About Using Electricity Pricing for Smart Grid Dynamic Management with Renewable Sources

Abstract

A new approach to the design subsets (clusters) of “objects” for optimal pricing in local systems of Smart Grid (SG) of the combined type has been proposed. In our case, under term “objects” we understand the day-time (more precisely, twenty-four hours) periods, in which the necessary measurements of informative, from the standpoint of the task, values (the energy generated by the components of the system, its current cost for each type of generator, etc.) were performed. We assume that systems Smart Grid are based on renewable generation sources such as solar radiation and wind energy in combination with such system components as high-power storage batteries and power generators based on autonomous power station. The obtained statistical information formed the basis of constructing models that describe certain optimal in terms of developed criteria of a subset of “objects” using bi-clustering algorithms. The authors of this innovative approach have in mind the further application of the model output (optimal clustering) for the dynamic estimation of the total cost of energy generated by its own components, taking into account the cost of the network involved in the subsequent periods of the day. In research the half-hourly sampling time within one day was used. Simulation on the basis of collected statistical data, the results of which can be applied in processes (algorithms) of electricity pricing for smart grid dynamic management with renewable sources has been performed.