Search results for: residential coal combustion

Authors: S. Šupić, M. Malešev, V. Radonjanin, M. Radeka, M. Laban

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The production of low cost and environmentally friendly products represents an important step for developing countries. Biomass is one of the largest renewable energy sources, and Serbia is among the top European countries in terms of the amount of available and unused biomass. Substituting cement with the ashes obtained by the combustion of biomass would reduce the negative impact of concrete industry on the environment and would provide a waste valorization by the reuse of this type of by-product in mortars and concretes manufacture. The study contains data on physical properties, chemical characteristics and pozzolanic properties of obtained biomass ashes: wheat straw ash and mixture of wheat and soya straw ash in Serbia, which were, later, used as supplementary cementitious materials in preparation of mortars. Experimental research of influence of biomass ashes on physical and mechanical properties of cement mortars was conducted. The results indicate that the biomass ashes can be successfully used in mortars as substitutes of cement without compromising their physical and mechanical performances.

Keywords: biomass, ash, cementitious material, mortar

Procedia PDF Downloads 166

Authors: Sudhakar Saroj, Satya Vir Singh

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Undoped and Fe doped TiO₂, Ti₁₋ₓFeₓO₂ (x=0.00, 0.01, 0.03, 0.05, 0.07 and 0.09) have been synthesized by solution combustion method using Titanium (IV) oxide as a precursor, and also were characterized by XRD, DRS, FTIR, XPS, SEM, and EDX. The formation of anatase phase of undoped and Fe TiO₂ nanoparticles were confirmed by XRD, and the average crystallite size was determined by Debye-Scherer's equation. The DRS analysis indicates the shifting of light absorbance in visible region from UV region with increasing the doping concentration in TiO₂. The vibrational band of the Ti-O lattice was confirmed by the FT-IR spectrum. The XPS results confirm the presence of elements of titanium, oxygen and iron in the synthesized samples and determine the binding energy of elements. SEM image of the above-synthesized nanoparticles showed the spherical shape of nanoparticles. The purities of the synthesized nanoparticles were confirmed by EDX analysis. The photocatalytic activities of the synthesized nanoparticles were tested by studying the degradation of dye (Direct Blue 199) in the photocatalytic reactor. The Ti₀.₉₇Fe₀.₀₃O₂ photocatalyst shows highest photodegradation activity among all the synthesized undoped and Fe doped TiO₂ photocatalyst.

Keywords: direct blue 199, nanoparticles, TiO₂, photodegradation

Procedia PDF Downloads 216

Authors: James Wapyer, Simon A. Kawagle

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The current downturn in the metal and oil prices has significantly affected the mineral and petroleum sectors of Papua New Guinea. The sectors have not grown substantially in the last three years compared to previous years. Resources of several projects have not been proved up as well as feasibility studies not undertaken on advanced projects. In the 2012-2015 periods, however, development licences for four projects have been granted - the Solwara-1 project in the Manus Basin, the Woodlark project, the Crater Mountains project and the Stanley gas-condensate project. There has been some progress on three advanced projects – Frieda River copper-gold porphyry, Mount Kare gold, and the Wafi-Golpu projects. The oilfields are small by world standard but have been high rates of production. The developments of liquefied natural gas projects are progressing well and the first LNG project with ExxonMobil and partners shipped its first cargo in May 2014, the second with Total and partners involving Elk-Antelope gas-condensate fields is in its development stage, and the third with Horizon Oil and partners involving gas fields in the western Papuan basin is in the planning stage. Significantly, in the years 2012-2015, the country has exported liquefied natural gas, nickel, cobalt and chromium, and has granted exploration licences for iron-sands and coal measures for the first time.

