Optimal Allocation Model of Virtual Power Plant Capacity considering Electric Vehicles

To push forward the development of electric vehicles while improving the economy and environment of virtual power plants (VPPs), research on the optimization of VPP capacity considering electric vehicles is carried out. In this paper, based on this, this paper first analyzes the framework of the VPP...

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Main Authors: Shiping Geng, Caixia Tan, Dongxiao Niu, Xiaopeng Guo
Format: Article
Language:English
Published: Hindawi Limited 2021-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2021/5552323
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spelling doaj-9907c65928424f999238ccc9b625d3172021-06-28T01:50:56ZengHindawi LimitedMathematical Problems in Engineering1563-51472021-01-01202110.1155/2021/5552323Optimal Allocation Model of Virtual Power Plant Capacity considering Electric VehiclesShiping Geng0Caixia Tan1Dongxiao Niu2Xiaopeng Guo3North China Electric Power UniversityNorth China Electric Power UniversityNorth China Electric Power UniversityNorth China Electric Power UniversityTo push forward the development of electric vehicles while improving the economy and environment of virtual power plants (VPPs), research on the optimization of VPP capacity considering electric vehicles is carried out. In this paper, based on this, this paper first analyzes the framework of the VPP with electric vehicles and models each unit of the VPP. Secondly, the typical scenarios of wind power, photovoltaic, electric vehicle charging and discharging, and load are formed by the Monte Carlo method to reduce the output deviation of each unit. Then, taking the maximization of the net income and clean energy consumption of the VPP as the objective function, the capacity optimal allocation model of the VPP considering multiobjective is constructed, and the conditional value-at-risk (CVaR) is introduced to represent the investment uncertainty faced by the VPP. Finally, a VPP in a certain area of Shanxi Province is used to analyze a calculation example and solve it with CPLEX. The results of the calculation example show that, on the one hand, reasonable selection of the optimal scale of EV connected to the VPP is able to improve the economy and environment of the VPP. On the other hand, the introduction of CVaR is available for the improvement of the scientific nature of VPP capacity allocation decisions.http://dx.doi.org/10.1155/2021/5552323
collection DOAJ
language English
format Article
sources DOAJ
author Shiping Geng
Caixia Tan
Dongxiao Niu
Xiaopeng Guo
spellingShingle Shiping Geng
Caixia Tan
Dongxiao Niu
Xiaopeng Guo
Optimal Allocation Model of Virtual Power Plant Capacity considering Electric Vehicles
Mathematical Problems in Engineering
author_facet Shiping Geng
Caixia Tan
Dongxiao Niu
Xiaopeng Guo
author_sort Shiping Geng
title Optimal Allocation Model of Virtual Power Plant Capacity considering Electric Vehicles
title_short Optimal Allocation Model of Virtual Power Plant Capacity considering Electric Vehicles
title_full Optimal Allocation Model of Virtual Power Plant Capacity considering Electric Vehicles
title_fullStr Optimal Allocation Model of Virtual Power Plant Capacity considering Electric Vehicles
title_full_unstemmed Optimal Allocation Model of Virtual Power Plant Capacity considering Electric Vehicles
title_sort optimal allocation model of virtual power plant capacity considering electric vehicles
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1563-5147
publishDate 2021-01-01
description To push forward the development of electric vehicles while improving the economy and environment of virtual power plants (VPPs), research on the optimization of VPP capacity considering electric vehicles is carried out. In this paper, based on this, this paper first analyzes the framework of the VPP with electric vehicles and models each unit of the VPP. Secondly, the typical scenarios of wind power, photovoltaic, electric vehicle charging and discharging, and load are formed by the Monte Carlo method to reduce the output deviation of each unit. Then, taking the maximization of the net income and clean energy consumption of the VPP as the objective function, the capacity optimal allocation model of the VPP considering multiobjective is constructed, and the conditional value-at-risk (CVaR) is introduced to represent the investment uncertainty faced by the VPP. Finally, a VPP in a certain area of Shanxi Province is used to analyze a calculation example and solve it with CPLEX. The results of the calculation example show that, on the one hand, reasonable selection of the optimal scale of EV connected to the VPP is able to improve the economy and environment of the VPP. On the other hand, the introduction of CVaR is available for the improvement of the scientific nature of VPP capacity allocation decisions.
url http://dx.doi.org/10.1155/2021/5552323
work_keys_str_mv AT shipinggeng optimalallocationmodelofvirtualpowerplantcapacityconsideringelectricvehicles
AT caixiatan optimalallocationmodelofvirtualpowerplantcapacityconsideringelectricvehicles
AT dongxiaoniu optimalallocationmodelofvirtualpowerplantcapacityconsideringelectricvehicles
AT xiaopengguo optimalallocationmodelofvirtualpowerplantcapacityconsideringelectricvehicles
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