风电并网系统的旋转备用优化策略研究

发布时间：2018-01-17 02:06

本文关键词：风电并网系统的旋转备用优化策略研究　出处：《东北电力大学》2017年硕士论文　论文类型：学位论文

【摘要】：大规模风电并网为维持系统有功平衡带来了压力。受到不同地势、气候条件等影响,风电出力的间歇性和波动性无法准确预期,在大规模风电出力预测偏差较大时,可能导致电力系统的机组启停和功率调控难度加剧。为在保证系统安全稳定运行的条件下,更多地接纳清洁能源,保持良好的系统运行经济性,急需针对大规模风电并网后系统的旋转备用容量优化配置问题进行合理有效的决策。本文从备用源、网、荷、风电四个方面分析了引起旋转备用的机理,量化旋转备用的风险成本。通过算例验证了系统在满足一定安全准则的条件下,运行成本与风险成本必然存在使总费用最小的折中。货币化系统中各方风险,将风险成本解析表达,基于折中准则建立了权衡机组运行成本和风险成本的优化模型,应用于日前调度,算例表明,利用该模型的优化使调度总成本下降了2.7%;系统中负荷与装机容量的比值越小,优化模型对经济性的提高就显著。在分析研究旋转备用的响应风险成本后,建立了动态经济调度旋转备用优化模型,应用于动态经济调度。模型协调备用风险响应成本和火电机组的运行成本,通过算例验证了模型经济性,与传统经济调度相比,该模型能够节省25%的备用费用。在风电预测能力难以提高时,协调发电成本和备用成本的经济性将有效降低总成本。基于此,建立了实时调度旋转备用优化的二层规划模型。上下两层的备用成本和发电成本协调优化,达到总运行费用最低,通过算例验证了用该模型分配负荷和旋转备用的良好经济性,且响应能力强,对不同的线路容量有良好的适用性,计算速度快。本文以确定风电并网系统的最优旋转备用需求和降低系统运行的总成本为目标,利用相关模型和算法为风电并网系统确定最优旋转备用容量提供了一套完整的优化策略,包括日前调度、动态经济调度及实时调度旋转备用的优化方法,在满足系统安全准则的条件下,有效降低了备用需求和系统运行总费用,有利于系统接纳风电能力的提升。
[Abstract]:Large-scale wind power grid brings pressure to maintain the balance of active power in the system. Due to the influence of different terrain and climate conditions, the intermittent and volatility of wind power can not be accurately predicted. In order to ensure the safe and stable operation of the power system, clean energy can be accepted more and more when the deviation of large-scale wind power generation prediction is large, which may lead to the increase of power system start-up and shutdown and power regulation. It is urgent to make a reasonable and effective decision on the optimal allocation of the rotating reserve capacity of the system after large-scale wind power is connected to the grid. Four aspects of wind power analysis of the mechanism of rotary reserve, quantification of the risk cost of rotating reserve, and a numerical example to verify that the system meets certain safety criteria. There must be a compromise between operation cost and risk cost to minimize the total cost. In the monetization system, the risk of each party is expressed analytically. Based on the compromise criterion, an optimization model of balancing unit operation cost and risk cost is established, which is applied to pre-day scheduling. An example shows that the optimization of this model can reduce the total scheduling cost by 2.7%. The smaller the ratio of load to installed capacity in the system, the more economical the optimization model is. After analyzing the response risk cost of rotating standby, a dynamic economic scheduling rotational standby optimization model is established. It is applied to dynamic economic dispatch. The model coordinates the cost of standby risk response and the operation cost of thermal power unit. The model economy is verified by an example, which is compared with the traditional economic dispatch. The model can save 25% of reserve cost. When the forecasting ability of wind power is difficult to improve, the economy of coordinating generation cost and reserve cost will reduce the total cost effectively. A two-layer programming model for real-time scheduling rotation reserve optimization is established. The coordination optimization of reserve cost and generation cost between the upper and lower layers reaches the lowest total operating cost. An example is given to verify the good economy of load distribution and rotation reserve with this model, and its strong response ability, which has good applicability to different line capacity. The purpose of this paper is to determine the optimal rotational reserve requirement of the wind power grid connected system and to reduce the total operating cost of the system. This paper provides a complete set of optimization strategies for wind power grid connection system to determine the optimal rotation reserve capacity by using relevant models and algorithms, including pre-day scheduling, dynamic economic scheduling and real-time scheduling rotation reserve optimization methods. Under the condition that the system safety criterion is satisfied, the reserve requirement and the total operating cost of the system are reduced effectively, and the ability of the system to accept wind power is improved.
【学位授予单位】：东北电力大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TM614

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