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ORIGINAL RESEARCH article

Front. Energy Res.
Sec. Smart Grids
Volume 12 - 2024 | doi: 10.3389/fenrg.2024.1486478
This article is part of the Research Topic Advanced Modeling and Methods for Renewable-dominated Power Systems Operations under Multiple Uncertainties View all 11 articles

Optimization Method of Time of Use Electricity Price Considering Losses in Distributed Photovoltaic Access Distribution Network

Provisionally accepted
Tianshou Li Tianshou Li *Qing Xu Qing Xu Weiwu Li Weiwu Li Xinying Wang Xinying Wang Zhengying Liu Zhengying Liu
  • State Grid Gansu Electric Power Company, Lanzhou, China

The final, formatted version of the article will be published soon.

    Currently, the time-of-use pricing model for electricity focuses on a single objective, often overlooking various factors that influence electricity costs. This oversight can lead to significant disparities in peak and off-peak electricity usage within the distribution network following optimization. Therefore, a new time of using electricity price optimization method is proposed that takes into account the losses of distributed photovoltaic access to the distribution network. Considering the topology structure of the distribution network after the integration of distributed photovoltaic, this paper calculates the comprehensive losses generated by the operation of the distribution network. Also, this paper constructs a time of use electricity price optimization mathematical model with the objectives of minimizing network loss, minimizing load variance, minimizing peak valley difference of equivalent load, and maximizing user satisfaction. And refer to the basic requirements for electricity pricing in the distribution network, set a series of constraints for optimizing electricity prices. Applying an improved imperialist competition algorithm this paper integrates Tent chaotic reverse learning to solve a multi-objective optimization model and obtain an optimized time of use electricity pricing plan. The experimental results show that after the implementation of this optimization method, the peak valley difference of the daily power load curve of the distribution network is only 350 MW, demonstrating superior peak shaving and valley filling effects.

    Keywords: Distributed photovoltaics, Network loss, time of use electricity price, Multi objective optimization, Improve imperialist competition algorithms, Peak Valley Difference

    Received: 26 Aug 2024; Accepted: 27 Sep 2024.

    Copyright: © 2024 Li, Xu, Li, Wang and Liu. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Tianshou Li, State Grid Gansu Electric Power Company, Lanzhou, China

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