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Advanced metering infrastructure systems record a high volume of residential load data, opening up an opportunity for utilities to understand consumer energy consumption behaviors. Existing studies have focused on load profiling and…

信号处理 · 电气工程与系统科学 2019-07-15 Wen-Jun Tang , Xian-Long Lee , Hao Wang , Hong-Tzer Yang

The smart meter data analysis contributes to better planning and operations for the power system. This study aims to identify the drivers of residential energy consumption patterns from the socioeconomic perspective based on the consumption…

机器学习 · 计算机科学 2021-11-03 Wenjun Tang , Hao Wang , Xian-Long Lee , Hong-Tzer Yang

Smart meter data analysis can provide insights into residential electricity consumption behaviors. Seasonal variation in consumption is not well understood but yet important to utilities for energy pricing and services. This paper aims to…

应用统计 · 统计学 2021-12-03 Zhenyu Wang , Hao Wang

Distribution system residential load modeling and analysis for different geographic areas within a utility or an independent system operator territory are critical for enabling small-scale, aggregated distributed energy resources to…

系统与控制 · 电气工程与系统科学 2022-08-16 Isaac Bromley-Dulfano , Xiangqi Zhu , Barry Mather

This paper addresses the use of smart-home sensor streams for continuous prediction of energy loads of individual households which participate as an agent in local markets. We introduces a new device level energy consumption dataset…

机器学习 · 计算机科学 2017-08-16 Christoph Doblander , Martin Strohbach , Holger Ziekow , Hans-Arno Jacobsen

Residential customers have traditionally not been treated as individual entities due to the high volatility in residential consumption patterns as well as a historic focus on aggregated loads from the utility and system feeder perspective.…

Recently there has been significant research on power generation, distribution and transmission efficiency especially in the case of renewable resources. The main objective is reduction of energy losses and this requires improvements on…

机器学习 · 统计学 2016-06-17 Stefan Hosein , Patrick Hosein

While non-parametric models, such as neural networks, are sufficient in the load forecasting, separate estimates of fixed and shiftable loads are beneficial to a wide range of applications such as distribution system operational planning,…

信号处理 · 电气工程与系统科学 2020-11-09 A. Khaled Zarabie , Sanjoy Das , Hongyu Wu

Most electricity systems worldwide are deploying advanced metering infrastructures to collect relevant operational data. In particular, smart meters allow tracking electricity load consumption at a very disaggregated level and at high…

机器学习 · 统计学 2020-03-09 Andrés M. Alonso , F. Javier Nogales , Carlos Ruiz

Electricity consumed by residential consumers counts for a significant part of global electricity consumption and utility companies can collect high-resolution load data thanks to the widely deployed advanced metering infrastructure. There…

人机交互 · 计算机科学 2021-03-11 Hao Wang , Gonzague Henri , Chin-Woo Tan , Ram Rajagopal

The widespread deployment of Advanced Metering Infrastructure has made granular data of residential electricity consumption available on a large scale. Smart meters enable a two way communication between residential customers and utilities.…

系统与控制 · 计算机科学 2016-08-15 Datong Zhou , Maximilian Balandat , Claire Tomlin

Smart Home technology is increasingly seen as a solution for improving household energy efficiency. However, its energy-saving potential depends largely on how consumers use the system. To explore how user perception and intention to use…

人机交互 · 计算机科学 2025-10-07 Alona Zharova , Hee-Eun Lee

Load shapes derived from smart meter data are frequently employed to analyze daily energy consumption patterns, particularly in the context of applications like Demand Response (DR). Nevertheless, one of the most important challenges to…

This paper describes a method for defining representative load profiles for domestic electricity users in the UK. It considers bottom up and clustering methods and then details the research plans for implementing and improving existing…

计算工程、金融与科学 · 计算机科学 2013-07-05 Ian Dent , Uwe Aickelin , Tom Rodden

The expansion of residential demand response programs and increased deployment of controllable loads will require accurate appliance-level load modeling and forecasting. This paper proposes a conditional hidden semi-Markov model to describe…

应用统计 · 统计学 2018-10-10 Yuting Ji , Elizabeth Buechler , Ram Rajagopal

In the Smart Grid environment, the advent of intelligent measuring devices facilitates monitoring appliance electricity consumption. This data can be used in applying Demand Response (DR) in residential houses through data analytics, and…

信号处理 · 电气工程与系统科学 2020-08-10 Abdelkareem Jaradat , Hanan Lutfiyya , Anwar Haque

One of the most far-reaching use cases of the internet of things is in smart grid and smart home operation. The smart home concept allows residents to control, monitor, and manage their energy consumption with minimum loss and…

系统与控制 · 电气工程与系统科学 2025-02-11 S. Saba Rafiei , Mahdi S. Naderi , Mehrdad Abedi

With the growth of smart building applications, occupancy information in residential buildings is becoming more and more significant. In the context of the smart buildings' paradigm, this kind of information is required for a wide range of…

信号处理 · 电气工程与系统科学 2022-09-26 Sangkeum Lee , Sarvar Hussain Nengroo , Hojun Jin , Yoonmee Doh , Chungho Lee , Taewook Heo , Dongsoo Har

Load points are one of the most vital parts of power systems. Due to the new load forms and programs introduced in the demand side, the load-serving entities (LSEs) no longer deal with lump loads, but rather with more dynamic, rational and…

系统与控制 · 电气工程与系统科学 2021-10-13 Ahmed S. Alahmed , Muhammed M. Almuhaini

This paper presents a comprehensive statistical review of data obtained from a wide range of literature on the most widely used electrical appliances in the UK residential load sector. It focuses on individual appliances and begins by…

物理与社会 · 物理学 2015-10-12 G. Tsagarakis , A. J. Collin , A. E. Kiprakis
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