scholarly journals Residential End-Use Energy Estimation Models in Korean Apartment Units through Multiple Regression Analysis

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2327 ◽  
Author(s):  
Soo-Jin Lee ◽  
You-Jeong Kim ◽  
Hye-Sun Jin ◽  
Sung-Im Kim ◽  
Soo-Yeon Ha ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Energy Consumption ◽  
Survey Data ◽  
Field Survey ◽  
Maximum Error ◽  
Hot Water ◽  
Annual Data ◽  
Estimation Model ◽  
Energy Estimation ◽  
End Use

The aim of this study was to develop a mathematical regression model for predicting end-use energy consumption in the residential sector. To this end, housing characteristics were collected through a field survey and in-depth interviews with residents of 71 households (15 apartment complexes) in Seoul, South Korea, and annual data on end-use energy consumption were collected from measurement systems installed within each apartment unit. Based on the data collected, correlativity between the field-survey data and end-use energy consumption was analyzed, and effective independent variables from the field-survey data were selected. Regression models were developed and validated for estimating six end uses of energy consumption: heating, cooling, domestic hot water (DHW), lighting, electric appliances, and cooking. Regression analysis for ventilation was not applied, and instead a calculation formula was derived, because the energy-consumption proportion was too low. The adj-R2 of the estimation model ranged from 0.406 to 0.703, and the maximum error between measured and estimated values was around ±30%, depending on the end use.

scholarly journals Analysis of Annual Energy Use Intensities (EUIs) by End-Use in Apartment Units According to Stratification Variables (2017 – 2018)

2019 ◽  
Vol 111 ◽  
pp. 04013
Author(s):  
Hye-Sun Jin ◽  
Han-Young Lim ◽  
You-Jeong Kim ◽  
Soo-Jin Lee ◽  
Sung-Im Kim ◽  
...  
Keyword(s):  
Information System ◽  
Energy Consumption ◽  
Energy Conservation ◽  
Energy Use ◽  
Hot Water ◽  
Space Heating ◽  
Building Sector ◽  
Domestic Hot Water ◽  
Space Cooling ◽  
End Use

To achieve the goal of reducing greenhouses gases, many countries have recognized the importance of energy conservation in the building sector, and such countries are considerably strengthening their building energy conservation policies by reinforcing design standards, encouraging remodeling, and requiring zero-energy construction. In order to effectively strengthen these policies, it is necessary to provide information concerning energy consumption in the building sector to ensure the technical and economic feasibility of policies in the marketplace, and to allow building users and policy makers to easily access and understand energy consumption characteristics. It is important to provide information that allows people to effectively understand the state of energy consumption by end-use (space heating, space cooling, domestic hot water, etc.) as part of the creation of a concrete plan for energy reduction that incorporates various service systems and is familiar to people. This is because providing such information plays an important role in establishing concrete policies and encouraging voluntary energy performance improvements by building occupants. South Korea operates the Korea Energy Statistics Information System (KESIS) and the information provided by this type of information system consists mainly of energy consumption by energy source (electricity, gas, etc.), and such systems remain inadequate for providing effective information on energy consumption and energy use intensity (EUI) by end-use (space heating, space cooling, domestic hot water, etc.) as part of the creation of a concrete plan for energy conservation. In order to accurately provide energy consumption information by end-use rather than limit the information to mainly consumption corresponding to energy sources, in this study, measurement systems were installed in 2014 ~ 2016 based on the overall sampling designs of previous studies for apartment units, classifications, measurement and data gathering methods for energy consumption by end-use. The annual statistical values for EUI by end-use were collected from the measurement data for 71 sample apartment units from May 2017 to April 2018. This data was calculated and analyzed using stratification variable levels for completion year, supplied area, and the heat source type.

