Search results for: energy consumption forecasting

Authors: Funda Kul, İsmail Gür

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Pension scheme providers have to price mortality risk by accurate mortality forecasting method. There are many mortality-forecasting methods constructed and used in literature. The Lee-Carter model is the first model to consider stochastic improvement trends in life expectancy. It is still precisely used. Mortality forecasting is done by mortality index in the Lee-Carter model. It is assumed that mortality index fits ARIMA time series model. In this paper, we propose and use dynamic normal inverse gaussian distribution to modeling mortality indes in the Lee-Carter model. Using population mortality data for Italy, France, and Turkey, the model is forecasting capability is investigated, and a comparative analysis with other models is ensured by some well-known benchmarking criterions.

Keywords: mortality, forecasting, lee-carter model, normal inverse gaussian distribution

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Authors: Aleksandr A. Gajour, Vladimir G. Merzlikin, Vladimir I. Veselov

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This paper refers to the analysis of the characteristics of industrial and lifestyle facilities heat- energy objects as a part of the thermal envelope of Earth's surface for inclusion in any database of economic forecasting. The idealized model of the Earth's surface is discussed. This model gives the opportunity to obtain the energy equivalent for each element of terrain and world ocean. Energy efficiency criterion of comfortable human existence is introduced. Dynamics of changes of this criterion offers the possibility to simulate the possible technogenic catastrophes with the spontaneous industrial development of the certain Earth areas. Calculated model with the confirmed forecast of the Gulf Stream freezing in the polar regions in 2011 due to the heat-energy balance disturbance for the oceanic subsurface oil polluted layer is given. Two opposing trends of human development under limited and unlimited amount of heat-energy resources are analyzed.

Keywords: Earth's surface, heat-energy consumption, energy criteria, technogenic catastrophes

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Authors: Yuichi Miyamoto

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In regards to the energy sector in the modern period, two points were raised. First is a vast and growing energy demand, and second is an environmental impact associated with it. The enormous consumption of fossil fuel to the mobile unit is leading to its rapid depletion. Nuclear power is not the only problem. A modal shift that utilizes personal transporters and independent power, in order to realize a sustainable society, is very effective. The paper proposes that the world will continue to work on this. Energy of the future society, innovation in battery technology and the use of natural energy is a big key. And it is also necessary in order to save on energy consumption.

Keywords: natural energy, modal shift, personal transportation, battery

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Authors: Rojin Bana Derakhshan, Abbas Toloie

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For the purpose of optimizing and developing energy efficiency in building, it is required to recognize key elements of success in optimization of energy consumption before performing any actions. Surveying Principal Components is one of the most valuable result of Linear Algebra because the simple and non-parametric methods are become confusing. So that energy management system implemented according to energy management system international standard ISO50001:2011 and all energy parameters in building to be measured through performing energy auditing. In this essay by simulating used of data mining, the key impressive elements on energy saving in buildings to be determined. This approach is based on data mining statistical techniques using feature selection method and fuzzy logic and convert data from massive to compressed type and used to increase the selected feature. On the other side, influence portion and amount of each energy consumption elements in energy dissipation in percent are recognized as separated norm while using obtained results from energy auditing and after measurement of all energy consuming parameters and identified variables. Accordingly, energy saving solution divided into 3 categories, low, medium and high expense solutions.

