Load Shifting of Residential Load for Demand Side Management Using Tunicate Swarm Algorithm

Demand Side Management (DSM) is a critical strategy in the improvement of efficiency and reliability of the electrical system in smart grids. One of the effective DSM strategies is load shifting, which involves changing the timing of electricity consumption to off-peak hours. This paper gives a new approach to load shifting within residential areas through the Tunicate Swarm Algorithm. The TSA is an algorithm inspired by the swarming behavior of marine organisms called tunicates. These organisms are well known for their efficiency in movement and resource use. It is desired, within the scope of the proposed method, to optimize schedules for household appliances towards minimal electricity cost and minimal peak demand. TSA-based load-shifting technique: simulation result comparison with classical techniques—genetic algorithm and particle swarm optimization. It should be stated that the simulation results show a comparison of the performance of this proposed TSA-based technique about cost reduction and the mitigation of peak demand, which outperformed both GA and PSO. The results obtained in this study demonstrated that the TSA-based technique offers much potential for effective residential load management in smart grids, where quantifiable benefits could be derived in terms of energy savings and system stability. In the future, work will focus on real-world implementation and integration with other DSM strategies to enhance the overall efficiency of the electrical grid. This research adds to the ever-increasing bank of bio-inspired algorithms for energy management and acts as a springboard toward further areas of investigation in the field.