Search results for: energy consumption analysis

Authors: M. Nuhu, S. Bilal, A. A. Hamisu, J. A. Abbas, Y. Z. Aminu, P. O. Helen

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Exergy and energy analysis of preheating unit of FCCU of KRPC has been calculated and presented in this study. From the design, the efficiency of each heat exchanger was 86%. However, on completion of this work the efficiencies was calculated to be 39.90%, 55.66%, 56.22%, and 57.14% for 16E02, 16E03, 16E04, and 16E05 respectively. 16E04 has the minimum energy loss of 0.86%. The calculated second law and exergy efficiencies of the system were 43.01 and 56.99% respectively.

Keywords: exergy analysis, ideal work, efficiency, exergy destruction, temperature

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Authors: Paola Quintana, Angélica Vaca, Sebastián Villacres, Henry Acurio

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Ecuador through the Organic Law of Energy Efficiency establishes that "Starting in the year 2025, all vehicles that are incorporated into the urban and inter-parroquial public transport service must only be electric”, this marks a foundation for the introduction of electric mobility in the country. The present investigation is based on developing an analysis and projection of the Energy Required for the incorporation of electric buses for public passenger transport in the city of Ambato-Ecuador, taking into account the useful life of the vehicle fleet, number of existing vehicles and analysis of transport routes in the study city. The energy demand based on the vehicular dynamics is analyzed, determination of equations for the calculation of force in the wheel since it is considered a variable of slope due to the fact that this has a great incidence in the autonomy when speaking of electric mobility, later the energy analysis applied to public transport routes, finally a projection of the energy requirement is made based on the change of public transport units according to their useful life.

Keywords: public transport, electric mobility, energy, ecuador

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Authors: Christian Böning, Henrik Prinzhorn, Eric C. Hund, Malte Stonis

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In this article, the flexible job-shop scheduling problem is extended by consideration of energy costs which arise owing to the power peak, and further decision variables such as work in process and throughput time are incorporated into the objective function. This enables a production plan to be simultaneously optimized in respect of the real arising energy and logistics costs. The energy-costs-aware flexible job-shop scheduling problem (EFJSP) which arises is described mathematically, and a memetic algorithm (MA) is presented as a solution. In the MA, the evolutionary process is supplemented with a local search. Furthermore, repair procedures are used in order to rectify any infeasible solutions that have arisen in the evolutionary process. The potential for lowering the real arising costs of a production plan through consideration of energy consumption levels is highlighted.

Keywords: energy costs, flexible job-shop scheduling, memetic algorithm, power peak

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Authors: Tesfaye Mengistu

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This thesis aims to investigate the effectiveness of Reinforcement Learning (RL) for Autonomous Energy Management solutions. The study explores the potential of Model Free RL approaches, such as Monte Carlo RL and Q-learning, to improve energy management by autonomously adjusting energy management strategies to maximize efficiency. The research investigates the implementation of RL algorithms for optimizing energy consumption in a single-agent environment. The focus is on developing a framework for the implementation of RL algorithms, highlighting the importance of RL for enabling autonomous systems to adapt quickly to changing conditions and make decisions based on previous experiences. Moreover, the paper proposes RL as a novel energy management solution to address nations' CO2 emission goals. Reinforcement learning algorithms are well-suited to solving problems with sequential decision-making patterns and can provide accurate and immediate outputs to ease the planning and decision-making process. This research provides insights into the challenges and opportunities of using RL for energy management solutions and recommends further studies to explore its full potential. In conclusion, this study provides valuable insights into how RL can be used to improve the efficiency of energy management systems and supports the use of RL as a promising approach for developing autonomous energy management solutions in residential buildings.

Keywords: artificial intelligence, reinforcement learning, monte carlo, energy management, CO2 emission

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Authors: Eman Simbawa, Budur Alasmri, Hanan Munahir, Hanin Munahir

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Solar energy has become currently the subject of attention around the world and is undergoing many researches and studies. Using solar energy, which is a renewable energy, is aligned with the Saudi Vision 2030. People are more aware of it and are starting to use it more for environmental and economical reasons. A questionnaire was conducted in this paper to measure the awareness of people in Saudi Arabia regarding solar energy and their attitude towards it. Then, two kinds of air conditioners (one powered by electricity only and one powered by solar panels and electricity) are compared in terms of their cost over a period of 20 years. This will help the users to decide which kind of device to use depending on its cost. The result shows that as the electricity tariffs in Saudi Arabia increases, depending on the sector, the solar air conditioner is cheaper. In fact, if the tariff in the future increases to reach 50 Halalah/kWh, the solar air conditioner is more economical. This will influence users to buy more solar powered devices, and it will decrease the consumption of electricity. Therefore, the dependence on oil will decrease.

