scholarly journals Update of specific electric loads of public premises located in residential buildings

2021 ◽  
Vol 23 (3) ◽  
pp. 62-72
Author(s):  
Yu. I. Soluyanov ◽  
A. R. Akhmetshin ◽  
V. I. Soluyanov
Keyword(s):  
Energy Consumption ◽  
Residential Buildings ◽  
Electricity Consumption ◽  
Normative Values ◽  
Electrical Load ◽  
Smart Meters ◽  
Apartment Buildings ◽  
Constant Change ◽  
Electrical Loads ◽  
Electric Loads

THE PURPOSE. To determine the composition of electricity consumers in apartment buildings. To analyze the power consumption of organizations located on the first two floors of apartment buildings. To justify the need to update the standards for electrical loads for public premises built into residential buildings. METHODS. Information on electricity consumption was received by automated electricity metering system from smart meters installed directly at consumers. To achieve this goal, statistical methods for analyzing energy consumption were used. RESULTS. The article describes the relevance of the topic, provides a rationale for adjusting the normative values of specific electrical loads for public premises built into residential buildings. The percentage of consumer groups is shown on the example of several apartment buildings. The annual specific average monthly graphs of electricity consumption are presented: shops, offices, pharmacies, restaurants. CONCLUSION. In an effort to increase the level of comfort, developers are interested in developing the infrastructure of the facilities, mainly for this, they use ground and first floors, in which retail and office areas are most often located. Research by the Roselectromontazh Association has shown that to determine the electrical load of non-residential commercial premises, one has to use one averaged value due to the constant change in the purpose of premises and the complexity of determining the occupied area.

scholarly journals Update of specific electric loads of public premises located in residential buildings

2021 ◽  
Vol 23 (3) ◽  
pp. 47-57
Author(s):  
Yu. I. Soluyanov ◽  
A. R. Akhmetshin ◽  
V. I. Soluyanov
Keyword(s):  
Energy Consumption ◽  
Residential Buildings ◽  
Electricity Consumption ◽  
Normative Values ◽  
Electrical Load ◽  
Smart Meters ◽  
Apartment Buildings ◽  
Constant Change ◽  
Electrical Loads ◽  
Electric Loads

THE PURPOSE. To determine the composition of electricity consumers in apartment buildings. To analyze the power consumption of organizations located on the first two floors of apartment buildings. To justify the need to update the standards for electrical loads for public premises built into residential buildings. METHODS. Information on electricity consumption was received by automated electricity metering system from smart meters installed directly at consumers. To achieve this goal, statistical methods for analyzing energy consumption were used. RESULTS. The article describes the relevance of the topic, provides a rationale for adjusting the normative values of specific electrical loads for public premises built into residential buildings. The percentage of consumer groups is shown on the example of several apartment buildings. The annual specific average monthly graphs of electricity consumption are presented: shops, offices, pharmacies, restaurants. CONCLUSION. In an effort to increase the level of comfort, developers are interested in developing the infrastructure of the facilities, mainly for this, they use ground and first floors, in which retail and office areas are most often located. Research by the Roselectromontazh Association has shown that to determine the electrical load of non-residential commercial premises, one has to use one averaged value due to the constant change in the purpose of premises and the complexity of determining the occupied area.

scholarly journals The influence of design features of housing facilities on energy consumption

2020 ◽  
Vol 175 ◽  
pp. 11019
Author(s):  
Sergei Kolodyazhniy ◽  
Valeriy Mishchenko ◽  
Elena Gorbaneva ◽  
Kristina Sevryukova
Keyword(s):  
Energy Consumption ◽  
Residential Buildings ◽  
Structural Characteristics ◽  
Electricity Consumption ◽  
End User ◽  
Total Energy Consumption ◽  
Apartment Buildings ◽  
Energy Models ◽  
Actual Energy Consumption ◽  
The Impact