Keywords: exploration, mineral, Papua New Guinea, petroleum

Procedia PDF Downloads 251

Authors: Pooja Rawat, Rakhi Tyagi

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Globally, almost 3 billion people rely on biomass (wood, charcoal, dung and crop residues) and coal as their primary source of domestic energy. Cooking and heating with solid fuels on open fire give rise to major pollutants. Women are primarily affected by these pollutants as they spend most of their time in the house. The WHO World Health Report 2002 estimates that indoor air pollution (IAP) is responsible for 2.7% of the loss of disability adjusted life years (DALYs) worldwide and 3.7% in high mortality developing countries. Indoor air pollution has the potential to not only impact health, but also impact the general economic well-being of the household. Exposure to high level of household pollution lead to acute and chronic respiratory conditions (e.g.: pneumonia, chronic obstructive pulmonary disease, lung cancer and cataract). There has been many strategies for reducing IAP like subsidize cleaner fuel technologies, for example use of kerosene rather than traditional biomass fuels. Another example is development, promotion of 'improved cooking stoves'. India, likely ranks second- distributing over 12 million improved stoves in the first seven years of a national program to develop. IAP should be reduced by understanding the welfare effects of reducing IAP within households and to understanding the most cost effective way to reduce it.

Keywords: open fire, indoor pollution, lung diseases, indoor air pollution

Procedia PDF Downloads 277

Authors: Md. Nazmul Haque, Mahinur Rahman

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The objective of the research is to determine the quantity of household waste generated and forecast the future condition of Ward No 24 (Nirala). For performing that, three core issues are focused: (i) the capacity and service area of the dumping stations; (ii) the present waste generation amount per capita per day; (iii) the responsibility of the local authority in the household waste collection. This research relied on field survey-based data collection from all stakeholders and GIS-based secondary analysis of waste collection points and their coverage. However, these studies are mostly based on the inherent forecasting approaches, cannot predict the amount of waste correctly. The findings of this study suggest that Nirala is a formal residential area introducing a better approach to the waste collection - self-controlled and collection system. Here, a forecasting model proposed for waste generation as Y = -2250387 + 1146.1 * X, where X = year.

Keywords: eco-friendly environment, household waste, linear regression, waste management

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Authors: Hao Liu, Lihui Zheng, Chinedu J. Okere, Chao Wang, Xiangchun Wang, Peng Zhang

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The coalbed methane (CBM) extraction industry (an unconventional energy source) is yet to promulgated an established standard code of practice for the experimental evaluation of sensitivity damage of coal samples. The existing experimental process of previous researches mainly followed the industry standard for conventional oil and gas reservoirs (CIS). However, the existing evaluation method ignores certain critical differences between CBM reservoirs and conventional reservoirs, which could inevitably result in an inaccurate evaluation of sensitivity damage and, eventually, poor decisions regarding the formulation of formation damage prevention measures. In this study, we propose improved experimental guidelines for evaluating seepage sensitivity damage of CBM reservoirs by leveraging on the shortcomings of the existing methods. The proposed method was established via a theoretical analysis of the main drawbacks of the existing methods and validated through comparative experiments. The results show that the proposed evaluation technique provided reliable experimental results that can better reflect actual reservoir conditions and correctly guide future development of CBM reservoirs. This study is pioneering the research on the optimization of experimental parameters for efficient exploration and development of CBM reservoirs.

Keywords: coalbed methane, formation damage, permeability, unconventional energy source

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Authors: Saeed Vahidifar, Mohammad Nakhaee Sharif, Mohammad Ghaffari

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Few people would dispute the fact that one of the most common applications of energy is creating comfort in buildings, so it is probably true to say that management of energy consumption is required due to the environmental issues and increasing the efficiency of mechanical systems. From the geographical point of view, Iran is located in a warm and semi-arid region; therefore, air-cooled chillers are usually used for cooling residential buildings, commercial buildings, medical buildings, etc. In this study, a heat exchanger was designed for providing laundry hot water by utilizing condenser heat lost base on analytical results of a 540-bed hospital in the city of Mashhad in Iran. In this paper, by using the analytical method, energy consumption reduces about 13%, and coefficient of performance increases a bit. Results show that this method can help in the management of energy consumption a lot.

