Search results for: short time energy (STE)

Authors: Joseph Levodo, Ndimbarafine Young Tobin, E. Messina, P. Edouma

Abstract:

Energy efficiency can contribute significantly towards increasing clean energy access to modern energy services. Many developing countries have largely focused on expanding energy access by increasing supply. This is due to the fact the links between energy efficiency and clean energy access are often unnoticed. Energy efficiency measures offer the promise of reducing energy use and saving money on electricity bills, as well as reducing negative environmental externalities associated with the production of electricity. This paper seeks to address the economic and effectiveness of reducing energy consumption by integrating energy efficiency as a priority to meet energy access examines the barriers to energy efficient in sub-Saharan African countries. The findings from this study reveal that an appropriate policy can promote the development of more energy-efficient buildings, products and strengthen incentives for consumers, businesses, and industrial customers to pursue cost-effective energy-efficiency measures and to make investments that will provide future energy-efficiency improvements.

Keywords: barriers, Sub-Saharan Africa, cost effective, energy savings, clean energy

Procedia PDF Downloads 23

Authors: H. J. Joshi, Satyajeet Patil, Parth Dandavate, Mihir Kulkarni, Harshita Agrawal

Abstract:

As the world looks towards a sustainable future, electric vehicles have become increasingly popular. Millions worldwide are looking to switch to Electric cars over the previously favored combustion engine-powered cars. This demand has seen an increase in Electric Vehicle Charging Stations. The big challenge is that the randomness of electrical energy makes it tough for these charging stations to provide an adequate amount of energy over a specific amount of time. Thus, it has become increasingly crucial to model these patterns and forecast the energy needs of power stations. This paper aims to analyze how different machine learning models perform on Electric Vehicle charging time-series data. The data set consists of authentic Electric Vehicle Data from the Netherlands. It has an overview of ten thousand transactions from public stations operated by EVnetNL.

Keywords: forecasting, smart grid, electric vehicle load forecasting, machine learning, time series forecasting

Procedia PDF Downloads 88

Authors: İrem Bulut, Mustafa Z. Söyük, Ertuğrul Yalçın, Simge Şişman-Bal

Abstract:

Eyewitness testimony is one of the most frequently used methods in criminal cases for the determination of crime and perpetrator. In the literature, the number of studies about the reliability of eyewitness testimony is increasing. The study aims to reveal the factors that affect the short-term and long-term visual memory performance of the participants in the event of an accident. In this context, the effect of the emotional content of the accident and the sounds during the accident on visual memory performance was investigated with eye-tracking. According to the results, the presence of visual and auditory stimuli with emotional content during the accident decreases the participants' both short-term and long-term recall performance. Moreover, the data obtained from the eye monitoring device showed that the participants had difficulty in answering even the questions they focused on at the time of the accident.

Keywords: eye tracking, eyewitness testimony, long-term recall, short-term recall, visual memory

Procedia PDF Downloads 143

Authors: Shukran M. Dadayev

Abstract:

To author's best knowledge, in this paper, the Basic Properties and Research methods of a Fundamental Particle is studied for the first time. That's to say, Fundamental Particle has not been discovered in the Nature yet. Because Fundamental Particle consists of specific Physical, Geometrical and Internal bases. Geometrical and Internal characteristics that are considered significant for the elementary and fundamental particles aren’t basic properties, characteristics or criteria of a Fundamental Particle. Of course, completely new Physical and Visual experimental methods of Quantum mechanics and Behavioral-Physical investigations of Particles are needed to study and discover the Fundamental Particle. These are new Physical, Visual and Behavioral-Physical experimental methods for describing and discovering the Fundamental Particle in the Nature and Microworld. Fundamental Particle consists of the same Energy-Mass-Motion system and a symmetry of Energy-Mass-Motion. Fundamental Particle supplies each of the elementary particles with the same Energy-Mass-Motion system at the same time and regulates each of the particles. Fundamental Particle gives Energy, Mass and Motion to each particles at the same time, each of the Particles consists of acquired Energy-Mass-Motion system and symmetry. Energy, Mass, Motion given by the Fundamental Particle to the particles are Symmetrical Equivalent and they remain in their primary shapes in all cases. Fundamental Particle gives Energy-Mass-Motion system and symmetry consisting of different measures and functions to each of the particles. The Motion given by the Fundamental Particle to the particles is Gravitation, Gravitational Interaction not only gives Motion, but also cause Motion by attracting. All Substances, Fields and Cosmic objects consist of Energy-Mass-Motion. The Field also includes specific Mass. They are always Energetic, Massive and Active. Fundamental Particle establishes the bases of the Nature. Supplement and Regulating of all the particles existing in the Nature belongs to Fundamental Particle.

