Search results for: electricity demand forecasting

Authors: Jonathan J. Burson

Abstract:

With the rise of virtually costless, mobile-based trading platforms, stock market trading activity has increased significantly over the past decade, particularly for the millennial generation. This increased stock market attention, combined with the recent market turmoil due to the economic upset caused by COVID-19, make the topics of market-timing and forecasting particularly relevant. While the overall stock market saw an unprecedented, historically-long bull market from March 2009 to February 2020, the end of that bull market reignited a search by investors for a way to reduce risk and increase return. Similar searches for outperformance occurred in the early, and late 2000’s as the Dotcom bubble burst and the Great Recession led to years of negative returns for mean-variance, index investors. Extensive research has been conducted on fundamental analysis, technical analysis, macroeconomic indicators, microeconomic indicators, and other techniques—all using different methodologies and investment periods—in pursuit of higher returns with lower risk. The enormous variety of timeframes, data, and methodologies used by the diverse forecasting methods makes it difficult to compare the outcome of each method directly to other methods. This paper establishes a process to evaluate the market-timing methods in an apples-to-apples manner based on simplicity, performance, and feasibility. Preliminary findings show that certain technical analysis models provide a higher return with lower risk when compared to the buy-and-hold method and to other market-timing strategies. Furthermore, technical analysis models tend to be easier for individual investors both in terms of acquiring the data and in analyzing it, making technical analysis-based market-timing methods the preferred choice for retail investors.

Keywords: buy-and-hold, forecast, market-timing, probit, technical analysis

Procedia PDF Downloads 85

Authors: Yousaf Ayub

Abstract:

A co-gasification process, which involves the utilization of both biomass and plastic waste, has been developed to enable the production of blue and green hydrogen. To support this endeavor, an Aspen Plus simulation model has been meticulously created, and sustainability analysis is being conducted, focusing on economic viability, energy efficiency, advanced exergy considerations, and exergoeconomics evaluations. In terms of economic analysis, the process has demonstrated strong economic sustainability, as evidenced by an internal rate of return (IRR) of 8% at a process efficiency level of 70%. At present, the process has the potential to generate approximately 1100 kWh of electric power, with any excess electricity, beyond meeting the process requirements, capable of being harnessed for green hydrogen production via an alkaline electrolysis cell (AEC). This surplus electricity translates to a potential daily hydrogen production of around 200 kg. The exergy analysis of the model highlights that the gasifier component exhibits the lowest exergy efficiency, resulting in the highest energy losses, amounting to approximately 40%. Additionally, advanced exergy analysis findings pinpoint the gasifier as the primary source of exergy destruction, totaling around 9000 kW, with associated exergoeconomics costs amounting to 6500 $/h. Consequently, improving the gasifier's performance is a critical focal point for enhancing the overall sustainability of the process, encompassing energy, exergy, and economic considerations.

Keywords: blue hydrogen, green hydrogen, co-gasification, waste valorization, exergy analysis

Procedia PDF Downloads 42

Authors: Jiraphorn Satechan, Thanaphon Khamthieng, Warunee Phanwong

Abstract:

This action research aimed at designing and developing the cleaning equipment to preventing dust diffusion of bus air filter. Quantitative and qualitative data collection methods were used to conduct data from October 1st, 2018 to September 30th, 2019. All of participants were male (100.0%) with aged 40- 49 years and 57.15%, of them finish bachelor degree. 71.43% of them was a driver and 57.15% of them had the working experience between 10 and 15 years. Research revealed that the participants assessed the quality of the bus air filter cleaning equipment for preventing dust diffusion at a moderate level (σ= 0.29), and 71.43 of them also suggested the development methods in order to improve the quality of bus air filters cleaning equipment as follows: 1) to install the circuit breaker for cutting the electricity and controlling the on-off of the equipment and to change the motor to the DC system, 2) should install the display monitor for wind pressure and electricity system as well as to install the air pressure gauge, 3) should install the tank lid lock for preventing air leakage and dust diffusion by increasing the blowing force and sucking power, 4) to stabilize the holding points for preventing the filter shaking while rotating and blowing for cleaning and to reduce the rotation speed in order to allow the filters to move slowly for the air system to blow for cleaning more thoroughly, 5) the amount of dust should be measured before and after cleaning and should be designed the cleaning equipment to be able to clean with a variety of filters, and sizes. Moreover, the light-weight materials should be used to build the cleaning equipment and the wheels should be installed at the base of the equipment in order to make it easier to move.

Keywords: Cleaning Equipment, Bus Air Filters, Preventing Dust Diffusion, Innovation

Procedia PDF Downloads 92

Authors: Amirreza Heidari, Akram Avami, Ehsan Heidari

Abstract:

Evaporative cooling systems are known as energy efficient cooling systems, with much lower electricity consumption than conventional vapor compression systems. A serious limitation of these systems, however, is that they are not applicable in humid regions. Combining a desiccant wheel with these systems, known as desiccant-based evaporative cooling systems, makes it possible to use evaporative cooling in humid climates. This paper evaluates the performane of a cooling system combining desiccant wheel, direct and indirect evaporative coolers (called desiccant-based indirect-direct evaporative cooling (DIDE) system) and then evaluates the energy saving potential of this system over the conventional vapor compression cooling and drying system. To illustrate the system ability of providing comfort conditions, a dynamic hourly simulation of this system is performed for a typical 60 m² building in Sydney, Australia. To evaluate the energy saving potential of this system, a conventional cooling and drying system is also simulated for the same cooling capacity. It has been found that the DIE system is able to provide comfort temperature and relative humidity in a subtropical humid climate like Sydney. The electricity and natural gas consumption of this system are respectively 39.2% and 2.6% lower than that of conventional system over a week. As the research has demonstrated, the innovative DIDE system is an energy efficient cooling system for subtropical humid regions.