Keywords: Airconditioner, solar energy, photovoltaic cells, present value

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Authors: Isaiah Phillip Smith

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It is reported that alcohol consumption accounts for 3 million annual deaths globally, thus, it is a significant public health challenge internationally. The excessive consumption of alcohol is argued in literature to be related to problematic behaviors like crime, accident, fighting, violence, and unprotected sex, among others. Alcohol consumption among university students in South Africa particularly is considered endemic – with a prevalence rate of 25.27%, 32.34%, and 23.34% across universities, colleges, and high schools. Adopting the tenets of social learning and ecological theories, the culture of drinking amongst male university students is critically explored. This study found that age, gender, early exposure to alcohol, and peer pressure are significant factors contributing to alcohol consumption amongst university students. While participants acknowledged that moderate and responsible consumption of alcohol is necessary, they agree that it does not translate to responsible drinking behaviours.

Keywords: alcohol, drinking, university, students

Procedia PDF Downloads 114

Authors: Rishabh Sharma

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The main design parameter of WSN (wireless sensor network) is the energy consumption. To compensate this parameter, hierarchical clustering is a technique that assists in extending duration of the networks life by efficiently consuming the energy. This paper focuses on dealing with the WSNs and the FIS (fuzzy interface system) which are deployed to enhance the BEENISH protocol. The node energy, mobility, pause time and density are considered for the selection of CH (cluster head). The simulation outcomes exhibited that the projected system outperforms the traditional system with regard to the energy utilization and number of packets transmitted to sink.

Keywords: wireless sensor network, sink, sensor node, routing protocol, fuzzy rule, fuzzy inference system

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Authors: G. S. Sumanasekara, A. Balasuriya

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Introduction: In Sri Lanka studies reveal higher trend in prevalence of diabetes. The office employees have sedentary life style and their eating patterns changed due to nutritional transition. Further overall, urban and rural pre diabetes is also increasing. Objectives - Study the general food pattern of office employees and its relation to overweight/obesity and prevalence of diabetes among them. Method: The data was collected from office employees between 30-60 years (n-400).Data analyzed using SPSS 16 version.The Study design was a descriptive cross sectional study. The study setting was Ministry of Economic Development. Anthropometric measurements and blood glucose assessed by trained nurses. Dietary pattern was studied through a food frequency questionairre thereby calculated daily nutrient intakes. Results: Mean age of office employees were 38.98 SD (7.033) CI=95%) and 245 females (61.2%) 155 males (38.8 %) ,Nationality includes Sinhala (67.5%), Tamil(20%), and Muslims (12.5%).Owerweight(7,1.8%), obese male(36,9%), obese female(66,16%)/ diabetes/obese(18,4.5%) out of 127(31.8%) who were above the normal BMI whereas 273(68.2) were within the normal. Mean BMI was 24.1593.Mean Blood sugar level was 104.646,SD(16.018).12% consume tobacco products,17.8 consumed alcohol.15.8% had nutrition training. Two main dietary patterns identified who were vegetarians and non vegetarians .Mean energy intake 1727.1, (SD 4.97), Mean protein consumption(11.33, SD 1.811), Mean fat consumption(24.07, SD 4.131),Mean CHO consumption (64.56, SD 4.54), Mean Fibre (30.05, SD 17.9), Mean cholesterol(16.85, SD 17.22), Energy intake was higher in non vegetarians and larger propotion of energy derived from proteins , and fat. Their carbohydrate and cholesterol intake was also higher. Tamils were mostly vegetarians. Mainly BMI were within normal range(18.5-23.5) whereas Muslims who had higher energy intakes showed BMI above the normal. Conclusion: Two distinct dietary patterns identified. Different ethnic groups consume different diets with different nutrient composition. Dietary pattern has a relation to overweight. Overweight related to high blood glucose levels but some overweight subjects do not show any relation.

Keywords: obesity, overweight, diabetes, dietary pattern, nutrition, BMI, non communicable disease

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Authors: O. O. Oguntoye

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Product consumption constitutes an important consideration for sustainable development. Seeing how product consumption could be highly unsustainable, coupled with how existing policies on corporate responsibility do not particularly address the consumption aspect of product lifecycle, conducting this research became necessary. The research makes an attempt to provide a framework by which to gauge corporate responsibility of product suppliers in terms of their commitment towards the sustainable consumption of their products. Through an exploration of relevant literature, independently established ideas with which to assess a given product supplier were galvanised into a four-criterion framework. The criteria are: (1) Embeddedness of consumption as a factor in corporate sustainability policy, (2) Level of understanding of consumption behaviour, (3) Breadth of behaviour-influencing strategies adopted, and (4) Inclusiveness for all main dimensions of sustainability. This resulting framework was then applied in a case study involving a UK-based furniture supplier where interviews and content analysis of corporate documents were used as the mode for primary data collection. From the case study, it was found that the supplier had performed to different levels across the four themes of the assessment. Two major areas for improvement were however identified – one is for the furniture supplier to focus more proactively on understanding consumption behaviour and, two is for it to widen the scope of its current strategies for enhancing sustainable consumption of supplied furniture. As a generalisation, the framework presented here makes it possible for companies to reflect with a sense of guidance, how they have demonstrated commitment towards sustainable consumption through their values, culture, and operations. It also provides a foundation for developing standardized assessment which the current widely used frameworks such as the GRI, the Global Compact, and others do not cover. While these popularly used frameworks mainly focus on sustainability of companies within the production and supply chain management contexts (i.e. mostly ‘upstream’), the framework here provides an extension by bringing the ‘downstream’ or consumer bit into light.

