A New Point Estimate Method for Stochastic Optimal Operation of Smart Distribution Systems Considering Demand Response Programs

Smart Distribution Systems (SDS) with different technologies in Distributed Energy Resources (DER) and different load management facilities require proper operation strategies with considering the stochastic behavior of decision variables. Accordingly, this paper proposes a new Point Estimate Method (PEM) for optimal operation of SDS considering Demand Response Programs (DRP) under uncertainty in load and generation. In this paper optimal scheduling of DER units is investigated from economic and reliability viewpoints and also, the effect of DRP on operation of SDS is studied. The network is assumed to be supplied by renewable energy resources and Energy Storage Systems (ESS). The optimization aim is to minimize the operation and maintenance costs, power loss cost and cost of energy not supplied (ENS) simultaneously. The uncertainties of load demand and renewable power generation are considered using PEM approach as remarkable tool to handle the uncertainty. Ant colony optimization (ACO) is employed to minimize the objective function as a powerful optimization algorithm. The effectiveness and efficiency of the proposed approach are validated on PG&E 69-bus distribution system. The obtained results show that the proposed framework can be considered as an efficient tool in optimal operation of future distribution networks.