ALOCAÇÃO ÓTIMA DE CHAVES E INDICADORES DE FALTA PARA MINIMIZAR AS PENALIDADES PAGAS POR CONCESSIONÁRIAS DE DISTRIBUIÇÃO DE ENERGIA ELÉTRICA.

Abstract

The importance of electric energy in the society imposes on utilities the need to assess the reliability of the electric power supply and to adopt measures that minimize the impact of interruptions. Regulatory agencies establish quality limits, which, if extrapolated, will result in penalties for distribution utilities. In this scenario, the reliability index estimation methods are tools that help the planning and operation of the electrical network oriented towards the fulfillment of acceptable standards. Reliability indices can measure the frequency and duration of interruptions in the distribution networks, i.e. the DEC index, which is the average annual unavailability for a group of consumers. The penalties paid by the distribution utilities depend on DEC. That is, each time the acceptable limit of DEC is violated, a penalty is paid. Thus, modifying DEC's probability density function implies a reduction in penalties. Another cost associated with the reliability indices is the customer interruption cost for the consumer classes. These costs express the economic impacts of an outage for different types of consumers based on the duration, frequency and energy not supplied due to outage. The allocation of devices in the electrical network is a low cost and very effective resource to maximize the reliability of distribution network. However, the effect of the allocation on the penalties has never been assessed. Automatic and manual switches are efficient in reducing consumers' restoration times due to the increased sectionalizing capacity of the network. Fault indicators and automatic keys are important to indicate a path closer to the fault. In this way, the consumers' restoration time is reduced due to the reduction of fault location time. Therefore, this dissertation proposes a method that aims to reduce the costs associated with penalties and interruptions through the optimal allocation of manual keys, automatic keys and fault indicators. This optimization problem was solved using multiobjective optimization techniques based on the Pareto surface theory. In addition, surrogate models have been developed to reduce the computational cost of estimating penalties. The results of the tests demonstrated that the multi-objective optimization model managed to obtain solutions with an acceptable compromise between installation / maintenance costs and reliability. Additionally, the surrogate models for estimating penalties demonstrated good accuracy and low computational cost in relation to Monte Carlo Simulation.