Demand-Side-Management-Based Bi-level Intelligent Optimal Approach for Cost-Centric Energy Management of a Microgrid System.

Demand side management (DSM) separates elastic and inelastic loads and reorganizes a distribution system's load demand model while reducing the overall cost of the operation. This is accomplished by shifting flexible loads to hours with lower utility costs per unit. In this study, a bi-level optimization technique is used to reduce the operating costs of a low voltage microgrid system that uses battery energy storage, renewable energy sources, and fossil fuel generators while running in grid-connected mode. The load model is reorganized at the first level of optimization according to the DSM involvement level. Thereafter, the restructured load demand models are taken into account, and distributed generator scheduling ideas are percolated for reducing the microgrid system's generating costs in the second level. The optimization tool for the study was a newly established hybrid swarm intelligence algorithm that has previously been utilized to solve a variety of power system optimization challenges. For various grid participation models and grid pricing schemes, both with and without taking into account DSM, the generating cost was reduced. When 10%, 20%, and 30% DSM involvement was taken into consideration, the numerical findings reveal 25%, 50%, and 70% reduction, respectively, in costs. [ABSTRACT FROM AUTHOR]