{"title":"Effect of electric vehicles, heat pumps, and solar panels on low-voltage feeders: Evidence from smart meter profiles","authors":"Thijs Becker , Raf Smet , Bruno Macharis , Koen Vanthournout","doi":"10.1016/j.segan.2025.101705","DOIUrl":null,"url":null,"abstract":"<div><div>Electric Vehicles (EVs), Heat Pumps (HPs) and solar panels are Low-Carbon Technologies (LCTs) that are being connected to the Low-Voltage Grid (LVG) at a rapid pace. One of the main hurdles to understand their impact on the LVG is the lack of recent, large electricity consumption datasets, measured in real-world conditions. We investigated the contribution of LCTs to the size and timing of peaks on LV feeders by using a large dataset of 42,089 smart meter profiles of residential LVG customers. These profiles were measured in 2022 by Fluvius, the Distribution System Operator (DSO) of Flanders, Belgium. The dataset contains customers that proactively requested higher-resolution smart metering data, and hence is biased towards energy-interested people. LV feeders of different sizes were statistically modeled with a profile sampling approach. For feeders with 40 connections, we found a contribution to the feeder peak of 1.2 kW for a HP, 1.4 kW for an EV and 2.0 kW for an EV charging faster than 6.5 kW. A visual analysis of the feeder-level loads shows that the classical duck curve is replaced by a night-camel curve for feeders with only HPs and a night-dromedary curve for feeders with only EVs charging faster than 6.5 kW. Consumption patterns will continue to change as the energy transition is carried out, because of <em>e.g</em>. dynamic electricity tariffs or increased battery capacities. Our introduced methods are simple to implement, making it a useful tool for DSOs that have access to smart meter data to monitor changing consumption patterns.</div></div>","PeriodicalId":56142,"journal":{"name":"Sustainable Energy Grids & Networks","volume":"42 ","pages":"Article 101705"},"PeriodicalIF":4.8000,"publicationDate":"2025-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sustainable Energy Grids & Networks","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352467725000876","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENERGY & FUELS","Score":null,"Total":0}
引用次数: 0
Abstract
Electric Vehicles (EVs), Heat Pumps (HPs) and solar panels are Low-Carbon Technologies (LCTs) that are being connected to the Low-Voltage Grid (LVG) at a rapid pace. One of the main hurdles to understand their impact on the LVG is the lack of recent, large electricity consumption datasets, measured in real-world conditions. We investigated the contribution of LCTs to the size and timing of peaks on LV feeders by using a large dataset of 42,089 smart meter profiles of residential LVG customers. These profiles were measured in 2022 by Fluvius, the Distribution System Operator (DSO) of Flanders, Belgium. The dataset contains customers that proactively requested higher-resolution smart metering data, and hence is biased towards energy-interested people. LV feeders of different sizes were statistically modeled with a profile sampling approach. For feeders with 40 connections, we found a contribution to the feeder peak of 1.2 kW for a HP, 1.4 kW for an EV and 2.0 kW for an EV charging faster than 6.5 kW. A visual analysis of the feeder-level loads shows that the classical duck curve is replaced by a night-camel curve for feeders with only HPs and a night-dromedary curve for feeders with only EVs charging faster than 6.5 kW. Consumption patterns will continue to change as the energy transition is carried out, because of e.g. dynamic electricity tariffs or increased battery capacities. Our introduced methods are simple to implement, making it a useful tool for DSOs that have access to smart meter data to monitor changing consumption patterns.
期刊介绍:
Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.