Keywords: air cooled chiller, energy management, environmental issues, heat exchanger, hospital laundry system

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Authors: Herviyanti, Gusnidar, M. Harianti

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The objective of this research were: a) using low-rank coal (subbituminous) as main humate material sources because this material will not be anthracite, and cannot using to be an energy sources b) to examine residual effects of humic matter from subbituminous which was combined with P fertilizers to adsorp Al and Fe metal, improving soil fertility, and increasing P fertilizing efficiency and Oxisol productivity. Therefore, optimalization crop productivity of upland rice can be achieved. The experiment was designed using a 3 x 4 factorial with 3 replications in randomly groups design. The 1st factor was 3 ways incubating humate material with P-fertilizer, which are: I1 = Incubation of humate material 1 week, then incubation P-fertilizers 1 week; I2 = Incubation of humate materials and P fertilizers directly into the soil for 2 weeks; and I3 = humate material and P fertilizer mixed for 1 week, then incubation to the soil for 1 week. The 2nd factor was residual effects of humate material and P-fertilizer combination which are 4 doses H1 = 400 ppm (0.8 Mg/ha) + 100% R; H2 = 400 ppm + 75% R; H3 = 800 ppm (1.6 Mg/ha) + 100% R,; and H4 = 800 ppm + 75% R. The 2nd year research results showed that the best treatment was founded residue effect of 800 ppm humate material and 100% R P-fertilizer doses in I3 way incubation that is equal to 6.19 t ha-1 upland rice yield. However, this result is almost the same as residual effects of 800 ppm humate material + 75% R P-fertilizer doses and upland rice yield the 1st year. It was concluded that addition of humate material can given the efficiency of P-fertilizer using up to 25% until the 2nd season planted.

Keywords: humate materials, P-fertilizer, subbituminous, upland rice

Procedia PDF Downloads 362

Authors: Ala’a H. Al-Muhtaseb, Farrukh Jamil, Lamya Al-Haj, Mohab Al-Hinai

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Bio-glycerol is considered as high boiling polar triol and immiscible with fossil fuel fractions due to which it is transformed into its respective ketals and acetals which help to improve the quality of diesel emitting less amount of aldehydes and carbon monoxide. Solketal visual appearance is transparent and it is odorless organic liquid used as fuel additive for diesel to improve its cold flow properties. Condensation of bio-glycerol with bio-acetone in presence of beta zeolite has been done for synthesizing solketal. It was observed that glycerol conversion and selectivity of solketal was largely effected by temperature, as it increases from 40 ºC to 60 ºC the conversion of glycerol rises from 80.04 % to 94.26 % and selectivity of solketal from 80.0 % to 94.21 % but further increase in temperature to 100 ºC glycerol conversion reduced to 93.06 % and solketal selectivity to 92.08 %. At the optimum conditions, the bio-glycerol conversion and solketal yield were about 94.26% and 94.21wt% respectively. This process offers an attractive route for converting bio-glycerol, the main by-product of biodiesel to solketal with bio-acetone; a value-added green product with potential industrial applications as a valuable green fuel additive or combustion promoter for gasoline/diesel engines.

Keywords: bio-acetone, bio-glycerol, acetylation, solketal

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Authors: Jalpit B. Prajapati, Ketankumar G. Patel

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Palm oil may be employed in diesel engine as an alternative fuel. Biofuel has so far been backed by government policies in the quest for low carbon fuel in the near future and promises to ensure energy security through partially replacing fossil fuels. This paper presents an experimental investigation of performance and emission characteristics by using palm oil in diesel engine. The properties of palm oil can be compared favorably with the characteristics required for internal combustion engine fuels especially diesel engine. Experiments will be performed for fixed compression ratio i.e. 18 using biodiesel-diesel blends i.e. B0, B10, B20, B30, B40, B50 with load variation from no load to full load and compared with base cases i.e. engine using diesel as a fuel. The parameters studied in performance characteristics are brake power, brake specific fuel consumption and brake thermal efficiency, in emission characteristics are carbon monoxide, unburnt hydrocarbons and nitrogen oxide. After experimental results B20 (20% palm oil and 80% diesel) is best in performance, but NOx formation is little higher in B20.

