Search results for: Residential electricity consumption.

Authors: L. L. Ivy-Yap, H. A. Bekhet

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As the Malaysian residential electricity consumption continued to increase rapidly, effective energy policies, which address factors affecting residential electricity consumption, is urgently needed. This study attempts to investigate the relationship between residential electricity consumption (EC), real disposable income (Y), price of electricity (Pe) and population (Po) in Malaysia for 1978-2011 period. Unlike previous studies on Malaysia, the current study focuses on the residential sector, a sector that is important for the contemplation of energy policy. The Phillips-Perron (P-P) unit root test is employed to infer the stationarity of each variable while the bound test is executed to determine the existence of co-integration relationship among the variables, modelled in an Autoregressive Distributed Lag (ARDL) framework. The CUSUM and CUSUM of squares tests are applied to ensure the stability of the model. The results suggest the existence of long-run equilibrium relationship and bidirectional Granger causality between EC and the macroeconomic variables. The empirical findings will help policy makers of Malaysia in developing new monitoring standards of energy consumption. As it is the major contributing factor in economic growth and CO₂ emission, there is a need for more proper planning in Malaysia to attain future targets in order to cut emissions.

Keywords: Co-integration, Elasticity, Granger causality, Malaysia, Residential electricity consumption.

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Authors: Mario Gómez, José Carlos Rodríguez

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The causality between energy consumption and economic growth has been an important issue in the economic literature. This paper studies the causal relationship between electricity consumption and economic growth in Mexico for the period of 1971-2011. In so doing, unit root and causality tests are applied. The results show that energy consumption and economic growth series are stationary and there is also a causality relationship running from economic growth to electricity consumption. Therefore, any energy conservation policy would have little or no impact at all on economic growth in México.

Keywords: Causality, economic growth, electricity consumption, Mexico.

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Authors: M. Benbouzid, Q. Bresson, A. Duclos, K. Longo, Q. Morel

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Currently, electricity suppliers must predict the consumption of their customers in order to deduce the power they need to produce. It is then important in a first step to optimize household consumptions to obtain more constant curves by limiting peaks in energy consumption. Here centralized real time scheduling is proposed to manage the equipments starting in parallel. The aim is not to exceed a certain limit while optimizing the power consumption across a habitat. The Raspberry Pi is used as a box; this scheduler interacts with the various sensors in 6LoWPAN. At the scale of a single dwelling, household consumption decreases, particularly at times corresponding to the peaks. However, it would be wiser to consider the use of a residential complex so that the result would be more significant. So the ceiling would no longer be fixed. The scheduling would be done on two scales, on the one hand per dwelling, and secondly, at the level of a residential complex.

Keywords: Smart grid, Energy box, Scheduling, Gang Model, Energy consumption, Energy management system, and Wireless Sensor Network.

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Authors: Saad F. Al Nuaimi

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Energy consumption is a very important topic these days especially regarding air conditioning in residential buildings, since this takes the biggest amount of energy in buildings total consumption, residential buildings constitute the biggest percentage of energy consumption in Bahrain. This research reflects on the effects of shading percentage in different solar orientations on the energy consumption inside residential buildings (domestic dwellings). The research as found that, there are different effects of shading in changing building orientation: • 0.69% for the shading percentage 25% when the building is oriented to the north (0º); • 18.59% for 75% of shading in north-west orientation (325º); • The best effect for shading is in north-west orientation (315º); • The less effect for shading was in case of the building orientation is the north (0º).

Keywords: Bahraini buildings, Building shading, energy consumption, residential buildings, shading effects.

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Authors: Rahib Abiyev, Vasif H. Abiyev, C. Ardil

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In this paper the development of neural network based fuzzy inference system for electricity consumption prediction is considered. The electricity consumption depends on number of factors, such as number of customers, seasons, type-s of customers, number of plants, etc. It is nonlinear process and can be described by chaotic time-series. The structure and algorithms of neuro-fuzzy system for predicting future values of electricity consumption is described. To determine the unknown coefficients of the system, the supervised learning algorithm is used. As a result of learning, the rules of neuro-fuzzy system are formed. The developed system is applied for predicting future values of electricity consumption of Northern Cyprus. The simulation of neuro-fuzzy system has been performed.

