This dataset and the content below if from this journal publication and Github repository.

Data science for building energy efficiency: A comprehensive text-mining review of scientific literature

This repository contains the data and code for paper:

Mahmoud M. Abdelrahman, Sicheng Zhan, Clayton Miller, and Adrian Chong (2021) Data science for building energy efficiency: A comprehensive data-driven review of scientific literature. Energy and Buildings. https://doi.org/10.1016/j.enbuild.2021.110885.

@article{ABDELRAHMAN2021110885,
 title = {Data science for building energy efficiency: A comprehensive text-mining driven review of scientific literature},
 author = {Mahmoud M. Abdelrahman and Sicheng Zhan and Clayton Miller and Adrian Chong},
 journal = {Energy and Buildings},
 pages = {110885},
 year = {2021},
 issn = {0378-7788},
 doi = {https://doi.org/10.1016/j.enbuild.2021.110885}
}

Graphical abstract

https://user-images.githubusercontent.com/6969514/102309569-066e2400-3fa4-11eb-920d-381f177f44b4.jpg" alt="visual_abstractAsset 18@4x-80">

Licenses

Text and figures : CC-BY-4.0

Overview:

This is the raw data of a current consumption measurement campaign of an end-device implementing the novel LoRaWAN LR-FHSS mechanism. The measurements have been made implementing a complete network, which includes a gateway, end-device and network server all implementing the LoRaWAN LR-FHSS technology. We used the following equipment:

Gateway: Kerlink iBTS Compact

End-Device: LR1121DVK1TBKS

Network Server: ChirpStack

Power Analyzer: Keysight 14585A

The provided files are for uplink LR-FHSS transmission measurements with and without confirmation with different LR-FHSS DR configurations. The current consumption exclusively accounts for the radio interface.

The configuration of the end-device is the following:

FRM Payload Size: 4 bytes

Transmission Power: +14 dBm

This dataset is part of a published journal article: R. Sanchez-Vital, L. Casals, B. Heer-Salva, R. Vidal, C. Gomez, E. Garcia-Villegas, "Energy Performance of LR-FHSS: Analysis and Evaluation", Sensors 24, no. 17: 5770, Sep. 2024. https://doi.org/10.3390/s24175770

The manuscript provides current consumption measurements, an analytical model of the average current consumption, battery lifetime, and energy efficiency of data transmission, and the evaluation of several parameters.

Journal Article Abstract:

Long-range frequency hopping spread spectrum (LR-FHSS) is a pivotal advancement in the LoRaWAN protocol that is designed to enhance the network’s capacity and robustness, particularly in densely populated environments. Although energy consumption is paramount in LoRaWAN-based end devices, this is the first study in the literature, to our knowledge, that models the impact of this novel mechanism on energy consumption. In this article, we provide a comprehensive energy consumption analytical model of LR-FHSS, focusing on three critical metrics: average current consumption, battery lifetime, and energy efficiency of data transmission. The model is based on measurements performed on real hardware in a fully operational LR-FHSS network. While in our evaluation, LR-FHSS can show worse consumption figures than LoRa, we find that with optimal configuration, the battery lifetime of LR-FHSS end devices can reach 2.5 years for a 50 min notification period. For the most energy-efficient payload size, this lifespan can be extended to a theoretical maximum of up to 16 years with a one-day notification interval using a cell-coin battery.

Data structure:

Filenames:

ACK and noACK state the use (or not) of confirmation. DR8 to DR11 state the use of each of the LR-FHSS DR configurations.

CSV file structure:

The first three rows refer to metadata (Power Analyzer and End-Device models, utilization of ACK, DR configuration, Sampling Period and Measurement Date).

Then, the labels are in the fourth row (Time, Current).

The other rows refer to the actual measurements. Time instants are measured in seconds and current in Amperes.

Corresponding dataset for the article "Sensor solutions for an energy-efficient and user-centered heating system" published in the Journal of Sensors and Sensor Systems Special Issue "Sensors and Measurement Systems 2016".