Keywords: palm biodiesel, performance, emission, diesel-biodiesel blend

Procedia PDF Downloads 344

Authors: Farrukh Jamil, Ala'a H. Al-Muhtaseb, Lamya Al-Haj, Mohab A. Al-Hinai

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Glycerol is considered as high boiling polar triol and immiscible with fossil fuel fractions due to which it is transformed into its respective ketals and acetals which help to improve the quality of diesel emitting less amount of aldehydes and carbon monoxide. Solketal visual appearance is transparent, and it is odorless organic liquid used as a fuel additive for diesel to improve its cold flow properties. Condensation of bio-glycerol with bio-acetone in presence of beta zeolite has been done for synthesizing solketal. It was observed that glycerol conversion and selectivity of solketal was largely effected by temperature, as it increases from 40 ºC to 60 ºC the conversion of glycerol rises from 80.04 % to 94.26 % and selectivity of solketal from 80.0 % to 94.21 % but further increase in temperature to 100 ºC glycerol conversion reduced to 93.06 % and solketal selectivity to 92.08 %. At the optimum conditions, the bio-glycerol conversion and solketal yield were about 94.26% and 94.21wt% respectively. This process offers an attractive route for converting bio-glycerol, the main by-product of biodiesel to solketal with bio-acetone; a value-added green product with potential industrial applications as a valuable green fuel additive or combustion promoter for gasoline/diesel engines.

Keywords: bio-glycerol, catalyst, green additive, biomass

Procedia PDF Downloads 220

Authors: Tolga Barisik, Ali Fuat Guneri, K. Dastan

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Major industrial facilities have a high potential for fire risk. In particular, the indices used for the detection of hidden fire are used very effectively in order to prevent the fire from becoming dangerous in the initial stage. These indices provide the opportunity to prevent or intervene early by determining the stage of the fire, the potential for hazard, and the type of the combustion agent with the percentage values of the ambient air components. In this system, artificial neural network will be modeled with the input data determined using the Levenberg-Marquardt algorithm, which is a multi-layer sensor (CAA) (teacher-learning) type, before modeling the modeling methods in the literature. The actual values produced by the indices will be compared with the outputs produced by the network. Using the neural network and the curves to be created from the resulting values, the feasibility of performance determination will be investigated.

Keywords: artifical neural networks, fire, Graham Index, levenberg-marquardt algoritm, oxygen decrease percentage index, risk assessment, Trickett Index

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

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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

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Authors: Kemal Çomakli, Uğur Çakir, Ayşegül Çokgez Kuş, Erol Şahin

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Kind of energy that buildings need changes in various types, like heating energy, cooling energy, electrical energy and thermal energy for hot top water. Usually the processes or systems produce thermal energy causes emitting pollutant emissions while they produce heat because of fossil fuels they use. A lower consumption of thermal energy will contribute not only to a reduction in the running costs, but also in the reduction of pollutant emissions that contribute to the greenhouse effect and a lesser dependence of the hospital on the external power supply. Cogeneration or CHP (Combined heat and Power) is the system that produces power and usable heat simultaneously. Combined production of mechanical or electrical and thermal energy using a simple energy source, such as oil, coal, natural or liquefied gas, biomass or the sun; affords remarkable energy savings and frequently makes it possible to operate with greater efficiency when compared to a system producing heat and power separately. Because of the life standard of humanity in new age, energy sources must be continually and best qualified. For this reason the installation of a system for the simultaneous generation of electrical, heating and cooling energy would be one of the best solutions if we want to have qualified energy and reduce investment and operating costs and meet ecological requirements. This study aims to bring out the contributions of cogeneration systems to the environment and sustainability by saving the energy and reducing the emissions.

Keywords: sustainability, cogeneration systems, energy economy, energy saving

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Authors: Harry Aginta

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Using Phillips curve framework, this paper seeks for new empirical evidence on the relationship between inflation and output in a major emerging economy. By exploiting sub-national data, the contribution of this paper is threefold. First, it resolves the issue of using on-target national inflation rates that potentially causes weakening inflation-output nexus. This is very relevant for Indonesia as its central bank has been adopting inflation targeting framework based on national consumer price index (CPI) inflation. Second, the study tests the relevance of mining sector in output gap estimation. The test for mining sector is important to control for the effects of mining regulation and nominal effects of coal prices on real economic activities. Third, the paper applies panel econometric method by incorporating regional variation that help to improve model estimation. The results from this paper confirm the strong presence of Phillips curve in Indonesia. Positive output gap that reflects excess demand condition gives rise to the inflation rates. In addition, the elasticity of output gap is higher if the mining sector is excluded from output gap estimation. In addition to inflation adaptation, the dynamics of exchange rate and international commodity price are also found to affect inflation significantly. The results are robust to the alternative measurement of output gap

