蓄热式电采暖柔性负荷特性建模及可调潜力研究

Research on the Characteristics Modeling and Adjustable Potential of Regenerative Electric Heating Flexible Load

为了充分挖掘蓄热式电采暖作为柔性负荷的可调潜力,将蓄热式电采暖柔性负荷特性作为研究对象,首先,分析了蓄热式电采暖系统运行的各项特点,对单体蓄热电采暖的负荷特性进行了建模;然后,运用中心点聚合算法,将电采暖负荷进行聚合,使每个聚合群体的参数相似;接着,基于用户房屋散热系数和蓄热电采暖用户温升系数等参数对电采暖进行集群处理,并由温度和功率的关系进行电采暖负荷聚合体的建模;最后,根据具体的算例,仿真分析了电采暖负荷的可调控容量和调控响应持续时间。算例结果表明,在室内外温差不断降低的情况下,电采暖聚合体的最大可调容量和调控响应持续时间随之上升,通过合理地设置用户的舒适温度区间,可以得到集群蓄热式电采暖的最大可调控容量,以对电网进行调峰支撑,达到最有效的需求响应效果。研究结果验证了所提蓄热式电采暖集群运行负荷模型和调控潜力分析的有效性。

In order to fully explore the adjustable potential of regenerative electric heating, this paper takes the flexible load characteristics of regenerative electric heating as the research object. Firstly, the characteristics of the operation of regenerative electric heating system are analyzed and the load characteristics of single regenerative electric heating are modeled. Then, the central point aggregation algorithm is used to aggregate the electric heating load so that the parameters of each aggregate group are similar. The electric heating is clustered based on parameters such as the heat dissipation coefficient of the user’s house and the temperature rise coefficient of the thermal storage electric heating user, and the electric heating load aggregate is modeled based on the relationship between temperature and power. Finally, according to specific calculation examples, the control capacity and control duration period of electric heating load are simulated and analyzed. The calculation example shows that the maximum adjustable capacity and the control response duration of the electric heating polymer increase with the continuous decrease of the temperature difference between indoor and outdoor.By reasonably setting the user’s comfortable temperature range, the maximum adjustable capacity of the cluster thermal storage electric heating can be obtained to support the peak regulation of the power grid and achieve the most effective demand response effect, at the same time, the validity of the regenerative electric heating cluster operating load model and control potential analysis proposed in this paper is verified.