• International conference on construction engineering and project management
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• 2022.06a
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• pp.401-407
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• 2022

Central heating, ventilation and air conditioning (HVAC) is one of the largest consumers of energy in the residential sector. This project explores the use of multiple HVAC units and/or Zoning in a single residence to reduce energy loads. The energy consumption data of a detached single-family home using two HVAC units, one primary for the main house and a secondary HVAC for a casita, was collected for the same month for two consecutive years, along with details related to the outdoor temperature and the square footage being air-conditioned by each HVAC. A regression algorithm was trained using the above details to find the relation between the parameters. Next, based on the occupancy and usage patterns, the HVAC was redesigned assuming more area under the secondary HVAC unit. The trained algorithm was then used to make energy usage predictions for the revised primary HVAC area, with the assumption that the secondary HVAC unit was turned off. The results were compared with existing energy usage data. It was determined that there were significant energy savings in the second scenario. It is expected that this study and its findings will help future research projects explore more ideas as alternatives to central HVAC, in improving the economic viability of existing options, and in developing a savings calculation tool that will help consumers make informed decisions on their best alternatives to central HVAC.

• Asian Journal of Business Environment
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• v.4 no.2
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• pp.17-21
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• 2014

Purpose - The paper analyzes basic indicators characterizing the volume of energy sector activity in the Russian Federation, Privolzhsky Federal district, Republic of Tatarstan. Research design, data, and methodology - The study analyzed data from the Privolzhsky Federal district, specifically, industrial production volume, electricity production, energy consumption, energy-balance data, capital investments, and capital investment structure. An array of data has been investigated in recent years. The dataset's dynamics were analyzed in 1998. Fixed capital investment dynamics were studied in 1946 the figures were converted to a comparable form using the index method. Trends were analyzed using multivariate statistics methods and the Statgraphics software package. Results - Hypothesis 1. There are sectoral disproportions in energy flows,taking into account the volume of electricity production and consumption. Trends in electricity production in general coincide with industrial production volume trends. Energy flows have disparities in individual territorial units, and in general. Hypothesis 2. The degree of sectoral economic stability decreases with insufficient levels of investment in fixed capital energy organizations. Conclusions - Because totalelectricity production is largely determined by fixed capital investments, the study of their trends and patterns will coordinate efforts on investment operations in this area.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.41 no.1
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• pp.84-93
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• 2018

In this paper, we propose an Elman recurrent neural network to predict and analyze a time series of power energy consumption. To this end, we consider the volatility of the time series and apply the sample variance and the detrended fluctuation analyses to the volatilities. We demonstrate that there exists a correlation in the time series of the volatilities, which suggests that the power consumption time series contain a non-negligible amount of the non-linear correlation. Based on this finding, we adopt the Elman recurrent neural network as the model for the prediction of the power consumption. As the simplest form of the recurrent network, the Elman network is designed to learn sequential or time-varying pattern and could predict learned series of values. The Elman network has a layer of "context units" in addition to a standard feedforward network. By adjusting two parameters in the model and performing the cross validation, we demonstrated that the proposed model predicts the power consumption with the relative errors and the average errors in the range of 2%~5% and 3kWh~8kWh, respectively. To further confirm the experimental results, we performed two types of the cross validations designed for the time series data. We also support the validity of the model by analyzing the multi-step forecasting. We found that the prediction errors tend to be saturated although they increase as the prediction time step increases. The results of this study can be used to the energy management system in terms of the effective control of the cross usage of the electric and the gas energies.

• KIEAE Journal
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• v.17 no.3
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• pp.75-81
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• 2017

Purpose: The energy consumption of apartment units is affected by the lifestyle of the residents rather than system technology. In this study the numerical analysis of assumed energy consumption correlation factors with arbitrary value due to uncertainty. It is intended to be used as a simulation correction value which can be utilized as a predicted value of actual energy usage. The correction value of the simulation is set in the developed form of the existing process that derives the actual usage amount. The simulation results used in the existing evaluation system are used to maintain the useful value as the current system evaluation scale and predict the actual capacity. Method: The method of the study is to statistically analyze the data frames of all complexes capable of collecting the annual energy usage and to reconstruct the population by adding the variables that are expected to be correlated. Repeat the data frame configuration with variables that are assumed to be highly correlated with energy use levels. Determine whether there is correlation or not. The intensity of the external characteristics of the building equipment related to the energy consumption is presented as the quantitative value. Result: The correlation between electricity consumption and trading price since 2010 is analyzed as (Correlation coefficient 0.82). These results are higher than (Correlation coefficient 0.79), which is the correlation between residential area and trading price. This paper signifies the starting point of the methodology that broadens the field of view of verification of simulation feasibility limited to the prediction technique focused on the simulation tool and the element technology scope.The diversified phenomenon reproduction method develops the existing energy simulation method.It can be completed with a simulation methodology that can infer actual energy consumption.

• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.161-166
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• 2009

Condensing gas boiler units may make a big role for the reduction of energy consumption in heating industries. In order to decrease the energy consumption of a boiler unit, the effective operation is necessary. In this study, the supply water temperature algorithm of a condensing gas boiler was developed. This includes the setpoint algorithm and the control algorithm of the supply water temperature. The setpoint algorithm was developed by the fuzzy logic and the control algorithm was developed by the proportional integral algorithm. In order to analyse the performance of the supply water temperature algorithm, the dynamic model of a condensing gas boiler system was used. Simulation results showed that the supply water temperature algorithm developed for this study may be practically applied for the control of the condensing gas boiler.

• Proceedings of the SAREK Conference
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• 2007.11a
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• pp.34-39
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• 2007

Condensing gas boiler units may make a big role for the reduction of energy consumption in heating industries. In order to decrease the energy consumption of a condensing gas boiler unit, the effective operations and controls of the system are necessary. In this study, mathematical models of a condensing gas boiler system were developed and programmed in order to predict dynamic behaviors of the system. These include dynamic models for a blower, a gas valve, a pump, a burner, a boiler heat exchanger, and a hot water heat exchanger. Control algorithms for the control of a gas valve, a blower, and a pump were also assumed. Simulation results showed good predictions of the dynamic phenomena of a boiler system. Therefore, the simulation program developed for this study may be effectively used for the development of control algorithms of the boiler system.

• Proceedings of the SAREK Conference
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• 2008.11a
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• pp.399-404
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• 2008

Condensing gas boiler units may make a big role for the reduction of energy consumption in heating industries. In order to decrease the energy consumption of a condensing gas boiler unit, the effective control of the system is necessary. In this study, control algorithms of a condensing gas boiler were developed. Control algorithms are composed of the setpoint algorithm and the control algorithm. The setpoint algorithm consists of the supply water temperature setpoint algorithm and the pump setpoint algorithm. The control algorithm consists of the gas valve control algorithm and the blower control algorithm. In order to analyse the performance of control algorithms, dynamic models of a condensing gas boiler system were used. Simulation results showed that control algorithms developed for this study may be practically applied to the condensing gas boiler.

• Journal of the Korean Dietetic Association
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• v.14 no.4
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• pp.396-403
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• 2008

We attempted to determine whether energy density would influence calorie intake via cognitive cues, as reflected by satiety. This experiment was designed using two different energy density levels of Kimbab: normal Kimbab (1.6 kcal/g) vs low-density Kimbab (1.0 kcal/g). 26 female college students participated in this study. The subjects ate Kimbab in the lab once a week for 2 weeks. Each week at noon, they were served 24 units of either normal or low-density Kimbab, and we determined the units, grams, and calories of the real & cognitive intake of Kimbab, and also analyzed the satiety rate after eating Kimbab. Our results demonstrated that the real calorie intake from the low-density Kimbab was significantly lower than that of the normal Kimbab (290.3 kcal vs 474.4 kcal, p<0.001), but we noted no significant differences in the units and grams of real and cognitive intake between the normal and low-density Kimbab. However, despite consuming 39% lower caloric intake, the subjects reported similar levels of satiety rates with the two different density levels of Kimbab, as they did not perceive themselves to have eaten more normal Kimbab than low-density Kimbab. Thus, this study provides evidence that the energy density of food is a crucial determinant of caloric intake, and supports the notion that the consumption of low energy-dense foods may result in a reduction of caloric intake without altering satiety.

• Advances in Automotive Engineering
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• v.1 no.1
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• pp.79-104
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• 2018

A detailed literature review is presented for the applications of the heat pump technologies on the electric vehicles Heating, Ventilation and Air Conditioning (HVAC) system. Due to legal regulations, automotive manufacturers have to produce more efficient and low carbon emission vehicles. Electric vehicles can be provided these requirements but the battery technologies and energy managements systems are still developing considering battery life and vehicle range. On the other hand, energy consumption for HVAC units has an important role on the energy management of these vehicles. Moreover, the energy requirement of HVAC processes for different environmental conditions are significantly affect the total energy consumption of these vehicles. For the heating process, the coolant of internal combustion (IC) engine can be utilized but in electric vehicles, we have not got any adequate waste heat source for this process. The heat pump technology is one of the alternative choices for the industry due to having high coefficient of performance (COP), but these systems have some disadvantages which can be improved with the other technologies. In this study, a literature review is performed considering alternative refrigerants, performance characteristics of different heat pump systems for electric vehicles and thermal management systems of electric vehicles.

• Journal of Information Processing Systems
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• v.11 no.1
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• pp.116-124
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• 2015

Smart grids propose new solutions for electricity consumers as a means to help them use energy in an efficient way. In this paper, we consider the demand-side management issue that exists for a group of consumers (houses) that are equipped with renewable energy (wind turbines) and storage units (battery), and we try to find the optimal scheduling for their home appliances, in order to reduce their electricity bills. Our simulation results prove the effectiveness of our approach, as they show a significant reduction in electricity costs when using renewable energy and battery storage.