Optimal probabilistic planning of passive harmonic filters in distribution networks with high penetration of photovoltaic generation

In recent years, distribution networks have been increasingly affected by the random nature of harmonic sources introduced by nonlinear load and renewable energy sources (RES) such as photovoltaic (PV) systems. This paper presents an approach based on Genetic Algorithm (GA) and Monte-Carlo Simulation (MCS) for the optimal planning of single-tuned passive harmonic filters (PHFs) in a distribution network. The resistance and inductance of the lines within the network are modeled by frequency dependent characteristics. The probabilistic characteristics of the load and PV system currents are also considered for optimal planning of PHFs. In our optimization model, the objective function minimizes the total PHF installation cost and the energy losses, by considering the total harmonic distortion (THD) of bus voltages and maximum capacity of PHF as constraints. The proposed method is validated by a simulation study using an unbalanced three-phase real distribution system. An advantage of this method over most of the conventional approaches is that both harmonic current magnitude and phase angle of real PV systems are taken into account. Numerical results show the applicability and effectiveness of the proposed method.