Keywords: corporate sustainability, design for sustainable consumption, extended producer responsibility, sustainable consumer behaviour

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Authors: A. Sgobba, C. Meskell

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The feasibility of on-site electricity production from solar and wind and the resulting load management for a specific manufacturing plant in Ireland are assessed. The industry sector accounts directly and indirectly for a high percentage of electricity consumption and global greenhouse gas emissions; therefore, it will play a key role in emission reduction and control. Manufacturing plants, in particular, are often located in non-residential areas since they require open spaces for production machinery, parking facilities for the employees, appropriate routes for supply and delivery, special connections to the national grid and other environmental impacts. Since they have larger spaces compared to commercial sites in urban areas, they represent an appropriate case study for evaluating the technical and economic viability of energy system integration with low power density technologies, such as solar and wind, for on-site electricity generation. The available open space surrounding the analysed manufacturing plant can be efficiently used to produce a discrete quantity of energy, instantaneously and locally consumed. Therefore, transmission and distribution losses can be reduced. The usage of storage is not required due to the high and almost constant electricity consumption profile. The energy load of the plant is identified through the analysis of gas and electricity consumption, both internally monitored and reported on the bills. These data are not often recorded and available to third parties since manufacturing companies usually keep track only of the overall energy expenditures. The solar potential is modelled for a period of 21 years based on global horizontal irradiation data; the hourly direct and diffuse radiation and the energy produced by the system at the optimum pitch angle are calculated. The model is validated using PVWatts and SAM tools. Wind speed data are available for the same period within one-hour step at a height of 10m. Since the hub of a typical wind turbine reaches a higher altitude, complementary data for a different location at 50m have been compared, and a model for the estimate of wind speed at the required height in the right location is defined. Weibull Statistical Distribution is used to evaluate the wind energy potential of the site. The results show that solar and wind energy are, as expected, generally decoupled. Based on the real case study, the percentage of load covered every hour by on-site generation (Level of Autonomy LA) and the resulting electricity bought from the grid (Expected Energy Not Supplied EENS) are calculated. The economic viability of the project is assessed through Net Present Value, and the influence the main technical and economic parameters have on NPV is presented. Since the results show that the analysed renewable sources can not provide enough electricity, the integration with a cogeneration technology is studied. Finally, the benefit to energy system integration of wind, solar and a cogeneration technology is evaluated and discussed.

Keywords: demand, energy system integration, load, manufacturing, national grid, renewable energy sources

Procedia PDF Downloads 119

Authors: M. Manjunath, R. Rakesh, Y. T. Krishne Gowda, G. Panduranga Murthy

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The availability of energy resources plays a vital role in the progress of a country. Over the last decades, there is an increase in the consumption of energy worldwide resulting in the depletion of fossil fuels. This necessitates dependency on other countries for energy resources. Therefore, a renewable eco-friendly alternate fuel is replaced in place of fossil fuel which can be vegetable oils as a substitute fuel for diesel. Since oils are more viscous it cannot be used directly in CI engines without any engine modification. Thus, a conversion of vegetable oils to biodiesel is done by a Transesterification process. The present paper is restricted to Biofuel substitute for diesel and which can be obtained from a number of edible and non-edible oil resources. The oil from these resources can be Transesterified by a suitable method depending on its FFA content for the production of biodiesel and that can be used to operate CI engine. In this work, an attempt is made to test the performance of CI engine using Transesterified peanut and sunflower oil methyl esters blends with diesel.

Keywords: SOME, POME, BMEP, BSFC, BTE

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Authors: M. Baldini, H. K. Jacobsen, M. Jaccard

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In light of the international efforts to comply with the Paris agreement and emission targets for future energy systems, Denmark and Canada are among the front-runner countries dealing with climate change. The experiences in the energy sector have seen both countries coping with trade-offs between investments in renewable energy technologies and energy efficiency, thus tackling the climate issue from the supply and demand side respectively. On the demand side, the industrial sector is going through a remarkable transformation, with implementation of energy efficiency measures, change of input fuel for end-use processes and forecasted electrification as main features under the spotlight. By looking at Canada and Denmark's experiences as pathfinders on the demand and supply approach to climate change, it is possible to obtain valuable experience that may be applied to other countries aiming at the same goal. This paper presents a comparative study on industrial energy efficiency between Canada and Denmark. The study focuses on technologies and system options, policy design and implementation and modelling methodologies when implementing industrial energy savings in optimization models in comparison to simulation models. The study identifies gaps and junctures in the approach towards climate change actions and, learning from each other, lessen the differences to further foster the adoption of energy efficiency measurements in the industrial sector, aiming at reducing energy consumption and, consequently, CO₂ emissions.

