[论文解读] Multi-state Operating Reserve Model of Aggregate Thermostatically-Controlled-Loads for Power System Short-Term Reliability Evaluation

Yi Ding, Wenqi Cui+4 more|arXiv (Cornell University)|Feb 1, 2019

Smart Grid Energy Management参考文献 38被引用 4

一句话总结

本文提出了一种新型的多状态运行备用模型，用于综合热力控制负荷（TCLs），以提升短期电力系统可靠性评估的准确性。通过建模TCLs滞环带内温度的动态迁移，并利用矩生成函数推导随机条件下备用容量的概率分布，该方法利用LZ变换实现了对备用可靠性的精确表示，经案例研究验证。

ABSTRACT

Thermostatically-controlled-loads (TCLs) have been regarded as a good candidate for maintaining the power system reliability by providing operating reserve. The short-term reliability evaluation of power systems, which is essential for power system operators in decision making to secure the system real time balancing, calls for the accurate modelling of operating reserve provided by TCLs. However, the particular characteristics of TCLs make their dynamic response different from the traditional generating units, resulting in difficulties to accurately represent the reliability of operating reserve provided by TCLs with conventional reliability model. This paper proposes a novel multi-state reliability model of operating reserve provided by TCLs considering their dynamic response during the reserve deployment process. An analytical model for characterizing dynamics of operating reserve provided by TCLs is firstly developed based on the migration of TCLs' room temperature within the temperature hysteresis band. Then, considering the stochastic consumers' behaviour and ambient temperature, the probability distribution functions of reserve capacity provided by TCLs are obtained by cumulants. On this basis, the states of reserve capacity and the corresponding probabilities at each time instant are obtained for representing the reliability of operating reserve provided by TCLs in the LZ-transform approach. Case studies are conducted to validate the proposed technique.

研究动机与目标

• 解决在短期电力系统可靠性评估中，准确建模热力控制负荷（TCLs）运行备用的挑战。
• 克服传统可靠性模型在备用投入过程中无法捕捉TCLs独特动态响应的局限性。
• 构建一个概率框架，以表征在随机用户行为与环境温度波动下，聚合TCLs提供的运行备用可靠性。
• 通过量化备用容量状态及其概率，使电力系统运营商能够基于更充分的信息做出实时平衡决策。

提出的方法

• 基于TCLs在备用投入期间室内温度在温度滞环带内迁移的分析，构建解析模型。
• 利用矩生成函数推导备用容量的概率密度函数，以考虑随机用户行为与环境温度波动的影响。
• 应用LZ变换方法，计算每个时间点备用容量的状态概率，实现多状态表征。
• 将单个TCL的响应聚合为适用于系统级可靠性评估的集体备用模型。
• 将动态响应特性整合进可靠性模型，以真实反映备用投入随时间的变化行为。
• 通过在真实系统条件下进行案例研究，验证模型的准确性与适用性。

实验结果

研究问题

• RQ1 如何在可靠性评估中准确建模热力控制负荷在备用投入过程中的动态响应？
• RQ2 随机用户行为与环境温度对聚合TCLs备用容量概率分布有何影响？
• RQ3 如何推导并应用多状态备用容量表征，以支持短期电力系统可靠性评估？
• RQ4 所提出的模型在捕捉基于TCL的运行备用可靠性方面，相较于传统模型提升了多少？
• RQ5 LZ变换方法是否能有效表征TCL衍生备用容量的时变状态及其概率？

主要发现

• 所提出的模型成功捕捉了TCLs在备用投入期间其滞环带内温度的动态迁移行为。
• 基于矩的推导方法能够准确逼近随机条件下备用容量的概率密度函数。
• LZ变换方法有效计算了备用容量的时变状态与概率，实现了多状态可靠性表征。
• 案例研究证实，该模型在短期系统规划中准确表征了基于TCL的运行备用可靠性。
• 该模型通过整合TCL特有的动态特性，优于传统方法，实现了更真实的备用容量评估。
• 该框架为电力系统运营商提供了一种可扩展且解析可处理的方法，用于基于TCL作为备用资源评估实时平衡需求。