Keywords: Fuzzy logic, neural network, neuro-fuzzy system, neuro-fuzzy prediction.

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Authors: J.Morris, D.Allinson, J.Harrison, K.J. Lomas

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The UK Government has emphasized the role of Local Authorities as a key player in its flagship residential energy efficiency strategies, by identifying and targeting areas for energy efficiency improvements. Residential energy consumption in England is characterized by significant geographical variation in energy demand, which makes centralized targeting of areas for energy efficiency intervention difficult. This paper draws on research which aims to understand how demographic, social, economic, urban form and climatic factors influence the geographical variations in English residential gas consumption. The paper reports the findings of a multiple regression model that shows how 64% of the geographical variation in residential gas consumption is accounted for by variations in these factors. Results from this study, after further refinement and validation, can be used by Local Authorities to identify areas within their boundaries that have higher than expected gas consumption, these may be prime targets for energy efficiency initiatives.

Keywords: UK Housing, Heating Energy, Socio-Economics, Statistical Modelling

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Authors: Saurabh Chanana, Monika Arora

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Demand response is getting increased attention these days due to the increase in electricity demand and introduction of renewable resources in the existing power grid. Traditionally demand response programs involve large industrial consumers but with technological advancement, demand response is being implemented for small residential and commercial consumers also. In this paper, demand response program aims to reduce the peak demand as well as overall energy consumption of the residential customers. Air conditioners are the major reason of peak load in residential sector in summer, so a dynamic model of air conditioning load with thermostat action has been considered for applying demand response programs. A programmable communicating thermostat (PCT) is a device that uses real time pricing (RTP) signals to control the thermostat setting. A new model incorporating PCT in air conditioning load has been proposed in this paper. Results show that introduction of PCT in air conditioner is useful in reducing the electricity payments of customers as well as reducing the peak demand. 

Keywords: Demand response, Home energy management Programmable communicating thermostat, Thermostatically controlled appliances.

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Authors: E.Assareh, M.A. Behrang, R. Assareh, N. Hedayat

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An integrated Artificial Neural Network- Particle Swarm Optimization (PSO) is presented for analyzing global electricity consumption. To aim this purpose, following steps are done: STEP 1: in the first step, PSO is applied in order to determine world-s oil, natural gas, coal and primary energy demand equations based on socio-economic indicators. World-s population, Gross domestic product (GDP), oil trade movement and natural gas trade movement are used as socio-economic indicators in this study. For each socio-economic indicator, a feed-forward back propagation artificial neural network is trained and projected for future time domain. STEP 2: in the second step, global electricity consumption is projected based on the oil, natural gas, coal and primary energy consumption using PSO. global electricity consumption is forecasted up to year 2040.

Keywords: Particle Swarm Optimization, Artificial NeuralNetworks, Fossil Fuels, Electricity, Forecasting.

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Authors: Mansour Nikpour, Mohd Zin kandar, Mohsen Ghasemi, Hossein Fallah

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Over half of the total electricity consumption is used in buildings. Air-conditioning and electric lighting are the two main resources of electricity consumption in high rise buildings. One way to reduce electricity consumption would be to limit heat gain into buildings, therefore reduce the demand for air-conditioning during hot summer months especially in hot regions. On the other hand natural daylight can be used to reduce the use of electricity for artificial lighting. In this paper effective factors on minimizing heat gain and achieving required day light were reviewed .As daylight always accompanied by solar heat gain. Also interactions between heat gain and daylight were discussed through previous studies and equations which are related to heat gain and day lighting especially in high rise buildings. As a result importance of building-s form and its component on energy consumption in buildings were clarified.