Keywords: industrial energy efficiency, comparative study, CO₂ reduction, energy system modelling

Procedia PDF Downloads 154

Authors: Sabri Mrayed, David Maccioni, Greg Leslie

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Seawater desalination has been accepted as one of the most effective solutions to the growing problem of a diminishing clean drinking water supply. Currently, two desalination technologies dominate the market – the thermally driven multi-stage flash distillation (MSF) and the membrane based reverse osmosis (RO). However, in recent years membrane distillation (MD) has emerged as a potential alternative to the established means of desalination. This research project intended to determine the viability of MD as an alternative process to MSF and RO for seawater desalination. Specifically the project involves conducting a thermodynamic analysis of the process based on the second law of thermodynamics to determine the efficiency of the MD. Data was obtained from experiments carried out on a laboratory rig. In order to determine exergy values required for the exergy analysis, two separate models were built in Engineering Equation Solver – the ’Minimum Separation Work Model’ and the ‘Stream Exergy Model’. The efficiency of MD process was found to be 17.3 %, and the energy consumption was determined to be 4.5 kWh to produce one cubic meter of fresh water. The results indicate MD has potential as a technique for seawater desalination compared to RO and MSF. However, it was shown that this was only the case if an alternate energy source such as green or waste energy was available to provide the thermal energy input to the process. If the process was required to power itself, it was shown to be highly inefficient and in no way thermodynamically viable as a commercial desalination process.

Keywords: desalination, exergy, membrane distillation, second law efficiency

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Authors: Paula Marín, Mohammad Saffari, Alvaro de Gracia, Luisa F. Cabeza, Svetlana Ushak

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Climate control represents an important issue when referring to energy consumption of buildings and associated expenses, both in installation or operation periods. The climate control of a building relies on several factors. Among them, localization, orientation, architectural elements, sources of energy used, are considered. In order to study the thermal behaviour of a building set up, the present study proposes the use of energy simulation program Energy Plus. In recent years, energy simulation programs have become important tools for evaluation of thermal/energy performance of buildings and facilities. Besides, the need to find new forms of passive conditioning in buildings for energy saving is a critical component. The use of phase change materials (PCMs) for heat storage applications has grown in importance due to its high efficiency. Therefore, the climatic conditions of Northern Chile: high solar radiation and extreme temperature fluctuations ranging from -10°C to 30°C (Calama city), low index of cloudy days during the year are appropriate to take advantage of solar energy and use passive systems in buildings. Also, the extensive mining activities in northern Chile encourage the use of large numbers of containers to harbour workers during shifts. These containers are constructed with lightweight construction systems, requiring heating during night and cooling during day, increasing the HVAC electricity consumption. The use of PCM can improve thermal comfort and reduce the energy consumption. The objective of this study was to evaluate the thermal and energy performance of containers of 2.5×2.5×2.5 m3, located in four cities of Chile: Antofagasta, Calama, Santiago, and Concepción. Lightweight envelopes, typically used in these building prototypes, were evaluated considering a container without PCM inclusion as the reference building and another container with PCM-enhanced envelopes as a test case, both of which have a door and a window in the same wall, orientated in two directions: North and South. To see the thermal response of these containers in different seasons, the simulations were performed considering a period of one year. The results show that higher energy savings for the four cities studied are obtained when the distribution of door and window in the container is in the north direction because of higher solar radiation incidence. The comparison of HVAC consumption and energy savings in % for north direction of door and window are summarised. Simulation results show that in the city of Antofagasta 47% of heating energy could be saved and in the cities of Calama and Concepción the biggest savings in terms of cooling could be achieved since PCM reduces almost all the cooling demand. Currently, based on simulation results, four containers have been constructed and sized with the same structural characteristics carried out in simulations, that are, containers with/without PCM, with door and window in one wall. Two of these containers will be placed in Antofagasta and two containers in a copper mine near to Calama, all of them will be monitored for a period of one year. The simulation results will be validated with experimental measurements and will be reported in the future.

