Analysis of the Impact of Time-sharing Tariff Policy on Regional Electricity Loads

As an essential way of demand-side electric energy management, a time-sharing tariff policy changes the user's electricity consumption behavior through tariff signals, guides the user to participate in grid peaking, and adjusts the load peak-valley difference. Compared with the peak and valley tariff mechanism, it effectively strengthens new energy consumption and eases the grid trend back-feeding. It positively impacts power supply preservation, energy resource allocation, grid operation and other aspects. Based on the data of a city's power grid, this paper analyzes the influence of the TOU tariff policy on the power consumption in this region from the whole network load, power flow change and load forecast.

Authors

Institutions

Publication Details

Published
2024-11-06
DOI
https://doi.org/10.1109/scems63294.2024.10756332
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Analysis of the Impact of Time-sharing Tariff Policy on Regional Electricity Loads

Chao Song, Bing Tian Zhao, Huiling Duan, Haitao Wu et al.
Electric Vehicles and Infrastructure
article

Analysis of the Impact of Time-sharing Tariff Policy on Regional Electricity Loads

Chao Song, Bing Tian Zhao, Huiling Duan, Haitao Wu, Haili Huang
article en

Abstract

As an essential way of demand-side electric energy management, a time-sharing tariff policy changes the user's electricity consumption behavior through tariff signals, guides the user to participate in grid peaking, and adjusts the load peak-valley difference. Compared with the peak and valley tariff mechanism, it effectively strengthens new energy consumption and eases the grid trend back-feeding. It positively impacts power supply preservation, energy resource allocation, grid operation and other aspects. Based on the data of a city's power grid, this paper analyzes the influence of the TOU tariff policy on the power consumption in this region from the whole network load, power flow change and load forecast.

Shanghai Electric (China) (CN)
Openalex Percentile: Top 81%
Electric Vehicles and Infrastructure
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.