Keywords: desiccant, evaporative cooling, dehumidification, indirect evaporative cooler

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Authors: Anucha Wittayakorn-Puripunpinyoo

Abstract:

The research objectives were 1) to study the situation and its trend of agricultural product export of Thailand 2) to study the impact of agricultural product export on income of Thai economy 3) the impact of agricultural product export on employment of Thai economy and 4) to find out the recommendations of agricultural product export policy of Thailand. In this research, secondary data were collected as yearly time series data from 1990 to 2016 accounted for 27 years. Data were collected from the Bank of Thailand database. Primary data were collected from the steakholders of agricultural product export policy of Thailand. Data analysis was applied descriptive statistics such as arithmetic mean, standard deviation. The forecasting of agricultural product was applied Mote Carlo Simulation technique as well as time trend analysis. In addition, the impact of agricultural product export on income and employment by applying econometric model while the estimated parameters were utilized the ordinary least square technique. The research results revealed that 1) agricultural product export value of Thailand from 1990 to 2016 was 338,959.5 Million Thai baht with its growth rate of 4.984 percent yearly, in addition, the forecasting of agricultural product export value of Thailand has increased but its growth rate has been declined 2) the impact of agricultural product export has positive impact on income in Thai economy, increasing in agricultural product export of Thailand by 1 percent would lead income increased by 0.0051 percent 3) the impact of agricultural product export has positive impact on employment in Thai economy, increasing in agricultural product export of Thailand by 1 percent would lead income increased by 0.079 percent and 4) in the future, agricultural product export policy would focused on finished or semi-finished agricultural product instead of raw material by applying technology and innovation in to make value added of agricultural product export. The public agricultural product export policy would support exporters in private sector in order to encourage them as agricultural exporters in Thailand.

Keywords: agricultural product export, income, employment, Thai economy

Procedia PDF Downloads 290

Authors: Jun-ichi Ochiai, Itsuki Noda, Ryo Kanamori, Keiji Hirata, Hitoshi Matsubara, Hideyuki Nakashima

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We conducted exhaustive simulations for data assimilation and evaluation of service quality for various setting in a new shared transportation system, called SAVS. Computational social simulation is a key technology to design recent social services like SAVS as new transportation service. One open issue in SAVS was to determine the service scale through the social simulation. Using our exhaustive simulation framework, OACIS, we did data-assimilation and evaluation of effects of SAVS based on actual tax-use data at Tajimi city, Japan. Finally, we get the conditions to realize the new service in a reasonable service quality.

Keywords: on-demand bus sytem, social simulation, data assimilation, exhaustive simulation

Procedia PDF Downloads 297

Authors: Mounir Filali

Abstract:

Companies use many innovative ways to reach their customers to stay ahead of the competition. Along with the growing demand for innovative business solutions is the demand for new technology. The most noticeable area of demand for business innovations is the mobile application industry. Recently, companies have recognized the growing need to integrate proprietary mobile applications into their suite of services; Companies have realized that developing mobile apps gives them a competitive edge. As a result, many have begun to rapidly develop mobile apps to stay ahead of the competition. Mobile application development helps companies meet the needs of their customers. Mobile apps also help businesses to take advantage of every potential opportunity to generate leads that convert into sales. Mobile app download growth statistics with the recent rise in demand for business-related mobile apps, there has been a similar rise in the range of mobile app solutions being offered. Today, companies can use the traditional route of the software development team to build their own mobile applications. However, there are also many platform-ready "low-code and no-code" mobile apps available to choose from. These mobile app development options have more streamlined business processes. This helps them be more responsive to their customers without having to be coding experts. Companies must have a basic understanding of mobile app architecture to attract and maintain the interest of mobile app users. Mobile application architecture refers to the buildings or structural systems and design elements that make up a mobile application. It also includes the technologies, processes, and components used during application development. The underlying foundation of all applications consists of all elements of the mobile application architecture; developing a good mobile app architecture requires proper planning and strategic design. The technology framework or platform on the back end and user-facing side of a mobile application is part of the mobile architecture of the application. In-application development Software programmers loosely refer to this set of mobile architecture systems and processes as the "technology stack."

Keywords: mobile applications, development, architecture, technology

Procedia PDF Downloads 91

Authors: Geetal Mahajan, R. V. Adivarekar

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In this research, an attempt has been made to develop integrated finish on textile fabrics. The demand for mosquito repellent, flame retardant, and water repellent finished fabric has increased. Integrated finishing was done using commercially available products. These finishing agents were first assessed individually for their functional properties and then used in combination with other agents. Dip-air dry and pad-dry-cure (PDC) were two different methods used for fabric finishing. The finished fabric was assessed using spray test, limiting oxygen index and mosquito repellence test. Integrated finished fabric is in great demand by the customers as it increases the aesthetic as well as the functional properties of the fabric with added benefit of water and energy conservation.

