Day-ahead scheduling of distribution level integrated electricity and natural gas system based on fast-ADMM with restart algorithm
Power generated by the natural gas (NG) is a promising option for solving the restrictions on the development of the power industry. Consequently, the high interdependence between NG network and electricity network should be considered in this integration. In this paper, a day-ahead scheduling frame...
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sg-ntu-dr.10356-877242020-03-07T13:57:31Z Day-ahead scheduling of distribution level integrated electricity and natural gas system based on fast-ADMM with restart algorithm Chen, Jian Zhang, Weitong Zhang, Yicheng Bao, Guannan School of Electrical and Electronic Engineering Day-ahead Scheduling Demand-side Response Power generated by the natural gas (NG) is a promising option for solving the restrictions on the development of the power industry. Consequently, the high interdependence between NG network and electricity network should be considered in this integration. In this paper, a day-ahead scheduling framework of integrated electricity and NG system (IENG) is proposed at a distribution level based on the fast alternating direction multiplier method with restart algorithm considering demand side response and uncertainties. Within the proposed framework, the detailed model of the IENG system at a distribution level is established, where the NG flow equation is processed by incremental linearization method to improve the computational efficiency. The objective is to minimize the operation costs of the entire system. With consideration of the uncertainties of distributed generation and electricity load as well as the uncertainties from the NG load, a two-stage robust optimization model is introduced to obtain the worst case within the uncertainty set, which is solved by column and constraints generation algorithm. In addition, the demand-side response (DSR) model including the decentralized air conditioning (AC) load model and the centralized ice-storage AC load model is integrated into the scheduling framework. Finally, the proposed day-ahead scheduling framework is verified by numerical studies where the optimal scheduling schemes are obtained in different cases, both the effects of the uncertainties and the performance with introducing DSR to the system operation are analyzed. Published version 2018-08-06T08:32:44Z 2019-12-06T16:47:59Z 2018-08-06T08:32:44Z 2019-12-06T16:47:59Z 2018 Journal Article Chen, J., Zhang, W., Zhang, Y., & Bao, G. (2018). Day-ahead scheduling of distribution level integrated electricity and natural gas system based on fast-ADMM with restart algorithm. IEEE Access, 6, 17557-17569. https://hdl.handle.net/10356/87724 http://hdl.handle.net/10220/45487 10.1109/ACCESS.2018.2818756 en IEEE Access © 2018 IEEE. Translations and content mining are permitted for academic research only. Personal use is also permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information. 13 p. application/pdf |
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Day-ahead Scheduling Demand-side Response Chen, Jian Zhang, Weitong Zhang, Yicheng Bao, Guannan Day-ahead scheduling of distribution level integrated electricity and natural gas system based on fast-ADMM with restart algorithm |
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Power generated by the natural gas (NG) is a promising option for solving the restrictions on the development of the power industry. Consequently, the high interdependence between NG network and electricity network should be considered in this integration. In this paper, a day-ahead scheduling framework of integrated electricity and NG system (IENG) is proposed at a distribution level based on the fast alternating direction multiplier method with restart algorithm considering demand side response and uncertainties. Within the proposed framework, the detailed model of the IENG system at a distribution level is established, where the NG flow equation is processed by incremental linearization method to improve the computational efficiency. The objective is to minimize the operation costs of the entire system. With consideration of the uncertainties of distributed generation and electricity load as well as the uncertainties from the NG load, a two-stage robust optimization model is introduced to obtain the worst case within the uncertainty set, which is solved by column and constraints generation algorithm. In addition, the demand-side response (DSR) model including the decentralized air conditioning (AC) load model and the centralized ice-storage AC load model is integrated into the scheduling framework. Finally, the proposed day-ahead scheduling framework is verified by numerical studies where the optimal scheduling schemes are obtained in different cases, both the effects of the uncertainties and the performance with introducing DSR to the system operation are analyzed. |
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School of Electrical and Electronic Engineering |
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School of Electrical and Electronic Engineering Chen, Jian Zhang, Weitong Zhang, Yicheng Bao, Guannan |
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Article |
author |
Chen, Jian Zhang, Weitong Zhang, Yicheng Bao, Guannan |
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Chen, Jian |
title |
Day-ahead scheduling of distribution level integrated electricity and natural gas system based on fast-ADMM with restart algorithm |
title_short |
Day-ahead scheduling of distribution level integrated electricity and natural gas system based on fast-ADMM with restart algorithm |
title_full |
Day-ahead scheduling of distribution level integrated electricity and natural gas system based on fast-ADMM with restart algorithm |
title_fullStr |
Day-ahead scheduling of distribution level integrated electricity and natural gas system based on fast-ADMM with restart algorithm |
title_full_unstemmed |
Day-ahead scheduling of distribution level integrated electricity and natural gas system based on fast-ADMM with restart algorithm |
title_sort |
day-ahead scheduling of distribution level integrated electricity and natural gas system based on fast-admm with restart algorithm |
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2018 |
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https://hdl.handle.net/10356/87724 http://hdl.handle.net/10220/45487 |
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