Fair and efficient energy consumption scheduling algorithm using tabu search for future smart grids

Group Autonomous Demand-Side Management (ADSM) programs have the ability to reduce the energy cost and the peak-to-average ratio of the load profile. This can be done through the scheduling of the day-ahead energy consumption profile. In this work, a group ADSM program in which customers cooperate to reduce the total energy generation cost is investigated. The requirements of smart appliances are mathematically modelled and an aggregative game is formulated to model the strategic behaviour of the customers. To reduce the computational complexity of the group ADSM programs, an efficient energy consumption scheduling (ECS) algorithm based on tabu search (TS) is proposed. To overcome the unfair billing that might be associated with current ADSM programs, a fair energy consumption billing mechanism is developed in which customers are charged according to their own energy consumption and commitment to the assigned schedules. Simulation results demonstrate that the proposed TS-based scheduling algorithm achieves a considerable reduction in the computational complexity as compared to ECS algorithms based on parallel-Monte Carlo tree search and the benchmark branch and bound. Additionally, the results confirm that the proposed billing mechanism enhances the fairness level of the program.