Keywords: flame retardant, integrated finishing, mosquito repellent, textiles, water repellent

Procedia PDF Downloads 263

Authors: Philipp Sommer, Amgad Agoub

Abstract:

The construction sector significantly impacts global CO₂ emissions, particularly through the energy usage of residential buildings. To address this, various governments, including Germany's, are focusing on reducing emissions via sustainable refurbishment initiatives. This study examines the application of machine learning (ML) to estimate energy demands dynamically in residential buildings and enhance the potential for large-scale sustainable refurbishment. A major challenge in Germany is the lack of extensive publicly labeled datasets for energy performance, as energy performance certificates, which provide critical data on building-specific energy requirements and consumption, are not available for all buildings or require on-site inspections. Conversely, England and other countries in the European Union (EU) have rich public datasets, providing a viable alternative for analysis. This research adapts insights from these English datasets to the German context by developing a comprehensive data schema and calibration dataset capable of predicting building energy demand effectively. The study proposes a minimal feature set, determined through feature importance analysis, to optimize the ML model. Findings indicate that ML significantly improves the scalability and accuracy of energy demand forecasts, supporting more effective emissions reduction strategies in the construction industry. Integrating energy performance certificates into municipal heat planning in Germany highlights the transformative impact of data-driven approaches on environmental sustainability. The goal is to identify and utilize key features from open data sources that significantly influence energy demand, creating an efficient forecasting model. Using Extreme Gradient Boosting (XGB) and data from energy performance certificates, effective features such as building type, year of construction, living space, insulation level, and building materials were incorporated. These were supplemented by data derived from descriptions of roofs, walls, windows, and floors, integrated into three datasets. The emphasis was on features accessible via remote sensing, which, along with other correlated characteristics, greatly improved the model's accuracy. The model was further validated using SHapley Additive exPlanations (SHAP) values and aggregated feature importance, which quantified the effects of individual features on the predictions. The refined model using remote sensing data showed a coefficient of determination (R²) of 0.64 and a mean absolute error (MAE) of 4.12, indicating predictions based on efficiency class 1-100 (G-A) may deviate by 4.12 points. This R² increased to 0.84 with the inclusion of more samples, with wall type emerging as the most predictive feature. After optimizing and incorporating related features like estimated primary energy consumption, the R² score for the training and test set reached 0.94, demonstrating good generalization. The study concludes that ML models significantly improve prediction accuracy over traditional methods, illustrating the potential of ML in enhancing energy efficiency analysis and planning. This supports better decision-making for energy optimization and highlights the benefits of developing and refining data schemas using open data to bolster sustainability in the building sector. The study underscores the importance of supporting open data initiatives to collect similar features and support the creation of comparable models in Germany, enhancing the outlook for environmental sustainability.

Keywords: machine learning, remote sensing, residential building, energy performance certificates, data-driven, heat planning

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Authors: Bryan Low

Abstract:

In the coming decades, the global maritime industry will face a most formidable environmental challenge -achieving net zero carbon emissions by 2050. To meet this target, the Maritime Port Authority of Singapore (MPA) has worked to establish green shipping and digital corridors with ports of several other countries around the world where ships will use low-carbon alternative fuels such as ammonia for power generation. While this paradigm shift to the bunkering of greener fuels is encouraging, fuels like ammonia will also introduce a new and unique type of environmental risk in the unlikely scenario of a spill. While numerous modelling studies have been conducted for oil spills and their associated environmental impact on coastal and marine ecosystems, ammonia spills are comparatively less well understood. For example, there is a knowledge gap regarding how the complex hydrodynamic conditions of the Singapore Straits may influence the dispersion of a hypothetical ammonia plume, which has different physical and chemical properties compared to an oil slick. Chemically, ammonia can be absorbed by phytoplankton, thus altering the balance of the marine nitrogen cycle. Biologically, ammonia generally serves the role of a nutrient in coastal ecosystems at lower concentrations. However, at higher concentrations, it has been found to be toxic to many local species. It may also have the potential to trigger eutrophication and harmful algal blooms (HABs) in coastal waters, depending on local hydrodynamic conditions. Thus, the key objective of this research paper is to support the development of a model-based forecasting system that can predict ammonia plume behaviour in coastal waters, given prevailing hydrodynamic conditions and their environmental impact. This will be essential as ammonia bunkering becomes more commonplace in Singapore’s ports and around the world. Specifically, this system must be able to assess the HAB-triggering potential of an ammonia plume, as well as its lethal and sub-lethal toxic effects on local species. This will allow the relevant authorities to better plan risk mitigation measures or choose a time window with the ideal hydrodynamic conditions to conduct ammonia bunkering operations with minimal risk. In this paper, we present the first part of such a forecasting system: a jointly coupled hydrodynamic-water quality model that can capture how advection-diffusion processes driven by ocean currents influence plume behaviour and how the plume interacts with the marine nitrogen cycle. The model is then applied to various ammonia spill scenarios where the results are discussed in the context of current ammonia toxicity guidelines, impact on local ecosystems, and mitigation measures for future bunkering operations conducted in the Singapore Straits.

Keywords: ammonia bunkering, forecasting, harmful algal blooms, hydrodynamics, marine nitrogen cycle, oceanography, water quality modeling

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Authors: Benhaddadi M., Déry D.

Abstract:

Electric motors are the single biggest consumer of electricity, and the consumption will have more than to double by 2050. Meanwhile, the existing technologies offer the potential to reduce the motor energy demand by up to 30 %, whereas the know-how to realise energy savings is not extensively applied. That is why the authors first conducted a detailed analysis of the regulation of the electric motor market in North America To illustrate the colossal energy savings potential permitted by the VFD, the authors have equipped experimental setup, based on centrifugal pump, simultaneously equipped with regulating throttle valves and variable frequency drive VFD. The obtained experimental results for 1.5 HP motor pump are extended to another motor powers, as centrifugal pumps that are different in power may have similar operational characteristics if they are located in a similar kind of process, permitting the simulations for 5 HP and 100 HP motors. According to the obtained results, VFDs tend to be most cost-effective when fitted to larger motor pumps, in addition to higher duty cycle of the motor and relative time operating at lower than full load. The energy saving permitted by the VFD use is huge, and the payback period for drive investment is short. Nonetheless, it’s important to highlight that there is no general rule of thumb that can be used to obtain the impact of the relative time operating at lower than full load. Indeed, in terms of energy-saving differences, 50 % flow regulation is tremendously better than 75 % regulation, but a slightly enhanced relative to 25 %. Two main distinct reasons can explain this somewhat not anticipated results: the characteristics of the process and the drop in efficiency when motor is operating at low speed.

