A Technical and Economic Approach to Multi-Level Optimization Models for Electricity Demand Considering User-Supplier Interaction

One-level optimization methods have been proposed to optimize a single user's load profile or a cluster of users. In this work, two two-level optimization methods are studied, one case considering technical requirements and another considering economic criteria. In the upper level, the supplier optimizes it objective function. Meanwhile, at the lower level, users optimize their electrical costs. The proposed methods are based on Genetic Algorithm (GA) methods. In this sense, an indirect control is established in which users react to a price signal. Simulation results illustrate that both cases improve the demand profile and increase the retailer profit with respect to an unscheduled case. However, when the supplier tries to maximize the profit, some users receive benefits in detriment of others, concluding that the technical approach is preferable to the economic one.