Distributed energy resources optimization for demand response using MILP

Demand response, over the years, has emerged as a key feature of smart grid. This paper investigates the problem of optimal demand response of residential customer equipped with smart loads, distributed storage and distributed generation which together form distributed energy resources (DER). A novel way of linking distributed storage i.e., battery operation to real time prices via a price threshold is proposed and incorporated in Mixed Integer Linear Programming (MILP) formulation to optimally schedule smart loads and battery. Simulation results validate that the price threshold constraint is effective in optimizing the battery charging/discharging cycles and MILP formulation optimally scheduled the loads for bill reduction within scheduling requirements. Finally, to show how distributed generation coupled with smart loads and distributed storage can further bring down energy costs, a comparison is drawn for various scenarios of customer DER set up.