Keywords: motor, drive, energy efficiency, centrifugal pump

Procedia PDF Downloads 55

Authors: Chansiri Singhtaun

Abstract:

This paper proposes a mathematical model and examines the performance of an exact algorithm for a location–transportation problems in humanitarian relief. The model determines the number and location of distribution centers in a relief network, the amount of relief supplies to be stocked at each distribution center and the vehicles to take the supplies to meet the needs of disaster victims under capacity restriction, transportation and budgetary constraints. The computational experiments are conducted on the various sizes of problems that are generated. Branch and bound algorithm is applied for these problems. The results show that this algorithm can solve problem sizes of up to three candidate locations with five demand points and one candidate location with up to twenty demand points without premature termination.

Keywords: disaster response, facility location, humanitarian relief, transportation

Procedia PDF Downloads 434

Authors: Abhiram Siva Prasad Pamula

Abstract:

Access to clean drinking water becomes scarce due to the increase in extreme weather events because of the rise in the average global temperatures and climate change. By 2030, approximately 47% of the world’s population will face water shortages due to uncertainty in seasonal rainfall. Over 10000 varieties of synthetic dyes are commercially available in the market and used by textile and paper industries, negatively impacting human health when ingested. Besides humans, textile dyes have a negative impact on aquatic ecosystems by increasing biological oxygen demand and chemical oxygen demand. This study assesses different treatment methods that remove dyes from textile wastewater while focusing on energy, economic, and engineering aspects of the treatment processes.

Keywords: textile wastewater, dye removal, treatment methods, hazardous pollutants

Procedia PDF Downloads 78

Authors: Naveen Porika, Snigdho Majumdar, Niraj Sethi

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Water, food and energy securities are emerging as increasingly important and vital issues for India and the world. Hyderabad urban agglomeration (HUA), the capital city of Andhra Pradesh State in India, is the sixth largest city has a population of about 8.2 million. The Musi River, which is a tributary of Krishna river flows from west to east right through the heart of Hyderabad, about 80% of the water used by people is released back as sewage, which flows back into Musi every day with detrimental effects on the environment and people downstream of the city. The average daily sewage generated in Hyderabad city is 950 MLD, however, treatment capacity exists only for 541 Million Liters per Day (MLD) but only 407 MLD of sewage is treated. As a result, 543 MLD of sewage daily flows into Musi river. Hyderabad’s current estimated water demand stands at 320 Million Gallons per Day (MGD). However, its installed capacity is merely 270 MGD; by 2020 estimated demand will grow to 400 MGD. There is huge gap between current supply and demand, and this is likely to widen by 2021. Developing new fresh water sources is a challenge for Hyderabad, as the fresh water sources are few and far from the City (about 150-200 km) and requires excessive pumping. The constraints presented above make the conventional alternatives for supply augmentation unsustainable and unattractive .One such dependable and captive source of easily available water is the treated sewage. With proper treatment, water of desired quality can be recovered from the waste water (sewage) for recycle and reuse. Hyderabad Amberpet sewage treatment of capacity 339 MLD is Asia’s largest sewage treatment plant. Tertiary sewage treatment Standard basic engineering modules of 30 MLD,60 MLD, 120MLD & 180 MLD for sewage treatment plants has been developed which are utilized for developing Sewage Reclamation & Reuse model in Asia’s largest sewage treatment plant. This paper will focus on Hyderabad Water Supply & Demand, Sewage Generation & Treatment, Technical aspects of Tertiary Sewage Treatment and Utilization of developed standard modules for reclamation & reuse of treated sewage to overcome the deficit of 130 MGD as projected by 2021.

Keywords: water reclamation, reuse, Andhra Pradesh, hyderabad, musi river, sewage, demand and supply, recycle, Amberpet, 339 MLD, engineering modules, tertiary treatment

Procedia PDF Downloads 603

Authors: Mounir Filali

Abstract:

Companies use many innovative ways to reach their customers to stay ahead of the competition. Along with the growing demand for innovative business solutions is the demand for new technology. The most noticeable area of demand for business innovations is the mobile application industry. Recently, companies have recognized the growing need to integrate proprietary mobile applications into their suite of services; Companies have realized that developing mobile apps gives them a competitive edge. As a result, many have begun to rapidly develop mobile apps to stay ahead of the competition. Mobile application development helps companies meet the needs of their customers. Mobile apps also help businesses to take advantage of every potential opportunity to generate leads that convert into sales. Mobile app download growth statistics with the recent rise in demand for business-related mobile apps, there has been a similar rise in the range of mobile app solutions being offered. Today, companies can use the traditional route of the software development team to build their own mobile applications. However, there are also many platform-ready "low-code and no-code" mobile apps available to choose from. These mobile app development options have more streamlined business processes. This helps them be more responsive to their customers without having to be coding experts. Companies must have a basic understanding of mobile app architecture to attract and maintain the interest of mobile app users. Mobile application architecture refers to the buildings or structural systems and design elements that make up a mobile application. It also includes the technologies, processes, and components used during application development. The underlying foundation of all applications consists of all elements of the mobile application architecture, developing a good mobile app architecture requires proper planning and strategic design. The technology framework or platform on the back end and user-facing side of a mobile application is part of the mobile architecture of the application. In-application development Software programmers loosely refer to this set of mobile architecture systems and processes as the "technology stack".

