uncertainty-based multi-objective modeling for short-term demand response program scheduling in the presence of retail electricity providers

In this paper, the shortterm scheduling for demand response program (drp) with retail electricity providers (reps) with light physical assets is proposed. the main contribution is to determine an optimal multiobjective model for these reps to integrate them into designmodel of the incentivebased drp for retail markets, considering load uncertainties on the locational marginal prices (lmp). fuzzy logic modeling is used for simulating load uncertainty. nondominated sorting genetic algorithm (nsgaii) is used, due to nonlinearity and thus the complexity of the proposed model. a nonlinear sorting system based on fuzzy logic is also utilized to find the best compromise among the set of solutions generated by the paretofront space. ieee 24 bus reliability test system is utilized to explain the optimal performance of the proposed approach.

Uncertainty-based Multi-objective Modeling for Short-term Demand Response Program Scheduling in the Presence of Retail Electricity Providers

In this paper, the shortterm scheduling for demand response program (DRP) with retail electricity providers (REPs) with light physical assets is proposed. The main contribution is to determine an optimal multiobjective model for these REPs to integrate them into designmodel of the incentivebased DRP for retail markets, considering load uncertainties on the locational marginal prices (LMP). Fuzzy logic modeling is used for simulating load uncertainty. Nondominated sorting genetic algorithm (NSGAII) is used, due to nonlinearity and thus the complexity of the proposed model. A nonlinear sorting system based on fuzzy logic is also utilized to find the best compromise among the set of solutions generated by the Paretofront space. IEEE 24 bus reliability test system is utilized to explain the optimal performance of the proposed approach.