Multi-Energy Optimal Dispatching of Port Microgrids Taking into Account the Uncertainty of Photovoltaic Power

Xiaoyong Wang, Xing Wei, Hanqing Zhang (), Bailiang Liu and Yanmin Wang
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Xiaoyong Wang: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Xing Wei: Yatai Construction Science & Technology Consulting Institute Co., Ltd., Beijing 100035, China
Hanqing Zhang: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Bailiang Liu: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China
Yanmin Wang: School of Electrical Engineering and Automation, Harbin Institute of Technology, Harbin 150001, China

Energies, 2025, vol. 18, issue 12, 1-23

Abstract: To tackle the problems of high scheduling costs and low photovoltaic (PV) accommodation rates in port microgrids, which are caused by the coupling of uncertainties in new energy output and load randomness, this paper proposes an optimized scheduling method that integrates scenario analysis with multi-energy complementarity. Firstly, based on the improved Iterative Self-organizing Data Analysis Techniques Algorithm (ISODATA) clustering algorithm and backward reduction method, a set of typical scenarios that represent the uncertainties of PV and load is generated. Secondly, a multi-energy complementary system model is constructed, which includes thermal power, PV, energy storage, electric vehicle (EV) clusters, and demand response. Then, a planning model centered on economy is established. Through multi-energy coordinated optimization, supply–demand balance and cost control are achieved. The simulation results based on the port microgrid of the LEKKI Port in Nigeria show that the proposed method can significantly reduce system operating costs by 18% and improve the PV accommodation rate through energy storage time-shifting, flexible EV scheduling, and demand response incentives. The research findings provide theoretical and technical support for the low-carbon transformation of energy systems in high-volatility load scenarios, such as ports.

Keywords: uncertainty of new energy; scene generation; port microgrid; multi-energy complementarity; optimized dispatching (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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