Ahmed Oday A, Chong K H, Koh S P, Yaw Chong Tak, Pasupuleti Jagadeesh
Department of Electrical Engineering, University of Technology- Iraq, 35299, Baghdad, Iraq.
Institute of Sustainable Energy, Universiti Tenaga Nasional (The Energy University), Jalan Ikram-Uniten, Kajang, 43000, Selangor, Malaysia.
Heliyon. 2024 Sep 6;10(18):e37332. doi: 10.1016/j.heliyon.2024.e37332. eCollection 2024 Sep 30.
The distribution network is a crucial component of the power system, with industrialization driving increased energy demand. Traditional power-generating techniques, such as thermal and hydroelectric are not enough to meet this demand, leading to the development of Distributed Generation (DG). DG requires an extensive re-evaluation of the current power system, as it modifies energy losses and line flows. Inadequate integration of DG can cause power outages, disruption of protection coordination, and lead to islanding. AI can help overcome this issue by determining the best system architecture. Researchers have been interested in the Artificial Immune System (AIS) algorithm, which has room for development and lacks a fixed template. In order to improve AIS, X3PAIS, a hybridization strategy that combines clonal selection with a three-parent crossover has been developed within the scope of the study. X3PAIS was pre-tested using applications in a planetary gear train, a wastewater treatment facility, and mathematical calculations, showcasing its robustness and versatility. In the context of power distribution, X3PAIS is used in the multiple DG architecture of the power distribution system, reducing power losses by placing DG units in the best locations and sizing them to match load profiles. The four DGs' experiment results show that X3PAIS can minimize power losses by more than 89 %. To optimize power losses in the power distribution system, X3PAIS may be improved with a three-parent multiple-point crossover operation.
配电网是电力系统的关键组成部分,随着工业化进程的推进,能源需求不断增加。传统的发电技术,如热力发电和水力发电,已不足以满足这一需求,从而推动了分布式发电(DG)的发展。分布式发电需要对当前的电力系统进行广泛的重新评估,因为它会改变能量损耗和线路潮流。分布式发电集成不当可能会导致停电、保护协调中断,并引发孤岛现象。人工智能可以通过确定最佳系统架构来帮助解决这一问题。研究人员对人工免疫系统(AIS)算法很感兴趣,该算法仍有发展空间且缺乏固定模板。为了改进人工免疫系统,在本研究范围内开发了一种将克隆选择与三亲代交叉相结合的杂交策略X3PAIS。X3PAIS在行星齿轮系、废水处理设施和数学计算中的应用进行了预测试,展示了其稳健性和通用性。在配电方面,X3PAIS用于配电系统的多分布式发电架构,通过将分布式发电单元放置在最佳位置并根据负载曲线确定其大小来降低功率损耗。四个分布式发电单元的实验结果表明,X3PAIS可以将功率损耗降低89%以上。为了优化配电系统中的功率损耗,X3PAIS可以通过三亲代多点交叉操作进行改进。