Research On The Spinning Reserve Optimization Model Of Power System Containing Wind

Spinning reserve is one of the most important measures to improve the security and reliability of power system operation. The total amount of spinning reserve is usually determined by traditionally deterministic method which regards secure and stable operation of power system as primary consideration while makes less analysis and calculation of the relationship between uncertain factors and spinning reserve. With the implementation of policy that encourages renewable energy to develop, the scale of grid-connected wind power will constantly increase. However, due to the inherent uncertainty and intermittent of output wind power, a certain spinning reserve is needed to ensure the active power balance of power system when security and stability operation of power system is taken into account.In order to reflect the influences of the stochastic uncertainty of wind power on optimal decision-making of the power system spinning reserve, this dissertation proposes a probabilistic spinning reserve optimization method of power system with wind power. Firstly, this dissertation introduces the basically mathematical model of unit commitment problem and discusses the application of mixed-integer linear programming method in solving unit commitment problem. Secondly, this dissertation takes uncertain factors including fault outage of generators, predicted deviation of load and wind turbine output into account, analyzes the three uncertain factors through modeling and establishes the capacity outage probability table (COPT) considering prediction error of load and wind power output capacity. Finally, through fitting the COPT with the exponential function and introducing the analytic expressed probability reserve constraints into the unit commitment model considering the wind power, the probability reserve constrained unit commitment problem can be achieved organically with the aim of optimizing the spinning reserve of power system with wind power to the expectable contingency level. The case analysis shows that the proposed model is reasonable, providing a new model for uncertainty analysis and optimal scheduling decisions of power system with wind power.