光伏发电容量可信度评估

发布时间：2018-04-25 17:05

  本文选题：大规模光伏发电 + 光伏发电容量可信度　； 参考：《合肥工业大学》2017年博士论文

【摘要】：在能源安全和环境保护的双重约束下,光伏发电在电力系统中的渗透率逐年提高。光伏发电在发挥其满足电力负荷需求的同时(体现为“电量价值”),还对电力系统容量充裕度具有不容忽略的贡献(体现为“容量价值”)。为了充分发挥及凸显光伏发电作为电源的重要特性,有必要对光伏发电的容量价值进行合理评估。本文用光伏发电的容量可信度描述光伏发电的容量价值,并从辐照强度分布及光伏电站输出功率的时空模型建立、基于可靠性计算的光伏容量可信度评估流程、光伏容量可信度通用性评估模型、光伏发电容量可信度的不确定性分析及光伏发电容量可信度的改善措施等五个方面对光伏发电的容量可信度进行逐层深入的分析。具体工作内容如下:(1)提出计及云层遮阴等多种影响因素的光照辐射强度的时空模型及计算方法,考虑了光伏组件温度对电站输出功率的影响,基于一阶低通滤波模型建立了适应多时间空间尺度的光伏电站输出功率模型。首先,通过建立云朵的Perlin噪声随机游走模型模拟了因云层遮阴导致的太阳辐射空间分布的随机性和不均匀性。此外,搭建了光伏组件高分辨率温度模型,该模型考虑了组件温度与辐照强度的滞后效应。最后,结合辐照强度及组件温度模型,建立了光伏电站输出功率的一阶低通滤波模型。该模型的建立为后续光伏发电容量可信度的研究提供了可靠的数据支撑。(2)在光伏电站输出功率模型的基础上,提出利用Monte Carlo仿真及通用生成函数法(universal generating function,UGF)两种方法计算含光伏发电的多状态系统可靠性。基于有效载荷容量(effective load carrying capability,ELCC)指标,对比分析了上述两种方法在光伏发电容量可信度评估中的应用。对影响光伏发电的各因素进行了敏感性分析,得到影响光伏发电容量可信度的主要因素。(3)在分析影响光伏发电容量可信度因素的基础上,利用人工神经网络搭建了容量可信度通用性评估模型,揭示了光伏发电容量可信度增量与光伏渗透率增量间的边际效应递减规律。同时,评估了计及光伏系统性能衰减下的光伏容量可信度在其寿命周期内的变化情况,指出了容量可信度的时变性。该通用性模型的建立便于系统规划人员快速确定光伏的容量价值及其对电力系统的影响。(4)为表征不确定性对容量可信度评估的影响,提出了基于三元区间数的光伏发电可靠性及容量可信度的不确定性评估方法。将UGF模型拓展到三元区间数形式的UGF模型(TPIUGF)中,并搭建了常规机组、光伏发电及负荷的三元区间数TPIUGF模型。通过改进型的三元区间数的布谷鸟搜索算法求解光伏发电的容量可信度。为了缩小搜索空间,采用了黄金分割法的区间缩减技术;为了加快收敛速度,提出了改进型的区间数形式的正交实验法。基于三元区间数的光伏容量可信度评估方法在指出容量可信度概率极大值的同时,其波动范围也为生产决策人员提供了参考依据。(5)提出通过引入储能系统提高光伏发电容量可信度的措施,基于最大功率波动率模型及基于小波包分解方法分别确定了储能系统的功率容量配置。并分析了储能系统三种不同控制策略对提高光伏发电容量可信度的影响,指出以提高光伏-负荷相关性为目标的控制策略有最好的效果。研究储能对光伏容量可信度的改善为光伏发电的并网及消纳提供了重要途径。本文建立的光伏发电容量可信度评估模型为含光伏发电的电力系统规划尤其是新型电源结构下的电源规划问题提供了理论参考。为光伏发电的友好型并网、实现光伏与电网的协调发展、创新电力系统未来运行管理模式等均有参考价值。
[Abstract]:Under the dual constraints of energy security and environmental protection, the permeability of photovoltaic power generation in the power system is increasing year by year. At the same time, the photovoltaic power generation can satisfy the demand of the power load ("the value of electricity"), and the capacity margin of the power system has no negligible contribution ("capacity value"). It is necessary to reasonably evaluate the capacity value of photovoltaic power generation. This paper describes the capacity value of photovoltaic power generation with the reliability of the capacity of photovoltaic power generation, and establishes the reliability of the photovoltaic capacity based on the distribution of radiation intensity and the time and space model of the output power of the photovoltaic power station. The evaluation process, the reliability evaluation model of PV capacity reliability, the uncertainty analysis of the reliability of photovoltaic capacity and the improvement measures of the capacity reliability of photovoltaic power generation are analyzed in depth by layer by layer in five aspects. The specific contents are as follows: (1) a variety of factors such as cloud shading are proposed. The space-time model and calculation method of the intensity of light radiation are taken into consideration. The output power model of the photovoltaic power station adapts to the multi time space scale based on the first order low pass filter model. First, the Perlin noise random walk model of the cloud is established to simulate the cloudy shade caused by the cloud. The spatial distribution of solar radiation is randomness and inhomogeneity. In addition, a high resolution temperature model of photovoltaic modules is built. The model takes into account the lag effect of component temperature and irradiation intensity. Finally, the first order low pass filter model of the output power of photovoltaic power station is established by combining the radiation intensity and the component temperature model. The research on the reliability of subsequent photovoltaic capacity provides reliable data support. (2) on the basis of the output