Keywords: energy saving, key elements of success, optimization of energy consumption, data mining

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Authors: Wasihun Girma Hailemariam

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Energy is one of the key elements required for every agricultural activity, especially for large scale agricultural production such as sugarcane cultivation which mostly is used to produce sugar and bioethanol from sugarcane. In such kinds of resource (energy) intensive activities, energy analysis of the production system and looking for other alternatives which can reduce energy inputs of the sugarcane production process are steps forward for resource management. The purpose of this study was to determine input energy (direct and indirect) per hectare of sugarcane production sector of Metehara sugar factory in Ethiopia. Total energy consumption of the production system was 61,642 MJ/ha-yr. This total input energy is a cumulative value of different inputs (direct and indirect inputs) in the production system. The contribution of these different inputs is discussed and a scenario of substituting the most influential input by other alternative input which can replace the original input in its nutrient content was discussed. In this study the most influential input for increased energy consumption was application of organic fertilizer which accounted for 50 % of the total energy consumption. Filter cake which is a residue from the sugar production in the factory was used to substitute the organic fertilizer and the reduction in the energy consumption of the sugarcane production was discussed

Keywords: energy analysis, organic fertilizer, resource management, sugarcane

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Authors: Gul Nihal Gugul, Merih Aydinalp-Koksal

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In this study, hourly energy consumption model of a single detached house in Ankara, Turkey is developed using ESP-r building energy simulation software. Natural gas is used for space heating, cooking, and domestic water heating in this two story 4500 square feet four-bedroom home. Hourly electricity consumption of the home is monitored by an automated meter reading system, and daily natural gas consumption is recorded by the owners during 2013. Climate data of the region and building envelope data are used to develop the model. The heating energy consumption of the house that is estimated by the ESP-r model is then compared with the actual heating demand to determine the performance of the model. Scenarios are applied to the model to determine the amount of reduction in the total energy consumption of the house. The scenarios are using photovoltaic panels to generate electricity, ground source heat pumps for space heating and solar panels for domestic hot water generation. Alternative scenarios such as improving wall and roof insulations and window glazing are also applied. These scenarios are evaluated based on annual energy, associated CO2 emissions, and fuel expenditure savings. The pay-back periods for each scenario are also calculated to determine best alternative energy source or technology option for this home to reduce annual energy use and CO2 emission.

Keywords: ESP-r, building energy simulation, residential energy saving, CO2 reduction

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Authors: Alfred Quarcoo

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The main purpose of this paper is to examine the causal relationship between energy consumption and economic growth in Sub-Saharan Africa using panel data techniques. An annual data on energy consumption and Economic Growth (proxied by real gross domestic product per capita) spanning from 1990 to 2016 from the World bank index database was used. The results of the Augmented Dickey–Fuller unit root test shows that the series for all countries are not stationary at levels. However, the log of economic growth in Benin and Congo become stationary after taking the differences of the data, and log of energy consumption become stationary for all countries and Log of economic growth in Kenya and Zimbabwe were found to be stationary after taking the second differences of the panel series. The findings of the Johansen cointegration test demonstrate that the variables Log of Energy Consumption and Log of economic growth are not co-integrated for the cases of Kenya and Zimbabwe, so no long-run relationship between the variables were established in any country. The Granger causality test indicates that there is a unidirectional causality running from energy use to economic growth in Kenya and no causal linkage between Energy consumption and economic growth in Benin, Congo and Zimbabwe.

Keywords: Cointegration, Granger Causality, Sub-Sahara Africa, World Bank Development Indicators

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Authors: Marziyeh Bahrami, Hamed Pahlevan Hsseini, Behnam Ghamami, Arman Alvanpour, Hamed Ezzati, Amir Salar Sadeghi

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One of the ways to increase the efficiency of services in the system of agents and, of course, in the world of cloud computing, is to use virtualization techniques. The aim of this research is to create changes in cloud computing services that will reduce as much as possible the energy consumption related to the migration of virtual machines and, in some way, the energy related to the allocation of resources and reduce the amount of pollution. So far, several methods have been proposed to increase the efficiency of cloud computing services in order to save energy in the cloud environment. The method presented in this article tries to prevent energy consumption by data centers and the subsequent production of carbon and biological pollutants as much as possible by increasing the efficiency of cloud computing services. The results show that the proposed algorithm, using the improvement in virtualization techniques and with the help of a genetic algorithm, improves the efficiency of cloud services in the matter of migrating virtual machines and finally saves consumption. becomes energy.