Keywords: High rise buildings, energy demand, day lighting, heat gain.

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Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

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To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: Building energy prediction, data mining, demand response, electricity market.

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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 bound 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 log of electricity consumption (LELC) and log of manufacturing value added (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: ARDL, cointegration, Nigeria's manufacturing, electricity.

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Authors: Amro Issam Hamed Attia Ramadan, Marco Zappatore, Pasquale Balena, Antonella Longo

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Considering the energy crisis that is hitting Europe, it becomes increasingly necessary to change energy policies to depend less on fossil fuels and replace them with energy from renewable sources. This has triggered the urge to use clean energy, not only to satisfy energy needs and fulfill the required consumption, but also to decrease the danger of climatic changes due to harmful emissions. Many countries have already started creating energy communities based on renewable energy sources. The first step to understanding energy needs in any place is to perfectly know the consumption. In this work, we aim to estimate electricity consumption for a municipality that makes up part of a rural area located in southern Italy using forecast models that allow for the estimation of electricity consumption for the next 10 years, and we then apply the same model to the province where the municipality is located and estimate the future consumption for the same period to examine whether it is possible to start from the municipality level to reach the province level when creating energy communities.

Keywords: ARIMA, electricity consumption, forecasting models, time series.

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Authors: Hong Bae Kim, Chang Ho Hur

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Many governments have tried to reduce CO₂ emissions which are believed to be the main cause for global warming. The deployment of electric automobiles is regarded as an effective way to reduce CO₂ emissions. The Korean government has planned to deploy about 200,000 electric automobiles. The policy for the deployment of electric automobiles aims at not only decreasing gasoline consumption but also increasing electricity production. However, if an electricity consuming regions is not consistent with an electricity producing region, the policy generates environmental problems between regions. Hence, this paper has established the energy multi-region input-output model to specifically analyze the impacts of the deployment of electric automobiles on regional energy consumption and CO₂ emissions. Finally, the paper suggests policy directions regarding the deployment of electric automobiles.

Keywords: Electric automobiles, CO2 emissions, regional imbalances in electricity production and consumption, energy multi-region input-output model.

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Authors: F. Gökgöz, M. E. Atmaca

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Electricity plays an indispensable role in human life and the economy. It is a unique product or service that must be balanced instantaneously, as electricity is not stored, generation and consumption should be proportional. Effective and efficient use of electricity is very important not only for society, but also for the environment. A competitive electricity market is one of the best ways to provide a suitable platform for effective and efficient use of electricity. On the other hand, it carries some risks that should be carefully managed by the market players. Risk management is an essential part in market players’ decision making. In this paper, risk management through diversification is applied with the help of Markowitz’s Mean-variance, Down-side and Semi-variance methods for a case study. Performance of optimal electricity sale solutions are measured and evaluated via Sharpe-Ratio, and the optimal portfolio solutions are improved. Two years of historical weekdays’ price data of the Turkish Day Ahead Market are used to demonstrate the approach.

Keywords: Electricity market, portfolio optimization, risk management in electricity market, Sharpe ratio.

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Authors: Ramin Vafadary, Maryam Khanbaghi

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Forecasting electricity load is important for various purposes like planning, operation and control. Forecasts can save operating and maintenance costs, increase the reliability of power supply and delivery systems, and correct decisions for future development. This paper compares various time series methods to forecast 24 hours ahead of electricity load. The methods considered are the Holt-Winters smoothing, SARIMA Modeling, LSTM Network, Fbprophet and Tensorflow probability. The performance of each method is evaluated by using the forecasting accuracy criteria namely, the Mean Absolute Error and Root Mean Square Error. The National Renewable Energy Laboratory (NREL) residential energy consumption data are used to train the models. The results of this study show that SARIMA model is superior to the others for 24 hours ahead forecasts. Furthermore, a Bagging technique is used to make the predictions more robust. The obtained results show that by Bagging multiple time-series forecasts we can improve the robustness of the models for 24 hour ahead electricity load forecasting.

