Stochastic analysis of the implementation of distributed generation utilizing Monte Carlo Simulation

Abstract

Over the years, there has been a significant increase in the number of photovoltaic installations, this is due to the innovation of the electric sector based on new regulations, government incentives and more accessible technologies. However, the vast majority of existing low voltage networks were not expected to absorb a large volume of distributed generation, mainly residential feeders, which generally have low demand during the day, when photovoltaic generation reaches its peak production, which it can cause a reversal of the energy flow in the feeder, resulting in a series of technical losses for the energy distributors. This article presents a method using Monte Carlo Method (MMC) to analyze the losses associated with high photovoltaic insertion in secondary distribution networks, in order to guarantee quality electrical energy, without jeopardizing the expansion of photovoltaic generation. To perform the simulations and allocations, the algorithm is implemented in Python programming language, which uses the OpenDSS COM interface for power flow calculations.