Welfare-aware strategic demand control in an intelligent market-based framework: Move towards sustainable smart grid

摘要

To address sustainability challenges appeared in today's power grids, it is essential for emerging demand control paradigm to be adapted more to the lifestyle of the customers. In this paper, due to the ever-growing interconnectivity of the grids, a distributed Commodity Market (CM) framework is proposed in which intelligent agents embedded inside of customers want to maximize their preferred welfare through real-time demand of power from an energy market. Since there is not a comprehensive model for the grids, utilizing Reinforcement Learning (RL) proves that the global optimal performance is achieved in the Nash Equilibrium (NE) of the proposed framework. This solution not only maximizes the resource utilization of the market, but also allocates strategically optimal demands of the customers who have budget constraints. Considering buying power and diverse assumption-free interests of the customers are two of the novelties offered. To consider social objectives for the communities that may give priority to social values, a socially intelligent ability is added to the proposed framework as an option. In this case, social concepts such as social welfare and social fairness will be met among the customers. Finally, a framework is developed for the customers who have the aim to consider economic goals such as cost minimization in addition to welfare maximization. Considering simultaneous quantitative and qualitative goals in a joint optimization form for the budget-constrained customers without any restrictions on the customers' preferences or the supply side is another novelty offered. The simulation results confirm that not only can the developed frameworks significantly improve the welfare in a stable manner, but also they are more successful in obtaining the demand during peak hours than just the economic frameworks proposed in the literature.