Keywords: Bagging, Fbprophet, Holt-Winters, LSTM, Load Forecast, SARIMA, tensorflow probability, time series.

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Authors: Amira M. Attia, Karim H. Youssef, Nabil H. Abbasy

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Energy consumption schedule (ECS) technique shifts usage of loads from on peak hours and redistributes them throughout the day according to residents’ operating time preferences. This technique is used as form of indirect control from utility to improve the load curve and hence its load factor and reduce customer’s total electric bill as well. Similarly, load shifting technique achieves ECS purposes but as direct control form applied from utility. In this paper, ECS is simulated twice as optimal constrained mathematical formula, solved by using CVX program in MATLAB^® R2013b. First, it is utilized for single residential building with ten apartments to determine max allowable energy consumption per hour for each residential apartment. Then, it is used for single apartment with number of shiftable domestic devices, where operating schedule is deduced using previous simulation output results as constraints. The paper ends by giving differences between ECS technique and load shifting technique via literature and simulation. Based on results assessment, it will be shown whether using ECS or load shifting is more beneficial to both customer and utility.

Keywords: Energy consumption schedule, load shifting technique, comparison.

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Authors: Tien-Shun Chan, Yung-Chung Chang, Cheng-Yu Chu, Wen-Hui Chen, Yuan-Lin Chen, Shun-Chong Wang, Chang-Chun Wang

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98% of the energy needed in Taiwan has been imported. The prices of petroleum and electricity have been increasing. In addition, facility capacity, amount of electricity generation, amount of electricity consumption and number of Taiwan Power Company customers have continued to increase. For these reasons energy conservation has become an important topic. In the past linear regression was used to establish the power consumption models for chillers. In this study, grey prediction is used to evaluate the power consumption of a chiller so as to lower the total power consumption at peak-load (so that the relevant power providers do not need to keep on increasing their power generation capacity and facility capacity). In grey prediction, only several numerical values (at least four numerical values) are needed to establish the power consumption models for chillers. If PLR, the temperatures of supply chilled-water and return chilled-water, and the temperatures of supply cooling-water and return cooling-water are taken into consideration, quite accurate results (with the accuracy close to 99% for short-term predictions) may be obtained. Through such methods, we can predict whether the power consumption at peak-load will exceed the contract power capacity signed by the corresponding entity and Taiwan Power Company. If the power consumption at peak-load exceeds the power demand, the temperature of the supply chilled-water may be adjusted so as to reduce the PLR and hence lower the power consumption.

Keywords: Gery system theory, grey prediction, chller.

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Authors: A. Teke, O. Timur

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Hospitals represent approximately 6% of total energy consumption in the utility buildings sector. Heating, Ventilation and Air Conditioning (HVAC) systems are the major part of electrical energy consumption at the hospitals. The air-conditioning system is responsible for around 70% of total electricity consumption. Electric motors and lighting systems in a hospital represent approximately 19% and 21% of the total energy consumption, respectively. In this paper, profiles of hospital energy end-use consumption and an overview of energy saving areas at the hospitals are presented.

Keywords: Energy efficiency, energy saving, healthcare energy consumption, hospital.

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Authors: Rolf Katzenbach, Frithjof Clauss, Jie Zheng

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The final energy use can be divided mainly in four sectors: commercial, industrial, residential, and transportation. The trend in final energy consumption by sector plays as a most straightforward way to provide a wide indication of progress for reducing energy consumption and associated environmental impacts by different end use sectors. The average share of end use energy for residential sector in the world was nearly 20% until 2011, in Germany a higher proportion is between 25% and 30%. However, it remains less studied than energy use in other three sectors as well its impacts on climate and environment. The reason for this involves a wide range of fields, including the diversity of residential construction like different housing building design and materials, living or energy using behavioral patterns, climatic condition and variation as well other social obstacles, market trend potential and financial support from government.

