Bi-objective Rolling Operation Optimization Based on Surrogate Model Acceleratiy of Community-Level Integrated Energy Systems

doi:10.11930/j.issn.1004-9649.202205056

Abstract

Abstract: Uncertainties in community-level integrated energy systems (CIESs) have been increasing due to the high penetration of distributed generation. Besides, the economic and environmental operation of CIESs should be considered at the same time, making its optimal operation problem a typical bi-objective one. In this paper, a bi-objective rolling scheduling method for CIES is proposed, based on the triangle splitting searching algorithm. Firstly, the surrogate model is employed to explore the feasible region. Then the surrogate model accelerated bi-objective optimization method is applied in the framework of model predictive control (MPC), in which the operation strategy is optimized according to the updated forecasting information. Finally, the proposed method is verified by a case study of a practical CIES to demonstrate its effectiveness and feasibility.

Key words: community-level integrated energy system (CIES), surrogate model, rolling optimization, bi-objective optimization, improved triangle splitting algorithm

HU Xiaoman, TIAN Weikun, SONG Guanyu, YU Hao. Bi-objective Rolling Operation Optimization Based on Surrogate Model Acceleratiy of Community-Level Integrated Energy Systems[J]. Electric Power, 2023, 56(4): 130-137,145.

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URL: https://www.electricpower.com.cn/EN/10.11930/j.issn.1004-9649.202205056

https://www.electricpower.com.cn/EN/Y2023/V56/I4/130

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