An adaptive piecewise linearized weighted directed graph for the modeling and operational optimization of integrated energy systems

被引:17
作者
Qin, Chun [1 ,2 ]
Zhao, Jun [1 ,2 ]
Chen, Long [1 ,2 ]
Liu, Ying [1 ,2 ]
Wang, Wei [1 ,2 ]
机构
[1] Dalian Univ Technol, Key Lab Intelligent Control & Optimizat Ind Equip, Minist Educ, Dalian 116024, Liaoning, Peoples R China
[2] Dalian Univ Technol, Sch Control Sci & Engn, Dalian 116024, Peoples R China
关键词
Integrated energy system; Weighted directed graph; Part-load performance; Piecewise linearization; Operational optimization; POWER-SYSTEM; HUB MODEL; MANAGEMENT; HEAT; FRAMEWORK; STRATEGY; DESIGN;
D O I
10.1016/j.energy.2021.122616
中图分类号
O414.1 [热力学];
学科分类号
摘要
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.(c) 2021 Elsevier Ltd. All rights reserved.
引用
收藏
页数:15
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