Keywords: energy saving, lightweight construction, PCM, simulation

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Authors: F. Taouche-Kheloui, O. Fedaoui-Akmoussi, K. Ait tahar, Li. Alex

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Currently, the reduction of energy consumption, through the use of abundant and recyclable natural materials, for better thermal insulation represents an important area of research. To this end, the use of bio-sourced materials has been identified as one of the green sectors with a very high economic development potential for the future. Because of its role in reducing the consumption of fossil-based raw materials, it contributes significantly to the storage of atmospheric carbon, limits greenhouse gas emissions and creates new economic opportunities. This study constitutes a contribution to the elaboration and the experimental characterization of the thermal behavior of a sawdust-reduced mortar matrix. We have taken into account the influence of the size of the grain fibers of sawdust, hence the use of three different ranges and also different percentage in the different confections. The intended practical application consists of producing a light weight compound at a lower cost to ensure a better thermal and acoustic behavior compared to that existing in the field, in addition to the desired resistances. Improving energy performance, while reducing greenhouse gas emissions from the building sector, is amongst the objectives to be achieved. The results are very encouraging and highlight the value of the proposed design of organic-source mortar panels which have specific mechanical properties acceptable for their use, low densities, lower cost of manufacture and labor, and above all a positive impact on the environment.

Keywords: mortar, sawdust waste, thermal, experimental, analysis

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Authors: Enas R. Shouman

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Economic development with population growth is leading to a continuous increase in energy demand. At the same time, growing global concern for the environment is driving to decrease the use of conventional energy sources and to increase the use of renewable energy sources. The objective of this study is to present the market trends of solar energy photovoltaic technology over the world and to represent economics methods for PV financial analyzes on the basis of expectations for the expansion of PV in many applications. In the course of this study, detailed information about the current PV market was gathered and analyzed to find factors influencing the penetration of PV energy. The paper methodology depended on five relevant economic financial analysis methods that are often used for investment decisions maker. These methods are payback analysis, net benefit analysis, saving-to-investment ratio, adjusted internal rate of return, and life-cycle cost. The results of this study may be considered as a marketing guide that helps diffusion of using PV Energy. The study showed that PV cost is economically reliable. The consumers will pay higher purchase prices for PV system installation but will get lower electricity bill.

Keywords: photovoltaic, financial methods, solar energy, economics, PV panel

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Authors: E. Cintura, M. I. Gomes

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Nowadays, sustainable development issues have a key role in the planning of the man-made environment. Ensuring this development means limiting the impact of human activity on nature. It is essential to secure healthy places and good living conditions. For these reasons, indoor air quality and building materials play a fundamental role in sustainable architectural projects. These factors significantly affect human health: they can radically change the quality of the internal environment and energy consumption. The use of natural materials such as earth has many beneficial aspects in comfort and indoor air quality. As well as advantages in the environmental impact of the construction, they ensure a low energy consumption. Since they are already present in nature, their production and use do not require a high-energy consumption. Furthermore, they have a high thermo-hygrometric capacity, being able to absorb moisture, contributing positively to indoor conditions. Indoor air quality is closely related to relative humidity. For these reasons, it can be affirmed that the use of earth materials guarantees a sustainable development and at the same time improves the health of the building users. This paper summarizes several researches that demonstrate the importance of indoor air quality for human health and how it strictly depends on the building materials used. Eco-efficient plasters are also considered: earth and ash mortar. The bibliography consulted has the objective of supporting future experimental and laboratory analyzes. It is necessary to carry on with research by the use of simulations and testing to confirm the hygrothermal properties of eco-efficient plasters and therefore their ability to improve indoor air quality.

Keywords: hygroscopicity, hygrothermal comfort, mortar, plaster

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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: Yuta Nakano, Kozo Kajiwara, Atsushi Hori, Takeshi Fujita

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In association with the wave of electric vehicles (EV), low energy consumption systems have become more and more important. One of the key technologies to realize low energy consumption is a dynamic vision sensor (DVS), or we can call it an event sensor, neuromorphic vision sensor and so on. This sensor has several features, such as high temporal resolution, which can achieve 1 Mframe/s, and a high dynamic range (120 DB). However, the point that can contribute to low energy consumption the most is its sparsity; to be more specific, this sensor only captures the pixels that have intensity change. In other words, there is no signal in the area that does not have any intensity change. That is to say, this sensor is more energy efficient than conventional sensors such as RGB cameras because we can remove redundant data. On the other side of the advantages, it is difficult to handle the data because the data format is completely different from RGB image; for example, acquired signals are asynchronous and sparse, and each signal is composed of x-y coordinate, polarity (two values: +1 or -1) and time stamp, it does not include intensity such as RGB values. Therefore, as we cannot use existing algorithms straightforwardly, we have to design a new processing algorithm to cope with DVS data. In order to solve difficulties caused by data format differences, most of the prior arts make a frame data and feed it to deep learning such as Convolutional Neural Networks (CNN) for object detection and recognition purposes. However, even though we can feed the data, it is still difficult to achieve good performance due to a lack of intensity information. Although polarity is often used as intensity instead of RGB pixel value, it is apparent that polarity information is not rich enough. Considering this context, we proposed to use the timestamp information as a data representation that is fed to deep learning. Concretely, at first, we also make frame data divided by a certain time period, then give intensity value in response to the timestamp in each frame; for example, a high value is given on a recent signal. We expected that this data representation could capture the features, especially of moving objects, because timestamp represents the movement direction and speed. By using this proposal method, we made our own dataset by DVS fixed on a parked car to develop an application for a surveillance system that can detect persons around the car. We think DVS is one of the ideal sensors for surveillance purposes because this sensor can run for a long time with low energy consumption in a NOT dynamic situation. For comparison purposes, we reproduced state of the art method as a benchmark, which makes frames the same as us and feeds polarity information to CNN. Then, we measured the object detection performances of the benchmark and ours on the same dataset. As a result, our method achieved a maximum of 7 points greater than the benchmark in the F1 score.

