Optimal active load scheduling in a day-ahead energy market with uncertainty in demand

Abstract

The existing power loads are continuously increasing and leading to various challenges related to economics and systems constraints. Any uncontrolled fluctuations of the demand over consecutive hours would dramatically complicate the correct management of the power generation. Therefore, this paper provides an effective solution for managing the uncertainty in loads and providing optimal scheduling of the power generation based on active load optimization in the day-ahead energy market. The proposed optimization model relies on operating active loads to encounter any unexpected change in the load pattern with taken into consideration the characteristics of these loads. The objective of the optimization model is to procure the lowest energy bill by reducing operational costs by taking into account the compensation cost in case of operating the active loads. The optimized problem is solved using mixed-integer linear programming through two technical stages. The first stage handles the normal operation of generation and passive demand, while the second stage treats all the uncertainty in stochastic scenarios. The active loads are operated under specific constraints such as the instantaneous min/max amount and the min/max duration over 24-h period of time. Case studies are used to demonstrate the effectiveness of implementing active loads.