Demand side management using fuzzy inference

Electrical distribution utilities have been dealing with the problem of estimating distribution network load diagrams, either for operation studies or in forecasting models for planning purposes. Load curve assessment is essential for the efficient management of electric distribution systems. Demand-side management (DSM) constitutes what is often a very effective integrated resource, because the load reduction is at the customer site and the information about its impact on load figures is crucial, mainly if we think about its effects in network expansion planning. In this paper, we present a fuzzy inference tool to model the demand-side actions through inference mechanisms aiming at explicitly including the influence of those factors in the estimation of load at a spatial load distribution level. This tool allows the DSM effects on the network and distribution/generation politics to be anticipated, integrated in a philosophy of sustainable development. The approach is also capable of explicitly including these influences in a spatial forecasting environment and easily reflecting the predicted results in the marginal costs of a real electricity network represented on a geographical basis.