Improved Polar Lights Optimizer Based Optimal Power Flow for ADNs with Renewable Energy and EVs
Peng Zhang,
Yifan Zhou,
Fuyou Zhao,
Xuan Ruan,
Wei Huang,
Yang He and
Bo Yang ()
Additional contact information
Peng Zhang: Yunnan Power Grid Co., Ltd., Kunming Power Supply Bureau, Kunming 650000, China
Yifan Zhou: Yunnan Power Dispatching and Control Center, Kunming 650000, China
Fuyou Zhao: Yunnan Power Grid Co., Ltd., Kunming Power Supply Bureau, Kunming 650000, China
Xuan Ruan: Yunnan Power Grid Co., Ltd., Kunming Power Supply Bureau, Kunming 650000, China
Wei Huang: Yunnan Power Grid Co., Ltd., Kunming Power Supply Bureau, Kunming 650000, China
Yang He: Yunnan Power Grid Co., Ltd., Kunming Power Supply Bureau, Kunming 650000, China
Bo Yang: Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 650500, China
Energies, 2025, vol. 18, issue 20, 1-25
Abstract:
With the large-scale integration of renewable energy sources such as wind and photovoltaic (PV) power, along with the increasing use of electric vehicle (EV), the operation of active distribution network (ADN) faces challenges, including bidirectional power flows, voltage fluctuations, and increased network losses. To address these issues, this study develops a multi-objective optimal power flow (MOOPF) model that simultaneously considers wind and PV generation, battery energy storage systems (BESSs), and EV charging loads. The proposed model aims to simultaneously optimize operating cost, node voltage deviation, and network losses, while ensuring voltage quality and system reliability. An improved polar lights optimizer (IPLO) is introduced to solve the MOOPF problem, enhancing global search capability and convergence efficiency without increasing computational complexity. Simulation results on the improved IEEE-33 bus test system show that compared with conventional algorithms such as GA, ABC, PSO and WOA, the IPLO optimizer achieves superior performance. Specifically, IPLO significantly reduces voltage deviation and network losses, while maintaining an average voltage level close to unity, thereby improving both voltage quality and energy efficiency. Furthermore, when compared with the original PLO, IPLO also demonstrates a reduction in operating cost. These results validate the effectiveness and applicability of the proposed IPLO-based MOOPF framework in ADNs with high use of renewable energy and EVs.
Keywords: active distribution network; optimal power flow; electric vehicle; renewable energy; energy storage; improved polar light optimizer (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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Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:18:y:2025:i:20:p:5403-:d:1770746
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