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Energy management method of integrated energy system based on collaborative optimization of distributed flexible resources

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  • Liu, Jizhen
  • Ma, Lifei
  • Wang, Qinghua

Abstract

Under the background of energy internet and low-carbon power, integrated energy system (IES) has become an important carrier of energy conservation and emission reduction. The IES utilizes innovative energy management mode to coordinate various energy sources such as natural gas, electric energy and heat energy. It is composed of energy production, conversion, storage and consumption subsystems, which emphasizes breaking the isolation of energy subsystems through reasonable scheduling, realizing energy cascade utilization and improving energy utilization efficiency. In this paper, an energy management model with two-stage scheduling before day and in real time is proposed aiming at the collaborative optimization of generator-load-storage of IES. Firstly, the first stage is the day-ahead economic dispatch, which aims to realize the power distribution of units in the system. The day-ahead economic dispatching model takes the maximization of economic benefits, the maximization of exergy efficiency and the minimization of carbon emission cost as the optimization objectives, so as to make the day-ahead global optimal dispatching decision. Secondly, the second stage is real-time optimal scheduling, which aims at real-time power adjustment of the previous scheduling plan. The real-time optimal scheduling model takes the minimum interactive power deviation punishment cost, wind abandonment punishment cost and user satisfaction loss cost as optimization objectives, so as to balance the energy supply and load demand deviation between planned output and actual output. Thirdly, according to the characteristics of the model, Non-dominated Sorting Genetic Algorithm-II (NSGA-II) is used to solve the first-stage day-ahead economic scheduling, and YALMIP toolbox is used to solve the real-time optimal scheduling model. Finally, based on the established model, a typical IES is selected for case simulation, which verifies that the proposed method can effectively improve the economy of system operation.

Suggested Citation

  • Liu, Jizhen & Ma, Lifei & Wang, Qinghua, 2023. "Energy management method of integrated energy system based on collaborative optimization of distributed flexible resources," Energy, Elsevier, vol. 264(C).
    • Handle: RePEc:eee:energy:v:264:y:2023:i:c:s0360544222028675
    DOI: 10.1016/j.energy.2022.125981
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    References listed on IDEAS

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    2. Roldán-Blay, Carlos & Escrivá-Escrivá, Guillermo & Roldán-Porta, Carlos & Dasí-Crespo, Daniel, 2023. "Optimal sizing and design of renewable power plants in rural microgrids using multi-objective particle swarm optimization and branch and bound methods," Energy, Elsevier, vol. 284(C).
    3. Zhibin Liu & Feng Guo & Jiaqi Liu & Xinyan Lin & Ao Li & Zhaoyan Zhang & Zhiheng Liu, 2023. "A Compound Coordinated Optimal Operation Strategy of Day-Ahead-Rolling-Realtime in Integrated Energy System," Energies, MDPI, vol. 16(1), pages 1-19, January.
    4. Wang, Yubin & Zheng, Yanchong & Yang, Qiang, 2023. "Nash bargaining based collaborative energy management for regional integrated energy systems in uncertain electricity markets," Energy, Elsevier, vol. 269(C).
    5. Wang, Yubin & Zheng, Yanchong & Yang, Qiang, 2023. "Optimal energy management of integrated energy systems for strategic participation in competitive electricity markets," Energy, Elsevier, vol. 278(PA).
    6. Li, Jiamei & Ai, Qian & Chen, Minyu, 2023. "Strategic behavior modeling and energy management for electric-thermal-carbon-natural gas integrated energy system considering ancillary service," Energy, Elsevier, vol. 278(C).

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