No abstract

No abstract

No abstract

No abstract

Impacts caused by the connection of three-phase, medium size generators (≥ 1 MVA) directly to primary distribution networks (with voltage ≥ 10 kV) have been intensively investigated over the last 10 years. As a consequence, analysis, operation and protection practices are relatively well defined and accepted. During the maturation of this paradigm change on the electric energy generation, in general, utility engineers used to evaluate new connection requests individually, providing a report with possible requirements for project modifications. However, with the publication of Normative Resolution #482 and other actions, one may notice the interest of Brazilian government on encouraging the connection of renewable-based distributed generation (mainly photovoltaic generation) to secondary distribution networks. Such fact leads to a new scenario, different from the one investigated over the last 10 years, creating the need for new studies and analysis methodologies. In such context, this M.Sc. dissertation presents a probabilistic analysis methodology that adopts Monte Carlo simulations to identify the aggregated impact of multiple photovoltaic generators. Modelling techniques are presented for all problem uncertainties, which are mainly related to the power produced by generators and consumed by loads at each instant of the day. Two practical applications of the proposed method are also developed. The first application consists in developing technical indices that provide a simple and quick estimate (without performing any simulation) of the maximum power that may be injected into secondary networks without the occurrence of technical violations. The second application consists in a technique to estimate the future impact of photovoltaic generation on a utility feeder, in order to support engineers on the expansion planning of distribution networks. The analysis methodology and applications presented in this work can help to overcome the barriers for the interconnection of photovoltaic distributed generators.