Keywords: basic properties of a fundamental particle, behavioral-physical and visual methods, energy-mass-motion system and symmetrical equivalence, fundamental particle

Procedia PDF Downloads 3532

Authors: P. Abachi, T. W. Coyle, P. S. Musavi Gharavi

Abstract:

By applying coating onto a structural component, the corrosion and/or wear resistance requirements of the surface can be fulfilled. Since the layer adhesion of the coating influences the mechanical integrity of the coat/substrate interface during the service time, it should be examined accurately. At the present work, the tensile bonding strength of the 316 stainless steel plasma sprayed coating on aluminum substrate was determined by using tensile adhesion test, TAT, specimen. The interfacial fracture toughness was specified using four-point bend specimen containing a saw notch and modified chevron-notched short-bar (SB) specimen. The coating microstructure and fractured specimen surface were examined by using scanning electron- and optical-microscopy. The investigation of coated surface after tensile adhesion test indicates that the failure mechanism is mostly cohesive and rarely adhesive type. The calculated value of critical strain energy release rate proposes relatively good interface status. It seems that four-point bending test offers a potentially more sensitive means for evaluation of mechanical integrity of coating/substrate interfaces than is possible with the tensile test. The fracture toughness value reported for the modified chevron-notched short-bar specimen testing cannot be taken as absolute value because its calculation is based on the minimum stress intensity coefficient value which has been suggested for the fracture toughness determination of homogeneous parts in the ASTM E1304-97 standard. 

Keywords: bonding strength, four-point bend test, interfacial fracture toughness, modified chevron-notched short-bar specimen, plasma sprayed coating, tensile adhesion test

Procedia PDF Downloads 248

Authors: M. M. Wagh, V. V. Kulkarni

Abstract:

The rising economic activities, growing population and improving living standards of world have led to a steady growth in its appetite for quality and quantity of energy services. As the economy expands the electricity demand is going to grow further, increasing the challenges of the more generation and stresses on the utility grids. Appropriate energy model will help in proper utilization of the locally available renewable energy sources such as solar, wind, biomass, small hydro etc. to integrate in the available grid, reducing the investments in energy infrastructure. Further to these new technologies like smart grids, decentralized energy planning, energy management practices, energy efficiency are emerging. In this paper, the attempt has been made to study and review the recent energy planning models, energy forecasting models, and renewable energy integration models. In addition, various modeling techniques and tools are reviewed and discussed.

Keywords: energy modeling, integration of renewable energy, energy modeling tools, energy modeling techniques

Procedia PDF Downloads 325

Authors: Y. Jin, N. Zhang, X. Luo, W. Zhang

Abstract:

China with annual increasing 0.5-0.6 billion squares city residence has brought in enormous energy consumption by HVAC facilities and other appliances. In this regard, governments and researchers are encouraging renewable energy like solar energy, geothermal energy using in houses. However, high cost of equipment and low energy conversion result in a very low acceptable to residents. So what’s the equilibrium point of eco-feedback to reach economic benefit and thermal comfort? That is the main question should be answered. In this paper, the objective is an on-site solar PV and heater house, which has been evaluated as a low energy building. Since HVAC system is considered as main energy consumption equipment, the residence with 24-hour monitoring system set to measure temperature, wind velocity and energy in-out value with no HVAC system for one month of summer and winter. Thermal comfort time period will be analyzed and confirmed; then the air-conditioner will be started within thermal discomfort time for the following one summer and winter month. The same data will be recorded to calculate the average energy consumption monthly for a purpose of whole day thermal comfort. Finally, two analysis work will be done: 1) Original building thermal simulation by computer at design stage with actual measured temperature after construction will be contrastive analyzed; 2) The cost of renewable energy facilities and power consumption converted to cost efficient rate to assess the feasibility of renewable energy input for residence. The results of the experiment showed that a certain deviation exists between actual measured data and simulated one for human thermal comfort, especially in summer period. Moreover, the cost-effectiveness is high for a house in targeting city Guilin now with at least 11 years of cost-covering. The conclusion proves that an eco-feedback of a low energy residence is never only consideration of its energy net value, but also the cost efficiency that is the critical factor to push renewable energy acceptable by the public.

