Incorporating user utility in a smart microgrid with distributed generation and elastic demand

Demand Side Management (DSM) will play a large role in creating a pathway to a low carbon future. Microgrids are an ideal test bed for DSM within the Smart Grid (SG) framework, allowing for increased integration of distributed generation (DG), here focused on distributed Renewable Energy Sources (RESs). Existing work uses conservative estimates to model the stochastic nature of RESs, resulting in inaccuracies in simulation results. Large uncertainty in user specific participation in DSM programs exists. This paper develops a flexible energy load function, effectively incorporating different user's behaviour patterns into the DSM framework. Uncertainty in connecting small-scale wind generation into the smart microgrid is reduced by using an expected cost function to accurately map predicted wind speed to power output. Actual wind speed is varied across numerous sub-horizons within each time slot by using a pseudo-random number generator. The stochastic nature of renewable generation is effectively managed, producing a robust simulation. Model sensitivities are investigated and graphical results presented.