scholarly journals Visual Analysis of a Smart City’s Energy Consumption

2019 ◽  
Vol 3 (2) ◽  
pp. 30
Author(s):  
Juan Trelles Trabucco ◽  
Dongwoo Lee ◽  
Sybil Derrible ◽  
G. Elisabeta Marai
Keyword(s):  
Energy Consumption ◽  
Visual Analysis ◽  
Census Data ◽  
Open Data ◽  
Analysis Tool ◽  
Available Energy ◽  
Qualitative Feedback ◽  
Consumption Data ◽  
Spatial Differences ◽  
Urban Energy

Through the use of open data portals, cities, districts and countries are increasingly making available energy consumption data. These data have the potential to inform both policymakers and local communities. At the same time, however, these datasets are large and complicated to analyze. We present the activity-centered-design, from requirements to evaluation, of a web-based visual analysis tool to explore energy consumption in Chicago. The resulting application integrates energy consumption data and census data, making it possible for both amateurs and experts to analyze disaggregated datasets at multiple levels of spatial aggregation and to compare temporal and spatial differences. An evaluation through case studies and qualitative feedback demonstrates that this visual analysis application successfully meets the goals of integrating large, disaggregated urban energy consumption datasets and of supporting analysis by both lay users and experts.

A Big Data Application for Energy Consumption Management of Commercial Buildings

2021 ◽  
Vol 2 (1) ◽  
pp. 0-0
Keyword(s):  
Big Data ◽  
Energy Consumption ◽  
Data Streams ◽  
Design And Implementation ◽  
Available Energy ◽  
Cost Of Energy ◽  
Data Application ◽  
Consumption Data ◽  
Big Data Application ◽  
The Cost

The demand for energy is increasing rapidly and, after a few years, it may surpass the available energy, which may lead the energy providers to increase the cost of energy consumption to compensate the cost for the production. This paper provides design and implementation details of a prototype big data application developed to help large buildings to automatically manage their energy consumption by setting energy consumption targets, collecting periodic energy consumption data, storing the data streams, displaying the energy consumption graphically in real-time, analyzing the consumption patterns, and generating energy consumption graphs and reports. The application is connected to Mongo NoSQL backend database to handle the large and continuously changing data. This big data energy consumption management system is expected to help the users in managing energy consumption by analyzing the patterns to see if it is within or above the desired consumption targets and displaying the data graphically.

Retrospective Testing of an Automated Building Commissioning Analysis Tool (ABCAT)

2009 ◽  
Author(s):  
Guanjing Lin ◽  
David E. Claridge
Keyword(s):  
Energy Consumption ◽  
Implementation Process ◽  
Building Energy ◽  
Energy Performance ◽  
Diagnostic Techniques ◽  
Analysis Tool ◽  
Building Energy Consumption ◽  
Building Commissioning ◽  
Consumption Data ◽  
Cost Efficient

Commissioning services have proven successful in reducing building energy consumption, but the optimal energy performance obtained by commissioning may subsequently degrade. Automated Building Commissioning Analysis Tool (ABCAT), which combines a calibrated simulation with diagnostic techniques, is a simple and cost efficient tool that can help maintain the optimal building energy performance after building commissioning. It can continuously monitor whole building energy consumption, warn operation personnel when an HVAC system problem has increased energy consumption, and assist them in identifying the possible cause(s) of the problem. This paper presents the results of a retrospective implementation of ABCAT on five buildings, each of which has at least three years of post-commissioning daily energy consumption data, on the Texas A&M University campus. The methodology of ABCAT is reviewed and the implementation process of ABCAT on one building is specifically illustrated. Eighteen faults were detected in 15 building-years of consumption data with a defined fault detection standard. The causes of some of the detected faults are verified with historical documentation. The remaining fault diagnoses remain unconfirmed due to data quality issues and incomplete information on maintenance performed in the buildings.

scholarly journals An Improved Forecasting Method and Application of China’s Energy Consumption under the Carbon Peak Target

2021 ◽  
Vol 13 (15) ◽  
pp. 8670
Author(s):  
Xiwen Cui ◽  
Shaojun E ◽  
Dongxiao Niu ◽  
Dongyu Wang ◽  
Mingyu Li
Keyword(s):  
Sustainable Development ◽  
Energy Consumption ◽  
Environmental Pollution ◽  
Optimization Methods ◽  
Support Vector ◽  
The Sustainable Development ◽  
Consumption Data ◽  
Forecasting Method ◽  
Forecasting Performance ◽  
Carbon Peak

