Optimal Evolutionary Dispatch for Integrated Community Energy Systems Considering Uncertainties of Renewable Energy Sources and Internal Loads
For the future development of integrated energy systems with high penetration of renewable energy, an integrated community energy systems (ICES) dispatch model is proposed including various renewable energy sources and energy conversion units. Energy coupling matrices of ICES based on traditional en...
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doaj-1382cb718c39427fb0b017daf3fcc00a2021-07-01T00:34:58ZengMDPI AGEnergies1996-10732021-06-01143644364410.3390/en14123644Optimal Evolutionary Dispatch for Integrated Community Energy Systems Considering Uncertainties of Renewable Energy Sources and Internal LoadsXinghua Liu0Shenghan Xie1Chen Geng2Jianning Yin3Gaoxi Xiao4Hui Cao5School of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, ChinaSchool of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, ChinaSchool of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, ChinaSchool of Electrical Engineering, Xi’an University of Technology, Xi’an 710048, ChinaSchool of Electrical and Electronic Engineering, Nanyang Technological University, Singapore 639798, SingaporeSchool of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, ChinaFor the future development of integrated energy systems with high penetration of renewable energy, an integrated community energy systems (ICES) dispatch model is proposed including various renewable energy sources and energy conversion units. Energy coupling matrices of ICES based on traditional energy hub (EH) models are constructed. Uncertainties of long-term forecast data of renewable energy sources and internal loads are depicted by multi-interval uncertainty sets (MIUS). To cope with the impacts caused by uncertainties of renewable energy sources and internal loads, the whole dispatch process is divided into two stages. Considering various constraints of ICES, we solved the dispatch model through the improved particle swarm optimization (IPSO) algorithm in the first stage. The optimal evolutionary dispatch is then proposed in the second stage to overcome the evolution and errors of short-term forecast data and obtain the optimal dispatch plan. The effectiveness of the proposed dispatch method is demonstrated using an example considering dramatic uncertainties. Compared with the traditional methods, the proposed dispatch method effectively reduces system operating costs and improves the environmental benefits, which helps to achieve a win-win situation for both energy companies and users.https://www.mdpi.com/1996-1073/14/12/3644integrated community energy systemenergy hubrenewable energy sourceoptimal dispatch |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Xinghua Liu Shenghan Xie Chen Geng Jianning Yin Gaoxi Xiao Hui Cao |
spellingShingle |
Xinghua Liu Shenghan Xie Chen Geng Jianning Yin Gaoxi Xiao Hui Cao Optimal Evolutionary Dispatch for Integrated Community Energy Systems Considering Uncertainties of Renewable Energy Sources and Internal Loads Energies integrated community energy system energy hub renewable energy source optimal dispatch |
author_facet |
Xinghua Liu Shenghan Xie Chen Geng Jianning Yin Gaoxi Xiao Hui Cao |
author_sort |
Xinghua Liu |
title |
Optimal Evolutionary Dispatch for Integrated Community Energy Systems Considering Uncertainties of Renewable Energy Sources and Internal Loads |
title_short |
Optimal Evolutionary Dispatch for Integrated Community Energy Systems Considering Uncertainties of Renewable Energy Sources and Internal Loads |
title_full |
Optimal Evolutionary Dispatch for Integrated Community Energy Systems Considering Uncertainties of Renewable Energy Sources and Internal Loads |
title_fullStr |
Optimal Evolutionary Dispatch for Integrated Community Energy Systems Considering Uncertainties of Renewable Energy Sources and Internal Loads |
title_full_unstemmed |
Optimal Evolutionary Dispatch for Integrated Community Energy Systems Considering Uncertainties of Renewable Energy Sources and Internal Loads |
title_sort |
optimal evolutionary dispatch for integrated community energy systems considering uncertainties of renewable energy sources and internal loads |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2021-06-01 |
description |
For the future development of integrated energy systems with high penetration of renewable energy, an integrated community energy systems (ICES) dispatch model is proposed including various renewable energy sources and energy conversion units. Energy coupling matrices of ICES based on traditional energy hub (EH) models are constructed. Uncertainties of long-term forecast data of renewable energy sources and internal loads are depicted by multi-interval uncertainty sets (MIUS). To cope with the impacts caused by uncertainties of renewable energy sources and internal loads, the whole dispatch process is divided into two stages. Considering various constraints of ICES, we solved the dispatch model through the improved particle swarm optimization (IPSO) algorithm in the first stage. The optimal evolutionary dispatch is then proposed in the second stage to overcome the evolution and errors of short-term forecast data and obtain the optimal dispatch plan. The effectiveness of the proposed dispatch method is demonstrated using an example considering dramatic uncertainties. Compared with the traditional methods, the proposed dispatch method effectively reduces system operating costs and improves the environmental benefits, which helps to achieve a win-win situation for both energy companies and users. |
topic |
integrated community energy system energy hub renewable energy source optimal dispatch |
url |
https://www.mdpi.com/1996-1073/14/12/3644 |
work_keys_str_mv |
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