Search results for: energy demand forecasting

Authors: Dongkwon Han, Sangho Kim, Sunil Kwon

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Unconventional gas resources have dramatically changed the future energy landscape. Unlike conventional gas resources, the key challenges in unconventional gas have been the requirement that applies to advanced approaches for production forecasting due to uncertainty and complexity of fluid flow. In this study, artificial neural network (ANN) model which integrates machine learning and data-driven approach was developed to predict productivity in shale gas. The database of 129 wells of Eagle Ford shale basin used for testing and training of the ANN model. The Input data related to hydraulic fracturing, well completion and productivity of shale gas were selected and the output data is a cumulative production. The performance of the ANN using all data sets, clustering and variables importance (VI) models were compared in the mean absolute percentage error (MAPE). ANN model using all data sets, clustering, and VI were obtained as 44.22%, 10.08% (cluster 1), 5.26% (cluster 2), 6.35%(cluster 3), and 32.23% (ANN VI), 23.19% (SVM VI), respectively. The results showed that the pre-trained ANN model provides more accurate results than the ANN model using all data sets.

Keywords: unconventional gas, artificial neural network, machine learning, clustering, variables importance

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Authors: Medya Fathi

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Moving toward sustainable development is among today’s critical issues worldwide that make all industries, particularly construction, pay increasing attention to a healthy environment and a society with a prosperous economy. One of the solutions is to improve buildings’ energy performance by cutting energy consumption and related carbon emissions, eventually improving the quality of life. Unfortunately, the energy demand for buildings is rising. For instance, in Europe, the building sector accounts for 19% of the global energy-related greenhouse gas (GHGs) emissions, the main contributor to global warming in the last 50 years, and 36% of the total CO2 emissions, according to European Commission 2019. The crisis of energy use demands expanding knowledge and understanding of the potential benefits of energy-efficient buildings. In this regard, the present paper aims to critically review the existing body of knowledge on improving energy efficiency in buildings and detail the significant research contributions. Peer-reviewed journal articles published in the last decade in reputed journals were reviewed using the database Scopus and keywords of Sustainability, Sustainable Development, Energy Performance, Energy Consumption, Energy Efficiency, and Buildings. All contributions will be classified by journal type, publication time, country/region, building occupancy type, applied strategies, and findings. This study will provide an essential basis for researchers working on missing areas and filling the existing gaps in the body of knowledge.

Keywords: sustainability, energy performance, energy efficiency, buildings, review

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Authors: Debby Rizqie Amelia Gustin, Purnomo Yusgiantoro

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Hydrocarbon energy is still pivotal to today’s economy, but its existence is continually declining. Thus, preserving future energy supply has become the national interest of many countries, which they cater in various way, from importing to expansion and occupation. Underwater of Natuna islands in Indonesia deposits great amount of natural gas reserved, numbered to 46 TCF (trillion cubic feet), which is highly potential to meet Indonesia future energy demand. On the other hand, there could be a possibility that others also seek this natural resources. Natuna is located in the borderline of Indonesia, directly adjacent to the South China Sea, an area which is prolonged to conflict. It is a challenge for Indonesia government to preserve their energy deposit in Natuna islands and to response accordingly if the tension in South China Sea rises. This paper examines that nowadays defense and border security is not only a matter of guarding a country from foreign invasion, but also securing its resources accumulated on the borderline. Countries with great amount of energy deposits on their borderline need to build up their defense capacity continually, to ensure their territory along with their energy deposits is free from any interferences.

Keywords: border security, defense, energy, national interest, threat

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Authors: A. S. Zgalei, B. T. Al-Mabrouk

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With a particularly significant growth rate observed in the Libyan commercial and residential buildings coupled with a growth in energy demand, solar desiccant evaporative cooling offers energy savings and promises a good sharing for sustainable buildings where the availability of solar radiation matches with the cooling load demand. The paper presents a short introduction for the desiccant systems. A mathematical model of a selected system has been developed and a simulation has been performed in order to investigate the system performance at different working conditions and an optimum design of the system structure is established. The results showed a technical feasibility of the system working under the Libyan climatic conditions with a reasonable COP at temperatures that can be obtained through the solar reactivation system. Discussion of the results and the recommendations for future work are proposed.

