Multi-Objective Coordinated Planning of Active-Reactive Power Resources for Decentralized Droop-Controlled Islanded Microgrids Based on Probabilistic Load Flow

The intermittency of distributed generation and the fluctuation of load will derive uncertainties to the decentralized droop-controlled islanded microgrids (IMGs) operation. In order to describe and analyse the probabilistic characteristics of the operating state of an IMG, this paper proposes an an...

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Main Authors: Zehuai Liu, Jiahao Yang, Yongjun Zhang, Tianyao Ji, Junhuang Zhou, Zexiang Cai
Format: Article
Language:English
Published: IEEE 2018-01-01
Series:IEEE Access
Subjects:
Online Access:https://ieeexplore.ieee.org/document/8410870/
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spelling doaj-7b2e3416e16744bb91e432456ca13d4f2021-03-29T20:59:06ZengIEEEIEEE Access2169-35362018-01-016402674028010.1109/ACCESS.2018.28556978410870Multi-Objective Coordinated Planning of Active-Reactive Power Resources for Decentralized Droop-Controlled Islanded Microgrids Based on Probabilistic Load FlowZehuai Liu0Jiahao Yang1Yongjun Zhang2https://orcid.org/0000-0002-1135-6788Tianyao Ji3Junhuang Zhou4Zexiang Cai5School of Electric Power, South China University of Technology, Guangzhou, ChinaSchool of Mechanical and Electrical Engineering, Xiamen University Tan Kah Kee College, Zhangzhou, ChinaSchool of Electric Power, South China University of Technology, Guangzhou, ChinaSchool of Electric Power, South China University of Technology, Guangzhou, ChinaSchool of Electric Power, South China University of Technology, Guangzhou, ChinaSchool of Electric Power, South China University of Technology, Guangzhou, ChinaThe intermittency of distributed generation and the fluctuation of load will derive uncertainties to the decentralized droop-controlled islanded microgrids (IMGs) operation. In order to describe and analyse the probabilistic characteristics of the operating state of an IMG, this paper proposes an analytical method based on cumulants to solve the probabilistic load flow (PLF) for decentralized droop-controlled IMGs, considering the correlation of input variables. Nataf transform is used to deal with the correlation, and the PLF is solved using the cumulant method and the Gram-Charlier series expansion. On this basis, a multi-objective coordinated planning model of active-reactive power resources is presented, considering the annual comprehensive cost and operating risk simultaneously. The Pareto optimal solution set is found using non-dominated sorting genetic algorithm-II to provide a set of alternative planning schemes. The proposed PLF based on cumulant method is compared with Monte Carlo simulation to verify its accuracy and efficiency. Besides, the simulation results also demonstrate that the proposed coordinated planning model of active-reactive power resources can coordinate the security and economy of the IMG operation.https://ieeexplore.ieee.org/document/8410870/Multi-objective planningdecentralized droop-controlled islanded microgridcumulantprobabilistic load flow
collection DOAJ
language English
format Article
sources DOAJ
author Zehuai Liu
Jiahao Yang
Yongjun Zhang
Tianyao Ji
Junhuang Zhou
Zexiang Cai
spellingShingle Zehuai Liu
Jiahao Yang
Yongjun Zhang
Tianyao Ji
Junhuang Zhou
Zexiang Cai
Multi-Objective Coordinated Planning of Active-Reactive Power Resources for Decentralized Droop-Controlled Islanded Microgrids Based on Probabilistic Load Flow
IEEE Access
Multi-objective planning
decentralized droop-controlled islanded microgrid
cumulant
probabilistic load flow
author_facet Zehuai Liu
Jiahao Yang
Yongjun Zhang
Tianyao Ji
Junhuang Zhou
Zexiang Cai
author_sort Zehuai Liu
title Multi-Objective Coordinated Planning of Active-Reactive Power Resources for Decentralized Droop-Controlled Islanded Microgrids Based on Probabilistic Load Flow
title_short Multi-Objective Coordinated Planning of Active-Reactive Power Resources for Decentralized Droop-Controlled Islanded Microgrids Based on Probabilistic Load Flow
title_full Multi-Objective Coordinated Planning of Active-Reactive Power Resources for Decentralized Droop-Controlled Islanded Microgrids Based on Probabilistic Load Flow
title_fullStr Multi-Objective Coordinated Planning of Active-Reactive Power Resources for Decentralized Droop-Controlled Islanded Microgrids Based on Probabilistic Load Flow
title_full_unstemmed Multi-Objective Coordinated Planning of Active-Reactive Power Resources for Decentralized Droop-Controlled Islanded Microgrids Based on Probabilistic Load Flow
title_sort multi-objective coordinated planning of active-reactive power resources for decentralized droop-controlled islanded microgrids based on probabilistic load flow
publisher IEEE
series IEEE Access
issn 2169-3536
publishDate 2018-01-01
description The intermittency of distributed generation and the fluctuation of load will derive uncertainties to the decentralized droop-controlled islanded microgrids (IMGs) operation. In order to describe and analyse the probabilistic characteristics of the operating state of an IMG, this paper proposes an analytical method based on cumulants to solve the probabilistic load flow (PLF) for decentralized droop-controlled IMGs, considering the correlation of input variables. Nataf transform is used to deal with the correlation, and the PLF is solved using the cumulant method and the Gram-Charlier series expansion. On this basis, a multi-objective coordinated planning model of active-reactive power resources is presented, considering the annual comprehensive cost and operating risk simultaneously. The Pareto optimal solution set is found using non-dominated sorting genetic algorithm-II to provide a set of alternative planning schemes. The proposed PLF based on cumulant method is compared with Monte Carlo simulation to verify its accuracy and efficiency. Besides, the simulation results also demonstrate that the proposed coordinated planning model of active-reactive power resources can coordinate the security and economy of the IMG operation.
topic Multi-objective planning
decentralized droop-controlled islanded microgrid
cumulant
probabilistic load flow
url https://ieeexplore.ieee.org/document/8410870/
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