This paper presents an extensive and in-depth analysis of the manner by which projects researched and operated by authors in the fields of energy efficiency primarily from the perspectives of both technical potential and initiative energy saving consciousness in the residential sectors especially in social housing buildings.

Keywords: Energy Efficiency, Renewable Energy, Retro-commissioning, Social Housing, Sustainability.

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Authors: Hossein Lotfizadeh, André McDonald, Amit Kumar

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Renewable energy resources, which can supplement space and water heating for residential buildings, can have a noticeable impact on natural gas consumption and air pollution. This study considers a technical analysis of a combined solar water heating system with evacuated tube solar collectors for different solar coverage, ranging from 20% to 100% of the total roof area of a typical residential building located in Edmonton, Alberta, Canada. The alternative heating systems were conventional (non-condensing) and condensing tankless water heaters and condensing boilers that were coupled to solar water heating systems. The performance of the alternative heating systems was compared to a traditional heating system, consisting of a conventional boiler, applied to houses of various gross floor areas. A comparison among the annual natural gas consumption, carbon dioxide (CO₂) mitigation, and emissions for the various house sizes indicated that the combined solar heating system can reduce the natural gas consumption and CO₂ emissions, and increase CO₂ mitigation for all the systems that were studied. The results suggest that solar water heating systems are potentially beneficial for residential heating system applications in terms of energy savings and CO₂ mitigation.

Keywords: CO2 emissions, CO2 mitigation, natural gas consumption, solar water heating system, tankless water heater.

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Authors: Jian Yao, Chengwen Yan

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The principle concern of this paper is to determine the impact of solar absorption coefficient of external wall on building energy consumption. Simulations were carried out on a typical residential building by using the simulation Toolkit DeST-h. Results show that reducing solar absorption coefficient leads to a great reduction in building energy consumption and thus light-colored materials are suitable.

Keywords: Solar absorption coefficient, External wall, Buildingenergy consumption.

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Authors: S. Kittipongvises, A. Dubsok

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The mineral and mining industry is necessary for countries to have an adequate and reliable supply of materials to meet their socio-economic development. Despite its importance, the environmental impacts from mineral exploration are hugely significant. This study aimed to investigate and quantify the amount of GHGs emissions emitted from both electricity and diesel vehicle fuel consumption in basalt mining in Thailand. Plant A, located in the northeastern region of Thailand, was selected as a case study. Results indicated that total GHGs emissions from basalt mining and operation (Plant A) were approximately 2,501,086 kgCO₂e and 1,997,412 kgCO₂e in 2014 and 2015, respectively. The estimated carbon intensity ranged between 1.824 kgCO₂e to 2.284 kgCO₂e per ton of rock product. Scope 1 (direct emissions) was the dominant driver of its total GHGs compared to scope 2 (indirect emissions). As such, transport related combustion of diesel fuels generated the highest GHGs emission (65%) compared to emissions from purchased electricity (35%). Some of the potential implications for mining entities were also presented.

Keywords: Basalt mining, diesel fuel, electricity, GHGs emissions, Thailand.

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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: O. Arikan, C. Kocatepe, G. Ucar, Y. Hacialiefendioglu

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In this paper, influence of harmonics on medium voltage distribution system of Bogazici Electricity Distribution Inc. (BEDAS) which takes place at Istanbul/Turkey is investigated. A ring network consisting of residential loads is taken into account for this study. Real system parameters and measurement results are used for simulations. Also, probable working conditions of the system are analyzed for 50%, 75%, and 100% loading of transformers with similar harmonic contents. Results of the study are exhibited the influence of nonlinear loads on %THDV, P.F. and technical losses of the medium voltage distribution system.

Keywords: Distribution system, harmonic, technical losses, power factor (PF), total harmonic distortion (THD), residential load, medium voltage.