Keywords: computer program, solar desiccant wheel cooling, system modelling, simulation, technical feasibility

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Authors: Yong Zhou, Congping Wu, Zhigang Zou

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With the rapid societal development, energy demand has increased exponentially and is mainly based on traditional and nonrenewable energy resources, such as petroleum, fossil fuels, and coal. The combustion of carbon-containing fuels releases a large amount of CO₂, causing the greenhouse effect that contribute to climate change. Photocatalytic CO₂ reduction into solar fuels is a promising approach to simultaneously alleviate current energy and environmental issues. In this study, we report the synthesis of a series of atomically ultrathin 2D structures, which contain an ultrahigh fraction of surface atoms, benefitting for efficiency and selectivity regulation of the target products toward CO₂ photoconversion.

Keywords: Photocatalysis, CO₂, Solar fuels, Nanostructure

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Authors: Same Noel Ngando, Yakub Abdulfatai Olatunji

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Renewable energy micro-grids, such as those powered by solar or wind energy, are often intermittent in nature. This means that the amount of energy generated by these systems can vary depending on weather conditions or other factors, which can make it difficult to ensure a steady supply of power. To address this issue, energy storage systems have been developed to increase the reliability of renewable energy micro-grids. Battery systems have been the dominant energy storage technology for renewable energy micro-grids. Batteries can store large amounts of energy in a relatively small and compact package, making them easy to install and maintain in a micro-grid setting. Additionally, batteries can be quickly charged and discharged, allowing them to respond quickly to changes in energy demand. However, the process involved in recycling batteries is quite costly and difficult. An alternative energy storage system that is gaining popularity is hydrogen storage. Hydrogen is a versatile energy carrier that can be produced from renewable energy sources such as solar or wind. It can be stored in large quantities at low cost, making it suitable for long-distance mass storage. Unlike batteries, hydrogen does not degrade over time, so it can be stored for extended periods without the need for frequent maintenance or replacement, allowing it to be used as a backup power source when the micro-grid is not generating enough energy to meet demand. When hydrogen is needed, it can be converted back into electricity through a fuel cell. Energy consumption data is got from a particular residential area in Daegu, South Korea, and the data is processed and analyzed. From the analysis, the total energy demand is calculated, and different hybrid energy system configurations are designed using HOMER Pro (Hybrid Optimization for Multiple Energy Resources) and MATLAB software. A techno-economic and environmental comparison and life cycle assessment (LCA) of the different configurations using battery and hydrogen as storage systems are carried out. The various scenarios included PV-hydrogen-grid system, PV-hydrogen-grid-wind, PV-hydrogen-grid-biomass, PV-hydrogen-wind, PV-hydrogen-biomass, biomass-hydrogen, wind-hydrogen, PV-battery-grid-wind, PV- battery -grid-biomass, PV- battery -wind, PV- battery -biomass, and biomass- battery. From the analysis, the least cost system for the location was the PV-hydrogen-grid system, with a net present cost of about USD 9,529,161. Even though all scenarios were environmentally friendly, taking into account the recycling cost and pollution involved in battery systems, all systems with hydrogen as a storage system produced better results. In conclusion, hydrogen is becoming a very prominent energy storage solution for renewable energy micro-grids. It is easier to store compared with electric power, so it is suitable for long-distance mass storage. Hydrogen storage systems have several advantages over battery systems, including flexibility, long-term stability, and low environmental impact. The cost of hydrogen storage is still relatively high, but it is expected to decrease as more hydrogen production, and storage infrastructure is built. With the growing focus on renewable energy and the need to reduce greenhouse gas emissions, hydrogen is expected to play an increasingly important role in the energy storage landscape.

Keywords: renewable energy systems, microgrid, hydrogen production, energy storage systems

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Authors: Bahadır Aydın

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Being one of the most important elements of social evolution, energy has a vital role for a sustainable economy and development. Energy has great importance to level up the welfare. By this importance, countries having rich resources can apply energy as an political instrument. While needs of energy is increasing, sources to respond this need is very limited. Therefore, countries seek for alternative resources to meet their needs. Renewable energy sources have firstly taken into consideration. Being clean and belonging to countries own sources, renewable energy resources have been widely applied during the last decades. However, renewable energy cannot meet all the expectation of energy needs. In this respect, energy efficiency can be seen as an alternative. Energy efficiency can minimize energy consumption without degrading standard of living, lessening quality of products and without increasing energy bills. In this article, energy resources, SWOT analysis of renewable sources, and energy efficiency topics are mainly discussed.

Keywords: energy efficiency, renewable energy, energy regulations, oil, international relations

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Authors: Klathea Sevilla, Marjorie Remolador, Bryan Baltazar, Imee Saladaga, Loureal Camille Inocencio, Ma. Rosario Concepcion Ang

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The underutilization of biomass resources in the Philippines, combined with its growing population and the rise in fossil fuel prices confirms demand for alternative energy sources. The goal of this paper is to provide a comparison of MODIS-based and Landsat-based agricultural land cover maps when used in the estimation of rice hull’s available energy potential. Biomass resource assessment was done using mathematical models and remote sensing techniques employed in a GIS platform.

