Two-stage economic and environmental load dispatching framework using particle filtering

Economic load dispatch (ELD) is the operation of generation plants producing reliable electricity at the lowest cost, while recognizing limitations of the system. The environmental economic load dispatch (EELD) problem extends the ELD to include environmental considerations which makes it even more challenging due to the fact that it considers a very large scale and dynamic system that is highly complex and has inherent uncertainty. In this study, we propose a novel two-stage economic and environmental load dispatching framework using particle filtering for the efficient and reliable dynamic dispatching of electricity under uncertainty. The proposed framework includes (1) a short term demand forecasting algorithm using wavelet transform adaptive modeling, and (2) a dynamic load dispatching algorithm using particle filtering developed in a simulation environment. The proposed approach has been successfully demonstrated for different scenarios in the original IEEE-30 bus test system, which has been benchmarked against contemporary models available in the literature; and a modified version of the IEEE-30 bus test system, where the loads are modeled to update according to the weather and other external conditions.