摘要
风力发电作为最主要的清洁能源利用形式之一,得到了快速的发展。风电机组的装机容量越来越大,占电网的比重也越来越高。长期来看,实现风电场的可控运行,将风电场纳入电网的调度体系,是大型风电场安全并网运行的发展趋势。因此,风电场的有功功率控制已成为风电场并网发电迫切需要解决的关键问题。本文主要从风电场有功功率控制策略、风电场有功功率控制在风电场以及风电机组中的实现、风电场有功功率控制下的风电机组控制算法及稳定性等方面展开研究工作。本文所取得的创新性成果如下:
1.为了抑制风电接入电网产生全场出力的波动,本文提出了一种基于风电机组有功功率超短期预测的风电场有功功率优化控制策略。该优化控制策略的研究工作主要包括:分析了风电接入电网后风电机组以及风电场与电网调度之间的关系,提出了一种基于时间尺度可变的风电场有功功率超短期预测方法,并将该方法应用于风电场有功功率控制策略中,从而实现风电场有功功率控制下的风电机组期望功率校准的目的,提高了风电场有功功率的控制精度;在有功功率分配策略中,采用以最少的风电机组停机为目标的优化降功率控制策略和以最少启动机组和最多启动机组为目标的优化升功率控制策略,实现了考虑风电场不同需求情况下风电机组功率的优化分配。
2.本文研究了一种基于WiMAX的风电场通信网络架构和一种基于智能多代理的风力发电机组控制策略,该控制策略的主要研究工作为:采用基于WiMAX的风电场通信网络架构,并且根据风电场中需要传输和通信数据的特点及重要性制定不同的传输层和应用层协议,从而达到风电场数据可靠、高效传输的目的;在风电机组中采用基于智能多代理的控制策略,以此来保证风电场有功功率控制在风电机组中的稳定性与可靠性。以上策略使得风电场侧的有功功率分配结果能够稳定、可靠的下传到风电场各风电机组,并且可以保证风电机组在复杂的控制任务下仍能顺利完成风电场有功功率控制系统分配的控制任务。
3.考虑到风电机组在风电场有功功率控制下需稳定运行的特点,本文针对风电机组在不同工况下的运行特性,提出了一种风力发电机组全局转速控制和负载转矩优化控制策略。该控制策略保证了风电机组在不同工况下的转速控制精度以及对应转速下的优化负载转矩输出,从而实现了风电机组在有功功率控制系统中的稳定、优化控制。此外,针对风力发电机在低速状态存在的严重的混沌属性,本文研究了针对风力发电机动态特性的自适应Backstepping控制算法。
4.针对第3点提出的风电机组控制策略,本文研究了一种用于风力发电机组控制器的稳定性分析方法。
基于以上的研究工作,本文设计了风电场有功功率控制系统,并将该有功功率控制系统应用于内蒙古某风电场现场进行实验。实验结果表明,本文设计的风电场有功功率控制系统在现场的控制误差小,风电场有功功率的输出稳定性强。
As the most important form of clean energy resource, wind power has developed rapidly. The capacity is growing at fast rate and wind power is taking more and more proportion in power supplies. Obviously, the effective control of output power in large-scale wind farm, together with the grid scheduling system, should be more and more important for wind power development. Therefore, active power control has become an urgent problem for the wind farm grid connection. This article has mainly studied on the power control theory of wind farm, the implementation of active power control in wind farms and wind turbines, the control algorithm of wind turbine and the stability of active power control. Some specific measures are included:
1. In order to resist the volatility and uncontrollability of output power, the relationship between wind farm and power scheduling has been analyzed when a wind farm is connected to the grid and a wind farm active power optimization control strategy based on ultra-short-term power prediction is studied. Besides, a wind turbine power ultra-short-term prediction method with variable time scale is proposed. This prediction method is utilized in the wind farm active power optimization control strategy to adjust the wind turbine output power and improve the control accuracy. Furthermore, on one hand, an optimal control algorithm for wind farm active power reduction is presented to minimize the number of shutting down wind turbines when decreasing the output power, on the other hand, an optimal control algorithm for wind farm active power increasement is presented to minimize and maximize the number of starting wind turbines when lifting the output power.
2. A wind farm communication network structure based on WiMAX and an intelligent wind turbine control strategy based on Multi-Agent are studied. The main research works are included in analyzing the WiMAX communication network architecture, designing different protocols to meet the requirements of data transmission and studying the multi-agent based intelligent control strategy to make the wind turbines more stable and reliable under the control of active power.
3. Considering the stability of wind turbine control based on the wind farm active power control and the wind turbine operation characteristics in different work states, a wind turbine global control strategy of rotating speed with load torque optimization control strategy is presented to improve the performance of the wind turbine rotating speed in different work states. In addition, considering the serious chaotic property of wind generator in the low-speed status, a wind generator adaptive Backstepping control algorithm is proposed.
4. In order to utilize the studied wind turbine control strategies in 3, a stability analysis method for wind turbine is proposed.
Based on the above works, an active power control system is designed and has been applied in a wind farm located in Inner Mongolia. The field experimental results show that the designed control system could reduce the active power error and improve the stability of the wind farm active power output.
引文
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