Keywords: Phillips curve, inflation, Indonesia, panel data

Procedia PDF Downloads 105

Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

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Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: electrical disaggregation, DTW, general appliance modeling, event detection

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Authors: Rawan Aljabbari, Thamer Alomayri, Faisal G. Al-Maqate, Abeer Al Suwat

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For environmentally friendly innovative technologies and a sustainable future, fly ash/TiO₂ thin film nanocomposites are essential. Fly ash will be doped with titanium dioxide in this work in order to better understand its optical characteristics and employ it in semiconductor electrical devices. This study focused on the structure, morphology, and optical properties of fly ash/TiO₂ thin films. The spin-coating technique was used to create thin coatings of fly ash/TiO₂. For the first time, the doping of TiO₂ in the fly ash host at ratios of 1, 2, and 3 wt% was investigated with the thickness of all samples fixed. When compared to undoped thin films, the surface morphology of the doped thin films was improved. The weakly crystalline structure of the doped fly ash films was verified by XRD. The optical bandgap energy of these films was successfully reduced by the TiO₂ doping, going from 3.9 to 3.5 eV. With increasing dopant concentration, the value of Urbach energy is increasing. The optical band gap is clearly in opposition to the disorder. While it considerably improved the optical conductivity to a value of 4.1 x 10^9 s^(-1), it also raised the refractive index and extinction coefficient. Depending on the TiO₂ doping ratio, the transmittance decreased, and the reflection increased. As the TiO₂ concentration rises, the absorption of photon energy rises, and the absorption coefficient of photon energy is reduced. results in their possible use as solar energy and semiconductor materials.

Keywords: fly ash, structural analysis, optical properties, morphology

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Authors: Alaa Al Hawari, Mohammad Khader, Wael El Hasan, Mahmoud Alijla, Ammar Manawi, Abdelbaki Benamour

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The production of aluminium alloys and ingots -starting from the processing of alumina to aluminium, and the final cast product- was studied using a Life Cycle Assessment (LCA) approach. The studied aluminium supply chain consisted of a carbon plant, a reduction plant, a casting plant, and a power plant. In the LCA model, the environmental loads of the different plants for the production of 1 ton of aluminium metal were investigated. The impact of the aluminium production was assessed in eight impact categories. The results showed that for all of the impact categories the power plant had the highest impact only in the cases of Human Toxicity Potential (HTP) the reduction plant had the highest impact and in the Marine Aquatic Eco-Toxicity Potential (MAETP) the carbon plant had the highest impact. Furthermore, the impact of the carbon plant and the reduction plant combined was almost the same as the impact of the power plant in the case of the Acidification Potential (AP). The carbon plant had a positive impact on the environment when it comes to the Eutrophication Potential (EP) due to the production of clean water in the process. The natural gas based power plant used in the case study had 8.4 times less negative impact on the environment when compared to the heavy fuel based power plant and 10.7 times less negative impact when compared to the hard coal based power plant.

Keywords: life cycle assessment, aluminium production, supply chain, ecological impacts

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Authors: Sol Girouard, Zona Kostic

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A home is often the largest and most expensive purchase a person makes. Whether the decision leads to a successful outcome will be determined by a combination of critical factors. In this paper, we propose a method that efficiently handles all the factors in residential real estate and performs predictions given a feature space with high dimensionality while controlling for overfitting. The proposed method was built on gradient descent and boosting algorithms and uses a mixed optimizing technique to improve the prediction power. Usually, a single model cannot handle all the cases thus our approach builds multiple models based on different subsets of the predictors. The algorithm was tested on 3 million homes across the U.S., and the experimental results demonstrate the efficiency of this approach by outperforming techniques currently used in forecasting prices. With everyday changes on the real estate market, our proposed algorithm capitalizes from new events allowing more efficient predictions.

