An algorithmic game approach for demand side management in smart grid with distributed renewable power generation and storage

In this paper, the problem of minimizing electricity cost and the peak system load in smart grids with distributed renewable energy resources is studied. Unlike prior research works that either assume all of the jobs are interruptible or power-shiftable, this paper focuses on more challenging scenarios in which jobs are non-interruptible and non-power-shiftable. In addition, as more and more newly-built homes have rooftop solar arrays, it is assumed that all users are equipped with a solar-plus-battery system in this paper. Thus, power can be drawn from the battery as needed to reduce the cost of electricity or to lower the overall system load. With a quadratic load-dependent cost function, this paper first shows that the electricity cost minimization problem in such a setting is NP-hard and presents a distributed demand-side management algorithm, called DDSM, to solve this. Experimental results show that the proposed DDSM algorithm is effective, scalable and converges to a Nash equilibrium in finite rounds.