Trip Energy Estimation Methodology and Model Based on Real-World Driving Data for Green-Routing Applications

2018 ◽  
Vol 2672 (24) ◽  
pp. 41-48 ◽  
Author(s):  
Jacob Holden ◽  
Harrison Van Til ◽  
Eric Wood ◽  
Lei Zhu ◽  
Jeffrey Gonder ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Fuel Consumption ◽  
Real World ◽  
Energy Use ◽  
Average Energy ◽  
Estimation Model ◽  
Energy Estimation ◽  
Conventional Vehicle ◽  
Look Up Table ◽  
Wide Range

A data-informed model to predict energy use for a proposed vehicle trip has been developed in this paper. The methodology leverages roughly one million miles of real-world driving data to generate the estimation model. Driving is categorized at the sub-trip level by average speed, road gradient, and road network geometry, then aggregated by category. An average energy consumption rate is determined for each category, creating an energy rate look-up table. Proposed vehicle trips are then categorized in the same manner, and estimated energy rates are appended from the look-up table. The methodology is robust and applicable to a wide range of driving data. The model has been trained on vehicle travel profiles from the Transportation Secure Data Center at the National Renewable Energy Laboratory and validated against on-road fuel consumption data from testing in Phoenix, Arizona. When compared against the detailed on-road conventional vehicle fuel consumption test data, the energy estimation model accurately predicted which route would consume less fuel over a dozen different tests. When compared against a larger set of real-world origin–destination pairs, it is estimated that implementing the present methodology should accurately select the route that consumes the least fuel 90% of the time. The model results can be used to inform control strategies in routing tools, such as change in departure time, alternate routing, and alternate destinations to reduce energy consumption. This work provides a highly extensible framework that allows the model to be tuned to a specific driver or vehicle type.

Estimation of major stream delays with a limited priority merge

2013 ◽  
Vol 40 (12) ◽  
pp. 1227-1233 ◽  
Author(s):  
Dong-fang Ma ◽  
Xiao-long Ma ◽  
Sheng Jin ◽  
Feng Sun ◽  
Dian-hai Wang
Keyword(s):  
Probability Theory ◽  
Survey Data ◽  
Relative Error ◽  
Traffic Accidents ◽  
Field Survey ◽  
Major Road ◽  
Estimation Model ◽  
Recursive Models ◽  
Changchun City ◽  
Maximum Minimum

The purpose of this paper is to develop an estimation model for major stream delays at an unsignalized intersection under limited priority conditions. The key idea of this paper is that, when the minor stream drivers accept smaller major stream gaps, some drivers on the major road have to slow down their speeds and adjust their relative positions to avoid traffic accidents, incurring some delays. Assuming that headways in the major stream follow the M3 distribution, the delay for the first major stream vehicle after a limited priority merge is presented using acceptance gap theory and probability theory, and then recursive models are developed for the following major stream vehicles before the next merge. Finally, the precision of the method proposed in this paper is calibrated using field survey data from Changchun city, China, and the results show that the maximum, minimum, and average relative error of the 12 samples are approximately 30.38%, 9.04%, and 18.97%, respectively.

scholarly journals An Exhaustive Search Energy Optimization Method for Residential Building Envelope in Different Climatic Zones of Kazakhstan

Buildings ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. 633
Author(s):  
Mirzhan Kaderzhanov ◽  
Shazim Ali Memon ◽  
Assemgul Saurbayeva ◽  
Jong R. Kim
Keyword(s):  
Energy Consumption ◽  
Energy Savings ◽  
Residential Buildings ◽  
Average Energy ◽  
Optimization Method ◽  
Building Envelope ◽  
Energy Reduction ◽  
Estimation Model ◽  
Total Energy Consumption ◽  
Energy Estimation

Nowadays, the residential sector of Kazakhstan accounts for about 30% of the total energy consumption. Therefore, it is essential to analyze the energy estimation model for residential buildings in Kazakhstan so as to reduce energy consumption. This research is aimed to develop the Overall Thermal Transfer Value (OTTV) based Building Energy Simulation Model (BESM) for the reduction of energy consumption through the envelope of residential buildings in seven cities of Kazakhstan. A brute force optimization method was adopted to obtain the optimal envelope configuration varying window-to-wall ratio (WWR), the angle of a pitched roof, the depth of the overhang shading system, the thermal conductivity, and the thicknesses of wall composition materials. In addition, orientation-related analyses of the optimized cases were conducted. Finally, the economic evaluation of the base and optimized cases were presented. The results showed that an average energy reduction for heating was 6156.8 kWh, while for cooling it was almost 1912.17 kWh. The heating and cooling energy savings were 16.59% and 16.69%, respectively. The frontage of the building model directed towards the south in the cold season and north in the hot season demonstrated around 21% and 32% of energy reduction, respectively. The energy cost savings varied between 9657 to 119,221 ₸ for heating, 9622 to 36,088 ₸ for cooling.