Keywords: real estate prediction, gradient descent, boosting, ensemble methods, active learning, training

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Authors: Donald C. Lantu, Henndy Ginting, M. Yorga Permana, Dany M. A. Ramdlany

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We constructed a training program for top-talents of a Bank with Scharmer Theory-U as the model. In this training program, we implemented the action learning perspective, as it is claimed to be the most effective one currently available. In the process, participants were encouraged to be more involved, especially compared to traditional lecturing. The goal of this study is to assess the effectiveness of this particular training. The program consists of six days non-residential workshop within two months. Between each workshop, the participants were involved in the works of action learning group. They were challenged by dealing with the real problem related to their tasks at work. The participants of the program were 30 best talents who were chosen according to their yearly performance. Using paired difference statistical test in the behavioral assessment, we found that the training was not effective to increase participants’ leadership competencies. For the future development program, we suggested to modify the goals of the program toward the next stage of development.

Keywords: action learning, behavior, leadership development, Theory-U

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Authors: S. Alotaibi, S. Omer, Y. Su

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The conventional Internal Combustion Engine (ICE) based vehicles are a threat to the environment as they account for a large proportion of the overall greenhouse gas (GHG) emissions in the world. Hence, it is required to replace these vehicles with more environment-friendly vehicles. Electric Vehicles (EVs) are promising technologies which offer both human comfort “noise, pollution” as well as reduced (or no) emissions of GHGs. In this paper, different types of EVs are reviewed and their advantages and disadvantages are identified. It is found that in terms of fuel economy, Plug-in Hybrid EVs (PHEVs) have the best fuel economy, followed by Hybrid EVs (HEVs) and ICE vehicles. Since Battery EVs (BEVs) do not use any fuel, their fuel economy is estimated as price per kilometer. Similarly, in terms of GHG emissions, BEVs are the most environmentally friendly since they do not result in any emissions while HEVs and PHEVs produce less emissions compared to the conventional ICE based vehicles. Fuel Cell EVs (FCEVs) are also zero-emission vehicles, but they have large costs associated with them. Finally, if the electricity is provided by using the renewable energy technologies through grid connection, then BEVs could be considered as zero emission vehicles.

Keywords: electric vehicles, zero emission car, fuel economy, CO₂ footprint

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Authors: Mohamed Adnan Landolsi, Ali F. Almutairi

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The paper addresses the problem of line-of-sight (LOS) vs. non-line-of-sight (NLOS) propagation link identification in ultra-wideband (UWB) wireless networks, which is necessary for improving the accuracy of radiolocation and positioning applications. A LOS/NLOS likelihood hypothesis testing approach is applied based on exploiting distinctive statistical features of the channel impulse response (CIR) using parameters related to the “skewness” of the CIR and its root mean square (RMS) delay spread. A log-normal fit is presented for the probability densities of the CIR parameters. Simulation results show that different environments (residential, office, outdoor, etc.) have measurable differences in their CIR parameters’ statistics, which is then exploited in determining the nature of the propagation channels. Correct LOS/NLOS channel identification rates exceeding 90% are shown to be achievable for most types of environments. Additional improvement is also obtained by combining both CIR skewness and RMS delay statistics.

Keywords: UWB, propagation, LOS, NLOS, identification

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Authors: Igho Ekiugbo, Christos Papanagnou

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The energy sector continues to face increased scrutiny due to climate change challenges emanating from the burning of fossil fuels, such as coal, oil, and gas. These climate change challenges have motivated industry practitioners and researchers alike to gain an interest in the way businesses operate. This paper aimed to investigate and assess how small and medium-sized enterprises (SMEs) are reducing the impact of their operations, especially those within their supply chains, by assessing the sustainability practices they have adopted and implemented as well as the benefits and challenges of adopting such practices. Data will be collected from SMEs operating across the downstream oil and gas sector in Nigeria using questionnaire surveys. To analyse the data, confirmatory factor analysis and regression analysis will be performed. This method is deemed more suitable and appropriate for testing predefined measurements of sustainable supply chain practices as contained in the extant literature. Preliminary observations indicate a consensus on the awareness of the sustainability concept amongst the target participants. To the best of our knowledge, this paper is among the first to investigate the sustainability practices of SMEs operating in the Nigerian oil and gas sector and will therefore contribute to the sustainability and circular economic literature.

