Long-term security-constrained unit commitment for reliability analyses

This presentation discusses a model for calculating the cost of power system reliability based on the stochastic optimization of long-term security-constrained unit commitment (SCUC). Random outages of generating units and transmission lines as well as load forecasting inaccuracy are modeled as scenario trees in the Monte Carlo simulation. The presentation considers uncertainties when calculating the optimal reserve in the unit commitment solution as a tradeoff between minimizing operating costs and satisfying power system reliability requirements. The probabilistic reliability criteria, i.e. LOLE as a constraint and EENS cost are introduced in the objective function of the SCUC problem. The optimal operating point of power systems is based on the minimum total cost which includes operating and EENS costs. This optimal point is influenced by power system characteristics, generating unit and transmission line constraints, fuel prices, and load shedding costs. The optimal reserve level is implicitly determined by this optimal point which indicates that the marginal cost of additional reserves at the optimal point is equal to the marginal cost of reducing EENS at that point. The study can be used for the scheduling of fuel contracts as well the maintenance outage of components in a vertically integrated utility. The same formulation applies to long-term applications in an ISO while satisfying short term constraints in electricity markets. The proposed model can be used by a vertically integrated utility or an ISO. In the first case, the utility considers the impact of long-term fuel and emission scheduling on power system reliability studies. In the second case, fuel and emission constraints of individual generating companies are submitted as energy constraints when solving the ISO´s reliability problem. Numerical simulations indicate the effectiveness of the proposed approach for minimizing the cost of reliability in stochastic power systems [1].