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.

# OptValue – Analysis of investments under uncertainty

Is a valuation tool for generation projects. It is based on the search for an internal rate of return which is compatible with the risk associated to the plant construction and operation.

Through Optvalue different generation technologies can be compared under a risk x return perspective.

The model basic building block is the computation of a price of energy so that the project internal rate of return (IRR) for stock holders will be above a given target at a pre-established VaR level (e.g. with probability of 95% IRR will be above 15%). This computation involves plant investment cost, project finance, type of contract for selling energy, taxes, uncertainties associated to hydrology, investment costs, construction time, credit rate associated to energy buyer and so on.

Its main outputs comprise:

- Project energy price compatible with a given minimum stock holders IRR at a pre-established VaR level, or with a given expected value for the stock holders IRR;
- Probability distribution for the stock holders IRR;
- Probability distribution for the project discounted net revenue;
- Project optimal contracting level for hydro plants;
- Cash flow probability distribution;
- Contract energy price decomposition into: Investment cost, taxes, O&M, fuel costs, etc;
- Time series graphics associated to plant generation, revenues and expenses in the spot market, net revenue for stock holders, etc.

The risk x return trade-off across projects is established in terms of the IRR standard deviation versus its expected value.

#### Solution Approach

The problem is formulated as a stochastic financial simulation model.