This suite of tools for energy portfolio management consists of physical assets and financial instruments of various kinds. Software are especially well–suited for risk analysis and decision making under uncertainty for a wide range of market evolution scenarios; and offer the additional vantage of already having several features of the current Brazilian regulation implemented.

OptFolio – Asset Portfolio Optimization

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Is a decision support tool for energy portfolio management, including physical assets, such as generating plants and financial assets, such as bilateral contracts and derivative instruments.

The objective is to maximize the present value of a cashflow of revenues of a given company. There are many sources of costs and revenues that are calculated by Optfolio when it builds the net cashflow:

  • Energy production costs, transmission tariffs, fixed costs, taxes, financial costs, such as contracts and other derivatives bought, and investment costs associated to the construction of new power plants;
  • Energy distribution revenues for distribution companies;
  • Financial revenues for contracts and other derivatives sold;
  • Company's market position (i.e. net seller or buyer). Market price scenarios can be considered.

The program determines the optimum investment decisions, both physical (i.e. building new power plants) and financial (i.e. buying or selling contracts and other derivatives) assets. Risk constraints in terms of Var such as minimum required revenue under Value at Risk may be considered.

The model has three options for the objective function:

  • Maximize for a given time horizon total net revenue;
  • Maximize utility function;
  • Maximize the minimum accumulated revenue in specified time intervals and over a set of hydrological scenarios.

The model represents the following aspects:

  • Obligatory project and mutually exclusive projects sets;
  • Power contracting limits;
  • Budget constraints;
  • Risk constraints in terms of Value at Risk - VaR;
  • Internal rate of return associated to each scenario.

Solution Approach

This problem is formulated as a mixed linear-integer programming.