This article analyzed the cost of capital under risk conditions for thermoelectric plants in Brazil, applying the Capital Asset Pricing Model—CAPM and the Weighted Average Capital Cost—WACC. To estimate the local CAPM, we used information from the Electric Energy Index—IEE of publicly traded companies in the electricity sector in Brazil and for the global CAPM, we observed the companies associated with the Edison Electric Institute—EEI, listed on the New York Stock Exchange—NYSE and at the National Association of Securities Dealers Automated Quotations—NASDAQ—USA. The risk conditions for capital costs were represented by Monte Carlo simulation using, as a basis, the WACC of a fuel oil thermoelectric plant and the local and global CAPM. The main results show that the IEE and EEI companies obtained a positive average daily return. Due to the Brazil risk, under deterministic conditions, the local WACC (11.13% p.a.) was more attractive to investors when compared to the global WACC (10.32% p.a.) and the regulatory WACC of 10.55% p.a., established by the National Electric Energy Agency—ANEEL. The most risk-sensitive input variables were: unleveraged beta, net debt and equity. Under risk conditions observed by the market from the point of view of Brazilian companies, the chances of the WACC of the fuel oil thermoelectric plant being 11.1% p.a. was 68.30% and from a global perspective, the chance of WACC being 10.32% p.a. was 99.51%. It is concluded that the cost of capital under risk conditions provides a more realistic view of decision-making for privately held companies.

A hydro–solar hybrid system is an important solution for expanding renewable generation capacity under the percepts of the energy transition. This type of association allows for the coordinated dispatch of solar and hydropower plants, resulting in operational benefits in terms of energy generation and reservoir management, that is, the better use of available water and energy resources. As in this case, the operation of the hydropower plant is associated with the cascade in which it operates, when it is hybridized (for example, by associating with a solar power plant), in addition to local changes, there are impacts on the operating conditions of the other hydropower plants in the same cascade. From such a perspective, this study presents an energy system management model for hybrid power plants composed of hydro and solar sources, aiming to optimize the joint operation and measure the operational consequences at the local level and in the cascade. The results from a case study of a hydro–solar power plant hybridization in the Tietê River (Brazil) revealed increased energy production and improvement in the operating conditions of the cascade’s reservoirs, while the grid capacity was found to be an important constraint that limits the capture of synergies resulting from the generation sources complementarity and thus on the benefits to the cascade.

In the context of high energy costs and energy transition, the optimal use of energy resources for industrial consumption is of fundamental importance. This paper presents a decision-making structure for large consumers with flexibility to manage electricity or natural gas consumption to satisfy the demands of industrial processes. The proposed modelling energy system structure relates monthly medium and hourly short-term decisions to which these agents are subjected, represented by two connected optimization models. In the medium term, the decision occurs under uncertain conditions of energy and natural gas market prices, as well as hydropower generation (self-production). The monthly decision is represented by a risk-constrained optimization model. In the short term, hourly optimization considers the operational flexibility of energy and/or natural gas consumption, subject to the strategy defined in the medium term and mathematically connected by a regret cost function. The model application of a real case of a Brazilian aluminum producer indicates a measured energy cost reduction of USD 3.98 millions over a six-month analysis period.

In the context of high energy costs and energy transition, the optimal use of energy resources for industrial consumption is fundamental. This paper presents a decision-making structure for large consumers having flexibility to manage electricity or natural gas consume to satisfy the demands of industrial processes. The proposed modelling energy system structure relates monthly medium and hourly short-term decisions to which these agents are subjected, represented by two connected optimization models. In the medium term, the decision occurs under uncertain conditions of energy and natural-gas market prices, as well as hydropower generation (self-production). The monthly decision is represented by a risk-constrained optimization model. In the short term, hourly optimization considers the operational flexibility of energy and/or natural-gas consumption, subject to the strategy defined in the medium term and mathematically connected by a regret cost function. The model application of a real case of a Brazilian aluminum producer indicates a measured energy cost reduction of U$ 3.98 million over a six-month analysis period.