scholarly journals Commercial-sector energy-consumption data-base-development project. Volume II. Survey of available energy use data

1978 ◽  
Author(s):  
Not Given Author
Keyword(s):  
Energy Consumption ◽  
Data Base ◽  
Energy Use ◽  
Development Project ◽  
Commercial Sector ◽  
Available Energy ◽  
Consumption Data

Modelling of energy consumption in sociotechnical systems with intelligent equipment

2021 ◽  
pp. 4-19
Author(s):  
Владимир Борисович Барахнин ◽  
Светлана Валентиновна Мальцева ◽  
Константин Владимирович Данилов ◽  
Василий Вячеславович Корнилов
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Electricity Consumption ◽  
Feedback Mechanism ◽  
Smart Devices ◽  
Consumption Function ◽  
Management Processes ◽  
Consumption Data ◽  
The Times ◽  
Dynamic Time

Современные социотехнические системы в различных областях характеризуются наличием в их составе большого количества интеллектуального оборудования, которое может самостоятельно регулировать собственное потребление энергии, а также взаимодействовать с другими потребителями в процессах принятия решений и управления. Одна из таких отраслей - энергетика, где самоорганизация и системы коллективного потребления являются наиболее перспективными с точки зрения обеспечения эффективности использования энергоресурсов. Рассмотрены подходы к установлению статических и динамических тарифов на электроэнергию. Проведено сравнение двух моделей энергопотребления - статического двухтарифного и динамического, учитывающих рациональное поведение умных устройств, способных выбирать лучшие режимы для потребления электроэнергии. Показано влияние количества таких устройств на возможность достижения равномерного потребления при использовании второй модели. Modern socio-technical systems in various fields include a large number of smart equipment that can independently regulate its own energy consumption, as well as interact with other consumers in decision-making and management processes. Energy is one of these areas. Self-organization and collective self-consumption are the most promising in terms of ensuring the efficiency of energy use. Existing and prospective approaches to using static and dynamic time-based tariffs are under consideration. The paper presents a mathematical description of two models of energy consumption: a static model based on the allocation of two zones with a fixed duration and tariffs for each one and a dynamic model of two-tariff accounting with feedback, which assumes tariffs changing based on the results of the analysis of current electricity consumption. A pilot study of both models was conducted by using energy consumption data and taking into account the rational behavior of smart devices as consumers who can choose the best periods for electricity consumption. During the experiments it was investigated how an increase in the share of smart devices in the composition of electricity consumers as well as options for establishing zones and tariffs, affect the possibility of achieving uniform consumption during the day. Experiments have shown that with a small proportion of smart devices, acceptable results that reduce the variation in the consumption function can favor usage of the model without feedback. An increase in the number of actors in the system inevitably requires including a feedback mechanism into the system that allows the resource supplier to prevent excessive concentration of smart devices during the period of the cheaper tariff. However, when the share of smart devices exceeds a certain critical value, a pronounced inversion of the times of cheap and expensive tariffs occurs in two successive iterations. In this case, in order to ensure a quite even distribution of electricity consumption, it is advisable for the supplier to return to the single tariff rate. Thus, an excessive increase in the number of actors in the system can neutralize the effect of their use

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.

scholarly journals Using Conversational Assistants and Connected Devices to Promote a Responsible Energy Consumption at Home

Proceedings ◽  
2019 ◽  
Vol 31 (1) ◽  
pp. 32
Author(s):  
Jesús Fontecha ◽  
Iván González ◽  
Alberto Salas-Seguín
Keyword(s):  
Energy Consumption ◽  
Home Environment ◽  
Smart Home ◽  
Energy Use ◽  
Consumption Data ◽  
Smart Home Environment ◽  
Current Energy ◽  
Positive Results ◽  
Natural Way ◽  
At Home

Today, households worldwide are being increasingly connected. Mobile devices and embedded systems carry out many tasks supported by applications which are based on artificial intelligence algorithms with the aim of leading homes to be smarter. One of the purposes of these systems is to connect appliances to the power network, as well as to the internet to monitor consumption data among others. In addition, new interaction ways are emerging to manage all these systems. For example, conversational assistants which allow us to interact by voice with devices at home. In this work, we present GreenMoCA, a system to monitor energy consumption data from connected devices at home with the aim of improving sustainability aspects and reducing such energy consumption, supported by a conversational assistant. This system is able to interact with the user in a natural way, providing information of current energy use and feedback based on previous consumption measures in a Smart Home environment. Finally, we assessed GreenMoCA from a usability and user experience approach on a group of users with positive results.