Keywords: cost efficiency, eco-feedback, low energy residence, thermal comfort

Procedia PDF Downloads 242

Authors: Wei Yao, Constantinos Alexiou

Abstract:

In the existing literature, many studies have focused on the implementation and effectiveness of quantitative easing (QE) since 2008, but only a few have evaluated QE’s effect on commodity prices. In this context, by following Frankel’s (1986) commodity price overshooting model, we study the dynamic covariation between the expected real interest rates and six agricultural commodities’ real returns over the period from 2000:1 to 2018 for the US economy. We use wavelet analysis to investigate the causal relationship and co-movement of time series data by calculating the coefficient of determination in different frequencies. We find that a) US unconventional monetary policy may cause more positive and significant covariation between the expected real interest rates and agricultural commodities’ real returns over the short horizons; b) a lead-lag relationship that runs from agricultural commodities’ real returns to the expected real short-term interest rates over the long horizons; and c) a lead-lag relationship from agricultural commodities’ real returns to the expected real long-term interest rates over short horizons. In the realm of monetary policy, we argue that QE may shift the negative relationship between most commodities’ real returns and the expected real interest rates to a positive one over a short horizon.

Keywords: QE, commodity price, interest rate, wavelet coherence

Procedia PDF Downloads 70

Authors: Eric Kumar, Erica Cochran, Zhiang Zhang, Wei Liang, Ronak Mody

Abstract:

The objective of this article was to create a modelling framework that exposes the marginal costs of shifting workloads across geographically distributed data-centers. Geographical distribution of internet services helps to optimize their performance for localized end users with lowered communications times and increased availability. However, due to the geographical and temporal effects, the physical embodiments of a service's data center infrastructure can vary greatly. In this work, we first identify that the sources of variances in the physical infrastructure primarily stem from local weather conditions, specific user traffic profiles, energy sources, and the types of IT hardware available at the time of deployment. Second, we create a traffic simulator that indicates the IT load at each data-center in the set as an approximator for user traffic profiles. Third, we implement a framework that quantifies the global level energy demands using building energy models and the traffic profiles. The results of the model provide a time series of energy demands that can be used for further life cycle analysis of internet services.

Keywords: data-centers, energy, life cycle, network simulation

Procedia PDF Downloads 129

Authors: M. Dahbi, M. Sellam, A. Benatiallah, A. Harrouz

Abstract:

The wind energy is one of the most significant and rapidly developing renewable energy sources in the world and it provides a clean energy resource, which is a promising alternative in the short term in Algeria The main purpose of this paper is to compared and discuss the wind power potential in three sites located in sahara of Algeria (south west of Algeria) and to perform an investigation on the wind power potential of desert of Algeria. In this comparative, wind speed frequency distributions data obtained from the web site SODA.com are used to calculate the average wind speed and the available wind power. The Weibull density function has been used to estimate the monthly power wind density and to determine the characteristics of monthly parameters of Weibull for these three sites. The annual energy produced by the BWC XL.1 1KW wind machine is obtained and compared. The analysis shows that in the south west of Algeria, at 10 m height, the available wind power was found to vary between 136.59 W/m2 and 231.04 W/m2. The highest potential wind power was found at Adrar, with 21h per day and the mean wind speed is above 6 m/s. Besides, it is found that the annual wind energy generated by that machine lie between 512 KWh and 1643.2 kWh. However, the wind resource appears to be suitable for power production on the sahara and it could provide a viable substitute to diesel oil for irrigation pumps and rural electricity generation.

Keywords: Weibull distribution, parameters of Wiebull, wind energy, wind turbine, operating hours

Procedia PDF Downloads 479

Authors: Bright Kwakye-Awuah, Elizabeth Von-Kiti, Isaac Nkrumah, Baah Sefa-Ntiri, Craig D. Williams

Abstract:

