Evaluating the Operator Risk-taking due to the Wind Resources and Load Uncertainties in Thermal Unit Commitment Problem by using Conditional Value at Risk Measure

The main advantage of employing stochastic programming compare to its deterministic counterpart in wind integrated thermal Unit Commitment (UC) problem is considering probable occurrence wind power and load scenarios by minimizing the expectation of operation cost. However, the major drawback of representing cost function by its expectation is ignoring the other important parameters of cost probability distribution function. One of the best methods to overcome this problem and at the same time maintaining the stochastic structure of the problem is the application of the concept of risk. In this context, in this paper the effect of wind resources ans load uncertainties on operator risk-taking in unit commitment problem will be analyzed by using the main risk measure namely Conditional Value at Risk (CVaR). The proposed model is Mixed Integer Linear Programming (MILP) which has been modified in the form of stochastic programming and containing risk measure terms. The wind power and load uncertainties has been considered in two ways including the consideration of wind penetration as a fraction of a basic value and also consideration of wind power and load prediction errors in the form of normal probability distribution with different variances.