This dataset contains timeseries data from hydronic heating (or heating hot water (HHW))) systems in 216 buildings across 49 US organizations. The dataset comprises over 100 million measurements taken by building automation systems from 2014-2023. A typical building’s dataset contains measured supply and return water temperature, flow rate, output heating power (or heating load), system state and outdoor temperature spanning 2.2 years (15-minute interval), though the types, span, and interval of data vary based on what was available for each building. Pump and boiler data are available for smaller subsets of buildings. The dataset also includes a broad range of metadata characteristics related to both the building and the HHW system, such as floor area, year of construction, building type, climate zone, heating system type, and heating design day temperature. Further heating system metadata such as equipment design capacity, nominal efficiency, and minimum turndown are available for a s..., See linked open access journal publication for detail regarding how this dataset was collected and processed., , # Data from hydronic heating systems in 216 commercial buildings

https://doi.org/10.5061/dryad.t4b8gtj8n

Description of the data and file structure

Please note that the open-access journal paper associated with this dataset contains further information regarding this dataset, including software code used to analyze the data, visualize it, and create the manuscript file submitted to the journal. The journal paper analyzes a total of 259 buildings. The public dataset stored on Dryad contains the data from 216 buildings which is a subset of the 259 buildings that includes all the buildings which the donors allowed the timeseries data to be shared. The supplementary material associated with the journal paper includes the metadata and high level summary statistics for the full 259 building dataset, but not the underlying timeseries data.

metadata.csv

This is a csv (comma separated value) format file. This anonymized public dataset contai...

Data underlying the figures included in the manuscript "Marginal abatement cost curve for NOx incorporating controls, renewable electricity, energy efficiency and fuel switching". Data include national and regional Marginal Abatement Cost Curves.

This dataset is associated with the following publication: Loughlin, D., A. Macpherson, K. Kaufman, and B. Keaveny. Marginal abatement cost curve for NOx incorporating controls, renewable electricity, energy efficiency and fuel switching. JOURNAL OF THE AIR & WASTE MANAGEMENT ASSOCIATION. Air & Waste Management Association, Pittsburgh, PA, USA, 67(10): 1115-1125, (2017).

Test results of the impact of the digital divide on energy efficiency and environmental protection.

This data submission is for Phase 2 of Active Management of Integrated Geothermal-CO2 Storage Reservoirs in Sedimentary Formations, which focuses on multi-fluid (CO2 and brine) geothermal energy production and diurnal bulk energy storage in geologic settings that are suitable for geologic CO2 storage. This data submission includes all data used in the Geosphere Journal article by Buscheck et al (2016). All assumptions are discussed in that article.

Model results–Energy efficiency behavior.

Abstract In the last ten years, the social housing sector in Brazil has been driven by the Programme “Minha Casa, Minha Vida” (“My House, My Life”). Although the Programme allowed the construction of a great number of dwellings throughout the country, field assessments have highlighted failures such as lack of climate suitability. Such an inadequacy can result in low levels of energy efficiency and the dissatisfaction of residents. Thus, the aim of this study is to review the national literature from the last ten years (from 2009 up to 2019) in order to determine the most impacting parameters for the energy efficiency of social housing. A synthesis of this information is necessary to consolidate the knowledge produced so far and to facilitate progress in this area. This study is expected to help future decisions by different stakeholders: researchers can define future goals by considering what has already been done, designers can apply user-centric design and energy efficiency criteria in practice, and policy makers can link the approval of social housing designs to energy efficiency parameters.

ABSTRACT Agribusiness and commerce are two major sectors that consume electricity. Agribusiness can generate energy but not enough to meet its needs. Thus, energy efficiency is fundamental for the sector’s sustainability. This study aimed to apply PROCEL energy evaluation methods in a Brazilian agribusiness company, specifically in the meat retail sector, located in the Alta Paulista region. This research has a quantitative approach, and PROCEL’s RTQ-C manual, bibliographical research on the energy issue, and the functioning of the company’s environment were used. The commercial establishment received the B classification index, which can be considered good but has several points of improvement, mainly on air conditioning, which provides better energy efficiency to the company. Therefore, the company can obtain economic and environmental returns by improving such areas, and the present research serves as a basis for evaluating energy efficiency in other companies in the same sector.

The Energy-SHIFTS Working Groups provided SSH research priority recommendations for four specific (SET-Plan focussed) energy topics. Members were leading energy-SSH researchers, representing wider disciplinary research communities e.g. via leadership of research groups/institutes, Horizon 2020 energy projects, and/or editorial roles for journals.The Working Groups produced a number of streams of data, including 10 interviews each, and surveys of hundreds of SSH scholars across Europe. Interview and survey protocols were also published by the project (see reference).

ABSTRACT The energy burdens of the Feira de Santana Integrated Water Supply System (SIAA-FSA) were analyzed using the life cycle assessment method. The higher energy burdens in the water supply chain were identified and scenarios for improvement were proposed. The supply chain of chemicals, transportation, electricity and replacement of pipes were considered for SIAA-FSA. The cumulative energy demand of SIAA-FSA was 3.51 kWh.m-3 of consumed water. The water uptake and distribution steps presented the highest energy demands, and the electricity for pumping represented 86% of the cumulative energy demand. The SIAA-FSA proposed scenarios showed significant improvements over the current one, with rational use of chemicals, electricity and water.

