Fuzzy mid term unit commitment considering large scale wind farms

Wind power provides a new challenge to system operators. Unlike conventional power generation sources, wind power generators supply intermittent power because of uncertainty in resource. In a large-scale wind power penetration scenario, wind intermittency could oblige the system operator to allocate the greater reserve power, in order to balance possible errors between predicted and actually wind power output. This would increase total operation cost. This paper presents a new approach to the fuzzy unit commitment problem using mixed integer nonlinear programming (MINLP), considering reserve requirement, load balance and wind power availability constraints. The modeling of constraints is an important issue in power system scheduling. These constraints are therefore ldquofuzzyrdquo in nature, and crisp treatment of them may lead to over conservative solutions. In this paper, a fuzzy optimization-based method is developed to solve power system UC problem with fuzzy objective and constraints. The problem is first converted to a crisp and separable optimization problem. Numerical testing results show that near optimal schedules are obtained, and the method can provide a good balance between reducing costs and satisfying reserve requirements.