Reliability-constrained optimal design of multicarrier microgrid

The unprecedented penetration of distributed generation in distribution energy networks provides utilities with a unique opportunity to manage portions of networks as microgrids (MGs). The implementation of an MG may offer many benefits, such as capital investments deferral, reduction of greenhouse gas emissions, improvement in reliability, and reduction in network losses. Future energy networks will contain various forms of energy which are acquired by mixing several sources and energy storages in the concept called multicarrier microgrid (MCMG). In order to draw the most effective performance from MCMG systems, appropriate design and operation are essential. This paper represents a compound co-optimization strategy to find the best type and size of components and the associated optimum dispatch in a grid-tied community MCMG implementing reliability criteria. Here, the required level of reliability is handled within the optimization process to fulfill multiple demands. The mixed-integer nonlinear programming (MINLP) technique of general algebraic modeling system (GAMS) and the genetic algorithm of MATLAB software are utilized to solve the co-optimization problem. Additionally, a contemporary time-based demand response program is modeled to reshape the load curve, as well as prevent the undue use of energy in peak hours. Eventually, the proposed strategy is applied to a test case to select the best components while respecting reliability restrictions. Numerical simulations prove the effectiveness of the proposed expansion planning.