Keywords: event camera, dynamic vision sensor, deep learning, data representation, object recognition, low energy consumption

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Authors: Sang-Wook Lee, So-Yeon Jeon, Min-Gi Cho, Dae-Young Shin, Sung-Ho Hwang

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Hydraulic system of excavator gets working energy from hydraulic pump which is connected to output shaft of engine. Recently, main control valve (MCV) which is composed of several independent metering valve (IMV) has been introduced for better energy efficiency of the hydraulic system so that fuel efficiency of the excavator can be improved. Excavator with IMV has 5 operating modes depending on the quantity of regeneration flow. In this system, the hydraulic pump is controlled to supply demanded flow which is needed to operate each mode. Because the regenerated flow supply energy to actuators, the hydraulic pump consumes less energy to make same motion than one that does not regenerate flow. The horse power control is applied to the hydraulic pump of excavator for maintaining engine start under a heavy load and this control makes the flow of hydraulic pump reduced. When excavator is in complex operation such as loading or unloading soil, the hydraulic pump discharges small quantity of working fluid in high pressure. At this operation, the engine of excavator does not run at optimal operating line (OOL). The engine needs to be operated on OOL to improve fuel efficiency and by controlling hydraulic pump the engine can drive on OOL. By continuous mode changing of IMV, the hydraulic pump is controlled to make engine runs on OOL. The simulation result of this study shows that fuel efficiency of excavator with IMV can be improved by considering engine OOL and continuous mode changing algorithm.

Keywords: continuous mode changing, engine fuel consumption, excavator, fuel efficiency, IMV

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Authors: Bahareh Arghand, Seyed Abbas Poorhashemi, Ramin Roshandel

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Nowadays, Economic growth and the increasing use of fossil fuel have caused major damages to environment. Therefore, international law has tried to codify the rules and regulations and identify legal principles to decrease conflict of interests between energy law and environmental law. The open relationship between energy consumption and the law of nature has been ignored for years, because the focus of energy law has been on an affordable price of a reliable supply of energy; while the focus of environmental law was on protection of the nature. In fact, the legal and overall policies of energy are based on Sic Omnes and inter part for governments whereas environmental law is based on common interests and Erga Omnes. The relationship between energy law, environmental law and economic aspects is multilateral, complex and important. Moreover, they influence each other. There are similarities in the triangle of energy, environment and economic aspects and in some cases there are conflict of interest but their conflicts are in goals not in practice and their legal jurisdiction is in international law. The development of national and international rules and regulations relevant to energy-environment has been done by separate sectors, whereas sustainable development principle, especially in the economic sector, requires environmental considerations. It is an important turning point to integrate and decrease conflict of interest among energy law, environmental law and economic aspects. The present study examines existing legal principles on energy and the environment and identifies the similarities and conflicts based on the descriptive-analytic study. The purpose of investigating these legal principles is to integrate and decrease conflict of interest between energy law and environmental law.

Keywords: energy law, environmental law, erga omnes, sustainable development

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Authors: Federico Hahn Schlam, Fermín Martínez Solís

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Leaf-cutting ants (Atta cephalotes) forage from mango tree leaves and flowers to feed their colony. Farmers find it difficult to control ants due to the great quantity of trees grown in commercial orchards. In this article, IoT can support farmers for ant detection in real time, as production losses can be considered of 324 US per tree.A wireless sensor network, WSN, was developed to warn the farmer from ant presence in trees during a night. Mango trees were gathered into groups of 9 trees, where the central tree holds the master microcontroller, and the other eight trees presented slave microcontrollers (nodes). At each node, anemitter diode-photodiode unitdetects ants climbing up. A capacitor is chargedand discharged after being sampled every ten minutes. The system usesBLE (Bluetooth Low Energy) to communicate between the master microcontroller by BLE.When ants were detected the number of the tree was transmitted via LoRa from the masterto the producer smartphone to warn him. In this paper, BLE, LoRa, and energy consumption were studied under variable vegetation in the orchard. During 2018, 19 trees were attacked by ants, and ants fed 26.3% of flowers and 73.7% of leaves.