Keywords: biomass, geographic information system (GIS), remote sensing, renewable energy

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Authors: K. Thakkar, C. Ghenai

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An integrated modeling approach was used in this study to (1) track energy consumption, production, and resource extraction, (2) track greenhouse gases emissions and (3) analyze emissions for local and regional air pollutions. The model was used in this study for short and long term energy and GHG emissions reduction analysis for the state of Florida. The integrated modeling methodology will help to evaluate the alternative energy scenarios and examine emissions-reduction strategies. The mitigation scenarios have been designed to describe the future energy strategies. They consist of various demand and supply side scenarios. One of the GHG mitigation scenarios is crafted by taking into account the available renewable resources potential for power generation in the state of Florida to compare and analyze the GHG reduction measure against ‘Business As Usual’ and ‘Florida State Policy’ scenario. Two more ‘integrated’ scenarios, (‘Electrification’ and ‘Efficiency and Lifestyle’) are crafted through combination of various mitigation scenarios to assess the cumulative impact of the reduction measures such as technological changes and energy efficiency and conservation.

Keywords: energy planning, climate change mitigation assessment, integrated modeling approach, energy alternatives, and GHG emission reductions

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Authors: H. M. Farghally, N. M. Ahmed, H. T. El-Madany, D. M. Atia, F. H. Fahmy

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Energy is required in almost every aspect of human activities and development of any nation in this world. Increasing fossil fuel price, energy security and climate change have important bearings on sustainable development of any nation. The renewable energy technology is considered one of the drastic approaches taken over the world to reduce the energy problem. The preservation of vegetables by freezing is one of the most important methods of retaining quality in agricultural products over long-term storage periods. Freezing factories show high demand of energy for both heat and electricity; the hybrid Photovoltaic/Thermal (PV/T) systems could be used in order to meet this requirement. This paper presents PV/T system design for freezing factory. Also, the complete mathematical modeling and Matlab Simulink of PV/T collector is introduced. The sensitivity analysis for the manufacturing parameters of PV/T collector is carried out to study their effect on the thermal and electrical efficiency.

Keywords: renewable energy, hybrid PV/T system, sensitivity analysis, ecological sciences

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Authors: Chiao-Yi Chen, Dung-Ying Lin

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With the growing awareness of environmental protection and the implementation of government carbon reduction policies, the number of electric vehicles (EVs) has rapidly increased, leading to a surge in charging demand and imposing significant challenges on the existing power grid’s capacity. Traditional urban power grid planning has not adequately accounted for the additional load generated by EV charging, which often strains the infrastructure. This study aims to optimize grid operation and load management by dynamically adjusting EV charging prices based on real-time electricity supply and demand, leveraging consumer demand elasticity to enhance system efficiency. This study uniquely addresses the intricate interplay between urban traffic patterns and power grid dynamics in the context of electric vehicle (EV) adoption. By integrating Hsinchu City's road network with the IEEE 33-bus system, the research creates a comprehensive model that captures both the spatial and temporal aspects of EV charging demand. This approach allows for a nuanced analysis of how traffic flow directly influences the load distribution across the power grid. The strategic placement of charging stations at key nodes within the IEEE 33-bus system, informed by actual road traffic data, enables a realistic simulation of the dynamic relationship between vehicle movement and energy consumption. This integration of transportation and energy systems provides a holistic view of the challenges and opportunities in urban EV infrastructure planning, highlighting the critical need for solutions that can adapt to the ever-changing interplay between traffic patterns and grid capacity. The proposed dynamic pricing strategy effectively reduces peak charging loads, enhances the operational efficiency of charging stations, and maximizes operator profits, all while ensuring grid stability. These findings provide practical insights and a valuable framework for optimizing EV charging infrastructure and policies in future smart cities, contributing to more resilient and sustainable urban energy systems.

