Search results for: cost of energy (COE)

Authors: Raouf Hassan

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Biogas energy production from sewage sludge is an economically feasible and eco-friendly in nature. Sewage sludge is considered nutrient-rich substrates, but had lower values of carbone which consider an energy source for anaerobic bacteria. The lack or lower values of carbone-to-nitrogen ratio (C/N) reduced biogas yield and fermentation rate. Anaerobic co-digestion of sewage sludge offers several benefits over mono-digestion such as optimize nutrient balance, increased cost-efficiency and increased degradation rate. The high produced amounts of animal manures, which reach up to 90% of the total collected organic wastes, are recommended for the co-digestion with sewage sludge, especially with the limitations of industrial substrates. Moreover, cattle manures had high methane production potential (500 m3/t vsadded). When mixed with sewage sludge the potential methane production increased with increasing cattle manure content. In this paper, the effect of cattle manure (CM) addition as co-substrates on the sewage sludge (SS) anaerobic digestion performance was investigated under mesophilic conditions (35°C) using anaerobic batch reactors. The batch reactors were operated with a working volume 0.8 liter, and a hydraulic retention time of 30 days. The research work focus on studying two main parameters; the biogas yield (expressed as VSS) and pH values inside the reactors.

Keywords: anaerobic digestion, sewage sludge, cattle manure, mesophilic, biogas yield, pH

Procedia PDF Downloads 315

Authors: Fally Titikpina, Abderafi Charki, Antoine Caucheteux, David Bigaud

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The building sector is one of the largest energy consumer with about 40% of the final energy consumption in the European Union. Ensuring building energy performance is of scientific, technological and sociological matter. To assess a building energy performance, the consumption being predicted or estimated during the design stage is compared with the measured consumption when the building is operational. When valuing this performance, many buildings show significant differences between the calculated and measured consumption. In order to assess the performance accurately and ensure the thermal efficiency of the building, it is necessary to evaluate the uncertainties involved not only in measurement but also those induced by the propagation of dynamic and static input data in the model being used. The evaluation of measurement uncertainty is based on both the knowledge about the measurement process and the input quantities which influence the result of measurement. Measurement uncertainty can be evaluated within the framework of conventional statistics presented in the \textit{Guide to the Expression of Measurement Uncertainty (GUM)} as well as by Bayesian Statistical Theory (BST). Another choice is the use of numerical methods like Monte Carlo Simulation (MCS). In this paper, we proposed to evaluate the uncertainty associated to the use of a simplified model for the estimation of the energy consumption of a given building. A detailed review and discussion of these three approaches (GUM, MCS and BST) is given. Therefore, an office building has been monitored and multiple sensors have been mounted on candidate locations to get required data. The monitored zone is composed of six offices and has an overall surface of 102 $m^2$. Temperature data, electrical and heating consumption, windows opening and occupancy rate are the features for our research work.

Keywords: building energy performance, uncertainty evaluation, GUM, bayesian approach, monte carlo method

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Authors: A. Bertašienė

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Energy harvesting from any structure makes a challenge. Different structure of air/wind flows in industrial, environmental and residential applications emerge the real flow investigation in detail. Many of the application fields are hardly achievable to the detailed description due to the lack of up-to-date statistical data analysis. In situ measurements aim crucial investments thus the simulation methods come to implement structural analysis of the flows. Different configurations of testing environment give an overview how important is the simple structure of field in limited area on efficiency of the system operation and the energy output. Several configurations of modeled working sections in air flow test facility was implemented in CFD ANSYS environment to compare experimentally and numerically air flow development stages and forms that make effects on efficiency of devices and processes. Effective form and amount of these flows under different geometry cases define the manner of instruments/devices that measure fluid flow parameters for effective operation of any system and emission flows to define. Different fluid flow regimes were examined to show the impact of fluctuations on the development of the whole volume of the flow in specific environment. The obtained results rise the discussion on how these simulated flow fields are similar to real application ones. Experimental results have some discrepancies from simulation ones due to the models implemented to fluid flow analysis in initial stage, not developed one and due to the difficulties of models to cover transitional regimes. Recommendations are essential for energy harvesting systems in both, indoor and outdoor cases. Further investigations aim to be shifted to experimental analysis of flow under laboratory conditions using state-of-the-art techniques as flow visualization tool and later on to in situ situations that is complicated, cost and time consuming study.

