Research On Wind Power Integration Planning Considering Peak-shaving Factors

Energy is important material basis for the survival and development of human society. Sustainable energy development is a prerequisite for sustainable economic and social development. With coal, oil, natural gas and other fossil energy resources depleting and environmental issues becoming increasingly prominent, the sustainability of energy is facing enormous challenges. It has become an inevitable choice of mankind to develop renewable energy vigorously. Wind energy becomes the focus of attention, for its advantages of abundance, widely distribution, and free pollution.Since the beginning of the21st century, wind power technology, which converts wind energy to electric power, has been developing rapidly. Installed capacity of wind power has increased annually, meanwhile, great wind power development and planing has been put forward in many countries including China. However, concerning its power fluctuation and uncertainty, large-scale wind power integration has great impacts upon the power system, such as peak-shaving, frequency regulating and voltage regulating issues, stability, power quality and so on. The peak-shaving power resources of China are originally scarce for the power generation structure is mainly based on coal-fired power. With large-scale wind power integration, the scarcity is becoming highlighted. The wind power peak-shaving issues are directly related to the realization of wind power development and planning objectives, especially in China.The research, in this dissertation, is mainly about wind power planning closely related with the peaking, including peak-shaving adequacy probability and capacity indices, probabilistic production simulation and generator maintenance scheduling which can consider the requirement of peak-shaving of wind power integrated systems. The main contents are as follows:(1) The impacts of the power source structure in China on peak-shaving capacity of wind power integrated system are analyzed. The research status of peak-shaving problems and planning problems of wind power integrated systems is summarized.(2) Based on the analysis of variation characteristics of wind, wind speed time series modeling principles are proposed. The actual sampling wind speed series and the time-series of regression analysis models are connected by probability measure transformation in order to avoid negative wind speed in regressive models. Based on the probability measure transformation methods, the models of autoregressive moving average (ARMA) and vector autoregressive (VAR) are used separately to build wind speed time-series models for single wind farm and multi-wind farms.(3) A peak-shaving adequacy evaluation method associated with large-scale wind power integrated systems is developed. It is based on sequential Monte-Carlo method, using reliability theory. Peak-shaving capacity insufficient probability index and its calculation method are proposed. Peak-shaving adequacy evaluation of IEEE-RTS system demonstrates that the proposed method is feasible and effective.(4) In order to increase the index operability, the peak-shaving capacity index evaluation method is developed. It is based on capacity credit evaluation theory. Two indexes of regulating requirement capacity of peak-valley difference and regulating requirement capacity for transmission are proposed by simplified Newton iteration method. Based on the IEEE-RTS system, the proposed method is verified to be effective.(5) A power system probabilistic product simulation method is built, which can consider the requirement of peak-shaving of wind power integrated systems. Based on the Monte-Carlo method, an expectation index of wind energy loss is proposed. In the probabilistic production method, day-ahead units arrangement is based on stealth enumeration method, and hydro power unit operation positions are determined by an iterative method of variable step size. Probabilistic product simulation of IEEE-RTS system demonstrates that the proposed method is feasible and effective, and the impacts of wind power prediction error and integration scale on system generation cost, unit utilization hours and loss of wind energy expectation are analyzed. (6) Based on Benders decomposition method, generator maintenance scheduling model is built, which can consider the requirement of peak-shaving of wind power integrated systems. The problem is decomposed to two parts:a deterministic multi-objective integer programming master problem and two sub-problems (loss of wind energy calculation and power generation reliability). The results on IEEE RTS system with wind farms demonstrate that the proposed method is feasible and effective.(7) An engineering example of Tongliao grid is built to verify the above methods further.