Research of the Building Energy Efficiency Data Analysis Based on Time ...
A detailed analysis of the results of the investigation concerning aspects of the current situation and trends in building energy consumption, energy efficiency strategy and the implementation of ...
In this paper, the statistical data combined with the actual situation of building energy efficiency during the period of the Eleventh-Five-Year in Anhui Province, China. Use exponential smoothing method of time series algorithm for forecast and analysis of building energy consumption and energy saving in Anhui Province.
Comprehensive energy demand and usage data for building automation
Research at the interface of room comfort and energy efficiency is of critical societal importance. At the same time , there is a lack of publicly available data to optimize important building ...
The advent of smart technologies and the Internet of Things (IoT) has revolutionized energy management in urban buildings . These technologies enable real- time monitoring and cloud- based data analysis of energy consumption patterns, allowing for advanced strategies like predictive maintenance and demand-response systems [1, 2, 3]. By reducing energy usage during peak demand periods and ...
Forecasting Time
Chou et al. (2016) presented a smart decision system based on big data analytics and cloud computing for energy efficiency in buildings [4]. Hartono et al. (2020) analyzed modern energy projects in Indonesia and confirmed that modern energy access is one of the main factors of energy spending, especially for low-income households and rural ...
Building energy performance forecasting (BEPF) is an active area of research with the potential to improve the efficiency of building energy management systems, support global sustainability goals, and mitigate climate change impacts. This systematic review examines three main prediction methods: model-driven, data -driven, and hybrid-driven, each with different principles, basics, advantages ...
A three
This dataset can be used in various applications—building energy benchmarking, load shape analysis , energy prediction, occupancy prediction and analytics, and HVAC controls—to improve the ...
The results highlight the effectiveness of hybrid modelling approaches with SHAP analyses based on different baselines to ensure the integration of environmental impacts, architectural design processes and engineering solutions in terms of building energy efficiency .
PDF A data
Abstract To address the limitations of conventional building energy benchmarking, which often lack energy end-uses and operation information, this study proposes a data - driven framework for building energy benchmarking. The framework utilizes time -series decomposition, clustering, and change-point regression (CPR) techniques.
The construction industry has emerged as a major contributor to global energy consumption and greenhouse gas emissions amidst continuously rising worldwide energy demands. Enhancing building energy efficiency represents a critical intervention for achieving energy conservation and emission reduction targets. In the context of smart city development, such optimization efforts provide ...