Keywords: fluid flow, initial region, tube coefficient, distinct shape

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Authors: Dawit Abay Tesfamariam

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Ethiopia’s Climate- Resilient Green Economy (ECRGE) strategy focuses mainly on generating and proper utilization of renewable energy (RE). Nonetheless, the current electricity generation of the country is dominated by hydropower. The data collected in 2016 by Ethiopian Electric Power (EEP) indicates that the intermittent RE sources from solar and wind energy were only 8 %. On the other hand, the EEP electricity generation plan in 2030 indicates that 36.1 % of the energy generation share will be covered by solar and wind sources. Thus, a case study was initiated to model and compute the balance and consumption of electricity in three different scenarios: 2016, 2025, and 2030 using the EnergyPLAN Model (EPM). Initially, the model was validated using the 2016 annual power-generated data to conduct the EnergyPLAN (EP) analysis for two predictive scenarios. The EP simulation analysis using EPM for 2016 showed that there was no significant excess power generated. Thus, the EPM was applied to analyze the role of energy storage in RE in Ethiopian grid systems. The results of the EP simulation analysis showed there will be excess production of 402 /7963 MW average and maximum, respectively, in 2025. The excess power was in the three rainy months of the year (June, July, and August). The outcome of the model also showed that in the dry seasons of the year, there would be excess power production in the country. Consequently, based on the validated outcomes of EP indicates, there is a good reason to think about other alternatives for the utilization of excess energy and storage of RE. Thus, from the scenarios and model results obtained, it is realistic to infer that if the excess power is utilized with a storage system, it can stabilize the grid system and be exported to support the economy. Therefore, researchers must continue to upgrade the current and upcoming storage system to synchronize with potentials that can be generated from renewable energy.

Keywords: renewable energy, power, storage, wind, energy plan

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Authors: Maziyar Nouraee

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Electronic markets in recent decades contribute remarkably in business transactions. Many organizations consider traditional ways of trade non-economical and therefore they do trade only through electronic markets. There are different categorizations of electronic markets functions. In one classification, functions of electronic markets are categorized into classes as information, transactions, and value added. In the present paper, effects of the three classes on the two major elements of the supply chain management are measured. The two elements are decrease in the product unit cost and reduction in response time to the customer. The results of the current research show that among nine minor elements related to the three classes of electronic markets functions, six factors and three factors influence on reduction of the product unit cost and reduction of response time to the customer, respectively.

Keywords: electronic commerce, electronic market, B2B trade, supply chain management

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Authors: Despina Vamvuka, Despina Pentari

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Forestry wastes are readily available in large quantities around the world. Based on European Green Deal for the deployment of renewable and decarbonized energy by 2050, as well as global energy crisis, energy recovery from such wastes reducing greenhouse gas emissions is very attractive. Gasification has superior environmental performance to combustion, producing a clean fuel gas utilized in internal combustion engines, gas turbines, solid oxide fuel cells, or for synthesis of liquid bio-fuels and value-added chemicals. In this work, pine needles, which are abundantly found in Mediterranean countries, were gasified by either steam or carbon dioxide via a two-step process to improve reactivity and eliminate tar, employing a fixed bed unit and a thermal analysis system. Solid, liquid and gaseous products from the whole process were characterized and their energy potential was determined. Thermal behaviour, reactivity, conversion and energy recovery were examined. The gasification process took place above 650°C. At 950°C conversion and energy recovery were 77% dry and 2 under a flow of steam and 85% dry and 2.9 under a flow of carbon dioxide, respectively. Organic matter was almost completely converted to syngas, the yield of which varied between 89% and 99%. The higher heating values of biochar, bio-oil and pyrolysis gas were 27.8 MJ/kg, 33.5 MJ/kg and 13.6 MJ/m3. Upon steam or carbon dioxide gasification, the higher heating value of syngas produced was 11.5 MJ/m3 and 12.7 MJ/m3, respectively.

