Design of Peak-Valley TOU Customized Package Based on Choice Behavior of Users

Ding, Wenqi; Xie, Xinyi; Wang, Bangcan; Yang, Dongyuan; Cui, Xue; Ying, Liming

doi:10.1109/psgec54663.2022.9880959

Cited by 2 publications

(2 citation statements)

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“…M0: Method for segmenting the current time period. M1: A method for segmenting TOU electricity price periods based on membership functions has been proposed (DING et al, 2001a).…”

Section: Case Study/case Analysis 41 Validation Of the Effectiveness ...mentioning

confidence: 99%

“…In contrast to the empirical and factor analysis methods, this approach is straightforward, effective, and scientifically grounded. However, its ultimate division outcomes hinge on the chosen affiliation threshold, making it challenging to accurately ascertain the peak and valley time interval's demarcation points (DING et al, 2001a;XING et al, 2007;Chong, 2019). The method of cluster analysis involves categorizing data into various groups, each containing similar elements, by analyzing the inherent correlation among data (Ravi et al, 2022).…”

Section: Introductionmentioning

confidence: 99%

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Optimization method of time-of-use electricity price for the cost savings of power grid investment

Dengfeng,

Zhonghao,

Xiaoju

et al. 2024

Front. Energy Res.

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The concept of time-of-use (TOU) electricity pricing is widely recognized as a key strategy to bridge the gap between electricity availability and consumption, enhance the efficiency of electricity, and refine the patterns of electricity usage. Nonetheless, the existing policy on pricing electricity based on TOU electricity pricing is missing a theoretical approach that evaluates the load properties and the advantages of investing in the power grid. Consequently, the article suggests a method for optimizing electricity prices based on TOU electricity pricing to reduce the costs associated with investing in power grids. Initially, a model for optimizing electricity prices based on TOU electricity pricing is developed, offering support for the pricing strategy of the power grid; Subsequently, a method for dividing TOU electricity pricing using the Gaussian Mixture Module (GMM) clustering algorithm is introduced, offering theoretical backing for the creation of such pricing strategies; Following this, a detailed optimization approach for electricity pricing of electricity TOU electricity pricing is suggested, along with taking into account the benefits of grid investments and the power grid’s load properties, the formulation of the electricity pricing strategy for TOU electricity pricing; Ultimately, this approach is corroborated by the Chongqing power system in China, aiming to minimize disparities in peak load valleys and enhance the advantages of grid investments, thereby offering technical assistance for the scientific determination of TOU electricity pricing.

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“…M0: Method for segmenting the current time period. M1: A method for segmenting TOU electricity price periods based on membership functions has been proposed (DING et al, 2001a).…”

Section: Case Study/case Analysis 41 Validation Of the Effectiveness ...mentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%