Empirical continuous metaheuristic for multiple distributed generation scheduling considering energy loss minimisation, voltage and unbalance regulatory limits

摘要

Distributed generation (DG) and other electric resources such as batteries and electric vehicles are transforming the planning and operation of power distribution system all over the world. Although the operation gets more complex in the presence of DG, it also brings some potential benefits to the grid. In this study, the authors propose an optimisation approach for multiple DG units scheduling, considering a daily load profile. The main objective is to minimise the total energy loss in a period of time, dealing with a specific voltage and unbalance constraints, required by the Brazilian Electricity Regulatory Agency. The problem formulation results in a discontinuous non-convex objective function. An empirical continuous metaheuristic (ECM) is proposed to solve this challenging optimisation problem. As metaheuristic methods are suitable for this kind of problems, they present some limitations regarding final results variability, relative dependence on initial conditions and usually a large set of parameters to tune. ECM confronts directly these limitations, presenting good quality results in comparison to other well-known algorithms. By using the Open Distribution System Simulator - OpenDSS, and the well-known IEEE-123 distribution system, the proposed approach shows its effectiveness and efficiency to optimise the grid operation, with special attention to the Brazilian requirements for unbalance.