Bauxite and kaolin from Ghana Bauxite Company mine site were used to synthesize zeolites. Bauxite served as the alumina source and kaolin the silica source. Synthesis variations include variation of aging time at constant crystallization time and variation of crystallization times at constant aging time. Characterization techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), energy dispersive x-ray analysis (EDX) and Fourier transform infrared spectroscopy (FTIR) were employed in the characterization of the raw samples as well as the synthesized samples. The results obtained showed that the transformations that occurred and the phase of the resulting products were coordinated by the aging time, crystallization time, alkaline concentration and Si/Al ratio of the system. Zeolites A, X, Y, analcime, Sodalite, and ZK-14 were some of the phases achieved. Zeolite LTA was achieved with short crystallization times of 3, 5, 18 and 24 hours and a maximum aging of 24 hours. Zeolite LSX was synthesized with 24 hr aging followed with 24 hr hydrothermal treatment whilst zeolite Y crystallized after 48 hr of aging and 24 hr crystallization. Prolonged crystallization time produced a mixed phased product. Prolonged aging times, on the other hand, did not yield any zeolite as the sample was amorphous. Increasing the alkaline content of the reaction mixture above 5M introduced sodalite phase in the final product. The properties of the final products were comparable to zeolites synthesized from pure chemical reagents.

Keywords: bauxite, kaolin, aging, crystallization, zeolites

Procedia PDF Downloads 203

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

Abstract:

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

Procedia PDF Downloads 380

Authors: Preecha Yupapin And Somnath

Abstract:

From the emptiness, the vibration induces the fractal, and the strings are formed. From which the first elementary particle groups, known as quarks, were established. The neutrino and electron are created by them. More elementary particles and life are formed by organic and inorganic substances. The universe is constructed, from which the multi-universe has formed in the same way. universe assumes that the intense energy has escaped from the singularity cone from the multi-universes. Initially, the single mass energy is confined, from which it is disturbed by the space-time distortion. It splits into the entangled pair, where the circular motion is established. It will consider one side of the entangled pair, where the fusion energy of the strong coupling force has formed. The growth of the fusion energy has the quantum physic phenomena, where the moving of the particle along the circumference with a speed faster than light. It introduces the wave-particle duality aspect, which will be saturated at the stopping point. It will be re-run again and again without limitation, which can say that the universe has been created and expanded. The Bose-Einstein condensate (BEC) is released through the singularity by the wormhole, which will be condensed to become a mass associated with the Sun's size. It will circulate(orbit) along the Sun. the consideration of the uncertainty principle is applied, from which the breath control is followed by the uncertainty condition ∆p∆x=∆E∆t~ℏ. The flowing in-out air into a body via a nose has applied momentum and energy control respecting the movement and time, in which the target is that the distortion of space-time will have vanished. Finally, the body is clean which can go to the next procedure, where the mind can escape from the body by the speed of light. However, the borderline between contemplation to being an Arahant is a vacuum, which will be explained.

Keywords: space-time, relativity, enlightenment, emptiness

Procedia PDF Downloads 53

Authors: Yujiang Wu

Abstract:

As electrical machine (e-machine) power density re-querulents become more stringent in vehicle electrification, mounting a temperature sensor for e-machine stator windings becomes increasingly difficult. This can lead to higher manufacturing costs, complicated harnesses, and reduced reliability. In this paper, we propose a deep-learning method for predicting electric machine winding temperature, which can either replace the sensor entirely or serve as a backup to the existing sensor. We compare the performance of our method, the stateful long short-term memory networks (LSTM) with truncated backpropagation through time (TBTT), with that of linear regression, as well as stateless LSTM with/without residual connection. Our results demonstrate the strength of combining stateful LSTM and TBTT in tackling nonlinear time series prediction problems with long sequence lengths. Additionally, in industrial applications, high-temperature region prediction accuracy is more important because winding temperature sensing is typically used for derating machine power when the temperature is high. To evaluate the performance of our algorithm, we developed a temperature-stratified MSE. We propose a simple but effective data preprocessing trick to improve the high-temperature region prediction accuracy. Our experimental results demonstrate the effectiveness of our proposed method in accurately predicting winding temperature, particularly in high-temperature regions, while also reducing manufacturing costs and improving reliability.

Keywords: deep learning, electrical machine, functional safety, long short-term memory networks (LSTM), thermal management, time series prediction

Procedia PDF Downloads 80

Authors: Sonali Banrjee, Swarup Kumar Mitra, Aritra Acharyya

Abstract:

A piano note recognition method has been proposed by the authors in this paper. The authors have used a comprehensive method for onset detection of each note present in a piano piece followed by segmented short-time Fourier transform (STFT) for the identification of piano notes. The performance evaluation of the proposed method has been carried out in different harsh noisy environments by adding different levels of additive white Gaussian noise (AWGN) having different signal-to-noise ratio (SNR) in the original signal and evaluating the note detection error rate (NDER) of different piano pieces consisting of different number of notes at different SNR levels. The NDER is found to be remained within 15% for all piano pieces under consideration when the SNR is kept above 8 dB.