In the process of economic development, the consumption of energy leads to environmental pollution. Environmental pollution affects the sustainable development of the world, and therefore energy consumption needs to be controlled. To help China formulate sustainable development policies, this paper proposes an energy consumption forecasting model based on an improved whale algorithm optimizing a linear support vector regression machine. The model combines multiple optimization methods to overcome the shortcomings of traditional models. This effectively improves the forecasting performance. The results of the projection of China’s future energy consumption data show that current policies are unable to achieve the carbon peak target. This result requires China to develop relevant policies, especially measures related to energy consumption factors, as soon as possible to ensure that China can achieve its peak carbon targets.

scholarly journals A Possible Smart Metering System Evolution for Rural and Remote Areas Employing Unmanned Aerial Vehicles and Internet of Things in Smart Grids

Sensors ◽  
2021 ◽  
Vol 21 (5) ◽  
pp. 1627
Author(s):  
Giovanni Battista Gaggero ◽  
Mario Marchese ◽  
Aya Moheddine ◽  
Fabio Patrone
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Unmanned Aerial Vehicles ◽  
Smart Metering ◽  
Rural And Remote ◽  
Electrical Grid ◽  
Remote Areas ◽  
Aerial Vehicles ◽  
Consumption Data ◽  
Rural And Remote Areas

The way of generating and distributing energy throughout the electrical grid to all users is evolving. The concept of Smart Grid (SG) took place to enhance the management of the electrical grid infrastructure and its functionalities from the traditional system to an improved one. To measure the energy consumption of the users is one of these functionalities that, in some countries, has already evolved from a periodical manual consumption reading to a more frequent and automatic one, leading to the concept of Smart Metering (SM). Technology improvement could be applied to the SM systems to allow, on one hand, a more efficient way to collect the energy consumption data of each user, and, on the other hand, a better distribution of the available energy through the infrastructure. Widespread communication solutions based on existing telecommunication infrastructures instead of using ad-hoc ones can be exploited for this purpose. In this paper, we recall the basic elements and the evolution of the SM network architecture focusing on how it could further improve in the near future. We report the main technologies and protocols which can be exploited for the data exchange throughout the infrastructure and the pros and cons of each solution. Finally, we propose an innovative solution as a possible evolution of the SM system. This solution is based on a set of Internet of Things (IoT) communication technologies called Low Power Wide Area Network (LPWAN) which could be employed to improve the performance of the currently used technologies and provide additional functionalities. We also propose the employment of Unmanned Aerial Vehicles (UAVs) to periodically collect energy consumption data, with evident advantages especially if employed in rural and remote areas. We show some preliminary performance results which allow assessing the feasibility of the proposed approach.

scholarly journals Energy Consumption Analysis and Characterization of Healthcare Facilities in the United States

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3775 ◽  
Author(s):  
Khaled Bawaneh ◽  
Farnaz Ghazi Nezami ◽  
Md. Rasheduzzaman ◽  
Brad Deken
Keyword(s):  
United States ◽  
Energy Consumption ◽  
Energy Intensity ◽  
The United States ◽  
High Energy ◽  
Total Energy Consumption ◽  
Healthcare Facilities ◽  
Energy Consumption Analysis ◽  
Consumption Data ◽  
End Use

Healthcare facilities in the United States account for 4.8% of the total area in the commercial sector and are responsible for 10.3% of total energy consumption in this sector. The number of healthcare facilities increased by 22% since 2003, leading to a 21% rise in energy consumption and an 8% reduction in energy intensity per unit of area (544.8 kWh/m2). This study provides an analytical overview of the end-use energy consumption data in healthcare systems for hospitals in the United States. The energy intensity of the U.S. hospitals ranges from 640.7 kWh/m2 in Zone 5 (very hot) to 781.1 kWh/m2 in Zone 1 (very cold), with an average of 738.5 kWh/m2. This is approximately 2.6 times higher than that of other commercial buildings. High energy intensity in the healthcare facilities, particularly in hospitals, along with energy costs and associated environmental concerns make energy analysis crucial for this type of facility. The proposed analysis shows that U.S. healthcare facilities have higher energy intensity than those of most other countries, especially the European ones. This necessitates the adoption of more energy-efficient approaches to the infrastructure and the management of healthcare facilities in the United States.

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