Most prior works on autonomous Demand Side Management (DSM) have focused on achieving various system goals, such as minimizing the total cost of generation or minimizing the peak-to-average ratio in the load demand. They fall short addressing the important issue of fairness . That is, while they usually guarantee optimality, they do not assure that the participating users are rewarded according to their contributions in achieving the overall system’s objectives. We design new autonomous DSM systems that can achieve both optimality and fairness. In this regard, we first develop a centralized DSM system to serve as a benchmark. Then, we propose a smart electricity billing mechanism that can improve fairness while maintaining close to optimal overall system performance. Next, we try to keep system optimality in our fair system. In this way, we introduce a fair. We show that there is a trade-off between optimality and fairness. Another important issue in implementing DSM programs is protecting the users’ privacy which is not widely addressed in DSM literature. We apply the Secure Sum algorithm to protect the users’ privacy in implementing these billing mechanisms. Key words Smart Grid, Demand Side Management, Fairness, Game Theory, Privacy.