This article analyzed the impact of the structural characteristics of old apartment buildings on actual energy consumption. The authors reviewed energy consumption in existing apartment buildings in Voronezh in order to determine the need for major repairs and energy efficiency. For this purpose, a comparative analysis of energy consumption in old apartment buildings and in new ones built in accordance with the current regulations was carried out. Three indicators of energy consumption were considered for analysis: total energy consumption by the end-user, heating of premises and electricity consumption depending on the year of construction of apartment buildings. The characteristics considered were used to quantify energy consumption (heating and power supply). Due to the results obtained, a statistical analysis of energy consumption in old apartment buildings and in new ones was carried out. It was noted that old apartment buildings consume more energy than those built at a late stage, in accordance with the current regulatory framework. The results can be useful in identifying priority elements of the building that will help to effectively reduce energy consumption during major repairs and classify existing residential buildings to build energy models.

scholarly journals Investigating Primary Factors Affecting Electricity Consumption in Non-Residential Buildings Using a Data-Driven Approach

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4046 ◽  
Author(s):  
Sooyoun Cho ◽  
Jeehang Lee ◽  
Jumi Baek ◽  
Gi-Seok Kim ◽  
Seung-Bok Leigh
Keyword(s):  
Energy Consumption ◽  
Energy Use ◽  
Simulation Analysis ◽  
Residential Buildings ◽  
Electric Energy ◽  
Electricity Consumption ◽  
Building Energy ◽  
Major Effect ◽  
Measuring Instruments ◽  
Building Energy Consumption

Although the latest energy-efficient buildings use a large number of sensors and measuring instruments to predict consumption more accurately, it is generally not possible to identify which data are the most valuable or key for analysis among the tens of thousands of data points. This study selected the electric energy as a subset of total building energy consumption because it accounts for more than 65% of the total building energy consumption, and identified the variables that contribute to electric energy use. However, this study aimed to confirm data from a building using clustering in machine learning, instead of a calculation method from engineering simulation, to examine the variables that were identified and determine whether these variables had a strong correlation with energy consumption. Three different methods confirmed that the major variables related to electric energy consumption were significant. This research has significance because it was able to identify the factors in electric energy, accounting for more than half of the total building energy consumption, that had a major effect on energy consumption and revealed that these key variables alone, not the default values of many different items in simulation analysis, can ensure the reliable prediction of energy consumption.

scholarly journals Analyzing Load Profiles of Energy Consumption to Infer Household Characteristics Using Smart Meters

Energies ◽  
2019 ◽  
Vol 12 (5) ◽  
pp. 773 ◽  
Author(s):  
Muhammad Fahim ◽  
Alberto Sillitti
Keyword(s):  
Energy Consumption ◽  
Time Series Data ◽  
Residential Buildings ◽  
Series Data ◽  
Smart Meters ◽  
Learning Mechanism ◽  
Efficient Energy ◽  
Household Characteristics ◽  
Univariate Time Series ◽  
Consumption Data

The increasing penetration of smart meters provides an excellent opportunity to monitor and analyze energy consumption in residential buildings. In this paper, we propose a framework to process the observed profiles of energy consumption to infer the household characteristics in residential buildings. Such characteristics can be used for improving resource allocation and for an efficient energy management that will ultimately contribute to reducing carbon dioxide (CO 2 ) emission. Our approach is based on automated extraction of features from univariate time-series data and development of a model through a variant of the decision trees technique (i.e., ensemble learning mechanism) random forest. We process and analyzed energy consumption data to answer four primitive questions. To evaluate the approach, we performed experiments on publicly available datasets. Our experiments show a precision of 82% and a recall of 81% in inferring household characteristics.

scholarly journals An exploration of load-shifting potential in real in-situ heat-pump/gas-boiler hybrid systems

2017 ◽  
Vol 38 (4) ◽  
pp. 450-460 ◽  
Author(s):  
Anne Stafford
Keyword(s):  
Energy Consumption ◽  
Heat Pump ◽  
Significant Proportion ◽  
Electricity Consumption ◽  
Operating Conditions ◽  
Heat Output ◽  
Electrical Load ◽  
Additional Energy ◽  
Operational Conditions ◽  
Smart Systems

