| Operational reliability is provided in part by scheduling capacity in excess of the load forecast. This reserve capacity balances the uncertain power demand with the supply in real time and provides for equipment outages. Traditionally, reserve scheduling has been ensured by enforcing reserve requirements in the operations planning. An alternate approach is to employ a stochastic formulation, which allows the explicit modeling of the sources of uncertainty. This thesis compares stochastic and reserve methods and evaluates the benefits of a combined approach for the efficient management of uncertainty in the unit commitment problem. Numerical studies show that the unit commitment solutions obtained for the combined approach are robust and superior with respect to the traditional approach. These robust solutions are especially valuable in areas with a high proportion of wind power, as their built-in flexibility allows the dispatch of practically all the available wind power while minimizing the costs of operation.;The scheduled reserve has an economic value since it reduces the outage costs. In several electricity markets, reserve demand functions have been implemented to take into account the value of reserve in the market clearing process. These often take the form of a step-down function at the reserve requirement level, and as such they may not appropriately represent the reserve value. The value of reserve is impacted by the reliability, dynamic and stochastic characteristics of system components, the system operation policies, and the economic aspects such as the risk preferences of the demand. In this thesis, these aspects are taken into account to approximate the reserve value and construct reserve demand functions. Illustrative examples show that the demand functions constructed have similarities with those implemented in some markets. |