Keywords: dynamic pricing, demand elasticity, EV charging, grid load balancing, optimization

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Authors: Soheila Sadeghi

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In construction projects, predicting project performance metrics accurately is essential for effective management and successful delivery. However, conventional methods often depend on fixed baseline plans, disregarding the evolving nature of project progress and external influences. To address this issue, we introduce a distinct approach based on machine learning to forecast key performance indicators, such as cost variance and earned value, for each Work Breakdown Structure (WBS) category within an urban road reconstruction project. Our proposed model leverages time series forecasting techniques, namely Autoregressive Integrated Moving Average (ARIMA) and Long Short-Term Memory (LSTM) networks, to predict future performance by analyzing historical data and project progress. Additionally, the model incorporates external factors, including weather patterns and resource availability, as features to improve forecast accuracy. By harnessing the predictive capabilities of machine learning, our performance forecasting model enables project managers to proactively identify potential deviations from the baseline plan and take timely corrective measures. To validate the effectiveness of the proposed approach, we conduct a case study on an urban road reconstruction project, comparing the model's predictions with actual project performance data. The outcomes of this research contribute to the advancement of project management practices in the construction industry by providing a data-driven solution for enhancing project performance monitoring and control.

Keywords: project performance forecasting, machine learning, time series forecasting, cost variance, schedule variance, earned value management

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Authors: A. Hakimiyan, H. Namazi

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Human behavior is defined as a range of behaviors exhibited by humans who are influenced by different internal or external sources. Human behavior is the subject of much research in different areas of psychology and neuroscience. Despite some advances in studies related to forecasting of human behavior, there are not many researches which consider the effect of the time delay between the presence of stimulus and the related human response. Analysis of EEG signal as a fractal time series is one of the major tools for studying the human behavior. In the other words, the human brain activity is reflected in his EEG signal. Artificial Neural Network has been proved useful in forecasting of different systems’ behavior especially in engineering areas. In this research, a time delay neural network is trained and tested in order to forecast the human EEG signal and subsequently human behavior. This neural network, by introducing a time delay, takes care of the lagging time between the occurrence of the stimulus and the rise of the subsequent action potential. The results of this study are useful not only for the fundamental understanding of human behavior forecasting, but shall be very useful in different areas of brain research such as seizure prediction.

Keywords: human behavior, EEG signal, time delay neural network, prediction, lagging time

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Authors: Fatemeh Behrouzi, Adi Maimun, Mehdi Nakisa

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The growth of population, rising fossil fuel prices which the fossil fuels are limited and decreased day by day, pollution problem due to use of fossil fuels and electrical demand are important role to encourage of using the green energy and renewable technologies. Among different renewable energy technologies, hydro power generation (large and small scale) is the prime choice in terms of contribution to the world's electricity generation by using water current turbines. Nowadays, researchers focus on design and development of different kind of turbines to capture hydro-power electricity generation as clean and reliable energy. This article is review about statues of water current turbines carried out to generate electricity from hydro-kinetic energy especially places that they do not have electricity, but they have access to the current water.

Keywords: water current turbine, renewable energy, hydro-power, mechanic

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Authors: Abdullah Alharbi

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Purpose: This research seeks to take a holistic strategic evaluation of the thermal power plants in Kuwait at both policy and technical level in order to allow a systematic retrofitting program. The new world order in energy generation and consumption demand that sources of energy can safeguard the use of natural resources and generate minimal impacts on the environment. For Kuwait, the energy used per capita is mainly associated with desalination plants. The overall impact of thermal power plant installations manifests indisposed of seawater and the health of marine life. Design/methodology/approach: The research adopts a case study based evaluation of performance data and documents of thermal plant installations in Kuwait. Findings: Research findings on the performance of existing thermal plants demand policy benchmarking with internationally acceptable standards in order to create clarity on decisions regarding demolition, retrofitting, or renewal. Research implications: This research has the potential to strategically inform and influence the piecemeal changes to power plants, including the replacement of power generation equipment, considering the varied technologies for thermal plants. Originality/value: This research provides evidence based data that can be useful for influencing operational efficiency after a holistic evaluation of existing capacity in comparison with future demands.

Keywords: energy, Kuwait, performance, stainability, tracking, thermal plant

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Authors: Pappu Kumar, Ajai Singh, Anshuman Singh

