Cost-saving potential of customer-driven distributed generation

Utilization of distributed generation (DG), in combination with the traditional supply from the grid, may help industrial and commercial customers to decrease their energy bills. The full cost-saving potential of DG would be released only in case when all inputs were known for the overall billing period in advance. Under the realistic conditions, where a set of important input variables exhibit a stochastic change and where the customers are billed not only for energy but also for the monthly peak demand, it remains to search for dispatch solutions capable of bringing the savings as close as possible to the theoretical maxima. In this paper, we propose a novel real-time near-optimal DG dispatching algorithm, which takes into account all the input parameters recognized up to now as respectable. The algorithm has been extensively tested showing an excellent performance over a wide range of operating conditions.

► A novel real-time near-optimal algorithm to dispatch customer distributed generation.
► A release of almost total theoretically available cost-saving potential.
► Up to now largest set of input parameters included in the models.
► A stochastics is respected where required.
► The method is validated using the Monte Carlo simulations.