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Authors: Thet Thet Han Yee, Su Su Win, Nyein Nyein Soe

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Energy consumption is one of the indices in determining the levels of development of a nation. Therefore, availability of energy supply to all sectors of life in any country is crucial for its development. These exists shortage of all kinds of energy, particularly electricity which is badly needed for economic development. Electricity from the sun which is quite abundant in most of the developing countries is used in rural areas to meet basic electricity needs of a rural community. Today-s electricity supply in Myanmar is generated by fuel generators and hydroelectric power plants. However, far-flung areas which are away from National Grids cannot enjoy the electricity generated by these sources. Since Myanmar is a land of plentiful sunshine, especially in central and southern regions of the country, the first form of energy- solar energy could hopefully become the final solution to its energy supply problem. The direct conversion of solar energy into electricity using photovoltaic system has been receiving intensive installation not only in developed countries but also in developing countries. It is mainly intended to present solar energy potential and application in Myanmar. It is also wanted to get the benefits of using solar energy for people in remote areas which are not yet connected to the national grids because of the high price of fossil fuel.

Keywords: Electricity supply in Myanmar, National Grids, solarenergy.

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Authors: Kung-Jen Tu, Danny Vernatha

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To assist individual departments within universities in their energy management tasks, this study explores the application of Building Information Modeling in establishing the ‘BIM based Energy Management Support System’ (BIM-EMSS). The BIM-EMSS consists of six components: (1) sensors installed for each occupant and each equipment, (2) electricity sub-meters (constantly logging lighting, HVAC, and socket electricity consumptions of each room), (3) BIM models of all rooms within individual departments’ facilities, (4) data warehouse (for storing occupancy status and logged electricity consumption data), (5) building energy management system that provides energy managers with various energy management functions, and (6) energy simulation tool (such as eQuest) that generates real time 'standard energy consumptions' data against which 'actual energy consumptions' data are compared and energy efficiency evaluated. Through the building energy management system, the energy manager is able to (a) have 3D visualization (BIM model) of each room, in which the occupancy and equipment status detected by the sensors and the electricity consumptions data logged are displayed constantly; (b) perform real time energy consumption analysis to compare the actual and standard energy consumption profiles of a space; (c) obtain energy consumption anomaly detection warnings on certain rooms so that energy management corrective actions can be further taken (data mining technique is employed to analyze the relation between space occupancy pattern with current space equipment setting to indicate an anomaly, such as when appliances turn on without occupancy); and (d) perform historical energy consumption analysis to review monthly and annually energy consumption profiles and compare them against historical energy profiles. The BIM-EMSS was further implemented in a research lab in the Department of Architecture of NTUST in Taiwan and implementation results presented to illustrate how it can be used to assist individual departments within universities in their energy management tasks.

Keywords: Sensor, electricity sub-meters, database, energy anomaly detection.

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Authors: Shahryar Shaghaghi G., Paria Violette Shakiba , Gholamreza Irani

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Nowadays, the earth is countered with serious problem of air pollution. This problem has been started from the industrial revolution and has been faster in recent years, so that leads the earth to ecological and environmental disaster. One of its results is the global warming problem and its related increase in global temperature. The most important factors in air pollution especially in urban environments are Automobiles and residential buildings that are the biggest consumers of the fossil energies, so that if the residential buildings as a big part of the consumers of such energies reduce their consumption rate, the air pollution will be decreased. Since Metropolises are the main centers of air pollution in the world, assessment and analysis of efficient strategies in decreasing air pollution in such cities, can lead to the desirable and suitable results and can solve the problem at least in critical level. Tabriz city is one of the most important metropolises in North west of Iran that about two million people are living there. for its situation in cold dry climate, has a high rate of fossil energies consumption that make air pollution in its urban environment. These two factors, being both metropolis and in cold dry climate, make this article try to analyze the strategies of climatic design in old districts of the city and use them in new districts of the future. These strategies can be used in this city and other similar cities and pave the way to reduce energy consumption and related air pollution to save whole world.

Keywords: Air pollution, Urban Environment, Metropolis, Residential building, Fossil energies.

