A two-stage framework for demand-side management and energy savings of various buildings in multi smart grid using robust optimization algorithms

Abstract

Advances in technology and population growth are two factors responsible for increasing electricity consumption, which directly increases the production of electrical energy. Also, due to environmental, technical and economic constraints, it is challenging to meet the demand at certain hours, such as peak hours. Therefore, it is necessary to manage the network consumption to modify the peak load and complete the power system constraints. One way to achieve this goal is to use a demand response program. The best infrastructure for running these types of programs is the smart grid (SG). This paper first considers many shiftable loads of different kinds in the SG, including residential, commercial, and industrial microgrids. The load shift method is, then, modeled as a multi-objective optimization problem to manage the shiftable load consumption of the SG. The main goals of this problem include reducing the cost of customer bills, the peak load, losses and improving network voltage. Simulations are performed by two methods of Simplex and Improved Grey Wolf Optimization (IGWO). The Simplex method is implemented with the CPLEX solver in General Algebraic Modelling System (GAMS) software and the IGWO algorithm is implemented in MATLAB software. Then, the effect of implementing the proposed program with both methods is examined and compared. For example, in terms of reducing the peak load, the CPLEX method could reduce the peak in the residential, commercial, and industrial microgrids by 6.7%, 1%, and 16% more than IGWO, respectively. CPLEX also can reduce the production costs of residential, commercial, and industrial microgrids by more than 3.5, 2.2, and 3.9% compared to IGWO. In general, the CPLEX solver provides better results than the IGWO in many cases.