The Contribution of Anthropogenic Energy Use to Urban Heat Island: Combining Energy Consumption Data with Satellite Observation of Land Surface Temperature

2020 ◽  
Author(s):  
Zhou Yu ◽  
Qi Li ◽  
Ting Sun ◽  
Leiqiu Hu
Keyword(s):  
Energy Consumption ◽  
Surface Temperature ◽  
Land Surface Temperature ◽  
Land Surface ◽  
Energy Use ◽  
Urban Climate ◽  
Building Energy ◽  
Consumption Data ◽  
Building Energy Use ◽  
Urban Heat

<p>Energy consumption, such as building energy use and traffic, is one of the key sources of anthropogenic heat flux in cities (Q<sub>F</sub>), which influences the urban climate. Different methods have been proposed to quantify Q<sub>F</sub>, such as using the inventory data and satellite observations of the land surface temperature. In this study, we develop an analysis framework based on urban surface energy balance and inverse calculation of the expected change of thermodynamic state as a result of different sources of energy consumption. This framework enables us to link the energy consumption data with remotely sensed land surface temperature (LST). Thus, the contribution of different sources of anthropogenic energy consumption to the urban land surface temperature can be readily quantified. We apply this method to ECOSTRESS LST, traffic volume and building energy consumption for cities in the US. We show that the exhaust heat from traffic and building energy use contributes differently to the surface urban heat island effect: the contributions differ in cities with different background climates, urban morphologies and green area fractions. Overall, the combined model-observation framework demonstrates potential in quantifying the impact of two major anthropogenic heating sources on urban climate, in particular with increasingly available high-quality urban energy-use data and fine-resolution satellite observations.  </p>

A Four-Parameter Change-Point Model for Predicting Energy Consumption in Commercial Buildings

1992 ◽  
Vol 114 (2) ◽  
pp. 77-83 ◽  
Author(s):  
David Ruch ◽  
David E. Claridge
Keyword(s):  
Energy Consumption ◽  
Change Point ◽  
Energy Use ◽  
Energy Savings ◽  
Grocery Store ◽  
Parameter Change ◽  
Point Model ◽  
Linear Change ◽  
Consumption Data ◽  
Change Point Model

This paper develops a four-parameter change-point model of energy consumption as a function of dry-bulb temperature, along with accompanying error diagnostics for the model’s parameters. The model is a generalization of the widely used three-parameter, or variable-base degree-day method. The model is applied to data from a case study grocery store, is compared to the three-parameter PRISM CO model of the store data, and is shown to provide a statistically better fit to consumption data below about 15°C. This model appears to be useful for diagnosing unexpected energy use in some buildings and should be useful for determining retrofit energy savings from monitored pre-retrofit and post-retrofit data for the class of buildings whose pre-retrofit consumption is fit by a four-parameter linear change-point model.

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.

scholarly journals The impacts of different façade types on energy use in residential buildings

2020 ◽  
Vol 172 ◽  
pp. 24010
Author(s):  
Serik Tokbolat ◽  
Yelaman Naizabekov ◽  
Stefano Mariani
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Residential Buildings ◽  
Simulation Software ◽  
Aluminum Composite ◽  
Climate Conditions ◽  
Inappropriate Use ◽  
Clay Bricks ◽  
Consumption Data ◽  
Fast Development

Globally, buildings are responsible for a significant share in energy consumption and greenhouse gas emissions profiles. Various attempts are undertaken to increase the energy efficiency of buildings and reduce their environmental impact. In semi-continental climate conditions with very hot summers and extremely cold winters, buildings should be carefully designed to ensure efficient harnessing of solar energy and reducing energy loss due to poor insulation and inappropriate use of materials. Amidst the fast development of the construction industry, different façade systems are used in Kazakhstan. In several cases, the choice of the façade materials is defined not by performance but rather by economic aspects and physical appearance. This project aimed to investigate various types of façades adopted in the construction of residential buildings and assess their performance in terms of their impact on buildings’ energy consumption. The preliminary results indicate that there are five main types of façades widely used. Five different models were therefore built using energy simulation software and the respective energy consumption data were estimated. The results testify that buildings with brickwork (clay bricks) and stonework (travertine) façades were more energy efficient than those with brickwork (silica bricks), aluminum composite panels and decorated plaster façades.

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