Eid Ahmad, Alsafrani Abdulrahman
Department of Electrical Engineering, College of Engineering, Qassim University, Buraidah, 52571, Saudi Arabia.
Sci Rep. 2024 Dec 30;14(1):31648. doi: 10.1038/s41598-024-80432-z.
Unbalanced power systems cause transformers and generators to overheat, system losses to climb, and protective devices to trigger. An optimization-based control technique for distributed generators (DG) balances demand and improves power quality in three imbalanced distribution systems with 10, 13, and 37 nodes. Each system phase has its own DG. Particle Swarm Optimization (PSO) and Dynamic Arithmetic Optimization Algorithm (DAOA) determine each phase's best locations, sizes, and power factors. The PSO and DAOA algorithms optimize the three imbalanced distribution systems at full load and throughout the day. The three DG sources are at the same node for easy operation, maintenance, and control. Each system's voltage, power, and current imbalance factors (VUF, PUF, CUF) are determined according to ANSI and IEEE standards. Optimization techniques lower VUF to meet the criteria for all studied systems. PUF values drop from 116%, 28%, and 17% to virtually zero for the 10-, 13-, and 37-bus systems, while CUF improves similarly. Power losses are minimized by 80%, 51%, and 52% for each system. The voltage profile improves, reducing voltage variance across all three systems.
不平衡的电力系统会导致变压器和发电机过热、系统损耗增加以及保护装置触发。一种基于优化的分布式发电机（DG）控制技术可平衡需求，并改善三个分别具有10、13和37个节点的不平衡配电系统的电能质量。每个系统相都有自己的分布式发电机。粒子群优化算法（PSO）和动态算术优化算法（DAOA）确定每个相的最佳位置、大小和功率因数。PSO和DAOA算法在满负荷和全天运行时对这三个不平衡配电系统进行优化。这三个分布式电源位于同一节点，便于操作、维护和控制。根据美国国家标准学会（ANSI）和电气与电子工程师协会（IEEE）标准确定每个系统的电压、功率和电流不平衡因数（VUF、PUF、CUF）。优化技术降低了VUF，使所有研究系统均符合标准。对于10节点、13节点和37节点系统，PUF值分别从116%、28%和17%降至几乎为零，CUF也有类似改善。每个系统的功率损耗分别降低了80%、51%和52%。电压分布得到改善，降低了所有三个系统的电压方差。