Keywords: mobile applications, development, architecture, technology

Procedia PDF Downloads 78

Authors: Benga Ebouele, Thomas Tengen

Abstract:

Implementing either periodic or continuous inventory review model within most manufacturing-companies-supply chains as a management tool may incur higher costs. These high costs affect the system flexibility which in turn affects the level of service required to satisfy customers. However, these effects are not clearly understood because the parameters of both inventory review policies (protection demand interval, order quantity, etc.) are not designed to be fully utilized under different and uncertain conditions such as poor manufacturing, supplies and delivery performance. Coming up with a hybrid model which may combine in some sense the feature of both continuous and a periodic inventory review models should be useful. Therefore, there is a need to build and evaluate such hybrid model on the annual total cost, stock out probability and system’s flexibility in order to search for the most cost effective inventory review model. This work also seeks to find the optimal sets of parameters of inventory management under stochastic condition so as to optimise each policy independently. The results reveal that a continuous inventory system always incurs lesser cost than a periodic (R, S) inventory system, but this difference tends to decrease as time goes by. Although the hybrid inventory is the only one that can yield lesser cost over time, it is not always desirable but also natural to use it in order to help the system to meet high performance specification.

Keywords: demand and lead time randomness, hybrid Inventory model, optimization, supply chain

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Authors: Manish Pandey, Gurinderjit Kaur, Meenu Talwar, Sachin Chauhan, Jagbir Gill

Abstract:

Health-care management systems are a unit of nice connection as a result of the supply a straightforward and fast management of all aspects relating to a patient, not essentially medical. What is more, there are unit additional and additional cases of pathologies during which diagnosing and treatment may be solely allotted by victimization medical imaging techniques. With associate ever-increasing prevalence, medical pictures area unit directly acquired in or regenerate into digital type, for his or her storage additionally as sequent retrieval and process. Data Mining is the process of extracting information from large data sets through using algorithms and Techniques drawn from the field of Statistics, Machine Learning and Data Base Management Systems. Forecasting may be a prediction of what's going to occur within the future, associated it's an unsure method. Owing to the uncertainty, the accuracy of a forecast is as vital because the outcome foretold by foretelling the freelance variables. A forecast management should be wont to establish if the accuracy of the forecast is within satisfactory limits. Fuzzy regression strategies have normally been wont to develop shopper preferences models that correlate the engineering characteristics with shopper preferences relating to a replacement product; the patron preference models offer a platform, wherever by product developers will decide the engineering characteristics so as to satisfy shopper preferences before developing the merchandise. Recent analysis shows that these fuzzy regression strategies area units normally will not to model client preferences. We tend to propose a Testing the strength of Exponential Regression Model over regression toward the mean Model.

Keywords: health-care management systems, fuzzy regression, data mining, forecasting, fuzzy membership function

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Authors: Peter Winzer, Erik Massarczyk

Abstract:

Experts, enterprises and operators expect that the bandwidth request will increase up to rates of 100 to 1,000 Mbps within several years. Therefore the most important question is, which technology shall satisfy the future consumer broadband demands. Currently the consensus is, that the fiber technology has the best technical characteristics to achieve such the high bandwidth rates. But fiber technology is so far very cost-intensive and resource consuming. To avoid these investments, operators are concentrating to upgrade the existing copper and hybrid fiber coax infrastructures. This work presents a comparison of the copper and fiber technologies including an overview about the current German broadband market. Both technologies are reviewed in the terms of demand, willingness to pay and economic efficiency in connection with the technical characteristics.

Keywords: broadband customer demand, fiber development, g.fast, vectoring, willingness to pay for broadband services

Procedia PDF Downloads 458

Authors: Mrinmoy Majumder, Apu Kumar Saha

Abstract:

The ever-increasing human population and its demand for energy is placing stress upon conventional energy sources; and as demand for power continues to outstrip supply, the need to optimize energy distribution and utilization is emerging as an important focus for various stakeholders. The distribution of available energy must be achieved in such a way that the needs of the consumer are satisfied. However, if the availability of resources is not sufficient to satisfy consumer demand, it is necessary to find a method to select consumers based on factors such as their socio-economic or environmental impacts. Weighting consumer types in this way can help separate them based on their relative importance, and cognitive optimization of the allocation process can then be carried out so that, even on days of particularly scarce supply, the socio-economic impacts of not satisfying the needs of consumers can be minimized. In this context, the present study utilized fuzzy logic to assign weightage to different types of consumers based at an educational campus in India, and then established optimal allocation by applying the non-linear mapping capability of neuro-genetic algorithms. The outputs of the algorithms were compared with similar outputs from particle swarm optimization and differential evolution algorithms. The results of the study demonstrate an option for the optimal utilization of available energy based on the socio-economic importance of consumers.

