LOAD FACTOR OPTIMIZATION WITH DIFFERENT ALGORITHM

Abstract

—The energy is obtained to the primary and secondary substations during high demand, using dynamic weight-based load. The shifting algorithms minimize demand by shifting the load, maximizing utilization and enhancing load factor efficiency by distributing loads over various time frames. Maintaining stable demand and increasing users' consumption is a cost-effective way of increasing output while maximizing the usage of electricity. The load factor would improve in both cases and, thus, reduce the average unit cost per kWh. The main factors in establishing the theory of optimal energy usage are high energy use and the depletion of established energy resources. The existing algebraic theory model approach is incapable of properly optimizing the load factor for a large distribution network, resulting in excessive load energy consumption. To solve this issue, this article proposes many load factor optimization methods. The trend of the grid's load curve is studied in order to achieve the grid's optimum load factor management under various situations. The simulation findings indicate that the Genetic Algorithm approach performs better in terms of control performance and accuracy while optimizing load factors