Keywords: consumption reduction, cloud computing, genetic algorithm, live migration, virtual Machine

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Authors: Okezie A. Ihugba

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The bounds testing ARDL (2, 2, 2, 2, 0) technique to cointegration was used in this study to investigate the effect of energy consumption and energy loss on Nigeria's manufacturing sector from 1981 to 2020. The model was created to determine the relationship between these three variables while also accounting for interactions with control variables such as inflation and commercial bank loans to the manufacturing sector. When the dependent variables are energy consumption and energy loss, the bounds tests show that the variables of interest are bound together in the long run. Because electricity consumption is a critical factor in determining manufacturing value-added in Nigeria, some intriguing observations were made. According to the findings, the relationship between LELC and LMVA is statistically significant. According to the findings, electricity consumption reduces manufacturing value-added. The target variable (energy loss) is statistically significant and has a positive sign. In Nigeria, a 1% reduction in energy loss increases manufacturing value-added by 36% in the first lag and 35% in the second. According to the study, the government should speed up the ongoing renovation of existing power plants across the country, as well as the construction of new gas-fired power plants. This will address a number of issues, including overpricing of electricity as a result of grid failure.

Keywords: L60, Q43, H81, C52, E31, ARDL, cointegration, Nigeria's manufacturing

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Authors: A. A. Azemati, H. Hosseini, B. Shirkavand Hadavand

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By using an adequate thermal barrier coating in buildings the energy saving will be happened. In this study, a range of wall paints with different absorption coefficient in different climates has been investigated. In order to study these effects, heating and cooling loads of a common building with different ordinary paints and paint with mineral coating have been calculated. The effect of building paint in different climatic condition was studied and comparison was done between ordinary paints and paint with mineral insulators in temperate climate to obtain optimized energy consumption. The results have been shown that coatings with inorganic micro particles as insulation reduce the energy consumption of buildings around 14%.

Keywords: climate, energy consumption, inorganic, mineral coating

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Authors: M. Feliciano, F. Rodrigues, A. Gonçalves, J. M. R. C. A. Santos, V. Leite

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With the objective of characterizing the profile and performance of energy use by slaughterhouses, surveys and audits were performed in two different facilities located in the northeastern region of Portugal. Energy consumption from multiple energy sources was assessed monthly, along with production and costs, for the same reference year. Gathered data was analyzed to identify and quantify the main consuming processes and to estimate energy efficiency indicators for benchmarking purposes. Main results show differences between the two slaughterhouses concerning energy sources, consumption by source and sector, and global energy efficiency. Electricity is the most used source in both slaughterhouses with a contribution of around 50%, being essentially used for meat processing and refrigeration. Natural gas, in slaughterhouse A, and pellets, in slaughterhouse B, used for heating water take the second place, with a mean contribution of about 45%. On average, a 62 kgoe/t specific energy consumption (SEC) was found, although with differences between slaughterhouses. A prominent negative correlation between SEC and carcass production was found specially in slaughterhouse A. Estimated Specific Energy Cost and Greenhouse Gases Intensity (GHGI) show mean values of about 50 €/t and 1.8 tCO2e/toe, respectively. Main results show that there is a significant margin for improving energy efficiency and therefore lowering costs in this type of non-energy intensive industries.

Keywords: meat industry, energy intensity, energy efficiency, GHG emissions

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Authors: Odinah Cuartero-Enteria, Aive Pecasales, Jhadly Philip Buniel, Christian Joy Vega, Shiela Estubo

