An adaptive piecewise linearized weighted directed graph for the modeling and operational optimization of integrated energy systems. (1st April 2022)

• Record Type: Journal Article
• Authors: Qin, Chun; Zhao, Jun; Chen, Long; Liu, Ying; Wang, Wei
• Is Part Of: Energy. Volume 244(2022)Part A
• Publication Date: 2022-04-01
• Subjects: Integrated energy system -- Weighted directed graph -- Part-load performance -- Piecewise linearization -- Operational optimization; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2021.122616
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: Operational optimization plays a vital role in ensuring the economy, security, and environmental friendliness of integrated energy systems (IES), while the nonlinear operating characteristics of energy converters have brought significant challenges to the accurate modeling and solution. Considering the nonlinear energy conversion processes, a novel adaptive piecewise linearized weighted directed graph model of IES is proposed in this paper. To accurately construct the complex energy flow relationship in IES, a weighted directed graph is first presented to describe the energy generation, conversion, storage, consumption, and demand response, thus realizing the automatic modeling of IES. On this basis, for the diverse partial-load performance of energy converters, an adaptive piecewise linearization strategy is developed to approximate the nonlinear operating characteristics of various energy converters adaptively. By taking the system operating cost, calculation time, energy mismatch, and optimization model complexity as evaluation indicators, the effectiveness of the proposed method is verified by the numerical simulations of a typical small-scale combined cooling, heating, and power (CCHP) system and a large-scale IES in a realistic industrial park. Compared with the constant efficiency method and the equispaced piecewise linearization method, the computational efficiency and accuracy are remarkably improved by the proposed method. Highlights: A weighted directed graph-based operational optimization model of IES is proposed. An adaptive piecewise linearization strategy is proposed for variable efficiencies. Numerical simulations of a typical CCHP system and a realistic IES are performed. Effects of energy release, DR, and temperature on the operation of IES are studied.