基于用户行为的分时电价时段划分和价格制定

以往分时电价的时段划分仅考虑负荷曲线的数值变化,忽视了时段划分对分时电价的制定和对用户行为的影响,使得分时电价优化受限,需求侧响应不能达到最优的效果。为此提出了基于用户行为的分时电价时段划分和价格制定模型,首先通过模糊聚类法初步制定峰段、平段、谷段,然后将峰谷时段的起始时间和终止时间设为待优化的变量,并根据消费者心理学建立用户电价电量响应行为模型,最后以用户满意度和电网收益最大化为目标,同时对分时电价和时段划分进行优化。仿真结果显示,与直接根据FCM模糊聚类分析方法划分时段相比,该模型更能针对负荷特性激励用户响应分时电价,促使用户响应曲线更加平滑,进一步降低调峰成本,验证了该模型通过优化时段划分方法提高社会福利的有效性。

Time division of time-of-use electricity price and price setting based on user behavior

The previous time-sharing of time-of-use electricity prices only considered the change in the value of the load curve, ignoring the impact of time-sharing on the establishment of time-of-use electricity prices and the impact on user behavior. As a result, the optimization of time-of-use electricity prices was limited, and the demand-side response could not achieve optimal results. In order to solve this problem, a model of time-of-use electricity price division and price formulation based on user behavior is proposed. First, the peak segment, flat segment, and valley segment are formulated by fuzzy clustering method. For the variables to be optimized, a consumer electricity price and electricity response behavior model is established according to consumer psychology. Finally, the goal is to maximize user satisfaction and grid revenue, while optimizing time-of-use electricity prices and time division. The simulation results show that, compared with dividing the period directly based on the FCM fuzzy clustering analysis method, the model can better stimulate the user to respond to the time-of-use electricity price according to the load characteristics, promote a smoother user response curve, and further reduce the peak shaving cost. Optimize the time division method to improve the effectiveness of social welfare.