Article
Green & Sustainable Science & Technology
Weiqi Wang, Zixuan Zhou, Zhongming Lu
Summary: Room air conditioners (RACs) are high energy-consuming home appliances. Developing a smart solution to evaluate and track the efficiency of RACs is essential. The data-driven framework proposed in this study identifies non-inverter window RACs with low efficiency by analyzing smart meter data and uses XGBoost to predict hourly electricity consumption. The framework separates RACs into low efficiency and normal efficiency categories based on the impact of outdoor temperature on electricity consumption, with promising validation results.
JOURNAL OF CLEANER PRODUCTION
(2022)
Article
Construction & Building Technology
Sanguk Park
Summary: This study aims to enable cost-effective IoT system design by removing redundant IoT sensors through correlation analysis of sensing data in a smart home environment. It presents a data analysis and prediction technology that enables meaningful inference through correlation analysis of data from different heterogeneous IoT sensors installed inside a smart home for energy efficiency. An intelligent service model based on machine learning algorithm is proposed.
Article
Energy & Fuels
K. Purna Prakash, Y. V. Pavan Kumar, Ch. Pradeep Reddy, D. John Pradeep, Aymen Flah, Ali Nasser Alzaed, Ahmad Aziz Al Ahamdi, Sherif S. M. Ghoneim
Summary: This paper highlights the importance of transforming traditional power grids into smart grids and proposes a simple approach for comprehensive exploration of smart home energy consumption datasets. The analysis of these datasets provides insights into customers' energy consumption behavior in the power network.
Review
Engineering, Multidisciplinary
Aniket Babuta, Bhavna Gupta, Abhimanyu Kumar, Souvik Ganguli
Summary: This paper provides a comprehensive survey on power and energy measurement devices, focusing on the development of wattmeters in various systems. It also discusses the evolution of energy measurement instruments from simple to complex structures, as well as the introduction of smart meters and the internet of energy. The future of the power sector in relation to current technology and energy theft is also explored, offering a direction for future research.
Article
Chemistry, Analytical
Omar Munoz, Adolfo Ruelas, Pedro Rosales, Alexis Acuna, Alejandro Suastegui, Fernando Lara
Summary: This paper presents the design, construction, and validation of a smart meter with load control to address the issue of rising electricity consumption. The meter not only monitors energy consumption but also provides additional parameters, and its accuracy was proven through experimentation. The real-life application of the device was also demonstrated.
Review
Energy & Fuels
Prajowal Manandhar, Hasan Rafiq, Edwin Rodriguez-Ubinas
Summary: Urban energy modeling plays a crucial role in planning and efficiently managing electric power systems. Electricity load forecasts are important for estimating load demand and aiding power system operation. This article reviews recent literature on data-driven electricity load forecasts, addressing the factors affecting accuracy, reviewing forecasting techniques, and highlighting challenges and proposed improvements.
Article
Energy & Fuels
Rui Tang, Jonathon Dore, Jin Ma, Philip H. W. Leong
Summary: This study introduces an interpolation model based on SRGAN to generate higher resolution PV and load power data from low resolution data, improving accuracy in modeling and optimization of PV-integrated battery systems. Results from validation and comparison show that the model can effectively capture the targeted data features and demonstrate consistency across different scenarios.
Article
Engineering, Chemical
Yu-Chen Hu, Yu-Hsiu Lin, Harinahalli Lokesh Gururaj
Summary: Smart meters allow for transmission of energy consumption data and enable consumer-centric use cases, but are unable to decompose energy consumption data into appliance-level data. The AI model introduced in the research can effectively perform energy decomposition in residential demand-side management.
Article
Thermodynamics
Jae Yong Lee, Taesu Yim
Summary: This study provides new perspectives on domestic hot water use through real-time data collection, revealing insights on seasonal behavior, demand deviation, discarded characteristics, and predictive modeling based on outdoor temperature. It offers guidelines for efficient use of domestic hot water.
Article
Engineering, Electrical & Electronic
Inam Ullah Khan, Nadeem Javaid, C. James Taylor, Xiandong Ma
Summary: The role of electricity theft detection is crucial in maintaining cost-efficiency in smart grids. Existing methods are limited by the large volume of data, missing values, and non-linearity. A novel framework is proposed that combines three modules to address these issues. The framework efficiently handles missing values, imbalanced datasets, and accurately predicts electricity theft cases using a hybrid classification approach and an improved artificial neural network.
IEEE TRANSACTIONS ON POWER SYSTEMS
(2023)
Article
Multidisciplinary Sciences
Lucas Pereira, Donovan Costa, Miguel Ribeiro
Summary: Smart meter data is crucial for next-generation power grids and machine learning algorithms. The SustDataED2 dataset described in this paper provides aggregated and individual appliance consumption data, as well as timestamps for evaluating machine learning problems.
Article
Energy & Fuels
Charalampos Ziras, Lisa Calearo, Mattia Marinelli
Summary: This paper discusses the implications of applying different net metering methods on a prosumer's energy exchanges with the grid, and the subsequent effect on costs and self-consumption. Results indicate that switching from instantaneous per phase netting to hourly summation netting leads to increased self-consumption and decreased annual energy imports.
SUSTAINABLE ENERGY GRIDS & NETWORKS
(2021)
Article
Chemistry, Analytical
Purna Prakash Kasaraneni, Yellapragada Venkata Pavan Kumar, Ganesh Lakshmana Kumar Moganti, Ramani Kannan
Summary: This paper proposes an ML-based ensemble classifiers approach to address anomalies in smart home energy consumption data. By identifying and removing anomalies, and imputing missing information, more accurate data analysis is achieved. The study finds that the ensemble classifier RF+SVM+DT performs superior in anomaly handling.