Keywords: power allocation, optimization problem, neural networks, environmental and ecological engineering

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Authors: Tugba Gurler, Irfan Kurtbas

Abstract:

Roof influences considerably energy demand of buildings. In order to reduce this energy demand, various solutions have been proposed, such as roofs with variable thermal insulation, cool roofs, green roofs, heat exchangers and ventilated roofs, and phase change material (PCM) layered roofs. PCMs suffer from relatively low thermal conductivity despite of their promise of the energy-efficiency initiatives for thermal energy storage (TES). This study not only presents the thermal performance of the concrete roof with PCM layers but also evaluates the products with different design configurations and thicknesses under Central Anatolia Region, Turkey and Nottinghamshire, UK weather conditions. System design limitations and proposed prediction models are discussed in this study. A two-dimensional numerical model has been developed, and governing equations have been solved at each time step. Upper surfaces of the roofs have been modelled with heat flux conditions, while lower surfaces of the roofs with boundary conditions. In addition, suitable roofs have been modeled under symmetry boundary conditions. The results of the designed concrete roofs with PCM layers have been compared with common concrete roofs in Turkey. The UK and the numerical modeling results have been validated with the data given in the literature.

Keywords: phase change material, regional energy demand, roof layers, thermal energy storage

Procedia PDF Downloads 86

Authors: Adedayo Adeleke, Dineo Pule

Abstract:

The ongoing load-shedding in most parts of South Africa, combined with climate change causing severe drought conditions in Cape Town, has left electricity consumers seeking alternative sources of power and water. Solar energy, which is abundant in most parts of South Africa and is regarded as a clean and renewable source of energy, allows for the generation of electricity via solar photovoltaic systems. Rainwater harvesting is the collection and storage of rainwater from building rooftops, allowing people without access to water to collect it. The lack of dependable energy and water source must be addressed by shifting to solar energy via solar photovoltaic systems and rainwater harvesting. Before this can be done, the potential of building rooftops must be assessed to determine whether solar energy and rainwater harvesting will be able to meet or significantly contribute to Atlantis industrial areas' electricity and water demands. This research project presents methods and approaches for automatically extracting building rooftops in Atlantis industrial areas and evaluating their potential for solar photovoltaics and rainwater harvesting systems using Light Detection and Ranging (LiDAR) data and aerial imagery. The four objectives were to: (1) identify an optimal method of extracting building rooftops from aerial imagery and LiDAR data; (2) identify a suitable solar radiation model that can provide a global solar radiation estimate of the study area; (3) estimate solar photovoltaic potential overbuilding rooftop; and (4) estimate the amount of rainwater that can be harvested from the building rooftop in the study area. Mapflow, a plugin found in Quantum Geographic Information System(GIS) was used to automatically extract building rooftops using aerial imagery. The mean annual rainfall in Cape Town was obtained from a 29-year rainfall period (1991- 2020) and used to calculate the amount of rainwater that can be harvested from building rooftops. The potential for rainwater harvesting and solar photovoltaic systems was assessed, and it can be concluded that there is potential for these systems but only to supplement the existing resource supply and offer relief in times of drought and load-shedding.

Keywords: roof potential, rainwater harvesting, urban plan, roof extraction

Procedia PDF Downloads 102

Authors: Daral Maesincee, Jompol Thongpaen

Abstract:

Thus far, most of the decisions made within the walls of Thai higher education (HE) institutions have primarily been supply-oriented. With the current supply-driven, itemized HE financing systems, the nation is struggling to systemically produce high-quality manpower that serves the market’s needs, often resulting in education mismatches and unemployment – particularly in science, technology, and innovation (STI)-related fields. With the COVID-19 pandemic challenges widening the education inequality (accessibility and quality) gap, HE becomes even more unobtainable for underprivileged students, permanently leaving some out of the system. Therefore, Thai HE needs a new financing system that produces the “right people” for the “right occupations” through the “right ways,” regardless of their socioeconomic backgrounds, and encourages the creation of non-degree courses to tackle these ongoing challenges. The “Demand-Side Financing for Thai Higher Education” policy aims to do so by offering a new paradigm of HE resource allocation via two main mechanisms: i) standardized formula-based unit-cost subsidizations that is specific to each study field and ii) student loan programs that respond to the “demand signals” from the labor market and the students, that are in line with the country’s priorities. Through in-dept reviews, extensive studies, and consultations with various experts, education committees, and related agencies, i) the method of demand signal analysis is identified, ii) the unit-cost of each student in the sample study fields is approximated, iii) the method of budget analysis is formulated, iv) the interagency workflows are established, and v) a supporting information database is created to suggest the number of graduates each HE institution can potentially produce, the study fields and skillsets that are needed by the labor market, the employers’ satisfaction with the graduates, and each study field’s employment rates. By responding to the needs of all stakeholders, this policy is expected to steer Thai HE toward producing more STI-related manpower in order to uplift Thai people’s quality of life and enhance the nation’s global competitiveness. This policy is currently in the process of being considered by the National Education Transformation Committee and the Higher Education Commission.

Keywords: demand-side financing, higher education resource, human capital, higher education

Procedia PDF Downloads 186

Authors: Muhammad Gillfran Samual, Rinaldy Dalimi, Fauzan Hanif Jufri, Budi Sudiarto, Ismi Rosyiana Fitri

Abstract:

Solar energy is increasingly recognized as an important future energy source due to its abundant availability and renewable nature. However, the intermittent nature of solar energy can cause fluctuations in the electricity produced, making it difficult to guarantee a stable and reliable electricity supply. One solution that can be implemented is to use batteries in a photovoltaic solar power plant system with a Moving Average control algorithm, which can help smooth and reduce fluctuations in solar power output power. The parameter that can be adjusted in the Moving Average algorithm is the window size or the arithmetic average width of the photovoltaic output power over time. This research evaluates the effect of a change of window size parameter in the Moving Average algorithm on the resulting smoothed photovoltaic output power and the technical effects on batteries, i.e., power and energy usage. Based on the evaluation, it is found that the increase of window size parameter will slow down the response of photovoltaic output power to changes in irradiation and increase the smoothing quality of the intermittent photovoltaic output power. In addition, increasing the window size will reduce the maximum power received on the load side, and the amount of energy used by the battery during the power smoothing process will increase, which, in turn, increases the required battery capacity.