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There are different water user sectors such as rural, urban, mining, subsistence and commercial irrigated agriculture, commercial forestry, industry, power generation which are present in the catchment in Subarnarekha River Basin and Ranchi city. There is an inequity issue in the access to water. The development of the rural area, construction of new power generation plants, along with the population growth, the requirement of unmet water demand and the consideration of environmental flows, the revitalization of small-scale irrigation schemes is going to increase the water demands in almost all the water-stressed catchment. The WEAP Model was developed by the Stockholm Environment Institute (SEI) to enable evaluation of planning and management issues associated with water resources development. The WEAP model can be used for both urban and rural areas and can address a wide range of issues including sectoral demand analyses, water conservation, water rights and allocation priorities, river flow simulation, reservoir operation, ecosystem requirements and project cost-benefit analyses. This model is a tool for integrated water resource management and planning like, forecasting water demand, supply, inflows, outflows, water use, reuse, water quality, priority areas and Hydropower generation, In the present study, efforts have been made to access the utility of the WEAP model for water supply and demand analysis for Ranchi city. A detailed works have been carried out and it was tried to ascertain that the WEAP model used for generating different scenario of water requirement, which could help for the future planning of water. The water supplied to Ranchi city was mostly contributed by our study river, Hatiya reservoir and ground water. Data was collected from various agencies like PHE Ranchi, census data of 2011, Doranda reservoir and meteorology department etc. This collected and generated data was given as input to the WEAP model. The model generated the trends for discharge of our study river up to next 2050 and same time also generated scenarios calculating our demand and supplies for feature. The results generated from the model outputs predicting the water require 12 million litter. The results will help in drafting policies for future regarding water supplies and demands under changing climatic scenarios.

Keywords: WEAP model, water demand analysis, Ranchi, scenarios

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Authors: Shane D. Inder, Mehrdad Khamooshi

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Efficient energy storage is a crucial factor in facilitating the uptake of renewable energy resources. Among the many options available for energy storage systems required to balance imbalanced supply and demand cycles, compressed air energy storage (CAES) is a proven technology in grid-scale applications. This paper reviews the current state of micro scale CAES technology and describes a micro-scale advanced adiabatic CAES (A-CAES) system, where heat generated during compression is stored for use in the discharge phase. It will also describe a thermodynamic model, developed in EES (Engineering Equation Solver) to evaluate the performance and critical parameters of the discharge phase of the proposed system. Three configurations are explained including: single turbine without preheater, two turbines with preheaters, and three turbines with preheaters. It is shown that the micro-scale A-CAES is highly dependent upon key parameters including; regulator pressure, air pressure and volume, thermal energy storage temperature and flow rate and the number of turbines. It was found that a micro-scale AA-CAES, when optimized with an appropriate configuration, could deliver energy input to output efficiency of up to 70%.

Keywords: CAES, adiabatic compressed air energy storage, expansion phase, micro generation, thermodynamic

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Authors: F. Ahwide, Y. Aldali

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This article presents a current and future energy situation in Libya. The electric power efficiency and operating hours in power plants are evaluated from 2005 to 2010. Carbon dioxide emissions in most of power plants are estimated. In 2005, the efficiency of steam power plants achieved a range of 20% to 28%. While, the gas turbine power plants efficiency ranged between 9% and 25%, this can be considered as low efficiency. However, the efficiency improvement has clearly observed in some power plants from 2008 to 2010, especially in the power plant of North Benghazi and west Tripoli. In fact, these power plants have modified to combine cycle. The efficiency of North Benghazi power plant has increased from 25% to 46.6%, while in Tripoli it is increased from 22% to 34%. On the other hand, the efficiency improvement is not observed in the gas turbine power plants. When compared to the quantity of fuel used, the carbon dioxide emissions resulting from electricity generation plants were very high. Finally, an estimation of the energy demand has been done to the maximum load and the annual load factor (i.e., the ratio between the output power and installed power).

Keywords: power plant, efficiency improvement, carbon dioxide emissions, energy situation in Libya

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Authors: Avichal Malhotra, Jerome Frisch, Christoph van Treeck

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The utilization of semantic, cadastral and topological data from geographic information systems (GIS) has exponentially increased for building and urban-scale energy performance simulations. Urban planners, simulation scientists, and researchers use virtual 3D city models for energy analysis, algorithms and simulation tools. For dynamic energy simulations at city and district level, this paper provides an overview of the available GIS data models and their levels of detail. Adhering to different norms and standards, these models also intend to describe building and construction industry data. For further investigations, CityGML data models are considered for simulations. Though geographical information modelling has considerably many different implementations, extensions of virtual city data can also be made for domain specific applications. Highlighting the use of the extended CityGML models for energy researches, a brief introduction to the Energy Application Domain Extension (ADE) along with its significance is made. Consequently, addressing specific input simulation data, a workflow using Modelica underlining the usage of GIS information and the quantification of its significance over annual heating energy demand is presented in this paper.

