低碳电力下含抽水蓄能的风水火联合经济调度

发布时间：2018-02-01 00:22

本文关键词： 低碳电力机组组合多目标抽水蓄能风力发电水力发电　出处：《广西大学》2014年硕士论文　论文类型：学位论文

【摘要】：低碳电力系统由于影响因素众多、规模庞大及储能装置与新能源发电技术的联合应用,增加了系统优化调度结构的复杂性。随着世界能源日趋紧张、环境日益恶化,如何高效的实现低碳电力的优化调度已成为目前研究的热点话题。本文考虑了含抽水蓄能的最优经济调度问题,通过分析低碳电力调度涉及的关键因素、抽水蓄能功率的互补约束特性方程,建立了含抽水蓄能的多目标机组组合低碳调度模型；对机组组合、多目标优化问题及抽水蓄能的互补约束条件进行探讨,并在10机24时段、10机96时段及扩展算例中进行计算分析,结果验证了所述模型在兼顾影响低碳运行相关因素及运行成本的条件下,通过合理安排火电机组、有效利用抽水蓄能装置的削峰填谷作用实现了系统的低碳、经济运行。考虑新能源的低碳、经济、节能效应,建立了含抽水蓄能的风水火联合优化调度模型；为处理风力发电存在的随机性和波动性问题,本文先采用最小二乘支持向量机算法对风速进行预测,并利用风速-功率特性方程计算预测功率；再采用非参数估计法求出预测功率置信区间,并根据相对预测误差分布特性求出随机预测功率曲线。通过对10机96时段及扩展算例的仿真分析验证了模型在充分利用水电调峰作用的同时,能很好的协调风电随机性给电网带来的波动性,最终实现电网的环保、经济、稳定运行。
[Abstract]:Because of the large scale and the combined application of energy storage unit and new energy generation technology, low carbon power system has increased the complexity of the optimal scheduling structure of the system. The environment is deteriorating day by day. How to efficiently realize the optimal dispatching of low carbon power has become a hot topic. In this paper, the optimal economic dispatching problem with pumped storage is considered. By analyzing the key factors involved in low carbon power dispatching, the complementary constraint characteristic equation of pumped storage power is analyzed. The low carbon dispatching model of multi-objective unit with pumped storage is established. The problems of unit combination, multi-objective optimization and complementary constraints of pumped storage energy are discussed, and the calculation and analysis are carried out in 10 machines, 24 hours, 10 machines, 96 periods and extended examples. The results show that the model can effectively utilize the peak cutting and filling effect of pumped storage unit to realize the system low carbon by reasonable arrangement of thermal power units under the condition of considering the factors and operating cost of low carbon operation. Economic operation. Considering the low carbon, economic and energy saving effects of new energy, a model for optimal operation of geomantic fire with pumped storage is established. In order to deal with the randomness and volatility of wind power generation, the least square support vector machine (LS-SVM) algorithm is used to predict the wind speed, and the predicted power is calculated by the wind speed power characteristic equation. Then the nonparametric estimation method is used to calculate the confidence interval of the predicted power. According to the characteristic of relative prediction error distribution, the random predicted power curve is obtained. The simulation results of 10 machine 96 period and extended example show that the model makes full use of the function of hydropower peak shaving at the same time. It can coordinate the fluctuation of wind power randomness, and finally realize the environmental protection, economy and stable operation of power grid.
【学位授予单位】：广西大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM73;TV743

【参考文献】