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In the Philippines, Mindanao Island has the cheapest electricity because of the hydroelectric plants. Due to the rapid increase of the electricity consumption which the sources of electricity cannot support, it causes rotating brownout during summer season. This study investigated the household energy usage and practices in the rural areas of northern part of the Mindanao Island, Philippines. The questionnaire that includes the respondents’ profile and their common practices in energy consumptions was used as a tool in gathering the data. Several households were subjected to the survey. Results show energy consumption is not dependent on the profile of the respondents. It was observed that most of the families prefer to use energy saving methods of reducing electricity consumption. The main energy saving methods are unplugging unused home appliances, using of compact fluorescent bulb and energy-efficient gadgets, and using high electricity consumption appliances by schedule. Based on the results, the households in the rural areas know the practices of reducing electricity consumption. However, it is highly recommended that concern agencies should initiate information dissemination and strict implementation of well-formulated energy conservation practices all over the areas in Mindanao.

Keywords: Philippines, Mindanao island, rural areas, households, energy usages, practices

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Authors: Abdelkarim Ait Brik, Abdelaziz Khoukh, Mustapha Jammali, Hamid Chaikhy

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The energy audit is the essential initial step to ensure a good definition of energy control actions. The in-depth study of the various energy-consuming equipments makes it possible to determine the actions and investments with best cost for the company. The analysis focuses on the energy consumption of production equipment and utilities (lighting, heating, air conditioning, ventilation, transport). Successful implementation of this approach requires, however, to take into account a number of prerequisites. This paper proposes a number of useful recommendations concerning the energy audit in order to achieve better results, and a case study concerning the lighting audit of a Moroccan company by showing the gains that can be made through this audit.

Keywords: energy audit, energy diagnosis, consumption, electricity, energy efficiency, lighting audit

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Authors: Yuhanis Yusof, Zuriani Mustaffa, Siti Sakira Kamaruddin

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Data mining is a fundamental technique in identifying patterns from large data sets. The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical. Prior to that, data are consolidated so that the resulting mining process may be more efficient. This study investigates the effect of different data normalization techniques, which are Min-max, Z-score, and decimal scaling, on Swarm-based forecasting models. Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC). Forecasting models are later developed to predict the daily spot price of crude oil and gasoline. Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max. Nevertheless, the GWO is more superior that ABC as its model generates the highest accuracy for both crude oil and gasoline price. Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.

Keywords: artificial bee colony, data normalization, forecasting, Grey Wolf optimizer

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Authors: Eyup Dogan

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The number of research articles analyzing the integration properties of energy variables has rapidly increased in the energy literature for about a decade. The stochastic behaviors of energy variables are worth knowing due to several reasons. For instance, national policies to conserve or promote energy consumption, which should be taken as shocks to energy consumption, will have transitory effects in energy consumption if energy consumption is found to be stationary in one country. Furthermore, it is also important to know the order of integration to employ an appropriate econometric model. Despite being an important subject for applied energy (economics) and having a huge volume of studies, several known limitations still exist with the existing literature. For example, many of the studies use aggregate energy consumption and national level data. In addition, a huge part of the literature is either multi-country studies or solely focusing on the U.S. This is the first study in the literature that considers a form of energy consumption by sectors at sub-national level. This research study aims at investigating unit root properties of electricity consumption for 12 regions of Turkey by four sectors in addition to total electricity consumption for the purpose of filling the mentioned limits in the literature. In this regard, we analyze stationarity properties of 60 cases . Because the use of multiple unit root tests make the results robust and consistent, we apply Dickey-Fuller unit root test based on Generalized Least Squares regression (DFGLS), Phillips-Perron unit root test (PP) and Zivot-Andrews unit root test with one endogenous structural break (ZA). The main finding of this study is that electricity consumption is trend stationary in 7 cases according to DFGLS and PP, whereas it is stationary process in 12 cases when we take into account the structural change by applying ZA. Thus, shocks to electricity consumption have transitory effects in those cases; namely, agriculture in region 1, region 4 and region 7, industrial in region 5, region 8, region 9, region 10 and region 11, business in region 4, region 7 and region 9, total electricity consumption in region 11. Regarding policy implications, policies to decrease or stimulate the use of electricity have a long-run impact on electricity consumption in 80% of cases in Turkey given that 48 cases are non-stationary process. On the other hand, the past behavior of electricity consumption can be used to predict the future behavior of that in 12 cases only.

