Improving The Performance of Distribution Systems with The Aid of Intelligent Cooperative Agents

Abstract

In this work, the performance of distribution systems is improved via reactive power compensation. Reactive power compensation is an important procedure for transmission and distribution power systems. The installation of shunt capacitors on radial distribution systems is essential for power flow control, improving voltage stability, power factor correction, voltage profile management, and loss minimization. It is important to find the optimal size and location of capacitors required to minimize feeder losses (power and energy), and the suitable time to switch the capacitors on and off. Normally, the solution techniques are classified into four categories; analytical, numerical programming, heuristic, and artificial intelligence-based (AI-Based). Many nature inspired meta-heuristic algorithms have been attempted for reactive power compensation of radial distribution feeders. In this work, we introduce and implement a novel accelerated particle swarm optimization technique. Results of the proposed approach are compared with previous methods to show the superiority of the proposed method using many actual distribution feeders (e.g. 9 bus, 15 bus, and 69 bus feeders). This new simple technique has the ability to give the best results for maximum reduction in system losses and costs among all previous studied techniques.