ResumoNo setor elétrico brasileiro, as companhias de transmissão são remuneradas pela disponibilidade da capacidade de seus ativos, independentemente da quantidade de energia elétrica transmitida. Para induzir a operação eficiente das transmissoras, a ANEEL deve revisar periodicamente as receitas permitidas das transmissoras, considerando custos operacionais eficientes. Recentemente, a ANEEL publicou uma resolução em que descreve a metodologia utilizada no cálculo dos custos operacionais eficientes das transmissoras, a qual inclui um modelo de análise envoltória de dados (DEA). Neste trabalho propomos uma adaptação deste modelo DEA e apresentamos uma análise de sensibilidade dos resultados obtidos pelos dois modelos.Palavras-chave: análise envoltória de dados; transmissão de energia elétrica; revisão tarifária. AbstractIn the Brazilian power sector, the transmission companies (TRANSCOS) receive revenues by the availability of their transmission facilities, regardless of the amount of the electric power transmitted. To promote their efficient operation the regulator periodically revises the revenue caps. The calculation of efficient operational costs is the first stage of the tariff revision process. Recently, the regulator agent published a resolution describing the methodology used to set the revenues of the Brazilian TRANSCOS. This algorithm includes a data envelopment model (DEA) which is described in this paper. In this work we propose an alternative DEA model and present a comparison of the results obtained by the two models.
Information technology, when used appropriately, becomes an important factor for companies searching for logistics excellence. Among the information systems used to support logistics within the supply chain, Warehouse Management System (WMS) has been implemented by many companies that have complex warehousing operations. This article’s goal is to present a WMS implementation process project in a Distribution Center (DC) of a multinational corporation’s subsidiary located in Brazil that deals with home-care products within a high number of varieties. The introduction of the information system itself is not included in this article. Therefore, its current logistics operation is mapped and the main expected benefits with the WMS are analyzed. The article offers the main lessons learned with this new information system project.
In Brazil, power supply safety criteria is established by the sector regulation, the power supply insufficiency risk must not exceed 5% limit. Thus, the tools that enable agents to model the rationing more accurately became necessary, estimating the impact caused by such kind of event and the future consequences. The official model used by Brazilian electric sector to carry out the expansion planning and medium/long-term operation is based on Stochastic Dual Dynamic Programming technique (SDDP). The main results that this model presents are the monthly evolution projection of Short Run Marginal Cost (SRMC) and hydrothermal dispatch, considering various hydrological scenarios. However, such model does not contain the representation of conjuncture changes occurred during a rationing, such as, for example, demand retraction and thermal dispatch out of merit order. This paper presents a new alternative to estimate rationing effects on power operation planning.
ResumoO novo ambiente regulatório da energia elétrica no Brasil introduziu grandes mudanças na área de comercialização. Principalmente a adoção dos leilões de compra centralizada nos quais o governo adquire energia para os consumidores cativos. Nesse novo quadro institucional, as distribuidoras têm a responsabilidade de estimar a energia requerida para atendimento de suas áreas de concessão e são punidas caso cometam erros de previsão. As estimativas a menor são mais duramente punidas. Neste trabalho foram feitas simulações dos custos de contratação utilizando como aleatórios os percentuais de contratação da demanda prevista e um modelo de reamostragem do PLD (Preço de Liquidação das Diferenças), empregado no cálculo das punições. Concluiu-se que o sistema é frágil porque modificações no conjunto de usinas considerado pelo software NEWAVE (que determina os CMOs -Custos Marginais de Operação e, indiretamente, os PLDs) levam a resultados muito diferentes no que diz respeito ao valor das punições para uma mesma estratégia de contratação adotada por uma distribuidora.Palavras-chave: leilões de energia; simulação; regulação econômica. AbstractThe new regulatory framework in Brazilian electricity sector implemented several changes in the way energy is traded. Energy required by all captive consumers is now centrally purchased by the government. Distributors are only responsible for demand estimation in their concession areas. In case estimations prove wrong, distributors are punished differently for under or overestimations. Underestimations are punished harder. In this paper we simulate energy purchasing costs for a hypothetical utility in which random percentages of the forecasted demand are used. We also develop a resampling scheme for the PLD (Settlement Price), which is used to calculate penalties incurred by utilities. We conclude that, despite a very sophisticated regulatory framework, the system is fragile because changes in the inputs of the NEWAVE software (used to calculate the marginal cost of operations (CMO), which directly affects the PLD) yield very different punishment fees for a given (fixed) utility acquisition strategy.
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