Intelligent Optimization Technique For Multi-Source Energy Management In Residential Power Systems

Residential power grids are required to integrate energy storage devices and renewable energy sources of growing need for renewable energy. However, managing the variable nature of these energy sources while ensuring system reliability and cost efficiency remains a significant challenge. Current optimization techniques often struggle to address the dynamic fluctuations of renewable energy generation and the interplay between diverse energy sources, leading to inefficiencies and increased operational costs. Hence the multi-source energy management system is enhanced by implementing a novel intelligent Kepler optimization (IKO) framework in residential systems. Mathematical model for energy resources such as solar energy, wind energy, battery storage and grid power were developed for thermal and electrical appliances such as washing machines, television (TV), and microwave oven. The objective of the research is to implement an exact solution for the energy consumption problem that minimizes electricity costs in a residential power system, and optimizing the operation modes of various energy sources while coordinating their interaction for efficient energy management. The results were produced based on computing time, power consumption, and energy efficiency for washing machines (95sec)(480W)(92%), TV(75sec)(180W)(88%), and microwave oven (80sec) (1100W) (82%). The proposed method provides a robust and sustainable solution for energy management in residential power systems, effectively optimizing the multiple energy source and improving overall system efficiency.