Co-Planning of Demand Response and Distributed Generators in an Active Distribution Network
The integration of renewables is fast-growing, in light of smart grid technology development. As a result, the uncertain nature of renewables and load demand poses significant technical challenges to distribution network (DN) daily operation. To alleviate such issues, price-sensitive demand response...
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doaj-4f24467fa2bc42cf933ec9e945b227402020-11-25T00:41:20ZengMDPI AGEnergies1996-10732018-02-0111235410.3390/en11020354en11020354Co-Planning of Demand Response and Distributed Generators in an Active Distribution NetworkYi Yu0Xishan Wen1Jian Zhao2Zhao Xu3Jiayong Li4School of Electrical Engineering, Wuhan University, Wuhan 430072, ChinaSchool of Electrical Engineering, Wuhan University, Wuhan 430072, ChinaDepartment of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, ChinaDepartment of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, ChinaDepartment of Electrical Engineering, The Hong Kong Polytechnic University, Hong Kong, ChinaThe integration of renewables is fast-growing, in light of smart grid technology development. As a result, the uncertain nature of renewables and load demand poses significant technical challenges to distribution network (DN) daily operation. To alleviate such issues, price-sensitive demand response and distributed generators can be coordinated to accommodate the renewable energy. However, the investment cost for demand response facilities, i.e., load control switch and advanced metering infrastructure, cannot be ignored, especially when the responsive demand is large. In this paper, an optimal coordinated investment for distributed generator and demand response facilities is proposed, based on a linearized, price-elastic demand response model. To hedge against the uncertainties of renewables and load demand, a two-stage robust investment scheme is proposed, where the investment decisions are optimized in the first stage, and the demand response participation with the coordination of distributed generators is adjusted in the second stage. Simulations on the modified IEEE 33-node and 123-node DN demonstrate the effectiveness of the proposed model.http://www.mdpi.com/1996-1073/11/2/354demand responsesolar energywind poweruncertaintiesdistributed generatoractive distribution network |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Yi Yu Xishan Wen Jian Zhao Zhao Xu Jiayong Li |
spellingShingle |
Yi Yu Xishan Wen Jian Zhao Zhao Xu Jiayong Li Co-Planning of Demand Response and Distributed Generators in an Active Distribution Network Energies demand response solar energy wind power uncertainties distributed generator active distribution network |
author_facet |
Yi Yu Xishan Wen Jian Zhao Zhao Xu Jiayong Li |
author_sort |
Yi Yu |
title |
Co-Planning of Demand Response and Distributed Generators in an Active Distribution Network |
title_short |
Co-Planning of Demand Response and Distributed Generators in an Active Distribution Network |
title_full |
Co-Planning of Demand Response and Distributed Generators in an Active Distribution Network |
title_fullStr |
Co-Planning of Demand Response and Distributed Generators in an Active Distribution Network |
title_full_unstemmed |
Co-Planning of Demand Response and Distributed Generators in an Active Distribution Network |
title_sort |
co-planning of demand response and distributed generators in an active distribution network |
publisher |
MDPI AG |
series |
Energies |
issn |
1996-1073 |
publishDate |
2018-02-01 |
description |
The integration of renewables is fast-growing, in light of smart grid technology development. As a result, the uncertain nature of renewables and load demand poses significant technical challenges to distribution network (DN) daily operation. To alleviate such issues, price-sensitive demand response and distributed generators can be coordinated to accommodate the renewable energy. However, the investment cost for demand response facilities, i.e., load control switch and advanced metering infrastructure, cannot be ignored, especially when the responsive demand is large. In this paper, an optimal coordinated investment for distributed generator and demand response facilities is proposed, based on a linearized, price-elastic demand response model. To hedge against the uncertainties of renewables and load demand, a two-stage robust investment scheme is proposed, where the investment decisions are optimized in the first stage, and the demand response participation with the coordination of distributed generators is adjusted in the second stage. Simulations on the modified IEEE 33-node and 123-node DN demonstrate the effectiveness of the proposed model. |
topic |
demand response solar energy wind power uncertainties distributed generator active distribution network |
url |
http://www.mdpi.com/1996-1073/11/2/354 |
work_keys_str_mv |
AT yiyu coplanningofdemandresponseanddistributedgeneratorsinanactivedistributionnetwork AT xishanwen coplanningofdemandresponseanddistributedgeneratorsinanactivedistributionnetwork AT jianzhao coplanningofdemandresponseanddistributedgeneratorsinanactivedistributionnetwork AT zhaoxu coplanningofdemandresponseanddistributedgeneratorsinanactivedistributionnetwork AT jiayongli coplanningofdemandresponseanddistributedgeneratorsinanactivedistributionnetwork |
_version_ |
1725285900572688384 |