Study On Optimal Generation Scheduling Models And Methods Of Large-scale Wind Power Integrated System

The great development of wind power and other renewable energy is conducive to China's energy structure adjustment, the energy conservation and emission reduction of power system is also promoted. However, the volatility, uncertainty and inverse peaking character of wind power bring a lot of problems to the operation of the power system. The influence of AGC reserve, spinning reserve and peak regulation are considered in this dissertation, and the optimal scheduling model and algorithm of large-scale wind power integrated into power system are studied.A forecast method of AGC reserve demand caused by wind power is proposed. The volatility of wind power is analyzed by maximum entropy spectral analysis method, and the wind power fluctuation components of critical time-scale are separated by the rolling average method. AGC reserve capacity demand caused by wind power is calculated and analyzed with practical case data.In order to take full advantages of various types of AGC unit and promote the full competition of AGC units, an optimal AGC reserve scheduling approach of wind power integrated system is proposed. The objective function is to minimize both the cost of electrical energy and AGC reserve capacity. AGC regulation speed constraint, AGC regulation capacity constraint and AGC regulation range constraint are taken into account. The unit commitment and AGC reserve scheduling model of wind power integrated system is established. Case study demonstrats that the proposed approach and model can quantify AGC reserve capacity demand which is caused by wind power, and distinguish AGC regulation performance of different units effectively.In order to analyze the impact of N-1contingency and wind power on spinning reserve capacity scheduling, an optimal spinning reserve scheduling approach considering wind power and load fluctuations and N-1contingency is proposed. A reasonable range for each time interval is determined based on the wind power forecast error distribution and load forecast error distribution. Firstly, the uncertainty scenarios are determined. Secondly, the line transmission capacity constraints, structural changes of network topology in single contingency scenarios, and the ramping constraints in continuous fluctuation scenarios and instantaneous discrete fault scenarios are considered. At last, an optimal spinning reserve scheduling model with the consideration of multi-scene is established. Meanwhile, Benders decomposition is used to reduce the scale of the model. Numerical example results show that this approach can co-optimize the unit commitment and spinning reserve scheduling, and its self-healing correction capability in each scenario is assured.This dissertation adopted the probabilistic approach to deal with the uncertainty of wind power and N-1contingency. The wind power scenarios are generated by Latin hypercube sampling method based on the prediction of wind power and its prediction error distribution, and these scenarios are reduced by simultaneous backward and fast forward reduction method. The probability of N-1contingency is forecasted by markov chain. On this basis, a flexible stochastic optimal scheduling model considering wind power and energy storage system is developed with the consideration of the unit commitment and hierarchical coordinated optimal dispatch of AGC and reserve capacity. The proposed approach and model consider the uncertainty and severity of N-1contingency and intermittent power resources, the cost of AGC and reserve capacity ancillary services, the remaining charge and discharge ability of energy storage devices as well as the network constraints. This complicated model is linearized and solved by commercial mixed-integer linear programming solver CPLEX. Numerical example results demonstrats that the proposed approach can hierarchical optimize the AGC reserve and spinning reserve of each unit. The impact of different time-scale's fluctuations and uncertainties of intermittent power are considered.In order to solve the consumptive problem caused by large-scale wind power in China, solutions to accommodate transprovincial wind power are proposed, and this dissertation studied the co-operation mode of wind power and energy storage system which is used to accommodate wind power locally. The wind power integration capacity under different peak regulation modes are analyzed. The minimum relative regulate deviation scheduling model of the regulation market is established. The applicability and effectiveness of the proposed model are verified. As for the scheduling mode of energy storage system which is used to accommodate wind power locally, the maximum wind power integration and economical wind power scheduling mode are proposed. The wind power integration capacity and system economy under different scenarios of wind power penetration and storage capacity are analyzed. Example shows that Energy Storage System(ESS) can balance the contradiction between peak regulation and abandoned wind power under economical wind power integrate mode.The optimal scheduling model of large-scale wind power integrated system and the scheduling model to accommodate wind power are proposed in this dissertation. It not only has academic value, but also has a practical value to promote the dispatch level of grid and the fast development of renewable energy.