Collaborative optimization scheduling of integrated energy system considering user dissatisfaction

Kai Ma, Rencai Zhang, Jie Yang and Debao Song

Energy, 2023, vol. 274, issue C

Abstract: Traditional industrial parks generally have the problem of energy waste and low energy utilization. In this paper, we study a multi-energy collaborative optimization problem between integrated energy system (IES) energy scheduling and production control of plant, which considers the change of user dissatisfaction caused by load adjustment after industrial users participate in multi-energy demand response (MEDR). The collaborative optimization problem is described as a quadratic programming (QP) problem, including energy equipment output and production equipment operation load under constraints. The QP problem is solved by Cplex solver. An IES framework is constructed and its components are modeled separately. Then, based on Taguchi loss function and Fanger thermal comfort model, a collaborative optimization model of plant IES considering the user dissatisfaction is proposed. Furthermore, the collaborative optimization model is applied to control the IES and plant production. Simulation results show that the proposed optimization model can reduce the energy cost and user dissatisfaction, and improve the energy efficiency.

Keywords: Collaborative optimization; Integrated energy system; Multi-energy demand response; User dissatisfaction; Quadratic programming (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:274:y:2023:i:c:s0360544223007053

DOI: 10.1016/j.energy.2023.127311

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