journal article·2025-08-01Open access

A multi-objective flexible scheduling approach for power systems through incorporating multiple resources

Binxin Yin, Tong Liu, Yinzhao Zhang, Jidong Hu, Wang Ma, Liangyi Zhang, Ji Han

AIP Advances· Volume 15· Issue 8

Abstract

The power system scheduling process faces significant flexibility challenges due to the growing need for coordinated operation among diverse power sources and the increasing penetration of renewable energy. This paper proposes a multi-objective power system dispatch method that adapts to dynamic operating conditions and varying levels of renewable energy integration. The proposed approach considers the coordinated operation of wind, photovoltaic, hydropower, thermal power, and energy storage systems. The proposed method, developed within a unified scheduling framework, integrates key components, including deep peak shaving of thermal power, cascade coordination of hydropower, dynamic evolution of energy storage states, and forecasting of wind and solar outputs. It incorporates the operational characteristics and constraints of diverse power sources into the system model. Multiple scheduling objectives are unified into a weighted optimization model by introducing adjustable objective weight coefficients, allowing flexible switching between different operational preferences. The objectives include minimizing thermal power generation costs, maximizing energy storage benefits, minimizing renewable energy curtailment, and reducing external power purchase costs. Simulation results based on an improved IEEE 30-bus system demonstrate that the method effectively coordinates resources under varying load conditions and weight configurations, while balancing economic efficiency and renewable energy utilization. The approach shows strong practical applicability and scheduling flexibility.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Electric Power System Optimization · Smart Grid Energy Management · Optimal Power Flow Distribution

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

State Grid Hubei Electric Power Research Institute 1 , Wuhan 430077,

College of New Energy, Harbin Institute of Technology at Weihai 2 , Weihai 264200,

Hubei Fangyuan Dongli Electric Power Science Research Co., Ltd. 3 , Wuhan 430077,

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