Estimating the Feasible Operating Region of Active Distribution Networks using the Genetic Algorithm

The efficient use of flexibility that lies in the Distribution Network (DN) is essential for the integration of distributed energy sources. The Feasible Operating Region (FOR) can be used to aggregate this flexibility and enable its efficient use. Conventional methods used to estimate the FOR feature several disadvantages that can be mitigated using metaheuristic optimization methods, such as the Genetic Algorithm (GA). This paper is the first to use GA in the context of the FOR estimation problem, introducing the GA-FOR methodology. The characteristics and intricacies of the proposed methodology are thoroughly described, with emphasis on the fitness function, and the introduction of a problem-specific GA operator. The effectiveness of the GA-FOR is demonstrated using a case study, where the accuracy and efficiency of the method is compared to that of its nonlinear optimization counterpart.