Article
Chemistry, Analytical
Muhammad Arslan Shaukat, Haafizah Rameeza Shaukat, Zakria Qadir, Hafiz Suliman Munawar, Abbas Z. Kouzani, M. A. Parvez Mahmud
Summary: Load forecasting is crucial in the realm of smart grids, and this paper proposes time-series forecasting for short-term load prediction using statistical and mathematical models. A business case is presented to analyze different clusters and predict customer behavior, with the most accurate prediction model observed to be the ARIMA model with (P, D, Q) values of (1, 1, 1).
Article
Construction & Building Technology
Maohui Luo, Qichun Zheng, Ye Zhao, Fei Zhao, Xiang Zhou
Summary: This study introduces the design and benefits of occupant-centric smart thermostats (OCST) in improving energy efficiency and thermal comfort. Through data analysis, it is shown that OCST can significantly reduce energy consumption in single-family houses.
ENERGY AND BUILDINGS
(2023)
Article
Thermodynamics
Sukjoon Oh, Jeff S. Haberl
SCIENCE AND TECHNOLOGY FOR THE BUILT ENVIRONMENT
(2016)
Article
Thermodynamics
Sukjoon Oh, Jeff S. Haberl
SCIENCE AND TECHNOLOGY FOR THE BUILT ENVIRONMENT
(2016)
Article
Thermodynamics
Sukjoon Oh, Jeff S. Haberl
SCIENCE AND TECHNOLOGY FOR THE BUILT ENVIRONMENT
(2016)
Article
Thermodynamics
Sukjoon Oh, Jeff S. Haberl, Juan-Carlos Baltazar
SCIENCE AND TECHNOLOGY FOR THE BUILT ENVIRONMENT
(2020)
Article
Energy & Fuels
Sukjoon Oh, Chul Kim, Joonghyeok Heo, Sung Lok Do, Kee Han Kim
Article
Energy & Fuels
Sukjoon Oh, Suwon Song
Summary: Thermal comfort, indoor air quality, and energy use are closely related in building performance. Real-time monitoring data analysis on a childcare center showed that operating the ERV system reduced CO2 and PM10 concentrations significantly during occupied hours, but there were also comfort frequency issues during unoccupied hours. To enhance indoor environmental quality and save energy, it is important to consider IAQ, thermal comfort, and energy use together when controlling the ERV system.
Article
Construction & Building Technology
Samiran Khorat, Debashish Das, Rupali Khatun, Sk Mohammad Aziz, Prashant Anand, Ansar Khan, Mattheos Santamouris, Dev Niyogi
Summary: Cool roofs can effectively mitigate heatwave-induced excess heat and enhance thermal comfort in urban areas. Implementing cool roofs can significantly improve urban meteorology and thermal comfort, reducing energy flux and heat stress.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Qi Li, Jiayu Chen, Xiaowei Luo
Summary: This study focuses on the vertical wind conditions as a main external factor that limits the energy assessment of high-rise buildings in urban areas. Traditional tools for energy assessment of buildings use a universal vertical wind profile estimation, without taking into account the unique wind speed in each direction induced by the various shapes and configurations of buildings in cities. To address this limitation, the study developed an omnidirectional urban vertical wind speed estimation method using direction-dependent building morphologies and machine learning algorithms.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Xiaojun Luo, Lamine Mahdjoubi
Summary: This paper presents an integrated blockchain and machine learning-based energy management framework for multiple forms of energy allocation and transmission among multiple domestic buildings. Machine learning is used to predict energy generation and consumption patterns, and the proposed framework establishes optimal and automated energy allocation through peer-to-peer energy transactions. The approach contributes to the reduction of greenhouse gas emissions and enhances environmental sustainability.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Ying Yu, Yuanwei Xiao, Jinshuai Chou, Xingyu Wang, Liu Yang
Summary: This study proposes a dual-layer optimization design method to maximize the energy sharing potential, enhance collaborative benefits, and reduce the storage capacity of building clusters. Case studies show that the proposed design significantly improves the performance of building clusters, reduces energy storage capacity, and shortens the payback period.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Felix Langner, Weimin Wang, Moritz Frahm, Veit Hagenmeyer
Summary: This paper compares two main approaches to consider uncertainties in model predictive control (MPC) for buildings: robust and stochastic MPC. The results show that compared to a deterministic MPC, the robust MPC increases the electricity cost while providing complete temperature constraint satisfaction, while the stochastic MPC slightly increases the electricity cost but fulfills the thermal comfort requirements.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Somil Yadav, Caroline Hachem-Vermette
Summary: This study proposes a mathematical model to evaluate the performance of a Double Skin Facade (DSF) system and its impact on indoor conditions. The model considers various design parameters and analyzes their effects on the system's electrical output and room temperature.
ENERGY AND BUILDINGS
(2024)
Article
Construction & Building Technology
Ruijun Chen, Holly Samuelson, Yukai Zou, Xianghan Zheng, Yifan Cao
Summary: This research introduces an innovative resilient design framework that optimizes building performance by considering a holistic life cycle perspective and accounting for climate projection uncertainties. The study finds that future climate scenarios significantly impact building life cycle performance, with wall U-value, windows U-value, and wall density being major factors. By using ensemble learning and optimization algorithms, predictions for carbon emissions, cost, and indoor discomfort hours can be made, and the best resilient design scheme can be selected. Applying this framework leads to significant improvements in building life cycle performance.
ENERGY AND BUILDINGS
(2024)