Keywords: small and medium-sized enterprises, sustainability practices, supply chains, sustainable supply chain management, corporate sustainability, oil and gas, business performance

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Authors: D. Shobha Rani, M. Muralidhar

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Solar photovoltaic (SPV) power systems can be employed as electrical power sources to meet the daily residential energy needs of rural areas that have no access to grid systems. In view of this, a standalone SPV powered air cooling system is proposed in this paper, which constitutes a dc-dc boost converter, two voltage source inverters (VSI) connected to two brushless dc (BLDC) motors which are coupled to a centrifugal water pump and a fan blower. A simple and efficient Maximum Power Point Tracking (MPPT) technique based on Silver Mean Method (SMM) is utilized in this paper. The air cooling system is developed and simulated using the MATLAB / Simulink environment considering the dynamic and steady state variation in the solar irradiance.

Keywords: boost converter, solar photovoltaic array, voltage source inverter, brushless DC motor, solar irradiance, maximum power point tracking, silver mean method

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Authors: Paramjit Kaur, Harish Kundra

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In the recent years, swarm intelligence based firefly algorithm has become a great focus for the researchers to solve the real time optimization problems. Here, firefly algorithm is used for the application of satellite image classification. For experimentation, Alwar area is considered to multiple land features like vegetation, barren, hilly, residential and water surface. Alwar dataset is considered with seven band satellite images. Firefly Algorithm is based on the attraction of less bright fireflies towards more brightener one. For the evaluation of proposed concept accuracy assessment parameters are calculated using error matrix. With the help of Error matrix, parameters of Kappa Coefficient, Overall Accuracy and feature wise accuracy parameters of user’s accuracy & producer’s accuracy can be calculated. Overall results are compared with BBO, PSO, Hybrid FPAB/BBO, Hybrid ACO/SOFM and Hybrid ACO/BBO based on the kappa coefficient and overall accuracy parameters.

Keywords: image classification, firefly algorithm, satellite image classification, terrain classification

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Authors: José Luis Lorenzo Bayona, Ljiljana Medic-Pejic, Isabel Amez Arenillas, Blanca Castells Somoza

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The communication presents the study results carried out by the Official Laboratory J. M. Madariaga (LOM) of the Polytechnic University of Madrid to analyze the reliability of methane detection systems used in underground mining. Poor firedamp control in work can cause from production stoppages to fatal accidents and since there is currently a great variety of equipment with different functional characteristics, a study is needed to indicate which measurement principles have the highest degree of confidence. For the development of the project, a series of fixed, transportable and portable methane detectors with different measurement principles have been selected to subject them to laboratory tests following the methods described in the applicable regulations. The test equipment has been the one usually used in the certification and calibration of these devices, subject to the LOM quality system, and the tests have been carried out on detectors accessible in the market. The conclusions establish the main advantages and disadvantages of the equipment according to the measurement principle used; catalytic combustion, interferometry and infrared absorption.

Keywords: ATEX standards, gas detector, methane meter, mining safety

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Authors: Ji Hoon Kim, Jong Man Kim, Hyung Woo Lee, Soo Hyung Kim

Abstract:

The applications of nanoenergetic materials (nEMs) could be extended by developing more convenient and reliable ignition methods. However, the underwater ignition of nEMs is a significant challenge because water perturbs the reactants prior to ignition and also quenches the subsequent combustion reaction of nEMs upon ignition. In this study, we developed flash and laser-ignitable nEMs for underwater explosion. This was achieved by adding various carbon nanotubes (CNTs) as the optical igniter into an nEM matrix, composed of Al/CuO nanoparticles. The CNTs absorb the irradiated optical energy and rapidly convert it into thermal energy, and then the thermal energy is concentrated to ignite the core catalysts and neighboring nEMs. The maximum burn rate was achieved by adding 1 wt% CNTs into the nEM matrix. The burn rate significantly decreased with increasing amount of CNTs (≥ 2 wt%), indicating that the optical ignition and controlled-explosion reactivity of nEMs are possible by incorporating an appropriate amount of CNTs.

