Efficient Scheduling of Power Generating Units Using Grasshopper Optimization Algorithm

This article introduces a novel method for addressing the unit commitment problem in power systems by utilizing the Grasshopper Optimization Algorithm (GOA). Unit commitment is a crucial technique used in electric power systems for operational planning, aiming to schedule power generating units efficiently to meet load demand while minimizing total operational costs. This involves considering various operational constraints such as power balance, generation capacity, start-up expenses, and minimum durations for both starting up and shutting down. GOA is a mathematical model that accurately replicates the distinct characteristics of grasshopper behavior during both the nymph and adulthood phases, specifically their foraging behavior in search of food sources in the natural environment. The aim of this study is to identify the most efficient unit commitment for producing scheduling, with the goal of minimizing the total operating cost while considering various limitations. The proposed technique is applied to a test system consisting of 5 generating units over a time horizon of 24 hours. The numerical outcomes of the GOA are being compared to those of the Dynamic Programming (DP) technique in terms of the total operating cost. The findings revealed that GOA offers the most economical total operating cost in comparison to DP.