Keywords: unit root, electricity consumption, sectoral data, subnational data

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Authors: Wu Xingchun, Chen Xi

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Nowadays, China's building energy consumption constitutes 25% of the total energy consumption, half of which was caused by air conditioning in both summer and winter. The ventilation system in Chinese traditional residence, which is totally passive and environmentally friendly, works effectively to create comfortable indoor environment. The research on the ventilation system in Chinese traditional residence can provide advancements to architecture design and energy savings to the society. Through field investigation, case analysis, strategy proposing and other methods, it comes out that the location and layout, the structure system and the design of atrium are the most important elements for a good ventilation system. Taking every factor into consideration, techniques are deployed extensively such as the organization of draught, the design of the thermal pressure ventilation system and the application of modern materials. With the enlightenment of the ventilation system in Chinese traditional residence, we can take effective measures to achieve low energy consumption and sustainable architecture.

Keywords: ventilation system, chinese traditional residence, energy consumption, sustainable architecture

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Authors: Margarida Plana

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One of the most important energy challenge of the European policies is the transition to a Net Zero Energy Building (NZEB) model. A NZEB is a new concept of building that has the aim of reducing both the energy consumption and the carbon emissions to nearly zero of the course of a year. To achieve this nearly zero consumption, apart from being buildings with high efficiency levels, the energy consumed by the building has to be produced on-site. This paper is focused on presenting the results of the analysis developed on basis of real projects’ data in order to quantify the impact of end-users behavior. The analysis is focused on how the behavior of building’s occupants can vary the achievement of the energy savings targets and how they can be limited. The results obtained show that on this kind of project, with very high energy performance, is required to limit the end-users interaction with the system operation to be able to reach the targets fixed.

Keywords: end-users impacts, energy efficiency, energy savings, NZEB model

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Authors: Ahmad Awajan, Sadam Al Wadi

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In this study, a hybrid method based on Empirical Mode Decomposition and Holt-Winter (EMD-HW) is used to forecast Amman stock market data. First, the data are decomposed by EMD method into Intrinsic Mode Functions (IMFs) and residual components. Then, all components are forecasted by HW technique. Finally, forecasting values are aggregated together to get the forecasting value of stock market data. Empirical results showed that the EMD- HW outperform individual forecasting models. The strength of this EMD-HW lies in its ability to forecast non-stationary and non- linear time series without a need to use any transformation method. Moreover, EMD-HW has a relatively high accuracy comparing with eight existing forecasting methods based on the five forecast error measures.

Keywords: Holt-Winter method, empirical mode decomposition, forecasting, time series

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Authors: Kehinde Damilola Ilesanmi, Dev Datt Tewari

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South Africa is in its post-industrial era moving from the primary and secondary sector to the tertiary sector. The study investigated the impact of the disaggregated energy consumption (coal, oil, and electricity) on the primary, secondary and tertiary sectors of the economy between 1980 and 2012 in South Africa. Using vector error correction model, it was established that South Africa is an energy dependent economy, and that energy (especially electricity and oil) is a limiting factor of growth. This implies that implementation of energy conservation policies may hamper economic growth. Output growth is significantly outpacing energy supply, which has necessitated load shedding. To meet up the excess energy demand, there is a need to increase the generating capacity which will necessitate increased investment in the electricity sector as well as strategic steps to increase oil production. There is also need to explore more renewable energy sources, in order to meet the growing energy demand without compromising growth and environmental sustainability. Policy makers should also pursue energy efficiency policies especially at sectoral level of the economy.

