An Environmental-Economic Dispatch Method for Smart Microgrids Using VSS_QGA

The increasing penetration of distributed generation resources demands better economic performance of microgrids under the smart-grid era. In this paper, a comprehensive environmental-economic dispatch method for smart microgrids is proposed, with the objective for minimizing the summation of genera...

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Main Authors: Wenxia Liu, Yuying Zhang, Bo Zeng, Shuya Niu, Jianhua Zhang, Yong Xiao
Format: Article
Language:English
Published: Wiley 2014-01-01
Series:Journal of Applied Mathematics
Online Access:http://dx.doi.org/10.1155/2014/623216
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author Wenxia Liu
Yuying Zhang
Bo Zeng
Shuya Niu
Jianhua Zhang
Yong Xiao
author_facet Wenxia Liu
Yuying Zhang
Bo Zeng
Shuya Niu
Jianhua Zhang
Yong Xiao
author_sort Wenxia Liu
collection DOAJ
description The increasing penetration of distributed generation resources demands better economic performance of microgrids under the smart-grid era. In this paper, a comprehensive environmental-economic dispatch method for smart microgrids is proposed, with the objective for minimizing the summation of generation and emission costs in the system. As the proposed model belongs to a large-scale nonlinear and nonconvex programming problem, a hybrid heuristic algorithm, named variable step-size chaotic fuzzy quantum genetic algorithm (VSS_QGA), is developed. The algorithm utilizes complementarity among multiple techniques including the variable step size optimization, the rotation mutational angle fuzzy control, and the quantum genetic algorithm and combines them so as to solve problems with superior accuracy and efficiency. The effectiveness of the proposed model is demonstrated through a case study on an actual microgrid system and the advantages in the performance of VSS_QGA is also verified through the comparison with genetic algorithm (GA), the evolutionary programming approach (EP), the quantum genetic algorithm (QGA), and the chaotic quantum genetic algorithm (CQGA).
format Article
id doaj-art-939b3c54895b4ce385c8c3d9f935f844
institution Kabale University
issn 1110-757X
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language English
publishDate 2014-01-01
publisher Wiley
record_format Article
series Journal of Applied Mathematics
spelling doaj-art-939b3c54895b4ce385c8c3d9f935f8442025-08-20T03:37:20ZengWileyJournal of Applied Mathematics1110-757X1687-00422014-01-01201410.1155/2014/623216623216An Environmental-Economic Dispatch Method for Smart Microgrids Using VSS_QGAWenxia Liu0Yuying Zhang1Bo Zeng2Shuya Niu3Jianhua Zhang4Yong Xiao5Transmission and Distribution System Research Institute, North China Electric Power University, Number 2 Beinong Road, Changping District, Beijing 102206, ChinaTransmission and Distribution System Research Institute, North China Electric Power University, Number 2 Beinong Road, Changping District, Beijing 102206, ChinaTransmission and Distribution System Research Institute, North China Electric Power University, Number 2 Beinong Road, Changping District, Beijing 102206, ChinaTransmission and Distribution System Research Institute, North China Electric Power University, Number 2 Beinong Road, Changping District, Beijing 102206, ChinaTransmission and Distribution System Research Institute, North China Electric Power University, Number 2 Beinong Road, Changping District, Beijing 102206, ChinaGuizhou Electric Power Test Research Institute, China Southern Power Grid, Number 32 Jiefang Road, Nanming District, Guiyang 550000, ChinaThe increasing penetration of distributed generation resources demands better economic performance of microgrids under the smart-grid era. In this paper, a comprehensive environmental-economic dispatch method for smart microgrids is proposed, with the objective for minimizing the summation of generation and emission costs in the system. As the proposed model belongs to a large-scale nonlinear and nonconvex programming problem, a hybrid heuristic algorithm, named variable step-size chaotic fuzzy quantum genetic algorithm (VSS_QGA), is developed. The algorithm utilizes complementarity among multiple techniques including the variable step size optimization, the rotation mutational angle fuzzy control, and the quantum genetic algorithm and combines them so as to solve problems with superior accuracy and efficiency. The effectiveness of the proposed model is demonstrated through a case study on an actual microgrid system and the advantages in the performance of VSS_QGA is also verified through the comparison with genetic algorithm (GA), the evolutionary programming approach (EP), the quantum genetic algorithm (QGA), and the chaotic quantum genetic algorithm (CQGA).http://dx.doi.org/10.1155/2014/623216
spellingShingle Wenxia Liu
Yuying Zhang
Bo Zeng
Shuya Niu
Jianhua Zhang
Yong Xiao
An Environmental-Economic Dispatch Method for Smart Microgrids Using VSS_QGA
Journal of Applied Mathematics
title An Environmental-Economic Dispatch Method for Smart Microgrids Using VSS_QGA
title_full An Environmental-Economic Dispatch Method for Smart Microgrids Using VSS_QGA
title_fullStr An Environmental-Economic Dispatch Method for Smart Microgrids Using VSS_QGA
title_full_unstemmed An Environmental-Economic Dispatch Method for Smart Microgrids Using VSS_QGA
title_short An Environmental-Economic Dispatch Method for Smart Microgrids Using VSS_QGA
title_sort environmental economic dispatch method for smart microgrids using vss qga
url http://dx.doi.org/10.1155/2014/623216
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