Keywords: battery, intermittent, moving average, photovoltaic, power smoothing

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Authors: Bai-Chen Xie, Xian-Peng Chen

Abstract:

China has become the world's largest energy producer and consumer, and its development of renewable energy is of great significance to global energy governance and the fight against climate change. The rapid growth of solar power in China could help achieve its ambitious carbon peak and carbon neutrality targets early. However, the non-technical costs of solar power in China are much higher than at international levels, meaning that inefficiencies are rooted in poor management and improper policy design and that efficiency distortions have become a serious challenge to the sustainable development of the renewable energy industry. Unlike fossil energy generation technologies, the output of solar power is closely related to the volatile solar resource, and the spatial unevenness of solar resource distribution leads to potential efficiency spatial distribution differences. It is necessary to develop an efficiency evaluation method that considers the volatility of solar resources and explores the mechanism of the influence of natural geography and social environment on the spatially varying characteristics of efficiency distribution to uncover the root causes of managing inefficiencies. The study sets solar resources as stochastic inputs, introduces a chance-constrained data envelopment analysis model combined with the directional distance function, and measures the solar resource utilization efficiency of 222 solar power plants in representative photovoltaic bases in northwestern China. By the meta-frontier analysis, we measured the characteristics of different power plant clusters and compared the differences among groups, discussed the mechanism of environmental factors influencing inefficiencies, and performed statistical tests through the system generalized method of moments. Rational localization of power plants is a systematic project that requires careful consideration of the full utilization of solar resources, low transmission costs, and power consumption guarantee. Suitable temperature, precipitation, and wind speed can improve the working performance of photovoltaic modules, reasonable terrain inclination can reduce land cost, and the proximity to cities strongly guarantees the consumption of electricity. The density of electricity demand and high-tech industries is more important than resource abundance because they trigger the clustering of power plants to result in a good demonstration and competitive effect. To ensure renewable energy consumption, increased support for rural grids and encouraging direct trading between generators and neighboring users will provide solutions. The study will provide proposals for improving the full life-cycle operational activities of solar power plants in China to reduce high non-technical costs and improve competitiveness against fossil energy sources.

Keywords: solar power plants, environmental factors, data envelopment analysis, efficiency evaluation

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Authors: Vojko Kilar, Boris Azinović, David Koren

Abstract:

Recently, an increasing trend of passive and low-energy buildings transferring form non earthquake-prone to earthquake-prone regions has thrown out the question about the seismic safety of such buildings. The paper describes the most commonly used thermal insulating materials and the special details, which could be critical from the point of view of earthquake resistance. The most critical appeared to be the cases of buildings founded on the RC foundation slab lying on a thermal insulation (TI) layer made of extruded polystyrene (XPS). It was pointed out that in such cases the seismic response of such buildings might differ to response of their fixed based counterparts. The main parameters that need special designers’ attention are: the building’s lateral top displacement, the ductility demand of the superstructure, the foundation friction coefficient demand, the maximum compressive stress in the TI layer and the percentage of the uplifted foundation. The analyses have shown that the potentially negative influences of inserting the TI under the foundation slab could be expected only for slender high-rise buildings subjected to severe earthquakes. Oppositely it was demonstrated for the foundation friction coefficient demand which could exceed the capacity value yet in the case of low-rise buildings subjected to moderate earthquakes. Some suggestions to prevent the horizontal shifts are also given.

Keywords: earthquake response, extruded polystyrene (XPS), low-energy buildings, foundations on thermal insulation layer

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Authors: Jiin Jeong, Taekwang Kim, Kwang Ryel Ryu

Abstract:

The target microgrid in this paper is isolated from the large central power system and is assumed to consist of wind generators, photovoltaic power generators, an energy storage system (ESS), a diesel power generator, the community load, and a dump load. The operation of such a microgrid can be hazardous because of the uncertain prediction of power supply and demand and especially due to the high fluctuation of the output from the wind generators. In this paper, we propose an iterative replanning method for determining the appropriate level of diesel generation and the charging/discharging cycles of the ESS for the upcoming one-hour horizon. To cope with the uncertainty of the estimation of supply and demand, the one-hour plan is built repeatedly in the regular interval of one minute by rolling the one-hour horizon. Since the plan should be built with a sufficiently large safe margin to avoid any possible black-out, some energy waste through the dump load is inevitable. In our approach, the level of safe margin is optimized through learning from the past experience. The simulation experiments show that our method combined with the margin optimization can reduce the dump load compared to the method without such optimization.

Keywords: microgrid, operation planning, power efficiency optimization, supply and demand prediction

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Authors: Erika Yamaguchi, Sirawadee Arunyanrt, Shunichi Ohmori, Kazuho Yoshimoto

Abstract:

