计及间歇性能源时空相关性的电力系统运行决策方法

Wind power and photovoltaic generation are low-carbon, clean, and sustainable energy. Their large-scale development are of great significance for China to achieve the national strategy for clean energy. However, the output of this kind of energy is intermittent and difficult to forecast. The risk of their large-scale integration into the power system will have a profound impact on power system operation. This project will perform a comprehensive study on how to optimize the short-term operation of power system while being aware of the risk of intermittent energy. Firstly, according to the common feature of the intermittent energy, the spatial-temporal correlation of their outputs will be studied to understand how their outputs are coupled in space and time. Secondly, the project will build a conditional uncertainty model for their short term forecasting error that is able to considerate their spatial-temporal correlation. Based on this model, the project will propose a unit comment model that coordinates the generation costs and the level of risk. The model considers in detail the risk of generation balancing and network security caused by the intermittent energy outputs with complex spatio-temporal correlation. The technique of transforming and simplifying this optimization model will be developed that the model could be solved efficiently for practical implementation. Finally, the project will propose a decision making model for determining short-term electric power and electricity balance. The model will better help the utility with the reserve allocation, the energy dispatching, and the inter-regional power and energy exchange planning under uncertainty environment. We hope the achievements of this research will contribute to the operation optimization of large-scale intermittent energy in China.

风电与太阳能光伏发电是低碳、清洁、可持续的能源，其大规模开发对于我国实现清洁能源战略具有重要意义。然而这类能源出力具有间歇性，且难以准确预测，其大规模接入将为电力系统调度运行带来风险和挑战。本课题将深入研究间歇性能源大规模接入下电力系统短期运行优化决策方法。首先针对间歇性能源出力具有明显时空相关性这一共性特征，研究间歇性能源出力在时间与空间上的耦合机理并建立其相关性模型；其次构建全面考虑时空相关性的间歇性能源预测误差条件概率模型；在此基础上提出协调系统运行成本与风险的日前随机机组组合模型，使发电决策能够兼顾间歇性能源时空耦合不确定性引起的正负备用不足与潮流越界风险；研究模型的转化方法并提出高效求解技术；最后提出短期电力电量平衡决策方法，实现不确定环境下系统短期分区备用、分区电量分配以及区域间电力电量交换的科学决策。期望本课题能尝试为我国大规模间歇性能源优化运行提供新的方法与技术。

风电与太阳能光伏发电是低碳、清洁、可持续的能源，其大规模开发对于我国实现国家清洁能源战略具有重要意义。然而这类能源出力具有间歇性且难以准确预测，其大规模接入将为电力系统调度运行带来风险。本课题研究了风电以及太阳能光伏发电大规模接入下电力系统短期运行优化决策方法。首先针对间歇性能源出力具有明显时空相关性这一共性特征，采用Copula理论建立额其相关性模型并揭示了间歇性能源出力在时间与空间上的耦合机理，再此基础上提出并发展了相依概率性序列运算理论；然后，构建了全面考虑时空相关性的间歇性能源预测误差条件概率模型,揭示了风电以及光伏发电不同预测值下预测误差的分布规律；在此基础上，提出协调系统运行成本与风险的日前随机机组组合模型，使发电决策能够感知间歇性能源时空耦合不确定性引起的正负备用不足与潮流越界风险，提出了模型的转化方法并提出高效的实用化求解技术；最后基于可再生能源容量可信度的概念，提出了短期电力电量平衡决策方法，实现了不确定环境下系统短期分区备用、分区电量分配以及区域间电力电量交换的科学决策。希望本课题的研究成果我国大规模间歇性能源优化运行提供方法与技术支撑。