power model of the photovoltaic power plant, it is proposed to use the Monte Carlo simulation and the universal generation function method (Universal generating function, UGF) to calculate the reliability of the multi state system with photovoltaic power generation. Based on the payload capacity (EFF), the capacity of the photovoltaic power generation (EFF) is calculated. Ective load carrying capability, ELCC) index, compared and analyzed the application of the above two methods in the assessment of the capacity of photovoltaic power generation. The sensitivity analysis of the factors affecting the photovoltaic power generation was analyzed, and the main factors influencing the reliability of the photovoltaic power generation capacity were obtained. (3) the basis for the analysis of the reliability factors of the photovoltaic power generation capacity was analyzed. On the other hand, a general evaluation model of capacity reliability is built by artificial neural network. The law of diminishing marginal effect between the increment of reliability of photovoltaic power generation capacity and the increment of photovoltaic permeability is revealed. At the same time, the variation of the reliability of the photovoltaic capacity under the performance of the photovoltaic system is evaluated, and the capacity is pointed out. The establishment of this universal model facilitates the system planners to quickly determine the capacity value of PV and its influence on the power system. (4) in order to characterize the impact of uncertainty on capacity reliability assessment, an uncertainty evaluation method based on the three element interval number of photovoltaic power generation reliability and capacity reliability is proposed. UGF The model is extended to the UGF model (TPIUGF) of the three element interval number, and the three element interval number TPIUGF model of the conventional unit, the photovoltaic power generation and the load is built. The capacity reliability of the photovoltaic power generation is solved by a cuckoo search algorithm of improved three yuan interval number. In order to reduce the search space, the interval reduction technique of gold segmentation is adopted. In order to speed up the convergence speed, an improved orthogonal experimental method of interval number is proposed. The method of evaluating the reliability of photovoltaic capacity based on three element interval numbers indicates the maximum of the capacity reliability probability, and its fluctuation range provides the reference basis for the production decision makers. (5) it is proposed to improve the PV hair by introducing the energy storage system. The measure of the capacity reliability is based on the maximum power volatility model and the wavelet packet decomposition method to determine the power capacity configuration of the energy storage system. The influence of three different control strategies on the reliability of the photovoltaic power generation capacity is analyzed. The control strategy for improving the photovoltaic load correlation is pointed out. The improvement of the reliability of energy storage for photovoltaic capacity provides an important way for the grid and cancellation of photovoltaic power generation. This paper provides a theoretical reference for the power system planning, especially in the new power supply structure, for photovoltaic power generation. It has reference value for friendly grid connection, realizing the coordinated development of PV and power grid, and innovating the future operation and management mode of power system.

【学位授予单位】：合肥工业大学
【学位级别】：博士
【学位授予年份】：2017
【分类号】：TM615
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本文编号：1802207