Monitoring data from two hybrid air-source heat-pump/gas-boiler systems were used to explore the systems’ potential for energy flexibility, i.e. the potential for shifting electrical load in response to grid requirements while maintaining acceptable performance in the overall hybrid system. In both cases, a significant proportion of the heat-pump load could potentially be shifted to the gas boiler with only a modest increase in the overall energy consumption, provided certain operational conditions were met. Furthermore, under these operational conditions, it is possible to estimate this additional energy consumption for a given system from simple heat output, and gas and electricity consumption data. This provides a potential basis for groups of similar systems equipped with smart technology to offer flexibility to the grid, while minimising the resulting energy penalty by choosing to use the most appropriate systems at any given time with respect to their operating conditions at that time. In addition, this type of flexibility means that the thermal comfort within the dwelling remains unaffected since overall heating requirement is met at all times by one of the two heating sub-systems. Practical application: The ability to shift or shed electrical load in response to grid requirements is likely to become a significant, commercially incentivised aspect of building energy systems in the future, to mitigate the stress on electrical grids at times of peak consumption. For domestic systems, aggregation will be a key factor, requiring ‘smart’ systems to provide real-time information to potential aggregators or grid operators. This article explores what type of system information may be necessary in the case of hybrid heat-pump/gas-boiler systems if loads are to be shifted from the heat-pump to the gas-boiler element, while minimising the resulting energy penalties.

SOME ASPECTS OF ENERGY EFFICIENCY IN HOUSING CONSTRUCTION IN RUSSIA

2020 ◽  
Vol 13 (2) ◽  
pp. 90-96
Author(s):  
E.V. Nezhnikova ◽  
◽  
M.V Chernyaev ◽  
Keyword(s):  
Energy Efficiency ◽  
Energy Consumption ◽  
Real Estate ◽  
Energy Efficient ◽  
Residential Buildings ◽  
Electricity Consumption ◽  
Electrical Energy ◽  
Housing Construction ◽  
Residential Real Estate ◽  
Domestic Legislation

The article presents the problems of ensuring energy efficiency of housing construction in the Russian Federation. Unfortunately, for a variety of reasons and, despite the existence of federal and regional legislation, today Russia does not pay due attention to this issue, which leads to an unreasonable increase in electricity consumption both during the creation of residential real estate objects and during their operation. 96 Экономические системы. 2020. № 2 Economic Systems. 2020. No. 2 The relevance of the topic is enhanced by significant energy consumption of residential buildings in use: more than 50% of electrical energy consumption falls on these real estate objects. Therefore, it is no coincidence, but a completely logical trend of the 21st century, that the governments of most countries popularized the idea of designing and building energy-efficient residential buildings. It was established that the improvement of domestic legislation in terms of energy efficiency has greatly improved the regulatory framework for the design and construction of energy-efficient residential real estate.

scholarly journals Prediction of Future Electric Energy Consumption using Machine Learning Framework

2020 ◽  
Vol 9 (3) ◽  
pp. 3347-3350
Keyword(s):  
Machine Learning ◽  
Energy Consumption ◽  
Prediction Models ◽  
Electric Energy ◽  
Power Saving ◽  
Electricity Consumption ◽  
Energy System ◽  
Energy Utilization ◽  
Smart Meters ◽  
Learning Framework

In the last few years, the expanding energy utilization has imposed the formation of solutions for saving electricity. Of many solutions, one is generating a power saving policies which is defined as prediction of energy in smart environments. This model is built, based on the idea that the building residences are provided with smart meters to monitor energy consumption and can be managed accordingly. Recent prediction models focuses on performance of the prediction, but for developing a reliable energy system, it is required to predict the demand taking into account different scenarios. In this paper we propose a model for predicting future demand for energy according to different conditions using advanced machine learning framework. In this system we have a projector that builds proper state for a particular condition and using that defined state a future power demand is forecasted by the predictor. The proposed model generates utilization predictions for every 2 hours. Demonstrating the electricity consumption data for 5 years, the proposed system achieves a better performance.

scholarly journals Top Energy Saver of the Year: Results of an Energy Saving Competition in Public Buildings

2020 ◽  
Vol 24 (3) ◽  
pp. 278-293
Author(s):  
Jan Kaselofsky ◽  
Ralf Schüle ◽  
Marika Rošā ◽  
Toms Prodaņuks ◽  
Anda Jekabsone ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Saving ◽  
Energy Use ◽  
Residential Buildings ◽  
Electricity Consumption ◽  
Energy Performance ◽  
Heat Consumption ◽  
The European Union ◽  
Public Building ◽  
Team Members

