Optimal Design of Regulated Capacitor Banks Based on Load Curve Changes Using Intelligent Algorithms

Abstract

The use of controlled parallel capacitor banks is one of the most common methods to reduce losses and compensate reactive power in industrial distribution networks. Compensating reactive power can achieve goals such as reducing energy losses, peak power reduction, releasing equipment capacity, and improving voltage profile. The main challenge in selecting variable capacitor banks (controlled by regulators) is determining the appropriate number and value of each capacitor and the number of regulator steps. The optimal number and capacity of capacitors in each capacitor bank should be determined in harmony with the load curve of the network. In choosing a capacitor bank, the number and capacity of capacitors should be selected in a way that, while controlling the power factor and voltage range within the permissible range and proportional to the load curve, minimizes costs and the potential drawbacks of capacitor switching. Therefore, after evaluating the capacitor bank's capacity, this article aims to use an intelligent algorithm to select the number and value of capacitors (regulator steps) in a way that optimizes the cost of equipment procurement and the number of capacitor switching operations for the specified load curve and problem constraints. The optimization results using intelligent algorithms are simulated in DigSilent software to evaluate the algorithm's performance and accuracy. This article utilizes DigSilent for load flow and power network analysis and MATLAB for implementing optimization algorithms, and the results of the studies demonstrate good accuracy and reliability.