Keywords: nanoenergetic materials, carbon nanotubes, optical ignition, tunable explosion

Procedia PDF Downloads 284

Authors: Gamal Alamri, Tariq Iqbal

Abstract:

This paper presents an optimum designs and thermal analysis of concrete house in the hot climate of Libya. For this goal we have used BEopt software (building energy optimization) that provides capabilities for estimating residential building design and thermal analysis. The most area of the house that is exposed to the sunlight’s is the roof leading to heat gain. Therefore, house cooling consumes high energy. The cooling energy consumption is three times the heating energy consumption. In order to maintain comfortable indoor conditions in a low-energy house, the entire building envelope needs to be perfectly insulated and prevented from air leakages. Insulated roof is selected to reduce cooling demand, and the paper presents details and BEopt simulation results. Designed house needs 12.02mmbtus/year. Furthermore, the modeling indicates that the designed house is close to achieving the Passive standard.

Keywords: concrete house design, thermal analysis, hot climate, BEopt software

Procedia PDF Downloads 392

Authors: Noura Al Akkari, Aurélie Foucquier, Sylvain Lespinats

Abstract:

Load monitoring is a management process for energy consumption towards energy savings and energy efficiency. Non Intrusive Load Monitoring (NILM) is one method of load monitoring used for disaggregation purposes. NILM is a technique for identifying individual appliances based on the analysis of the whole residence data retrieved from the main power meter of the house. Our NILM framework starts with data acquisition, followed by data preprocessing, then event detection, feature extraction, then general appliance modeling and identification at the final stage. The event detection stage is a core component of NILM process since event detection techniques lead to the extraction of appliance features. Appliance features are required for the accurate identification of the household devices. In this research work, we aim at developing a new event detection methodology with accurate load disaggregation to extract appliance features. Time-domain features extracted are used for tuning general appliance models for appliance identification and classification steps. We use unsupervised algorithms such as Dynamic Time Warping (DTW). The proposed method relies on detecting areas of operation of each residential appliance based on the power demand. Then, detecting the time at which each selected appliance changes its states. In order to fit with practical existing smart meters capabilities, we work on low sampling data with a frequency of (1/60) Hz. The data is simulated on Load Profile Generator software (LPG), which was not previously taken into consideration for NILM purposes in the literature. LPG is a numerical software that uses behaviour simulation of people inside the house to generate residential energy consumption data. The proposed event detection method targets low consumption loads that are difficult to detect. Also, it facilitates the extraction of specific features used for general appliance modeling. In addition to this, the identification process includes unsupervised techniques such as DTW. To our best knowledge, there exist few unsupervised techniques employed with low sampling data in comparison to the many supervised techniques used for such cases. We extract a power interval at which falls the operation of the selected appliance along with a time vector for the values delimiting the state transitions of the appliance. After this, appliance signatures are formed from extracted power, geometrical and statistical features. Afterwards, those formed signatures are used to tune general model types for appliances identification using unsupervised algorithms. This method is evaluated using both simulated data on LPG and real-time Reference Energy Disaggregation Dataset (REDD). For that, we compute performance metrics using confusion matrix based metrics, considering accuracy, precision, recall and error-rate. The performance analysis of our methodology is then compared with other detection techniques previously used in the literature review, such as detection techniques based on statistical variations and abrupt changes (Variance Sliding Window and Cumulative Sum).

Keywords: general appliance model, non intrusive load monitoring, events detection, unsupervised techniques;

Procedia PDF Downloads 57

Authors: Saba Arif, Anam Nadeem, Roman Kalvin, Tanzeel Rashid, Burhan Ali, Juntakan Taweekun

Abstract:

Currently, the energy crisis is taking serious attention. Globally, industries and building are major share takers of energy. 72% of total global energy is consumed by residential houses, markets, and commercial building. Additionally, in appliances air conditioners are major consumer of electricity; about 60% energy is used for cooling purpose in houses due to HVAC units. Energy demand will aid in determining what changes will be needed whether it is the estimation of the required energy for households or instituting conservation measures. Bottom-up model is one of the most famous methods for forecasting. In current research bottom-up model of air conditioners' energy consumption in all income classes in comparison with seasonal variation and hourly consumption is calculated. By comparison of energy consumption of all income classes by usage of air conditioners, total consumption of actual demand and current availability can be seen.

Keywords: air conditioning, bottom up model, income classes, energy demand

Procedia PDF Downloads 223