Reliability‐constrained optimal design of multicarrier microgrid

Abstract

Summary 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.

Reliability Assessment of Wind-Solar PV Integrated Distribution System Using Electrical Loss Minimization Technique

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“…To fulfill the RA in EDS [15], has introduced a restoration strategy for ENS calculation. The optimization of reliability indices has been considered in [20,23], and the improvement in the system's reliability is observed.…”

“…Voltage stability margin or bus voltages are also dependent on this RP support. The RPL is obtained at different pf of DG using Equation (23).…”

Hybrid wind‐solar grid‐connected system planning using scenario aggregation method

“…Simulation results showed that MO-CSA found well-distributed and widely spread non-dominated solutions in the Pareto front. Amir et al 20 presented a co-optimization method based on the mixed integer nonlinear programming and GA to find best size and of components of microgrid. Different reliability indices were considered in solving the optimization problem.…”

“…Supply-demand equality constraint mentioned in Equation 14is expressed using Equation (27). The C s , H s , U s , and V s matrices in the compact matrix form express the matrices in Equations (16), (18), (19), (20), and (21) of the optimization problem described Section 3. The vector d s in Equation (27) represents the demand expressed in Equation (22).…”