Microgrids Operation by Considering Demand Response and Supply Programs in the Presence of IGDT-Based Reverse Risk

Abstract

Concerning the advantages of smart microgrids and the importance of selecting and using technologies accustomed to optimized planning and design of typology and capacity of supplies, demand response programs, and energy-storage charges, existing research has focused on the optimized design of microgrids using ant colony optimization algorithm. Conditions of the optimization problem are enacted on the objective function based on the technical and operational limitations of supplies and microgrids, which may lead to the limitation of response space of the problem. Additionally, a methodology is proposed for modeling and analyzing a novel design to consider the uncertainty of production and demand with reverse risk in the design of residential microgrids. The proposed methodology focuses on the uncertainty of photovoltaic production and load demand by solving two-dimensional multipurpose optimization problem based on information gap decision theory (IGDT). In the mentioned approach, the photovoltaic generation’s uncertainty and charge of photovoltaic generation are integrated into an equation to be solved as a problem. Regardless of the likelihood density function of uncertainty parameters and without preparing a firm framework, the current method integrates wind and photovoltaic production into the microgrids. The results of the mentioned method are conclusive, which make the problems solvable.

Keywords

• Ant colony algorithm
• distributed generation units
• demand response
• IGDT
• microgrid
• multipurpose stochastic optimization