Optimal Power Flow Analysis with Focus on Stochastic Demand Side Management

Abstract

This study introduces a comprehensive method to optimize distribution networks, focusing on improving performance and efficiency. The process consists of several distinct stages aimed at achieving these goals such as minimizing Active, Reactive power losses and Voltage Profile improvement. The journey begins by conducting a load flow analysis spanning 24 hours, initially excluding Distributed Generators (DGs) and Demand Side Management (DSM). Once this baseline is established, DGs are strategically placed within the distribution network. To further refine the system, tailored DSM strategies are applied separately for both Summer and Winter Seasons. This integrated approach significantly reduces losses. To guide the optimization process, a Multi-Objective Index (MOI) is employed. This index considers factors like Active Power Loss, Reactive Power Loss, and the inverse of Average Voltage. The ultimate goal is to minimize the MOI, leading to improved network efficiency by using the Sea Horse Optimization (SHO) Algorithm. The most optimal MOI value for each hour is selected from these iterations. These refined values are then integrated into the Easyfit distribution analysis, a tool that identifies the distribution pattern that best fits the data. The final solution is determined based on the MOI value associated with the highest Probability Density Graph. This systematic and data-driven approach ensures the IEEE-33 bus system for the distribution network is efficiently optimized to accommodate real-world load fluctuations and operational needs. In the end, we compared the outcomes of the existing ABC algorithm with our new SHO algorithm. The results clearly show that our SHO algorithm is better and works more efficiently than ABC.