Keywords: AWGN, onset detection, piano note, STFT

Procedia PDF Downloads 150

Authors: Marinko Skare, Malgorzata Porada Rochon

Abstract:

This paper study the link between energy justice and economic growth. The link between energy justice and growth has not been extensively studied. Here we study the impact and importance of energy justice, as a part of the energy transition process, on economic growth. Our study shows energy justice growth is an important determinant of economic growth and development that should be addressed at the industry and economic levels. We use panel data modeling and causality testing to research the empirical link between energy justice and economic growth. Industry and economy-level policies designed to support energy justice initiatives are beneficial to economic growth. Energy justice is a necessary condition for green growth and sustainability targets.

Keywords: energy justice, economic growth, panel data, energy transition

Procedia PDF Downloads 97

Authors: Naira Ghambaryan, Gagik Hakobyan

Abstract:

Purpose:The study was to evaluate the survival rate of short implants (5-6 mm) functionalized with UV radiation placed in the posterior segments of the atrophied maxilla. Materials and Methods:The study included 47 patients with unilateral/bilateral missing teeth and vertical atrophy of the posterior maxillary area. A total of 64 short UV-functionalized implants and 62 standard implants over 10 mm in length were placed in patients. The clinical indices included the following parameters: ISQБ MBL, OHIP-G scale. Results: For short implants, the median ISQ at placement was 62.2 for primary stability, and the median ISQ at 5 months was 69.6 ISQ. For standart implant, the mean ISQ at placement was 64.3 ISQ, and ISQ after 5 months was 71.6 ISQ. Аfter 6 months mean MBL short implants 0.87 mm, after 1 year, 1.13 mm, after 5 year was 1.48 mm. Аfter 6 months, mean MBL standard implants 0.84 mm, after 1 year, 1.24 mm, after 5 year was 1.58 mm. Mean OHIP-G scores -patients satisfaction with the implant at 4.8 ± 0.3, satisfaction with the operation 4.6 ± 0.4; satisfaction with prosthetics 4.7 ± 0.5. Cumulative 5-year short implants rates was 96.7%, standard implants was 97.4%, and prosthesis cumulative survival rate was 97.2%. Conclusions: Short implants with ultraviolet functionalization for prosthetic rehabilitation of the posterior resorbed maxilla region is a reliable, reasonable alternative to sinus lift, demonstrating fewer complications, satisfactory survival of a 5-year follow-up period, and reducing the number of additional surgical interventions and postoperative complications.

Keywords: short implant, ultraviolet functionalization, atrophic posterior maxilla, prosthodontic rehabilitation

Procedia PDF Downloads 65

Authors: Xiang-Yao Zheng, Jen-Cheng Wang, Joe-Air Jiang

Abstract:

Improving the line ampacity while using existing power grids is an important issue that electricity dispatchers are now facing. Using the information provided by the dynamic thermal rating (DTR) of transmission lines, an overhead power grid can operate safely. However, dispatchers usually lack real-time DTR information. Thus, this study proposes a long-short-term memory (LSTM)-based method, which is one of the neural network models. The LSTM-based method predicts the DTR of lines using the weather data provided by Central Weather Bureau (CWB) of Taiwan. The possible thermal bottlenecks at different locations along the line and the margin of line ampacity can be real-time determined by the proposed LSTM-based prediction method. A case study that targets the 345 kV power grid of TaiPower in Taiwan is utilized to examine the performance of the proposed method. The simulation results show that the proposed method is useful to provide the information for the smart grid application in the future.

Keywords: electricity dispatch, line ampacity prediction, dynamic thermal rating, long-short-term memory neural network, smart grid

Procedia PDF Downloads 270

Authors: Kassa Endalamaw Rewnu

Abstract:

