含大规模新能源的电力系统优化调度问题研究

发布时间：2018-03-28 07:12

本文选题：风电　切入点：光伏发电　出处：《华北电力大学》2014年硕士论文

【摘要】：随着经济的高速发展和常规能源的日益枯竭,大力发展新能源势在必行。以风电和光伏发电为代表的新能源发电产业已逐步趋于产业化和规模化,其并网运行有效地缓解了电网承受的负荷压力。然而,新能源发电出力具有随机性且不可调控,并网后会增加系统的不确定性因素,影响系统的稳定运行。因此,有必要对传统调度模式进行调整,以满足新能源电力系统的运行要求。本文针对含大规模新能源的电力系统优化调度问题进行了研究。本文首先分析了风电和光伏发电的出力特性,基于其独立输出功率的概率分布,利用卷积建立了风-光联合出力的概率模型。此后,为了体现风光出力的波动性对系统发电和备用计划的影响,采用功率区间预测和场景预测两种方法对风光出力的预测信息进行了描述。在基于区间预测的调度模型中,利用查找效率较高的二分法计算得到功率预测区间。通过将预测区间纳入调度计划中来反映风光出力的随机性,并通过置信概率的选择对系统运行风险进行控制,进而建立了以系统发电和备用成本最小为目标的优化调度模型。以10机系统为算例,采用GAMS/Cplex优化软件进行求解,验证了模型的有效性。在基于场景预测的调度模型中,利用拉丁超立方采样及场景缩减技术得到模拟风光出力波动的典型场景,并定义了备用风险指标以衡量波动场景下系统备用的紧张程度,实现对系统风险的控制。系统运行的经济性和可靠性取决于风险指标限制的设定和场景数的选取。调度部门可以此为依据,合理安排系统中机组出力及备用计划。然后,通过对上述两种模型优化结果的对比,分析了二者在经济性和可靠性上取得的优化效果：对于基于区间预测的调度模型,其经济性和可靠性取决于置信概率,为了保证备用足够充裕,置信概率一般取值较大,导致经济性下降。而考虑场景预测信息,则能保证系统在出现概率较大的典型场景下实现可靠运行,这种调度计划经济性较好,但往往无法考虑出现可能性很小的极端情况。最后,本文引入可中断负荷和储能系统两项措施,并通过算例分析了其对含大规模新能源的电力系统运行性能的改善作用,有助于制定更为全面有效的调度计划。
[Abstract]:With the rapid development of economy and the depletion of conventional energy, it is imperative to vigorously develop new energy. The new energy generation industry, represented by wind power and photovoltaic power generation, has gradually become industrialized and large-scale. However, the power generation of new energy is random and uncontrollable, which will increase the uncertainty of the system and affect the stable operation of the system. It is necessary to adjust the traditional dispatching mode to meet the operational requirements of new energy power system. In this paper, the characteristics of wind power generation and photovoltaic power generation are analyzed. Based on the probability distribution of its independent output power, a probability model of combined wind and light output is established by convolution. In order to reflect the influence of the fluctuation of the wind force on the power generation and standby plan of the system, the forecasting information of the wind force is described by two methods, namely, the power interval prediction and the scene prediction. In the scheduling model based on interval prediction, the power prediction interval is calculated by using the dichotomy method with high searching efficiency. The prediction interval is incorporated into the scheduling plan to reflect the randomness of the wind force. The system operation risk is controlled by the selection of confidence probability, and the optimal scheduling model with the minimum power generation and reserve cost as the goal is established. Taking the 10-machine system as an example, the optimization software GAMS/Cplex is used to solve the problem. The validity of the model is verified. In the scheduling model based on scenario prediction, the Latin hypercube sampling and scene reduction techniques are used to obtain the typical scenarios that simulate the fluctuation of wind and wind force, and the backup risk index is defined to measure the degree of system reserve tension in the fluctuating scenario. The economy and reliability of the system operation depends on the setting of the risk index limit and the selection of the number of scenarios. The dispatching department can reasonably arrange the generating unit output and reserve plan based on this. Then, by comparing the optimization results of the above two models, the optimization results of the two models are analyzed. For the scheduling model based on interval prediction, its economy and reliability depend on the confidence probability. In order to ensure that the reserve is sufficient enough, the confidence probability is generally larger, which leads to the decrease of economy. Considering the scenario prediction information, it can ensure the system to run reliably in the typical scenario with high probability. This kind of scheduling is better in planned economy, but it is often unable to consider extreme cases with very little possibility. Finally, two measures, interruptible load and energy storage system, are introduced in this paper. An example is given to analyze its effect on improving the operation performance of power system with large scale new energy, which is helpful to make a more comprehensive and effective dispatching plan.
【学位授予单位】：华北电力大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TM73

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