Keywords: BLE, atta cephalotes, LoRa, WSN-smartphone, energy consumption

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Authors: Somesh Kumar Sharma, Sunanad Gupta

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The contribution of aviation to society and economy is undisputedly significant. The aviation industry drives economic and social progress by contributing prominently to tourism, commerce and improved quality of life. Identifying the amount of fuel consumed by an aircraft while moving in both airspace and ground networks is critical to air transport economics. Aviation fuel is a major operating cost parameter of the aviation industry and at the same time it is prone to various constraints. This article aims to develop a model for fuel consumption of aviation product. The paper tailors the information for the fuel consumption optimization in terms of information development, information evaluation and information refinement. The information is evaluated and refined using statistical package R and Factor Analysis which is further validated with neural networking. The study explores three primary dimensions which are finally summarized into 23 influencing variables in contrast to 96 variables available in literature. The 23 variables explored in this study should be considered as highly influencing variables for fuel consumption which will contribute significantly towards fuel optimization.

Keywords: fuel consumption, civil aviation industry, neural networking, optimization

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Authors: Jainendra Singh, Zaheeruddin

Abstract:

A typical wireless sensor networks (WSNs) consists of several tiny and low-power sensors which use radio frequency to perform distributed sensing tasks. The longevity of wireless sensor networks (WSNs) is a major issue that impacts the application of such networks. While routing protocols are striving to save energy by acting on sensor nodes, recent studies show that network lifetime can be enhanced by further involving sink mobility. A common approach for energy efficiency is partitioning the network into clusters with correlated data, where the representative nodes simply transmit or average measurements inside the cluster. In this paper, we propose an energy- efficient homogenous clustering (EHC) technique. In this technique, the decision of each sensor is based on their residual energy and an estimate of how many of its neighboring cluster heads (CHs) will benefit from it being a CH. We, also explore the routing algorithm in clustered WSNs. We show that the proposed schemes significantly outperform current approaches in terms of packet delay, hop count and energy consumption of WSNs.

Keywords: wireless sensor network, energy efficiency, clustering, routing

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Authors: Kishor T. Zingre, Seshadhri Srinivasan

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Energy consumption by the building sector is increasing at an alarming rate throughout the world and leading to more building-related CO₂ emissions into the environment. In buildings, the main contributors to energy consumption are heating, ventilation, and air-conditioning (HVAC) systems, lighting, and electrical appliances. It is hypothesised that the energy efficiency in buildings can be achieved by implementing sustainable technologies such as i) enhancing the thermal resistance of fabric materials for reducing heat gain (in hotter climates) and heat loss (in colder climates), ii) enhancing daylight and lighting system, iii) HVAC system and iv) occupant localization. Energy performance of various sustainable technologies is highly dependent on climatic conditions. This paper investigated the use of machine learning techniques for accurate prediction of air-conditioning energy in seasonal climates. The data required to train the machine learning techniques is obtained using the computational simulations performed on a 3-story commercial building using EnergyPlus program plugged-in with OpenStudio and Google SketchUp. The EnergyPlus model was calibrated against experimental measurements of surface temperatures and heat flux prior to employing for the simulations. It has been observed from the simulations that the performance of sustainable fabric materials (for walls, roof, and windows) such as phase change materials, insulation, cool roof, etc. vary with the climate conditions. Various renewable technologies were also used for the building flat roofs in various climates to investigate the potential for electricity generation. It has been observed that the proposed technique overcomes the shortcomings of existing approaches, such as local linearization or over-simplifying assumptions. In addition, the proposed method can be used for real-time estimation of building air-conditioning energy.

Keywords: building energy efficiency, energyplus, machine learning techniques, seasonal climates

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Authors: Widhi Hanantyo Suryadinata

Abstract:

Efforts undertaken by Indonesia and China to shift the strategies and security of renewable energy on a global stage involve approaches through policy construction related to rare minerals processing or value-adding in Indonesia and manufacturing policies through the New Energy Vehicles (NEVs) policy in China. Both policies encompass several practical regulations and policies that can be utilized for the implementation of Indonesia and China's grand efforts and ideas. Policy development in Indonesia and China can be analyzed using a comparative analysis method, as well as employing a pyramid illustration to identify policy construction phases based on the real conditions of the domestic market and implemented policies. This approach also helps to identify the potential integration of policies needed to enhance the policy development phase of a country within the pyramid. It also emphasizes the significance of integration policy to redefine renewable energy strategy and security on the global stage.