The variability properties of a quasar sample, spectroscopically complete to magnitude J = 22.0, are investigated on a time baseline of 2 years using three different photometric bands (U, J and F). The original sample was obtained using a combination of different selection criteria: colors, slitless spectroscopy and variability, based on a time baseline of 1 yr. The main goals of this work are two-fold: first, to derive the percentage of variable quasars on a relatively short time baseline; secondly, to search for new quasar candidates missed by the other selection criteria; and, thus, to estimate the completeness of the spectroscopic sample. In order to achieve these goals, we have extracted all the candidate variable objects from a sample of about 1800 stellar or quasi-stellar objects with limiting magnitude J = 22.50 over an area of about 0.50 deg2. We find that > 65% of all the objects selected as possible variables are either confirmed quasars or quasar candidates on the basis of their colors. This percentage increases even further if we exclude from our lists of variable candidates a number of objects equal to that expected on the basis of `contamination' induced by our photometric errors. The percentage of variable quasars in the spectroscopic sample is also high, reaching about 50%. On the basis of these results, we can estimate that the incompleteness of the original spectroscopic sample is < 12%. We conclude that variability analysis of data with small photometric errors can be successfully used as an efficient and independent (or at least auxiliary) selection method in quasar surveys, even when the time baseline is relatively short. Finally, when corrected for the different intrinsic time lags corresponding to a fixed observed time baseline, our data do not show a statistically significant correlation between variability and either absolute luminosity or redshift.

Keywords: nuclear activity, galaxies, active quasars, variability

Procedia PDF Downloads 60

Authors: Sirus Mohammadi, Sara Ansari, Darush dehghan, Habib Hoshyari

Abstract:

Batteries for storage of electricity from solar and wind generation farms are a key element in the success of sustainability. In recent years, due to large integration of Renewable Energy Sources (RESs) like wind turbine and photovoltaic unit into the Micro-Grid (MG), the necessity of Battery Energy Storage (BES) has increased dramatically. The BES has several benefits and advantages in the MG-based applications such as short term power supply, power quality improvement, facilitating integration of RES, ancillary service and arbitrage. This paper presents the cost-based formulation to determine the optimal size of the BES in the operation management of MG. Also, some restrictions, i.e. power capacity of Distributed Generators (DGs), power and energy capacity of BES, charge/discharge efficiency of BES, operating reserve and load demand satisfaction should be considered as well. In this paper, a methodology is proposed for the optimal allocation and economic analysis of ESS in MGs on the basis of net present value (NPV). As the optimal operation of an MG strongly depends on the arrangement and allocation of its ESS, economic operation strategies and optimal allocation methods of the ESS devices are required for the MG.

Keywords: microgrid, energy storage system, optimal sizing, net present value

Procedia PDF Downloads 480

Authors: Kwa-Sur Tam, Byung O. Kang

Abstract:

By using different ranges of daily sky clearness index defined in this paper, any day can be classified as a clear sky day, a partly cloudy day or a cloudy day. This paper demonstrates how short-term forecasting of solar irradiation can be improved by taking into consideration the type of day so defined. The source of day type dependency has been identified. Forecasting methods that take into consideration of day type have been developed and their efficacy have been established. While all methods that implement some form of adjustment to the cloud cover forecast provided by the U.S. National Weather Service provide accuracy improvement, methods that incorporate day type dependency provides even further improvement in forecast accuracy.

Keywords: day types, forecast methods, National Weather Service, sky cover, solar energy

Procedia PDF Downloads 452

Authors: A. Hadadi, M. Abdollahi, A. Dustmohammadi

Abstract:

The growing use of DGs in distribution networks provide many advantages and also cause new problems which should be anticipated and be solved with appropriate solutions. One of the problems is transient voltage drop and short circuit in the electrical network, in the presence of distributed generation - which can lead to instability. The appearance of the short circuit will cause loss of generator synchronism, even though if it would be able to recover synchronizing mode after removing faulty generator, it will be stable. In order to increase system reliability and generator lifetime, some strategies should be planned to apply even in some situations which a fault prevent generators from separation. In this paper, one fault current limiter is installed due to prevent DGs separation from the grid when fault occurs. Furthermore, an innovative objective function is applied to determine the impedance optimal amount of fault current limiter in order to improve transient stability of distributed generation. Fault current limiter can prevent generator rotor's sudden acceleration after fault occurrence and thereby improve the network transient stability by reducing the current flow in a fast and effective manner. In fact, by applying created impedance by fault current limiter when a short circuit happens on the path of current injection DG to the fault location, the critical fault clearing time improve remarkably. Therefore, protective relay has more time to clear fault and isolate the fault zone without any instability. Finally, different transient scenarios of connection plan sustainability of small scale synchronous generators to the distribution network are presented.

