Allocation Model of Distributed Generation Considering Capacity Curve and Real-time Price Based Demand Response



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Author: Shuaijia He¹,Hongjun Gao¹,Hao Tian²,Lingfeng Wang³,Youbo Liu¹,Junyong Liu¹
Author Affiliation: 1.College of Electrical Engineering, Sichuan University, Chengdu 610065, China;2.Economic and Technology Research Institute, State Grid Chongqing Electric Power Company, Chongqing 201120, China;3.Department of Electrical Engineering and Computer Science, University of Wisconsin-Milwaukee, Milwaukee, WI 53211, USA
Foundation:	This work was supported by the National Key R&D Program of China (No. 2019YFE0111500),the National Natural Science Foundation of China (No.51807125), and Sichuan Science and Technology Program (No. 2020YFH0040).

Abstract:	Demand response, the reactive power output of distributed generation (DG), and network reconfiguration have significant impacts on a DG allocation strategy. In this context, a novel real-time price-based demand response formulation is integrated into the allocation model of DG. The tariff is regulated by the difference between the load and active power of renewable energy. Meanwhile, network reconfiguration and the capacity curve describing the active and reactive power limits of DG are included in the optimization model for promoting the allocation of DG. With these measures, the optimal allocation model of DG is established with the goal of maximizing the net annual profit while guaranteeing the efficient utilization of renewable energy. In addition, the uncertainties of renewable energy are considered on the basis of a two-stage robust optimization method. Finally, the entire optimization model is solved by the column and constraint generation algorithm in the IEEE 33-bus distribution system and a practical 99-bus distribution system. Numerical simulations show that the proposed model is effective in terms of improving both the usage of renewable energy and net annual profit.
Keywords:	Distributed generation (DG) allocation ; demand response (DR) ; capacity curve ; network reconfiguration ; uncertainty

Received:November 27, 2019 Online Time:2021/01/22



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