Distributed Demand Side Management With Stochastic Wind Power Forecasting

In this article, we propose a distributed demand-side management (DSM) approach for smart grids taking into account uncertainty in wind power forecasting. The grid model comprehends traditional users as well active (prosumers). Through rolling-horizon approach, prosumers participate DSM program, aiming at minimizing their cost the presence of uncertain generation by game theory approach. We assume that each user selfishly formulates its optimization problem noncooperative game. core challenge article is defining an to cope with availability. tackle issue from two different sides: employing expected value define deterministic counterpart and adopting stochastic approximated framework. latter case, employ sample average approximation (SAA) technique, whose results are based on probability density function (PDF) speed forecasts. improve PDF using historical data, control index takes weather condition stability. Numerical simulations real data set show proposed strategy generates lower individual costs compared standard