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Authors: Chonmapat Torasa

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This paper presents the performance of electricity generation and consumption from solar generator installed at Rajabhat Suan Sunandha’s learning center in Samutsongkram. The result from the experiment showed that solar cell began to work and distribute the current into the system when the solar energy intensity was 340 w/m2, starting from 8:00 am to 4:00 pm (duration of 8 hours). The highest intensity read during the experiment was 1,051.64w/m2. The solar power was 38.74kWh/day. The electromotive force from solar cell averagely was 93.6V. However, when connecting solar cell with the battery charge controller system, the voltage was dropped to 69.07V. After evaluating the power distribution ability and electricity load of tested solar cell, the result showed that it could generate power to 11 units of 36-watt fluorescent lamp bulbs, which was altogether 396W. In the meantime, the AC to DC power converter generated 3.55A to the load, and gave 781VA.

Keywords: Solar Cell, Solar-cell power generating system.

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Authors: K. C. Rajan, H. B. Rijal, Kazui Yoshida, Masanori Shukuya

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The electricity consumption in the Japanese household sector has increased with higher rate than that of other sectors. This may be because of aging and information oriented society that requires more electrical appliances to make the life better and easier, under this circumstances, energy saving is one of the essential necessity in Japanese society. To understand the way of energy use and demand response of the residential occupants, it is important to understand the structure of energy used. Home Energy Management System (HEMS) may be used for understanding the pattern and the structure of energy used. HEMS is a visualization system of the energy usage by connecting the electrical equipment in the home and thereby automatically control the energy use in each device, so that the energy saving is achieved. Therefore, the HEMS can provide with the easiest way to understand the structure of energy use. The HEMS has entered the mainstream of the Japanese market. The objective of this study is to understand the pattern of energy saving and cost saving in different regions including Japan during HEMS use. To observe thermal comfort level of HEMS managed residential buildings in Japan, the field survey was made and altogether, 1534 votes from 37 occupants related to thermal comfort, occupants’ behaviors and clothing insulation were collected and analyzed. According to the result obtained, approximately 17.9% energy saving and 8.9% cost saving is possible if HEMS is applied effectively. We found the thermal sensation and overall comfort level of the occupants is high in the studied buildings. The occupants residing in those HEMS buildings are satisfied with the thermal environment and they have accepted it. Our study concluded that the significant reduction in Japanese residential energy use can be achieved by the proper utilization of the HEMS. Better thermal comfort is also possible with the use of HEMS if energy use is managed in a rationally effective manner.

Keywords: Energy reduction, thermal comfort, HEMS market, thermal environment.

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Authors: Yong-Sung Kim, Je-Seok Shin, Ho-Jun Jo Jin-O Kim

Abstract:

Home Energy Management System (HEMS), which makes the residential consumers, contribute to the demand response is attracting attention in recent years. An aim of HEMS is to minimize their electricity cost by controlling the use of their appliances according to electricity price. The use of appliances in HEMS may be affected by some conditions such as external temperature and electricity price. Therefore, the user’s usage pattern of appliances should be modeled according to the external conditions, and the resultant usage pattern is related to the user’s comfortability on use of each appliances. This paper proposes a methodology to model the usage pattern based on the historical data with the copula function. Through copula function, the usage range of each appliance can be obtained and is able to satisfy the appropriate user’s comfort according to the external conditions for next day. Within the usage range, an optimal scheduling for appliances would be conducted so as to minimize an electricity cost with considering user’s comfort. Among the home appliance, electric heater (EH) is a representative appliance, which is affected by the external temperature. In this paper, an optimal scheduling algorithm for an electric heater (EH) is addressed based on the method of branch and bound. As a result, scenarios for the EH usage are obtained according to user’s comfort levels and then the residential consumer would select the best scenario. The case study shows the effects of the proposed algorithm compared with the traditional operation of the EH, and it represents impacts of the comfort level on the scheduling result.

Keywords: Load scheduling, usage pattern, user’s comfort, copula function, branch, bound, electric heater.

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