Zangmo Rinchen, Sudabattula Suresh Kumar, Dharavat Nagaraju, Mishra Sachin, Basha C H Hussaian, Irfan Mohammed Mujahid
School of Electronics & Electrical Engineering, Lovely Professional University, Phagwara, 144411, Punjab, India.
School of Computer Science and Artificial Intelligence, SR University, Warangal, 506371, Telangana, India.
Sci Rep. 2025 Mar 10;15(1):8273. doi: 10.1038/s41598-025-92335-8.
In response to the market's increasing need for electricity and the escalating technical and environmental challenges, the Power System (PS) sector has strongly emphasised the escalating technical and ecological challenges, and the PS sector has placed a strong emphasis on integrating distributed energy resources (DERs) into distribution systems (DS). However, if not allocated optimally, integrating DERs can provide various technical topics such as power quality, stability, reliability, and voltage management concerns. Therefore, creating effective and efficient optimisation techniques to solve issues of DER integration is crucial. In this paper, the integration of DERs into DS is utilised by the Multi-Objective Evolution of the Whale Optimisation Algorithm (MEWOA). MEWOA is an optimisation method inspired by humpback whales' hunting strategies and has demonstrated promising results in solving challenging optimisation issues. The suggested approach tries to optimise the location and sizing of DERs in DS while considering several factors, including voltage variation, Power loss (P) reduction, and operational cost. The extensive simulations are run on the Indian 28-bus and IEEE 69-bus distribution systems to show the viability of the suggested approach. The findings demonstrate that the proposed method can significantly enhance the voltage profile, lessen P, lower the annual operating expenses and save revenue from P minimisation. The results also show that MEWOA outperforms other optimisation techniques like the Grasshopper Optimisation Algorithm (GOA), the Dragonfly Algorithm (DA), and the Whale Optimisation Algorithm (WOA) in terms of convergence speed and solution quality. As a result, the suggested way for integrating DERs into DS utilising MEWOA is a successful and efficient optimisation technique. The results demonstrate that the proposed approach can enhance distribution system performance while lowering operational expenses and environmental impact.
为响应市场对电力日益增长的需求以及不断升级的技术和环境挑战，电力系统（PS）部门强烈强调了不断升级的技术和生态挑战，并且电力系统部门高度重视将分布式能源资源（DER）整合到配电系统（DS）中。然而，如果分配不当，整合DER可能会带来各种技术问题，如电能质量、稳定性、可靠性和电压管理等问题。因此，创建有效且高效的优化技术来解决DER整合问题至关重要。在本文中，利用鲸鱼优化算法的多目标进化（MEWOA）将DER整合到DS中。MEWOA是一种受座头鲸捕食策略启发的优化方法，在解决具有挑战性的优化问题方面已展现出有前景的结果。所提出的方法试图在考虑包括电压变化、功率损耗（P）降低和运营成本等多个因素的同时，优化DS中DER的位置和规模。在印度28节点和IEEE 69节点配电系统上进行了广泛的仿真，以展示所提方法的可行性。研究结果表明，所提出的方法可以显著改善电压分布、减少P、降低年度运营费用并从P最小化中节省收益。结果还表明，在收敛速度和解决方案质量方面，MEWOA优于其他优化技术，如蚱蜢优化算法（GOA）、蜻蜓算法（DA）和鲸鱼优化算法（WOA）。因此，利用MEWOA将DER整合到DS中的所提方法是一种成功且高效的优化技术。结果表明，所提出的方法可以提高配电系统性能，同时降低运营费用和环境影响。
