English
Related papers

Related papers: Quantifying and Predicting Residential Building Fl…

200 papers

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…

Machine Learning · Statistics 2020-03-09 Andrés M. Alonso , F. Javier Nogales , Carlos Ruiz

The rising integration of variable renewable energy sources (RES), like solar and wind power, introduces considerable uncertainty in grid operations and energy management. Effective forecasting models are essential for grid operators to…

Systems and Control · Electrical Eng. & Systems 2024-08-02 Jesus Silva-Rodriguez , Elias Raffoul , Xingpeng Li

Appliance-level load forecasting plays a critical role in residential energy management, besides having significant importance for ancillary services performed by the utilities. In this paper, we propose to use an LSTM-based…

Signal Processing · Electrical Eng. & Systems 2021-06-30 Mina Razghandi , Hao Zhou , Melike Erol-Kantarci , Damla Turgut

It is envisioned that building systems will become active participants in the smart grid operation by controlling their energy consumption to optimize complex criteria beyond ensuring local end-use comfort satisfaction. A forecast of the…

Optimization and Control · Mathematics 2018-06-08 Soumya Kundu , Thiagarajan Ramachandran , Yan Chen , Draguna Vrabie

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.…

Systems and Control · Computer Science 2016-08-15 Datong Zhou , Maximilian Balandat , Claire Tomlin

Electricity is a volatile power source that requires great planning and resource management for both short and long term. More specifically, in the short-term, accurate instant energy consumption forecasting contributes greatly to improve…

Artificial Intelligence · Computer Science 2022-07-05 Nuno Oliveira , Norberto Sousa , Isabel Praça

Accurate electrical load forecasting is of great importance for the efficient operation and control of modern power systems. In this work, a hybrid long short-term memory (LSTM)-based model with online correction is developed for day-ahead…

Systems and Control · Electrical Eng. & Systems 2024-03-07 Nan Lu , Quan Ouyang , Yang Li , Changfu Zou

Towards integrating renewable electricity generation sources into the grid, an important facilitator is the energy flexibility provided by buildings' thermal inertia. Most of the existing research follows a single-step price- or…

Systems and Control · Electrical Eng. & Systems 2023-12-11 Yun Li , Neil Yorke-Smith , Tamas Keviczky

Climate change is one of the most concerning issues of this century. Emission from electric power generation is a crucial factor that drives the concern to the next level. Renewable energy sources are widespread and available globally,…

Machine Learning · Computer Science 2020-05-27 Md Amimul Ehsan , Amir Shahirinia , Nian Zhang , Timothy Oladunni

Achieving the flexibility from house heating, cooling, and ventilation systems (HVAC) has the potential to enable large-scale demand response by aggregating HVAC load adjustments across many homes. This demand response strategy helps…

Systems and Control · Electrical Eng. & Systems 2025-10-27 Kunal Shankar , Ninad Gaikwad , Anamika Dubey

The increasing integration of renewable energy sources (RESs) into modern power systems presents significant opportunities but also notable challenges, primarily due to the inherent variability of RES generation. Accurate forecasting of RES…

Machine Learning · Computer Science 2026-01-19 Farshid Kamrani , Kristen Schell

Buildings represent a promising flexibility source to support the integration of renewable energy sources, as they may shift their heating energy consumption over time without impacting users' comfort. However, a building's predicted…

Systems and Control · Electrical Eng. & Systems 2025-10-02 Julie Rousseau , Hanmin Cai , Philipp Heer , Kristina Orehounig , Gabriela Hug

With the employment of smart meters, massive data on consumer behaviour can be collected by retailers. From the collected data, the retailers may obtain the household profile information and implement demand response. While retailers prefer…

Machine Learning · Computer Science 2022-10-19 Yi Dong , Yang Chen , Xingyu Zhao , Xiaowei Huang

Electricity demand forecasting is a well established research field. Usually this task is performed considering historical loads, weather forecasts, calendar information and known major events. Recently attention has been given on the…

Machine Learning · Computer Science 2023-09-14 Yun Bai , Simon Camal , Andrea Michiorri

The US EIA estimated in 2017 about 39\% of total U.S. energy consumption was by the residential and commercial sectors. Therefore, Intelligent Building Management (IBM) solutions that minimize consumption while maintaining tenant comfort…

Machine Learning · Computer Science 2019-02-20 Zhicheng Ding , Mehmet Kerem Turkcan , Albert Boulanger

The large scale deployment of Advanced Metering Infrastructure among residential energy customers has served as a boon for energy systems research relying on granular consumption data. Residential Demand Response aims to utilize the…

Systems and Control · Computer Science 2016-07-05 Datong Zhou , Maximilian Balandat , Claire Tomlin

Electric consumption prediction methods are investigated for many reasons such as decision-making related to energy efficiency as well as for anticipating demand in the energy market dynamics. The objective of the present work is the…

Machine Learning · Computer Science 2023-10-20 Davi Guimarães da Silva , Anderson Alvarenga de Moura Meneses

The inter-temporal consumption flexibility of commercial buildings can be harnessed to improve the energy efficiency of buildings, or to provide ancillary service to the power grid. To do so, a predictive model of the building's thermal…

Systems and Control · Computer Science 2016-03-23 Qie Hu , Frauke Oldewurtel , Maximilian Balandat , Evangelos Vrettos , Datong Zhou , Claire J. Tomlin

Ensuring optimal Indoor Environmental Quality (IEQ) is vital for occupant health and productivity, yet it often comes at a high energy cost in conventional Heating, Ventilation, and Air Conditioning (HVAC) systems. This paper proposes a…

Machine Learning · Computer Science 2025-10-01 Youssef Sabiri , Walid Houmaidi , Aaya Bougrine , Salmane El Mansour Billah

The flexibility in electricity consumption and production in communities of residential buildings, including those with renewable energy sources and energy storage (a.k.a., prosumers), can effectively be utilized through the advancement of…

Machine Learning · Computer Science 2024-02-22 Aleksei Kychkin , Georgios C. Chasparis