Keywords: causality, economic growth, energy consumption, hypothesis, sectoral output

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Authors: Ahmed Al-Adaileh, Souheil Khaddaj

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Outcomes of exhaustion of natural resources started influencing each spirit on this planet. Energy is an essential factor in this aspect. To restore the circumstance to the appropriate track, all attempts must focus on two fundamental branches: producing electricity from clean and renewable reserves and decreasing the overall unnecessary consumption of energy. The focal point of this paper will be on lessening the power consumption in the household's segment. This paper is an attempt to give a clear understanding of a framework called Reduction of Energy Consumption in Household Sector (RECHS) and how it should help householders to reduce their power consumption by substituting their household appliances, turning-off the appliances when stand-by modus is detected, and scheduling their appliances operation periods. Technically, the framework depends on utilizing Z-Wave compatible plug-ins which will be connected to the usual house devices to gauge and control them remotely and semi-automatically. The suggested framework underpins numerous quality characteristics, for example, integrability, scalability, security and adaptability.

Keywords: smart energy management systems, internet of things, wireless mesh networks, microservices, cloud computing, big data

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Authors: Milan Joshi, Harsh Agrawal, Pallaw Mishra, Sanand Sule

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Predicting electricity usage is a crucial aspect of organizing and controlling sustainable energy systems. The task of forecasting electricity load is intricate and requires a lot of effort due to the combined impact of social, economic, technical, environmental, and cultural factors on power consumption in communities. As a result, it is important to create strong models that can handle the significant non-linear and complex nature of the task. The objective of this study is to create and compare three machine learning techniques for predicting electricity load for both the day ahead and intraday, taking into account various factors such as meteorological data and social events including holidays and festivals. The proposed methods include a LightGBM, FBProphet, combination of FBProphet and LightGBM for day ahead and Motifs( Stumpy) based on Mueens algorithm for similarity search for intraday. We utilize these techniques to predict electricity usage during normal days and social events in the Himachal Region. We then assess their performance by measuring the MSE, RMSE, and MAPE values. The outcomes demonstrate that the combination of FBProphet and LightGBM method is the most accurate for day ahead and Motifs for intraday forecasting of electricity usage, surpassing other models in terms of MAPE, RMSE, and MSE. Moreover, the FBProphet - LightGBM approach proves to be highly effective in forecasting electricity load during social events, exhibiting precise day ahead predictions. In summary, our proposed electricity forecasting techniques display excellent performance in predicting electricity usage during normal days and special events in the Himachal Region.

Keywords: feature engineering, FBProphet, LightGBM, MASS, Motifs, MAPE

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Authors: Mahsa Faramarzi Asli, Mina Sarabi

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The important issues that are addressed in most advanced industrial countries in recent decades, discussion of minimizing heat losses through the buildings. And the most influential parameters in the calculation of building energy consumption, is heat exchange, which takes place between the interior and outer space. One of the solutions to reduce heat loss is using materials with low thermal conductivity. The purpose of this article, is the effect of using some frontages with nano-concrete photo catalytic precast materials for reducing energy consumption in buildings. For this purpose, estimating the energy dissipation through the facade built with nano-concrete photo catalytic precast materials on a sample building in Tabriz city by BCS 19 software ( topic 19 simulation) is done and the results demonstrate reduce heat loss through the facade nano- concrete.

Keywords: nano materials, optimize energy consumption, themal, stability

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Authors: Shuen-Tai Wang, Ying-Chuan Chen, Yu-Ching Lin

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There has been renewal of interest in the relation between Green IT and cloud computing in recent years. Cloud computing has to be a highly elastic environment which provides stable services to users. The growing use of cloud computing facilities has caused marked energy consumption, putting negative pressure on electricity cost of computing center or data center. Each year more and more network devices, storages and computers are purchased and put to use, but it is not just the number of computers that is driving energy consumption upward. We could foresee that the power consumption of cloud computing facilities will double, triple, or even more in the next decade. This paper aims at resource allocation and scheduling technologies that are short of or have not well developed yet to reduce energy utilization in cloud computing platform. In particular, our approach relies on recalling services dynamically onto appropriate amount of the machines according to user’s requirement and temporarily shutting down the machines after finish in order to conserve energy. We present initial work on integration of resource and power management system that focuses on reducing power consumption such that they suffice for meeting the minimizing quality of service required by the cloud computing platform.