AbstractNon-residential buildings in the European Union consume more than one third of the building sector’s total. Many non-residential buildings are owned by municipalities. This paper reports about an energy saving competition that was carried out in 91 municipal buildings in eight EU member states in 2019. For each public building an energy team was formed. The energy teams’ activities encompassed motivating changes in the energy use behaviour of employees and small investments. Two challenges added an element of gamification to the energy saving competition. To assess the success of the energy saving competition, an energy performance baseline was calculated using energy consumption data of each public building from previous years. Energy consumption in the competition year was monitored on a monthly base. After the competition the top energy savers from each country were determined by the percentage-based reduction of energy consumption compared to the baseline. On average, the buildings had an electricity and heat consumption in 2019 that was about 8 % and 7 %, respectively, lower than the baseline. As an additional data source for the evaluation, a survey among energy team members was conducted at the beginning and after the energy competition. Support from superiors, employee interest and motivation and behaviour change as assessed by energy team members show a positive, if weak or moderate, correlation with changes in electricity consumption, but not with changes in heat consumption.

scholarly journals Watt’s up at Home? Smart Meter Data Analytics from a Consumer-Centric Perspective

Energies ◽  
2021 ◽  
Vol 14 (3) ◽  
pp. 719
Author(s):  
Benjamin Völker ◽  
Andreas Reinhardt ◽  
Anthony Faustine ◽  
Lucas Pereira
Keyword(s):  
Energy Consumption ◽  
Data Processing ◽  
Electricity Consumption ◽  
Data Communication ◽  
Electrical Energy ◽  
Use Cases ◽  
Smart Meter ◽  
Smart Meters ◽  
Electricity Theft ◽  
Generation Scheduling

The key advantage of smart meters over traditional metering devices is their ability to transfer consumption information to remote data processing systems. Besides enabling the automated collection of a customer’s electricity consumption for billing purposes, the data collected by these devices makes the realization of many novel use cases possible. However, the large majority of such services are tailored to improve the power grid’s operation as a whole. For example, forecasts of household energy consumption or photovoltaic production allow for improved power plant generation scheduling. Similarly, the detection of anomalous consumption patterns can indicate electricity theft and serve as a trigger for corresponding investigations. Even though customers can directly influence their electrical energy consumption, the range of use cases to the users’ benefit remains much smaller than those that benefit the grid in general. In this work, we thus review the range of services tailored to the needs of end-customers. By briefly discussing their technological foundations and their potential impact on future developments, we highlight the great potentials of utilizing smart meter data from a user-centric perspective. Several open research challenges in this domain, arising from the shortcomings of state-of-the-art data communication and processing methods, are furthermore given. We expect their investigation to lead to significant advancements in data processing services and ultimately raise the customer experience of operating smart meters.

scholarly journals Modeling Residential Energy Consumption

2021 ◽  
Vol 29 (2) ◽  
pp. 166-193
Author(s):  
Roya Gholami ◽  
Rohit Nishant ◽  
Ali Emrouznejad
Keyword(s):  
Energy Consumption ◽  
Service Providers ◽  
Electricity Consumption ◽  
Residential Energy ◽  
Residential Energy Consumption ◽  
Smart Meters ◽  
Household Energy ◽  
Consumption Behavior ◽  
Data Mining Approach ◽  
Residential Characteristics

Smart meters that allow information to flow between users and utility service providers are expected to foster intelligent energy consumption. Previous studies focusing on demand-side management have been predominantly restricted to factors that utilities can manage and manipulate, but have ignored factors specific to residential characteristics. They also often presume that households consume similar amounts of energy and electricity. To fill these gaps in literature, the authors investigate two research questions: (RQ1) Does a data mining approach outperform traditional statistical approaches for modelling residential energy consumption? (RQ2) What factors influence household energy consumption? They identify household clusters to explore the underlying factors central to understanding electricity consumption behavior. Different clusters carry specific contextual nuances needed for fully understanding consumption behavior. The findings indicate electricity can be distributed according to the needs of six distinct clusters and that utilities can use analytics to identify load profiles for greater energy efficiency.

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