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<p>This study investigates the effects of renewable resource management in scenarios involving autonomous battery energy storage systems (BESS) controlled by an energy management strategy (EMS) to manage the timing of BESS charging and discharging as an independent entity. A cost-minimization problem is proposed, along with multiple objective, to improve the system’s reliability and performance by mitigating interruption costs for both the distribution system and consumers, to reduce the power loss costs occurring in line and distribution transformers (DT), and to enhance DT operation by minimizing aging costs. The Pareto-search (PS) algorithm is employed to optimize the allocation of solar photovoltaic (SPV) and wind turbine (WT) generators, along with BESS units, within a mixed-integer nonlinear programming framework. The research also focuses on reducing peak power demand and stabilizing power consumption during nonpeak periods. Three different case studies are validated using Bus 4 of the Roy Billinton Test System (RBTS). The modeling approach considers the fluctuating power outputs of renewable energy sources and the variation in load profile over time. The results demonstrate that the proposed approach can effectively mitigate system congestion during real-time operations, decreasing strain on conductors and equipment caused by peak power demand. Additionally, it leads to a decrease in system outages and power loss.</p>

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Integrating Renewable Energy Sources with Energy Storage for Distribution System Reliability and Performance Improvement: A Multi-Objective Cost-Minimization Approach

  • 期刊论文

  • 发表日期：

    2025年5月23日

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  • Sudipta Mohanty,
  • Manas Ranjan Nayak,
  • Amaresh Gantayet

摘要

This study investigates the effects of renewable resource management in scenarios involving autonomous battery energy storage systems (BESS) controlled by an energy management strategy (EMS) to manage the timing of BESS charging and discharging as an independent entity. A cost-minimization problem is proposed, along with multiple objective, to improve the system’s reliability and performance by mitigating interruption costs for both the distribution system and consumers, to reduce the power loss costs occurring in line and distribution transformers (DT), and to enhance DT operation by minimizing aging costs. The Pareto-search (PS) algorithm is employed to optimize the allocation of solar photovoltaic (SPV) and wind turbine (WT) generators, along with BESS units, within a mixed-integer nonlinear programming framework. The research also focuses on reducing peak power demand and stabilizing power consumption during nonpeak periods. Three different case studies are validated using Bus 4 of the Roy Billinton Test System (RBTS). The modeling approach considers the fluctuating power outputs of renewable energy sources and the variation in load profile over time. The results demonstrate that the proposed approach can effectively mitigate system congestion during real-time operations, decreasing strain on conductors and equipment caused by peak power demand. Additionally, it leads to a decrease in system outages and power loss.