In this paper, we suggest a simulation tool to make a decision of monthly production planning for maximizing a profit of Specialty store retailer of Private label Apparel (SPA) firms. Most of SPA firms are fabless and make outsourcing deals for productions with factories of their subcontractors. Every month, SPA firms make a booking for production lines and manpower in the factories. The booking is conducted a few months in advance based on a demand prediction and a monthly production planning at that time. However, the demand prediction is updated month by month, and the monthly production planning would change to meet the latest demand prediction. Then, SPA firms have to change the capacities initially booked within a certain range to suit to the monthly production planning. The booking system is called “capacity-booking”. These days, though it is an issue for SPA firms to make precise monthly production planning, many firms are still conducting the production planning by empirical rules. In addition, it is also a challenge for SPA firms to match their products and factories with considering their demand predictabilities and regulation abilities. In this paper, we suggest a model for considering these two issues. An objective is to maximize a total profit of certain periods, which is sales minus costs of production, inventory, and capacity-booking penalty. To make a better monthly production planning at SPA firms, these points should be considered: demand predictabilities by random trends, previous and next month’s production planning of the target month, and regulation abilities of the capacity-booking. To decide matching products and factories for outsourcing, it is important to consider seasonality, volume, and predictability of each product, production possibility, size, and regulation ability of each factory. SPA firms have to consider these constructions and decide orders with several factories per one product. We modeled these issues as a linear programming. To validate the model, an example of several computational experiments with a SPA firm is presented. We suppose four typical product groups: basic, seasonal (Spring / Summer), seasonal (Fall / Winter), and spot product. As a result of the experiments, a monthly production planning was provided. In the planning, demand predictabilities from random trend are reduced by producing products which are different product types. Moreover, priorities to produce are given to high-margin products. In conclusion, we developed a simulation tool to make a decision of monthly production planning which is useful when the production planning is set every month. We considered the features of capacity-booking, and matching of products and factories which have different features and conditions.

Keywords: capacity-booking, SPA, monthly production planning, linear programming

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Authors: Jenan Abu Qadourah

Abstract:

With the depletion of traditional fossil resources and the growing human population, it is now more important than ever to reduce our energy usage and harmful emissions. In the Mediterranean region, the intense solar radiation contributes to summertime overheating, which raises energy costs and building carbon footprints, alternatively making it suitable for the installation of solar energy systems. In urban settings, where multi-story structures predominate and roof space is limited, photovoltaic integrated shading devices (PVSD) are a clean solution for building designers. However, incorporating photovoltaic (PV) systems into a building's envelope is a complex procedure that, if not executed correctly, might result in the PV system failing. As a result, potential PVSD design solutions must be assessed based on their overall energy performance from the project's early design stage. Therefore, this paper aims to investigate and compare the possible impact of various PVSDs on the energy performance of new apartments in the Mediterranean region, with a focus on Amman, Jordan. To achieve the research aim, computer simulations were performed to assess and compare the energy performance of different PVSD configurations. Furthermore, an energy index was developed by taking into account all energy aspects, including the building's primary energy demand and the PVSD systems' net energy production. According to the findings, the PVSD system can meet 12% to 43% of the apartment building's electricity needs. By highlighting the potential interest in PVSD systems, this study aids the building designer in producing more energy-efficient buildings and encourages building owners to install PV systems on the façade of their buildings.

Keywords: photovoltaic integrated shading device, solar energy, architecture, energy performance, simulation, overall energy index, Jordan

Procedia PDF Downloads 65

Authors: Amando A. Radomes Jr., LLoyd Jun Benjamin T. Embernatre, Cherssy Kaye F. Eviota, Krizia Allyn L. Nunez, Jose Thaddeus B. Roble III

Abstract:

Sitio Kantaling is one of the 34 villages in Danao City, Cebu, in the central Philippines. As of 2015, the eight households in the mountainous village extending over 40 hectares of land area, including 12 hectares of arable land, are the source of over a fifth of the agricultural products that go into the city. Over the years, however, the local government had been concerned with the decline in agricultural productivity because increasing number of residents are migrating into the urban areas of the region to look for better employment opportunities. One of the major reasons for the agricultural productivity decline is underdeveloped irrigation infrastructure. The local government had partnered with the University of San Carlos to conduct research on developing an irrigation system that could sustainably meet both agricultural and household consumption needs. From a macro-perspective, a dynamic simulation model was developed to understand the long-term behavior of the status quo and proposed the system. Data on population, water supply and demand, household income, and urban migration were incorporated in the 20-year horizon model. The study also developed a smart irrigation system design. Instead of using electricity to pump water, a network of aqueducts with three main nodes had been designed and strategically located to take advantage of gravity to transport water from a spring. Simulation results showed that implementing a sustainable irrigation system would be able to significantly contribute to the socio-economic progress of the local community.

Keywords: agriculture, aqueduct, simulation, sustainable irrigation system

Procedia PDF Downloads 153

Authors: Mohsen Azarmjoo, Yasaman Azarmjoo, Zahra Alikhani Koopaei

Abstract:

The increasing global population and continued growth in energy consumption underscore the need for renewable and sustainable energy sources more than ever. Soil batteries are a method for generating electrical energy by using recycled materials. Recycled materials include galvanized and copper sheets and recycled tires. Additionally, hydrogen, being a clean and efficient fuel, has the potential to replace fossil fuels. Consequently, hydrogen production from water presents a sustainable solution for energy supply. By utilizing aged materials, hydrogen production becomes more cost-effective and environmentally friendly. This article focuses on energy-deprived agricultural lands, explaining how soil batteries and hydrogen can provide the necessary energy for agricultural equipment, such as irrigation, lighting, greenhouse ventilation, and heating. The article explores the benefits of utilizing this method, emphasizing its potential to reduce environmental pollution through the use of recyclable materials. It is worth mentioning that these technologies face challenges, but their progress toward achieving zero-energy consumer standards positions them as promising future technologies for electricity generation. This article provides detailed insights into emerging technologies using a constructed case study involving soil batteries and a hydrogen fuel production device.

Keywords: electricity generation, soil batteries, tires, hydrogen, heat supply, water, aged materials, recycling, agricultural lands

Procedia PDF Downloads 47