Keywords: global renewable energy security, global energy security, policy development, comparative analysis, shifting of global energy security, Indonesia, China

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Authors: Usman A. Usman

Abstract:

Undeniably, unlike the Classical side, the Keynesian perspective of the aggregate demand side indeed has a significant position in the policy, growth, and welfare of Nigeria due to government involvement and ineffective demand of the population living with poor per capita income. This study seeks to investigate the effect of Government Final Consumption Expenditure, Financial Deepening on Households, and NPISHs Final consumption expenditure using data on Nigeria from 1981 to 2019. This study employed the ADF stationarity test, Johansen Cointegration test, and Vector Error Correction Model. The results of the study revealed that the coefficient of Government final consumption expenditure has a positive effect on household consumption expenditure in the long run. There is a long-run and short-run relationship between gross fixed capital formation and household consumption expenditure. The coefficients cpsgdp (financial deepening and gross fixed capital formation posit a negative impact on household final consumption expenditure. The coefficients money supply lm2gdp, which is another proxy for financial deepening, and the coefficient FDI have a positive effect on household final consumption expenditure in the long run. Therefore, this study recommends that Gross fixed capital formation stimulates household consumption expenditure; a legal framework to support investment is a panacea to increasing hoodmold income and consumption and reducing poverty in Nigeria. Therefore, this should be a key central component of policy.

Keywords: government final consumption expenditure, household consumption expenditure, vector error correction model, cointegration

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Authors: Elnur Abbasov

Abstract:

Energy security and climate change comprise some of the most important concerns facing humankind today and probably in the future if they are not addressed appropriately. In order to stabilize the global climate, there is the need for the world to lessen its use of fossil energy, which requires enhancement of current energy efficiency as well as the development of novel energy sources, such as energy obtained from renewable sources. There is no doubt that the steady transition towards a solar-based economy is likely to result in the development of completely new sectors, behaviours, and jobs that are pro-environmental. Azerbaijan Republic as the largest nation state in the South Caucasus Region has the potential for using and developing the renewable sources of energy in order to support the environmental challenge resolution associated with the climate change, improving the environmental situation in the country. Solar PV comprises one of the direct usages of solar energy. In this paper, sustainable PV usage scenario in residential houses was introduced to reduce negative environmental effects of land use, water consumption, air pollution etc. It was recommended by an author that, PV systems can be part of function and design of residential building components: such as roofs, walls, windows.

Keywords: energy efficiency, environmentally friendly, photovoltaic engineering, sustainable energy usage scenario

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Authors: Nazanin Naderi, Milton Smith

Abstract:

Since worldwide demand for renewable energy is increasing rapidly because of the climate problem and the limitation of fossil fuels, technologies of alternative energy sources have been developed and the electric power network now includes renewable energy resources such as wind energy. Because of the huge advantages that wind energy has, like reduction in natural gas use, price pressure, emissions of greenhouse gases and other atmospheric pollutants, electric sector water consumption and many other contributions to the nation’s economy like job creation it has got too much attention these days from different parts of the world especially in the United States which is trying to provide 20% of the nation’s energy from wind by 2030. This study is trying to evaluate the effect of splitting wind farms on power output. We are trying to find if we can get more output by installing wind turbines in different sites rather than installing all wind turbines in one site. Five potential sites in Texas have been selected as a case study and two years wind data has been gathered for these sites. Wind data are analyzed and effect of correlation between sites on power output has been evaluated. Standard deviation and autocorrelation effect has also been considered for this study. The paper has been organized as follows: After the introduction the second section gives a brief overview of wind analysis. The third section addresses the case study and evaluates correlation between sites, auto correlation of sites and standard deviation of power output. In section four we describe the results.

Keywords: auto correlation, correlation between sites, splitting wind farms, power output, standard deviation

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Authors: Jovian Cheung, Thomas Kwok, Victor Wong

Abstract:

Buildings are entwined with smart city developments. Building performance relies heavily on electrical and mechanical (E&M) systems and services accounting for about 40 percent of global energy use. By cohering the advancement of technology as well as energy and operation-efficient initiatives into the buildings, people are enabled to raise building performance and enhance the sustainability of the built environment in their daily lives. Digital transformation in the buildings is the profound development of the city to leverage the changes and opportunities of digital technologies To optimize the building performance, intelligent power quality and energy management system is developed for transforming data into actions. The system is formed by interfacing and integrating legacy metering and internet of things technologies in the building and applying big data techniques. It provides operation and energy profile and actionable insights of a building, which enables to optimize the building performance through raising people awareness on E&M services and energy consumption, predicting the operation of E&M systems, benchmarking the building performance, and prioritizing assets and energy management opportunities. The intelligent power quality and energy management system comprises four elements, namely the Integrated Building Performance Map, Building Performance Dashboard, Power Quality Analysis, and Energy Performance Analysis. It provides predictive operation sequence of E&M systems response to the built environment and building activities. The system collects the live operating conditions of E&M systems over time to identify abnormal system performance, predict failure trends and alert users before anticipating system failure. The actionable insights collected can also be used for system design enhancement in future. This paper will illustrate how intelligent power quality and energy management system provides operation and energy profile to optimize the building performance and actionable insights to revitalize an existing building into a smart building. The system is driving building performance optimization and supporting in developing Hong Kong into a suitable smart city to be admired.

Keywords: intelligent buildings, internet of things technologies, big data analytics, predictive operation and maintenance, building performance

Procedia PDF Downloads 136