Keywords: CityGML, EnergyADE, energy performance simulation, GIS

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Authors: Eduardo Rodrigues, Gisela Mendes, José M. Torres, José E. Sousa

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In the sequence of the liberalisation of the electricity sector a progressive engagement of consumers has been considered and targeted by sector regulatory policies. With the objective of promoting market competition while protecting consumers interests, by transferring some of the upstream benefits to the end users while reaching a fair distribution of system costs, different market models to value consumers’ demand flexibility at the energy community level are envisioned. Local Energy and Flexibility Markets (LEFM) involve stakeholders interested in providing or procure local flexibility for community, services and markets’ value. Under the scope of DOMINOES, a European research project supported by Horizon 2020, the local market concept developed is expected to: • Enable consumers/prosumers empowerment, by allowing them to value their demand flexibility and Distributed Energy Resources (DER); • Value local liquid flexibility to support innovative distribution grid management, e.g., local balancing and congestion management, voltage control and grid restoration; • Ease the wholesale market uptake of DER, namely small-scale flexible loads aggregation as Virtual Power Plants (VPPs), facilitating Demand Response (DR) service provision; • Optimise the management and local sharing of Renewable Energy Sources (RES) in Medium Voltage (MV) and Low Voltage (LV) grids, trough energy transactions within an energy community; • Enhance the development of energy markets through innovative business models, compatible with ongoing policy developments, that promote the easy access of retailers and other service providers to the local markets, allowing them to take advantage of communities’ flexibility to optimise their portfolio and subsequently their participation in external markets. The general concept proposed foresees a flow of market actions, technical validations, subsequent deliveries of energy and/or flexibility and balance settlements. Since the market operation should be dynamic and capable of addressing different requests, either prioritising balancing and prosumer services or system’s operation, direct procurement of flexibility within the local market must also be considered. This paper aims to highlight the research on the definition of suitable DR models to be used by the Distribution System Operator (DSO), in case of technical needs, and by the retailer, mainly for portfolio optimisation and solve unbalances. The models to be proposed and implemented within relevant smart distribution grid and microgrid validation environments, are focused on day-ahead and intraday operation scenarios, for predictive management and near-real-time control respectively under the DSO’s perspective. At local level, the DSO will be able to procure flexibility in advance to tackle different grid constrains (e.g., demand peaks, forecasted voltage and current problems and maintenance works), or during the operating day-to-day, to answer unpredictable constraints (e.g., outages, frequency deviations and voltage problems). Due to the inherent risks of their active market participation retailers may resort to DR models to manage their portfolio, by optimising their market actions and solve unbalances. The interaction among the market actors involved in the DR activation and in flexibility exchange is explained by a set of sequence diagrams for the DR modes of use from the DSO and the energy provider perspectives. • DR for DSO’s predictive management – before the operating day; • DR for DSO’s real-time control – during the operating day; • DR for retailer’s day-ahead operation; • DR for retailer’s intraday operation.

Keywords: demand response, energy communities, flexible demand, local energy and flexibility markets

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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: Sandija Zeverte-Rivza, Irina Pilvere, Baiba Rivza

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The use of renewable energy sources incl. biogas has become topical in accordance with the increasing demand for energy, decrease of fossil energy resources and the efforts to reduce greenhouse gas emissions as well as to increase energy independence from the territories where fossil energy resources are available. As the technologies of biogas production from agricultural biomass develop, risk assessment and risk management become necessary for farms producing such a renewable energy. The need for risk assessments has become particularly topical when discussions on changing the biogas policy in the EU take place, which may influence the development of the sector in the future, as well as the operation of existing biogas facilities and their income level. The current article describes results of the risk assessment for farms producing biomass from agriculture biomass in Latvia, the risk assessment system included 24 risks, that affect the whole biogas production process and the obtained results showed the high significance of political and production risks.

Keywords: biogas production, risks, risk assessment, biosystems engineering

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Authors: Humeyra Bolakar Tosun

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The transport sector has an undisputed place in human life. People need transport access to continuous increase day by day with growing population. The number of rail network, urban transport planning, infrastructure improvements, transportation management and other related areas is a key factor affecting our country made it quite necessary to improve the work of transportation. In this context, it plays an important role in domestic rail freight demand planning. Alternatives that the increase in the transportation field and has made it mandatory requirements such as the demand for improving transport quality. In this study generally is known and used in studies by the definition, rail freight transport, railway line length, population, energy consumption. In this study, Iron Road Load Net Demand was modeled by multiple regression and ANN methods. In this study, model dependent variable (Output) is Iron Road Load Net demand and 6 entries variable was determined. These outcome values extracted from the model using ANN and regression model results. In the regression model, some parameters are considered as determinative parameters, and the coefficients of the determinants give meaningful results. As a result, ANN model has been shown to be more successful than traditional regression model.

