Abstract
A new methodology to dispatch in an economic and controlled manner the energy requirements of multiple energy storage devices, dispersed generators and loads belonging to a smart distribution grid (SDG) is presented in this paper. Plug-in electric vehicles (PEV) are mainly managed over a 24-hour time window. To maximize the economic social welfare of both a utility and PEV working as prosumers, this short-term economic dispatch (ED) problem incorporates two optimization processes interacting as an integrated model. In the first, aggregators located in the SDG maximize the economic benefits obtained by a PEV group. Fuzzy inference systems are used to estimate the decisions made by each PEV during its participation in energy exchanges with the SDG, which influence the PEV benefits. Using these results and a Mean-Variance Mapping Optimization algorithm, the economic benefits of the utility are maximized in the second process and, the ED is then solved.
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