Abstract
Power flow (PF) analysis of microgrids (MGs) has been gaining a lot of attention due to the evolution of islanded MGs. To calculate islanded MGs’ PF solution, a globally convergent technique is proposed using Differential Evolution (DE)- a popular optimization algorithm for global non-convex optimization. This paper formulates the PF problem as a constrained optimization problem (COP) considering all the operating conditions of the Droop Controlled Islanded MGs (DCIMGs). To solve the proposed COP, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\epsilon $ </tex-math></inline-formula> DE-NGM, (Epsilon based Differential Evolution with Newton-Gauss-based mutation) is proposed. The proposed algorithm, <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\epsilon $ </tex-math></inline-formula> DE-NGM, is a novel variant of DE since it comprises a novel mutation operator, Newton-Gauss-based mutation (NGM). NGM includes all the important features of DE’s mutation strategies as well as reduces the constraint violation by utilizing the information of constraint-space. Numerical experiments validate that the global convergence ability of proposed algorithms in solving COPs than existing state-of-the-art algorithms. Furthermore, the proposed algorithm as a PF tool has better robustness than existing tools on ill- and well-conditioned systems with heavy loads, different limit violations, and inappropriate final solutions (far from the flat start). The performed comparative analysis confirms good agreement of accuracy and efficacy with the existing method for islanded MG’s PF.
Highlights
A microgrid (MG) has been recognized as a collection of Distributed generation units (DGs) interconnected with thermal and electrical loads, energy storage units, and capacitor banks
To overcome all the above-discussed limitations of stateof-the-art algorithms, this paper proposes a new Power flow (PF) formulation expressed in the form of the constrained optimization problem (COP), where different modes of operations of DGs, such as PV, PQ, and droops operations are modeled as problem constraints
This paper introduces an algorithm to solve the problem with many equality constraints by introducing a Newton-Gaussbased mutation (NGM) operator that finds a feasible solution from an infeasible solution using the NG [58] algorithm at the infeasible solution as an initial solution
Summary
A microgrid (MG) has been recognized as a collection of Distributed generation units (DGs) interconnected with thermal and electrical loads, energy storage units, and capacitor banks. The authors of [19] introduced a method based on the Particle Swarm Optimization (PSO) algorithm to solve the PF problem of DCIMGs [19], where PSO is employed to calculate the optimum droop parameters for sharing the reactive power This method cannot consider the sharing of active power among the DGs. In [20], the work of [19] is extended by implementing two operators, mutation and guaranteed convergence, in PSO. To overcome all the above-discussed limitations of stateof-the-art algorithms, this paper proposes a new PF formulation expressed in the form of the COP, where different modes of operations of DGs, such as PV, PQ, and droops operations are modeled as problem constraints. The microgrid system and load are modeled This is followed by formulating the constrained optimization problem for a power flow analysis of islanded MGs. In the fourth section, the main steps of the optimization algorithm are proposed.
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