Keywords: railway load carrying, neural network, modelling transport, transportation

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Authors: Matthew B. Davis, Amit Kumar

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With potentially dangerous impacts of climate change on the horizon, Canada has an opportunity to take a lead role on the international stage to demonstrate how energy use intensity and greenhouse gas emission intensity may be effectively reduced. Through bottom-up modelling of Canada’s energy sector using Long-range Energy Alternative Planning (LEAP) software, it can be determined where efforts should to be concentrated to produce the most positive energy management results. By analyzing a provincially integrated Canada, one can develop strategies to minimize the country’s economic downfall while transitioning to lower-emission energy technologies. Canada’s electricity sector plays an important role in accommodating these transitionary technologies as fossil-fuel based power production is prevalent in many parts of the country and is responsible for a large portion (17%) of Canada’s greenhouse gas emissions. Current findings incorporate an in-depth model of Canada’s current energy supply and demand sectors, as well as a business-as-usual scenario up to the year 2035. This allows for in-depth analysis of energy flow from resource potential, to extraction, to fuel and electricity production, to energy end use and emissions in Canada’s residential, transportation, commercial, institutional, industrial, and agricultural sectors. Bottom-up modelling techniques such as these are useful to critically analyze and compare the various possible scenarios of implementing sustainable energy measures. This work can aid government in creating effective energy and environmental policies, as well as guide industry to what technology or process changes would be most worthwhile to pursue.

Keywords: energy management, LEAP, energy end-use, GHG emissions

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Authors: Phuong Nguyen, Trung Tran

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Along with the global ongoing energy transition, Vietnam has indicated a strong commitment in the last COP events on the zero-carbon emission target. However, it is a real challenge for the nation to replace fossil-fired power plants by a significant amount of renewable energy sources (RES) while maintaining security of supply. The unpredictability and variability of RES would cause technical issues for supply-demand balancing, network congestions, system balancing, among others. It is crucial to take these into account while planning the future grid infrastructure. This study will address both generation and transmission adequacy and reveal a comprehensive analysis about the impact of ongoing energy transition on the development of Vietnam power system in 2030. This will provide insight for creating an secure, stable, and affordable pathway for the country in upcoming years.

Keywords: generation adequacy, transmission adequacy, security of supply, energy transition

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Authors: T. M. Tawfik, M. A. Badr, E. Y. El-Kady, O. E. Abdellatif

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Electric power shortage is a serious problem in remote rural communities in Egypt. Over the past few years, electrification of remote communities including efficient on-site energy resources utilization has achieved high progress. Remote communities usually fed from diesel generator (DG) networks because they need reliable energy and cheap fresh water. The main objective of this paper is to design an optimal economic power supply from hybrid standalone energy system (HSES) as alternative energy source. It covers energy requirements for reverse osmosis desalination unit (DU) located in National Research Centre farm in Noubarya, Egypt. The proposed system consists of PV panels, Wind Turbines (WT), Batteries, and DG as a backup for supplying DU load of 105.6 KWh/day rated power with 6.6 kW peak load operating 16 hours a day. Optimization of HSES objective is selecting the suitable size of each of the system components and control strategy that provide reliable, efficient, and cost-effective system using net present cost (NPC) as a criterion. The harmonization of different energy sources, energy storage, and load requirements are a difficult and challenging task. Thus, the performance of various available configurations is investigated economically and technically using iHOGA software that is based on genetic algorithm (GA). The achieved optimum configuration is further modified through optimizing the energy extracted from renewable sources. Effective minimization of energy charging the battery ensures that most of the generated energy directly supplies the demand, increasing the utilization of the generated energy.

Keywords: energy management, hybrid system, renewable energy, remote area, optimization

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Authors: Isha Rathore, Peeyush Jain, Elangovan Rajasekar

Abstract:

The thermal capacity of the envelope impacts the cooling and heating demand of a building and modulates the peak electricity demand. This paper presents the thermal capacity tuning of a building envelope to minimize peak electricity demand for space cooling. We consider a 40 m² residential testbed located in Hyderabad, India (Composite Climate). An EnergyPlus model is validated using real-time data. A Parametric simulation framework for thermal capacity tuning is created using the Honeybee plugin. Diffusivity, Thickness, layer position, orientation and fenestration size of the exterior envelope are parametrized considering a five-layered wall system. A total of 1824 parametric runs are performed and the optimum wall configuration leading to minimum peak cooling demand is presented.

