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Tri-stage optimal scheduling for an islanded microgrid based on a quantum adaptive sparrow search algorithm
journal contributionposted on 2023-05-21, 07:27 authored by Li, B, Wang, H, Xiaolin WangXiaolin Wang, Michael NegnevitskyMichael Negnevitsky, Li, C
An islanded microgrid includes a combined heating and power system as well as electric vehicles. It is a key method for increasing energy efficiency, reducing pollution, and achieving carbon neutrality. Considering the uncertainties caused by renewable energy, load, and electric vehicles, this study presents a modified tri-stage scheduling method to realise the real-time dispatch of the islanded microgrid. The novel tri-stage scheduling method incorporates an information feedback mechanism into the traditional tri-stage scheduling method to address the problem of the sub-optimal solution obtained by the traditional method, which results from the significant errors between the day-ahead forecast data and intraday forecast data. In addition, users are guided by the tri-stage real-time price to charge/discharge electric vehicles orderly to fill in the valley and shave the peak of the electric load. In this study, a quantum adaptive sparrow search algorithm is proposed based on the characteristics of the tri-stage scheduling optimisation model and the limitation that the original algorithm easily falls into a local optimum. In the case study, the superiority of the novel tri-stage scheduling method, modified algorithm, and orderly charging/discharging of electric vehicles proposed in this paper are evaluated in different seasons. In the vehicle-to-grid mode, the influence of different numbers of electric vehicles on the real-time dispatch of the islanded microgrid is analyzed and discussed.
Publication titleEnergy Conversion and Management
Department/SchoolSchool of Engineering
PublisherPergamon-Elsevier Science Ltd
Place of publicationThe Boulevard, Langford Lane, Kidlington, Oxford, England, Ox5 1Gb
Rights statementCopyright 2022 Elsevier Ltd.