Abstract Anincreasingprocess of urbanisation anda growing urban population heighten the need to understand the energy costsof the production of building materials. One of the most importanttoolsapplied to monitor the use of non-renewableenergyresources in the production of conventionalconcretes is energy input, intowhichfurther research is needed. In this study, an ANFIS (adaptive neuro-fuzzy inference system) hybrid model was developed to predict energy input in order to evaluate the energy demand required for each component of the production of conventional concrete (cement, water, fine aggregate and coarse aggregate) using 101 experimental dosages, 101 validation dosages and energy coefficients available in literature. The resultsshowedthatan adequate dosage can generate energy cost savingsof 24.77% in the production of concrete, while still maintaining the mechanical characteristics of compressive strength for conventional constructions.

ABSTRACT This study aimed to evaluate the energy efficiency of a center pivot irrigation system operating in a terrain of variable topography. Values of Pumping Energy Efficiency (PEE), Supply Energy Efficiency (SEE), Global Energy Efficiency (GEE) and Specific Energy (Es in kWh m-3) computed at 18 different angular positions of the lateral line were used as energy efficiency indicators. An ultrasonic flow meter, digital pressure transducers and a power quality analyzer were used in order to evaluate hydraulic (total system flow-Q and total dynamic head-TDH) and electrical parameters (active electrical power - AEP) of the center pivot pumping unit that were required for evaluating the selected energy efficiency indictors. Topographic elevations of the water source, the pumping unit and of the center lateral line were also determined. For the center pivot lateral line, it was necessary to determine, at the 18 angular positions considered, the altitude of the track of each center pivot support tower. Results indicated that currently, even after more than 10000h of use, the center pivot system operates with satisfactory energy efficiency, as indicated by an average GEE value equal to 42.5%, that is classified as “good”. Statistical analysis indicated that the topographic disposition of the center pivot lateral line, as characterized by a uphill or downhill disposition, resulted on different PEE, SEE and GEE values, while the average Es value (0.42 kWh m-3) was not affected by the lateral line disposition.

Shaanxi energy consumption structure diversity and energy efficiency regression results.

Building energy efficiency standards implemented in Henan Province.

Accurate prediction of greenhouse temperature and relative humidity is critical for developing environmental control systems. Effective regulation strategies can help improve crop yields while reducing energy consumption. In this study, Multilayer Perceptron (MLP) and Radial Basis Function (RBF) networks were used for short-term prediction of temperature and relative humidity in a double-film greenhouse. The prediction models used indoor soil temperature, light intensity, and historical measurements of temperature and humidity from the previous 10 minutes as inputs. Results show that the MLP model with Levenberg-Marquardt optimization performs best in predicting the current temperature and humidity, with an RMSE of 0.439°C and R2 of 0.997 for temperature prediction and an RMSE of 1.141% and R2 of 0.996 for relative humidity prediction. For 30-minute short-term prediction, the Bayesian optimized RBF model showed better temperature prediction with an RMSE of 1.579°C and an R2 of 0.958, while the MLP model performed better in relative humidity prediction with an RMSE of 4.299% and an R2 of 0.948. This study provides theoretical support for advancing the intelligent regulation of greenhouse environmental factors in cold and arid regions, and the application of predictive models to intelligent environmental management systems could help optimize cultivation practices and energy efficiency.

Distinguishing behavioral attributes (per Boudet et al., 2016) of identified water-energy-saving measure classes.

Analysis of the energy-saving effect.

The government’s environmental protection policy can significantly contribute to alleviating resource shortages and curbing environmental pollution, but the impact of various policy instruments implemented by the government on energy efficiency is unclear. Based on the panel data of 30 provinces in China from 2005 to 2021, this paper analyses the impact of environmental regulation and the industrial structure on energy efficiency from the perspective of resource taxes. The U-shaped relationship between environmental regulation and energy efficiency and between the optimization of industrial structure can significantly improve energy efficiency, and the optimization of industrial structure is conducive to weakening the initial inhibitory effect of environmental regulation. In addition, the analysis of regional heterogeneity showed that the impact of environmental regulation was stronger in the central and western regions, while the impact of industrial structure was stronger in the eastern and western regions. The conclusions of this study can help to expand the understanding of the relationship between environmental regulation and industrial structure on energy efficiency, provide policy enlightenment for the realization of green development and high-quality development, and provide Chinese examples and experiences for developing countries to improve energy efficiency.