No abstract

The operation of power systems under peak demand conditions results in higher operational costs, more instability risks and often forces an excessive use of fossil fuels. In this context, this paper proposes a self-sustainable real-time pricing (RTP) tariff that is adjusted proportionally to the aggregated demand of a group of consumers, and is based on a changing rate for each hour of the day. Therefore, demand peaks are expected to be naturally reduced by the group due to the higher tariff values imposed during these operating conditions. In addition, consumers benefit from the opportunity to reduce their bills according to the tariff and can carry out financial strategies by setting up their own consumption profile. The proposed dynamic tariff has a self-sustainable and revenue neutral nature which protects both consumers and distribution power companies from being economically affected by varying price elasticity scenarios. This is achieved by mathematically guaranteeing for such companies a revenue equal to the one they would expect with the traditional application of flat tariff. The advantages of the proposal are highlighted through numerical simulations by comparing it with the so-called Conventional Tariff and White Tariff, which are currently adopted by residential consumers in Brazil.

O presente artigo tem como finalidade buscar reduzir, mediante a análise de contingências realizada por meio do software ANAREDE, a probabilidade das concessionáarias pagarem valores elevados em encargos devido a parcelas de ineficiência, visando, assim, melhorar a contratação do Montante de Uso do Sistema de Transmissão (MUST). O processo se desenvolveu a partir da verificação do comportamento e impactos do fluxo de potência na região de Pato Branco no Paraná. Por fim, com a análise dos resultados obtidos, tornou-se possível a sugestão de intervalos para a contratação do montante, permitindo que essa fosse feita de modo a evitar as multas pagas por contratação errôneas.