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An incentivized and optimized dynamic mechanism for demand response for managing voltage in distribution networks

Rahman, M.M., Arefi, A.ORCID: 0000-0001-9642-7639, Shafiullah, GM.ORCID: 0000-0002-2211-184X, Hettiwatte, S., Azizivahed, A., Muyeen, S.M. and Islam, Md.R. (2022) An incentivized and optimized dynamic mechanism for demand response for managing voltage in distribution networks. IEEE Access, 10 . pp. 96359-96377.

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Free to read: https://doi.org/10.1109/ACCESS.2022.3204618
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Abstract

The voltage regulation in distribution networks is one of the major obstacles when increasing the penetration of distributed generators (DGs) such as solar photovoltaics (PV), especially during cloud transients, causing potential stress on network voltage regulations. Residential demand response (DR) is one of the cost-effective solutions for voltage management in distribution networks. However, the main barriers of DR implementation are the complexities of controlling a large number and different types of residential loads, satisfying customers’ preferences and providing them fair incentives while identifying the optimum DR implementation locations and sizing as well as cooperating with the existing network equipment for the effective voltage management in the networks. A holistic and practical approach of DR implementation is missing in the literature. This study proposes a dynamic fair incentive mechanism using a multi-scheme load control algorithm for a large number of DR participants coordinating with the existing network equipment for managing voltage at medium voltage (MV) networks. The multi-scheme load control is comprised of short-interval (10-minute) and long-interval (2-hour) DR schemes. The dynamic incentive rates are optimized based on the energy contribution of DR participating consumers, their influence on the network voltage and total power loss improvement. The proposed method minimizes the DR implementation cost and size, fairly incentivizes the consumers participating in the DR and priorities their consumption preferences while reduces the network power losses and DGs’ reactive power contributions to effectively manage the voltage in the MV networks. An improved hybrid particle swarm optimization algorithm (IHPSO) is proposed for the load controller to provide fast convergence and robust optimization results. The proposed approach is comprehensively tested using the IEEE 33-bus and IEEE 69-bus networks with several scenarios considering a large number of DR participants coordinated with the DGs and on-load tap changer (OLTC) in the networks.

Item Type: Journal Article
Murdoch Affiliation(s): Engineering and Energy
Publisher: IEEE
Copyright: © 2022 M. M. Rahman et al.
URI: http://researchrepository.murdoch.edu.au/id/eprint/66127
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