scholarly journals Energy Consumption Estimation Model for Complete Coverage of a Tetromino Inspired Reconfigurable Surface Tiling Robot

Energies ◽  
2019 ◽  
Vol 12 (12) ◽  
pp. 2257 ◽  
Author(s):  
Arunmozhi Manimuthu ◽  
Anh Vu Le ◽  
Rajesh Elara Mohan ◽  
Prabahar Veerajagadeshwar ◽  
Nguyen Huu Khanh Nhan ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Energy Cost ◽  
Pulse Width Modulation ◽  
Real Life ◽  
Area Coverage ◽  
Estimation Model ◽  
Energy Estimation ◽  
Proposed Model ◽  
Estimation Scheme ◽  
Optimal Area

As autonomous tiling devices begin to perform floor cleaning, agriculture harvesting, surface painting tasks, with minimal or no human intervention, a new challenge arises: these devices also need to be energy efficient and be constantly aware of the energy expenditure during deployments. Typical approaches to this end are often limited to fixed morphology robots with little or no consideration for reconfiguring class of robots. The main contribution of the paper is an energy estimation scheme that allows estimating the energy consumption when a tetromino inspired reconfigurable floor tiling robot, hTetro moves from one configuration to another for completing the area covering task. To this end, the proposed model applying the Newton-Raphson algorithm in combination with Pulse width modulation (PWM)-H bridge to characterize the energy cost associated with locomotion gaits across all valid morphologies and identify optimal area coverage strategy among available options is presented. We validate our proposed approach using an 8’ × 8’ square testbed where there exist 12 possible solutions for complete area coverage however with varying levels of energy cost. Then, we implemented our approach to our hTetro platform and conducted experiments in a real-life environment. Experimental results demonstrate the application of our model in identifying the optimal area coverage strategy that has the least associated energy cost.

scholarly journals Field survey on energy consumption due to hot water supply and cooking in Nanjing and Hefei, China

2013 ◽  
Vol 2 (2) ◽  
pp. 134-146 ◽  
Author(s):  
Shuichi Hokoi ◽  
Daisuke Ogura ◽  
Xiuzhang Fu ◽  
Yong Rao
Keyword(s):  
Energy Consumption ◽  
Water Supply ◽  
Field Survey ◽  
Hot Water ◽  
Hot Water Supply

Development of the mathematical model for assessing the optimal measurement step when surveying the depth of the underground pipeline from the ground

2020 ◽  
Vol 10 (4) ◽  
pp. 364-371
Author(s):  
Ruslan V. Aginey ◽  
◽  
Rustem R. Islamov ◽  
Alexey A. Firstov ◽  
Elmira A. Mamedova ◽  
...  
Keyword(s):  
Mathematical Models ◽  
Survey Data ◽  
Ground Surface ◽  
Maximum Error ◽  
Large Error ◽  
Bending Stress ◽  
Buried Pipeline ◽  
Optimal Measurement ◽  
Pipeline Section ◽  
Bending Stresses

Existing methods for estimating the bending stresses of buried pipeline section based on the survey data for the depth of the axis of the pipeline from the ground surface are characterized by a large error between the real values of the bending stress and the values of the bending stress obtained from the calculation results based on the survey data. The purpose of this study is to improve the methodology for calculating the bending stresses of buried pipeline section based on the results of determining the depth of the axis of the pipeline from the ground surface, taking into account the design features of the pipeline and the used search equipment. Mathematical models are proposed that allow for the set value of the maximum error in determining bending stresses for a particular pipeline to choose the optimal measurement step before the survey, which will allow to reduce the error. Explanations are given on the choice of the maximum step of the study based on the strength characteristics of the pipeline. A calculation is provided that confirms the adequacy of the developed mathematical models and the possibility of their application in practice.

Sign in / Sign up

Export Citation Format

Share Document