Keywords: cloud computing, energy utilization, power consumption, resource allocation

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Authors: Ching Kin Keong, Koh Tieng Wei, Abdul Azim Abd. Ghani, Khaironi Yatim Sharif

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Maintaining factory default battery endurance rate over time in supporting huge amount of running applications on energy-restricted mobile devices has created a new challenge for mobile applications developer. While delivering customers’ unlimited expectations, developers are barely aware of efficient use of energy from the application itself. Thus developers need a set of valid energy consumption indicators in assisting them to develop energy saving applications. In this paper, we present a few software product metrics that can be used as an indicator to measure energy consumption of Android-based mobile applications in the early of design stage. In particular, Trepn Profiler (Power profiling tool for Qualcomm processor) has used to collect the data of mobile application power consumption, and then analyzed for the 23 software metrics in this preliminary study. The results show that McCabe cyclomatic complexity, number of parameters, nested block depth, number of methods, weighted methods per class, number of classes, total lines of code and method lines have direct relationship with power consumption of mobile application.

Keywords: battery endurance, software metrics, mobile application, power consumption

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Authors: A. Kumar, V. Devadas

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Energy is the basic element for any country’s economic development. India is one of the most populated countries, and is dependent on fossil fuel and nuclear-based energy generation. The energy sector faces huge challenges and is dependent on the import of energy from neighboring countries to fulfill the gap in demand and supply. India has huge setbacks for efficient energy generation, distribution, and consumption, therefore they consume more quantity of energy to produce the same amount of Gross Domestic Product (GDP) compared to the developed countries. Technology and technique use, availability, and affordability in the various sectors are varying according to their economic status. In this paper, an attempt is made to quantify the domestic electrical energy consumption in Jodhpur, India. Survey research methods have been employed and stratified sampling technique-based households were chosen for conducting the investigation. Pre-tested survey schedules are used to investigate the grassroots level study. The collected data are analyzed by employing statistical techniques. Thereafter, a multiple regression model is developed to understand the functions of total electricity consumption in the domestic sector corresponding to other independent variables including electrical appliances, age of the building, household size, education, etc. The study resulted in identifying the governing variable in energy consumption at the household level and their relationship with the efficiency of household-based electrical and energy appliances. The analysis is concluded with the recommendation for optimizing the gap in peak electrical demand and supply in the domestic sector.

Keywords: appliance, consumption, electricity, households

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Authors: P. Nafisi Poor, P. Javid

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Over the past few years, the idea of adaptive buildings and specifically, adaptive building energy management systems (ABEMS) has become popular. Well-performed management in terms of energy is to create a balance between energy consumption and user comfort; therefore, in new energy management models, efficient energy consumption is not the sole factor and the user's comfortability is also considered in the calculations. One of the main ways of measuring this factor is by analyzing user feedback on the conditions to understand whether they are satisfied with conditions or not. This paper provides a comprehensive review of recent approaches towards energy management systems based on users' feedbacks and subsequently performs a comparison between them premised upon their efficiency and accuracy to understand which approaches were more accurate and which ones resulted in a more efficient way of minimizing energy consumption while maintaining users' comfortability. It was concluded that the highest accuracy rate among the presented works was 95% accuracy in determining satisfaction and up to 51.08% energy savings can be achieved without disturbing user’s comfort. Considering the growing interest in designing and developing adaptive buildings, these studies can support diverse inquiries about this subject and can be used as a resource to support studies and researches towards efficient energy consumption while maintaining the comfortability of users.