Keywords: critical clearing time, fault current limiter, synchronous generator, transient stability, transient states

Procedia PDF Downloads 179

Authors: F. Lazzeri, I. Reiter

Abstract:

Energy production optimization has been traditionally very important for utilities in order to improve resource consumption. However, load forecasting is a challenging task, as there are a large number of relevant variables that must be considered, and several strategies have been used to deal with this complex problem. This is especially true also in microgrids where many elements have to adjust their performance depending on the future generation and consumption conditions. The goal of this paper is to present a solution for short-term load forecasting in microgrids, based on three machine learning experiments developed in R and web services built and deployed with different components of Cortana Intelligence Suite: Azure Machine Learning, a fully managed cloud service that enables to easily build, deploy, and share predictive analytics solutions; SQL database, a Microsoft database service for app developers; and PowerBI, a suite of business analytics tools to analyze data and share insights. Our results show that Boosted Decision Tree and Fast Forest Quantile regression methods can be very useful to predict hourly short-term consumption in microgrids; moreover, we found that for these types of forecasting models, weather data (temperature, wind, humidity and dew point) can play a crucial role in improving the accuracy of the forecasting solution. Data cleaning and feature engineering methods performed in R and different types of machine learning algorithms (Boosted Decision Tree, Fast Forest Quantile and ARIMA) will be presented, and results and performance metrics discussed.

Keywords: time-series, features engineering methods for forecasting, energy demand forecasting, Azure Machine Learning

Procedia PDF Downloads 281

Authors: B. E. Weber, N. Vrielink, M. G. Rietbergen

Abstract:

This paper explores the long-term effects of the Energy Box trajectory on households in the private rental sector, specifically households experiencing energy poverty. The concept of energy poverty has been getting increasing attention among policymakers over the past few years. In the Netherlands, as far as we know, there are no national policies on alleviating energy poverty, which negatively impacts energy-poor households. The Energy Box can help households experiencing energy poverty by stimulating them to improve the energy efficiency of their home by changing their energy-saving behavior. Important long-term effects are that respondents indicate that they live in a more environmentally friendly way and that they save money on their energy bills. Households feel engaged with the concept of energy-saving and can see the benefits of changing their energy-saving behavior. Respondents perceived the Energy Box as a means to live more environmentally friendly, instead of it solely being a means to save money on energy bills. The findings show that most respondents signed up for the Energy Box are interested in energy-saving as a lifestyle choice instead of a financial choice, which would likely be the case for households experiencing energy poverty.

Keywords: energy-saving behavior, energy poverty, poverty, private rental sector

Procedia PDF Downloads 91

Authors: Kostas Philippopoulos, Chris G. Tzanis, Despina Deligiorgi

Abstract:

Climate change adaptation requires the exploitation of renewable energy sources such as wind. However, climate variability can affect the regional wind energy potential and consequently the available wind power production. The goal of the research project is to examine the impact of atmospheric circulation on wind energy production over Greece. In the context of synoptic climatology, the proposed novel methodology employs Self-Organizing Maps for grouping and classifying the atmospheric circulation and nationally-aggregated capacity factor time series for a 30-year period. The results indicate the critical effect of atmospheric circulation on the national aggregated wind energy production values and therefore address the issue of optimum distribution of wind farms for a specific region.

Keywords: wind energy, atmospheric circulation, capacity factor, self-organizing maps

Procedia PDF Downloads 142

Authors: Asma Perveen, M. P. Jahan

Abstract:

Ni alloys have managed to cover wide range of applications such as automotive industries, oil gas industries, and aerospace industries. However, these alloys impose challenges while using conventional machining technologies. On the other hand, Micro-Electro-Discharge machining (micro-EDM) is a non-conventional machining method that uses controlled sparks energy to remove material irrespective of the materials hardness. There has been always a huge interest from the industries for developing optimum methodology and parameters in order to enhance the productivity of micro-EDM in terms of reducing machining time and tool wear for different alloys. Therefore, the aims of this study are to investigate the effects of the micro-EDM process parameters, in order to find their optimal values. The input process parameters include voltage, capacitance, and electrode rotational speed, whereas the output parameters considered are machining time, entrance diameter of hole, overcut, tool wear, and crater size. The surface morphology and element characterization are also investigated with the use of SEM and EDX analysis. The experimental result indicates the reduction of machining time with the increment of discharge energy. Discharge energy also contributes to the enlargement of entrance diameter as well as overcut. In addition, tool wears show reduction with the increase of discharge energy. Moreover, crater size is found to be increased in size along with the increment of discharge energy.

