Title: Capacity optimisation of rural distributed energy system based on two-stage robust optimisation algorithm

Authors: Juan Wang; Sirui Wang; Fengzhong Zhang; Xueyang Sun

Addresses: School of Electrical and Control Engineering, Shenyang Jianzhu University, Shenyang, 110168, China ' School of Electrical and Control Engineering, Shenyang Jianzhu University, Shenyang, 110168, China; State Power Investment Corporation Northeast New Energy Development Corporation Limited, Shenyang,110170, China ' School of Electrical and Control Engineering, Shenyang Jianzhu University, Shenyang, 110168, China ' School of Electrical and Control Engineering, Shenyang Jianzhu University, Shenyang, 110168, China

Abstract: In order to improve the energy utilisation of rural waste, a rural distributed energy system including wind energy, photovoltaic energy, biogas energy and energy storage is proposed in this paper. The capacity of the rural distributed energy system is optimised based on the two-stage robust optimisation model. The annualised life cycle cost, the differentiated time-of-use electricity price, as well as the discrete wind turbine capacity allocation are considered in the two-stage robust optimisation model. The results show that this distributed energy system including wind energy, photovoltaic energy, biogas energy and energy storage is suitable for rural energy distributed systems, it has excellent multi-energy complementary characteristics, which leads to a high utilisation rate of renewable energy. The capacity configuration without scheduling capacity can be calculated directly by the two-stage robust optimisation model. The uncertainty on the source and load side can be fully considered in the two-stage robust optimisation model, and it has excellent economy and security in the 'worst scenario'

Keywords: distributed energy; biogas power generation; two-stage robust optimisation; uncertainty.

DOI: 10.1504/IJMIC.2024.139096

International Journal of Modelling, Identification and Control, 2024 Vol.44 No.4, pp.368 - 378

Received: 24 Feb 2023
Accepted: 08 May 2023
Published online: 13 Jun 2024 *

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