Keywords: adaptive buildings, energy efficiency, intelligent buildings, user comfortability

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Authors: Ursachi Andrei

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The Smart Grid Simulator is a computer software based on advanced algorithms which has as the main purpose to lower the energy bill in the most optimized price efficient way as possible for private households, companies or energy providers. It combines the energy provided by a number of solar modules and wind turbines with the consumption of one household or a cluster of nearby households and information regarding weather conditions and energy prices in order to predict the amount of energy that can be produced by renewable energy sources and the amount of energy that will be bought from the distributor for the following day. The user of the system will not only be able to minimize his expenditures on energy fractures, but also he will be informed about his hourly consumption, electricity prices fluctuation and money spent for energy bought as well as how much money he saved each day and since he installed the system. The paper outlines the algorithm that supports the Smart Grid Simulator idea and presents preliminary test results that support the discussion and implementation of the system.

Keywords: smart grid, sustainable energy, applied science, renewable energy sources

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Authors: Fahim Ullah, Muhammad Usman

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Energy consumption and environmental sustainability are hard challenges of 21st century. Energy richness increases environmental pollution while energy poverty hinders economic growth. Considering these two aspects, present study calculates energy deficiency and examines the role of renewable energy to overcome rising energy deficiency and carbon emission for selected countries from 1990 to 2021. For empirical analysis, this study uses methods of moments panel quantile regression analysis and to check the robustness, study used panel quantile robust analysis. Graphical analysis indicated rising global energy deficiency since last three decades where energy consumption is higher than energy production. Empirical results showed that renewable energy is a significant factor for reducing energy deficiency. Secondly, the energy deficiency increases carbon emission level and again renewable energy decreases emissions level. This study recommends that global energy deficiency and rising carbon emissions can be controlled through structural change in the form of energy transition to replace non-renewable resources with renewable resources.

Keywords: energy deficiency, renewable energy, carbon emission, energy trade, PQL analysis

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Authors: Muhammad Tariq, Hammad Tahir, Fawwad Mahmood Butt

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Purpose: This study attempts to examine the best forecasting methodologies in the time series. The time series forecasting models such as VAR, ARCH and the ARMA are considered for the analysis. Methodology: The Bench Marks or the parameters such as Adjusted R square, F-stats, Durban Watson, and Direction of the roots have been critically and empirically analyzed. The empirical analysis consists of time series data of Consumer Price Index and Closing Stock Price. Findings: The results show that the VAR model performed better in comparison to other models. Both the reliability and significance of VAR model is highly appreciable. In contrary to it, the ARCH model showed very poor results for forecasting. However, the results of ARMA model appeared double standards i.e. the AR roots showed that model is stationary and that of MA roots showed that the model is invertible. Therefore, the forecasting would remain doubtful if it made on the bases of ARMA model. It has been concluded that VAR model provides best forecasting results. Practical Implications: This paper provides empirical evidences for the application of time series forecasting model. This paper therefore provides the base for the application of best time series forecasting model.

Keywords: forecasting, time series, auto regression, ARCH, ARMA

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Authors: Firas M. Tuaimah, Huda M. Abdul Abbas

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Accurate Short Term Load Forecasting (STLF) is essential for a variety of decision making processes. However, forecasting accuracy can drop due to the presence of uncertainty in the operation of energy systems or unexpected behavior of exogenous variables. Interval Type 2 Fuzzy Logic System (IT2 FLS), with additional degrees of freedom, gives an excellent tool for handling uncertainties and it improved the prediction accuracy. The training data used in this study covers the period from January 1, 2012 to February 1, 2012 for winter season and the period from July 1, 2012 to August 1, 2012 for summer season. The actual load forecasting period starts from January 22, till 28, 2012 for winter model and from July 22 till 28, 2012 for summer model. The real data for Iraqi power system which belongs to the Ministry of Electricity.

Keywords: short term load forecasting, prediction interval, type 2 fuzzy logic systems, electric, computer systems engineering

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