Keywords: micro holes, micro EDM, Ni Alloy, discharge energy

Procedia PDF Downloads 261

Authors: Arvind Dhingra, Tejinder Singh Saggu

Abstract:

As the energy demands rise and the pollution levels grow, it becomes imperative for us to save energy in all the fields in which it is used. The industrial sector is the major commercial energy consuming sector in India, where electrical energy is the most common and widely used type of energy. As the demand and price of energy are increasing day by day, therefore, the subject of energy conservation is a concern for most energy users particularly industry. Judicious use of energy becomes imperative for third world developing country being presence of energy crisis. This paper provides some measure for energy saving that can be commonly recommended for a rolling unit of steel industry. A case of hot rolling unit in JSL Stainless Ltd., Hisar for energy conservation is given. Overall improvement in energy consumption in light of the stated recommendation is illustrated along with the proposed utilization of the techniques and their applications. Energy conservation in conventional motor with replacement or use of star delta star converter, reduction in cable losses, replacement of filament of LED lamps, replacement of conventional transformer with cast resin dry type transformer and provision of energy management system for energy conservation and per unit production cost reduction are elaborated in this paper.

Keywords: energy audit, energy conservation, energy efficient motors

Procedia PDF Downloads 510

Authors: Muhammad Afzal, Muhammad Sajjad

Abstract:

Climate change has become a global environmental challenge and it has affected the world’s economy. Its impact is widespread across all major sectors of the economy i.e. agriculture, industry, and services sectors. This study attempts to measure the long run as well as the short-run dynamic between energy; environment and economic growth by using Autoregressive Distributed Lag (ARDL) bound testing approach at aggregate as well as sectoral level. We measured the causal relationship between electricity consumption, fuel consumption, CO₂ emission, and real Gross Domestic Product (GDP) for the period of 1980 to 2016 for Pakistan. Our co-integration results reveal that all the variables are co-integrated at aggregate as well as at sectoral level. Electricity consumption shows two-way casual relation at for industry, services and aggregate level. The inverted U-Curve hypothesis tested the relationship between greenhouse gas emissions and per capita GDP and results supported the Environment Kuznet Curve (EKC) hypothesis. This study cannot ignore the importance of energy for economic growth but prefers to focus on renewable and green energy to pave on the trajectory of development.

Keywords: climate change, economic growth, energy, environment

Procedia PDF Downloads 154

Authors: Jiahui Song, Ravindra P. Joshi

Abstract:

The use of high-intensity, short-duration electric pulses is a promising development with many biomedical applications. The uses include irreversible electroporation for killing abnormal cells, reversible poration for drug and gene delivery, neuromuscular manipulation, and the shrinkage of tumors, etc. High intensity, short-duration electric pulses result in the creation of high-density, nanometer-sized pores in the cellular membrane. This electroporation amounts to localized modulation of the transverse membrane conductance, and effectively provides a voltage shunt. The electrically controlled changes in the trans-membrane conductivity could be used to affect neural traffic and action potential propagation. A rat was taken as the representative example in this research. The simulation study shows the pathway from the sensorimotor cortex down to the spinal motoneurons, and effector muscles could be reversibly blocked by using high-intensity, short-duration electrical pulses. Also, actual experimental observations were compared against simulation predictions.

Keywords: action potential, electroporation, high-intensity, short-duration

Procedia PDF Downloads 251

Authors: Vaidehi Iyer, Konstantin Borozdin

Abstract:

Time series prediction problems have many important practical applications, but are notoriously difficult for statistical modeling. Recently, machine learning methods have been attracted significant interest as a practical tool applied to a variety of problems, even though developments in this field tend to be semi-empirical. This paper explores application of Long Short Term Memory based Recurrent Neural Networks to the one-step prediction of time series for both trend and stochastic components. Two types of data are analyzed - daily stock prices, that are often considered to be a typical example of a random walk, - and weather patterns dominated by seasonal variations. Results from both analyses are compared, and reinforced learning framework is used to select more efficient between Recurrent Neural Networks and more traditional auto regression methods. It is shown that both methods are able to follow long-term trends and seasonal variations closely, but have difficulties with reproducing day-to-day variability. Future research directions and potential real world applications are briefly discussed.

Keywords: long short term memory, prediction methods, recurrent neural networks, reinforcement learning

Procedia PDF Downloads 210