LAUSR

Abstract Power mismatching between the generated and consumed power is caused by the stochastic and unpredictable demand energy, resulting in increasing the electricity bill and the load energy waste. A consensus algorithm-based coalition game theory for optimal demand management scheme is proposed for multi-agent smart microgrids (SMGs). The consensus algorithm depends on the information and data transfer among the neighbors in the multi-agents SMGs. The consensus algorithm for the demand management system has been proposed to improve the coalition game theory. The allocation of the surplus energy on the deficient customers is based on Shapley value, which enables the unequal distribution of power according to the demand. The computational and storage units are shifted to the Fog layer to deal with the multi-agents SMGs' extensive data and information. The proposed method's main objectives are minimizing the energy cost, energy waste in the presence of packet losses, and power mismatching. A hypothetical SMG system has been simulated and modeled using the MATLAB environment program to prove the proposed method's effectiveness. Three scenarios are performed, including without a demand management system, coalition game theory only, and consensus algorithm-based coalition game theory. A comparison between the obtained results has been performed. Sensitivity analysis based on the increasing of iterations and the number of homes is performed to prove the effectiveness of the proposed method. Also, a comparison between the optimization outcomes obtained results is implemented using genetic algorithm (GA), particle swarm optimization (PSO), ant colony optimization (ACO), and artificial bee colony (ABC) optimization techniques. The results prove the applicability and feasibility of the proposed method for the demand management system in SMG. The proposed method achieves an improvement of 8.056%, 6.629%, and 98.888% for the incremental cost, the total electricity bill, and load energy waste concerning their values without applying the energy management system, respectively.