Keywords: thermal capacity, tuning, peak demand reduction, parametric analysis

Procedia PDF Downloads 184

Authors: Tianyu Wang, Nikita Karandikar

Abstract:

The uncertainty around cost, safety, and feasibility of the decarbonized shipping fuels has made it increasingly complex for the shipping companies to set pricing strategies and forecast their freight revenues going forward. The increase in the green fuel surcharges will ultimately influence the automobile’s consumer prices. The auto shipping demand (ton-miles) has been gradually shifting from long-haul to short-sea trade over the past years following the relocation of the original equipment manufacturer (OEM) manufacturing to regions such as South America and Southeast Asia. The objective of this paper is twofold: 1) to investigate the car-carriers freight revenue development over the years when the trade pattern is gradually shifting towards short-sea exports 2) to empirically identify the quantitative impact of such trade pattern shifting to mainly freight rate, but also vessel size, fleet size as well as Green House Gas (GHG) emission in Roll on-Roll Off (Ro-Ro) shipping. In this paper, a model of analyzing and forecasting ton-miles and freight revenues for the trade routes of AS-NA (Asia to North America), EU-NA (Europe to North America), and SA-NA (South America to North America) is established by deploying Automatic Identification System (AIS) data and the financial results of a selected car carrier company. More specifically, Wallenius Wilhelmsen Logistics (WALWIL), the Norwegian Ro-Ro carrier listed on Oslo Stock Exchange, is selected as the case study company in this paper. AIS-based ton-mile datasets of WALWIL vessels that are sailing into North America region from three different origins (Asia, Europe, and South America), together with WALWIL’s quarterly freight revenues as reported in trade segments, will be investigated and compared for the past five years (2018-2022). Furthermore, ordinary‐least‐square (OLS) regression is utilized to construct the ton-mile demand and freight revenue forecasting. The determinants of trade pattern shifting, such as import tariffs following the China-US trade war and fuel prices following the 0.1% Emission Control Areas (ECA) zone requirement after IMO2020 will be set as key variable inputs to the machine learning model. The model will be tested on another newly listed Norwegian Car Carrier, Hoegh Autoliner, to forecast its 2022 financial results and to validate the accuracy based on its actual results. GHG emissions on the three routes will be compared and discussed based on a constant emission per mile assumption and voyage distances. Our findings will provide important insights about 1) the trade-off evaluation between revenue reduction and energy saving with the new ton-mile pattern and 2) how the trade flow shifting would influence the future need for the vessel and fleet size.

Keywords: AIS, automobile exports, maritime big data, trade flows

Procedia PDF Downloads 120

Authors: Ying Su, Morgan C. Wang

Abstract:

Long-term time series forecasting is an important research area for automated machine learning (AutoML). Currently, forecasting based on either machine learning or statistical learning is usually built by experts, and it requires significant manual effort, from model construction, feature engineering, and hyper-parameter tuning to the construction of the time series model. Automation is not possible since there are too many human interventions. To overcome these limitations, this article proposed to use recurrent neural networks (RNN) through the memory state of RNN to perform long-term time series prediction. We have shown that this proposed approach is better than the traditional Autoregressive Integrated Moving Average (ARIMA). In addition, we also found it is better than other network systems, including Fully Connected Neural Networks (FNN), Convolutional Neural Networks (CNN), and Nonpooling Convolutional Neural Networks (NPCNN).

Keywords: automated machines learning, autoregressive integrated moving average, neural networks, time series analysis

Procedia PDF Downloads 105

Authors: Eliud Kiprop, Kenichi Matsui, Joseph Karanja, Hesborn Ondiba

Abstract:

To double the share of renewable energy in the global energy mix by 2030 as part of actions for the Paris Agreement, policymakers in each ratifying country must accelerate their efforts within the next few years by implementing their own renewable energy strategies. Kenya has increased its funding for research and development in renewable energy sources largely because it intends to reduce greenhouse gas GHG emissions by 30% from business as usual (BAU) levels (143 MtCO₂eq) by 2030. In 2013, the Kenyan government launched an ambitious plan to increase the installed power generation capacity from 1,768MW to more than 5,000MW by the end of 2017. This paper examines the formulation and implementation process of this plan and shows how this plan will affect Kenya’s renewable energy industry and national policy implementation in general. Results demonstrate that, despite having a well- documented policy in place, the Kenyan government cannot meet its target of 5000MW by the end of 2017. Among other factors, we find that the main reason is attributable to the failure in adhering to the main principles of the policy plan. We also find that the government has failed to consider the future energy demand. Had the policy been implemented on time, we argue that there would have been excess power.

Keywords: policy implementation, policy plan, renewable energy, sustainable development

Procedia PDF Downloads 216