Keywords: gasification, biomass, steam, carbon dioxide

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Authors: P. Mandree, S. O. Ramchuran, F. O'Brien, L. Sethunya, S. Khumalo

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South Africa is identified as one of the five emerging waste management markets, globally. The waste sector in South Africa influences the areas of energy, water and food at an economic and social level. Recently, South African industries have focused on waste valorization and diversification of the current product offerings in an attempt to reduce industrial waste, target a zero waste-to-landfill initiative and recover energy. South Africa has a number of waste streams including industrial and agricultural biomass, municipal waste and marine waste. Large volumes of agricultural and forestry residues, in particular, are generated which provides significant opportunity for production of bio-based fuels and chemicals. This could directly impact development of a rural economy. One of the largest agricultural industries is the sugar industry, which contributes significantly to the country’s economy and job creation. However, the sugar industry is facing challenges due to fluctuations in sugar prices, increasing competition with low-cost global sugar producers, increasing energy and agricultural input costs, lower consumption and aging facilities. This study is aimed at technology development for the production of various bio-based chemicals using feedstock from the sugar refining process. Various indigenous bacteria and yeast species were assessed for the potential to produce platform chemicals in flask studies and at 30 L fermentation scale. Quantitative analysis of targeted bio-based chemicals was performed using either gas chromatography or high pressure liquid chromatography to assess production yields and techno-economics in order to compare performance to current commercial benchmark processes. The study also creates a decision platform for the research direction that is required for strain development using Industrial Synthetic Biology.

Keywords: bio-based chemicals, biorefinery, industrial synthetic biology, waste valorization

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Authors: Soheila Sadeghi

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Construction projects are complex and often subject to significant cost overruns due to the multifaceted nature of the activities involved. Accurate cost estimation is crucial for effective budget planning and resource allocation. Traditional methods for predicting overruns often rely on expert judgment or analysis of historical data, which can be time-consuming, subjective, and may fail to consider important factors. However, with the increasing availability of data from construction projects, machine learning techniques can be leveraged to improve the accuracy of overrun predictions. This study applied machine learning algorithms to enhance the prediction of cost overruns in a case study of a construction project. The methodology involved the development and evaluation of two machine learning models: Random Forest and Neural Networks. Random Forest can handle high-dimensional data, capture complex relationships, and provide feature importance estimates. Neural Networks, particularly Deep Neural Networks (DNNs), are capable of automatically learning and modeling complex, non-linear relationships between input features and the target variable. These models can adapt to new data, reduce human bias, and uncover hidden patterns in the dataset. The findings of this study demonstrate that both Random Forest and Neural Networks can significantly improve the accuracy of cost overrun predictions compared to traditional methods. The Random Forest model also identified key cost drivers and risk factors, such as changes in the scope of work and delays in material delivery, which can inform better project risk management. However, the study acknowledges several limitations. First, the findings are based on a single construction project, which may limit the generalizability of the results to other projects or contexts. Second, the dataset, although comprehensive, may not capture all relevant factors influencing cost overruns, such as external economic conditions or political factors. Third, the study focuses primarily on cost overruns, while schedule overruns are not explicitly addressed. Future research should explore the application of machine learning techniques to a broader range of projects, incorporate additional data sources, and investigate the prediction of both cost and schedule overruns simultaneously.

Keywords: resource allocation, machine learning, optimization, data-driven decision-making, project management

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Authors: Daud Mustafa Minhas, Raja Rehan Khalid, Georg Frey

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The next generation power systems are equipped with abundantly available free renewable energy resources (RES). During their low-cost operations, the price of electricity significantly reduces to a lower value, and sometimes it becomes negative. Therefore, it is recommended not to operate the traditional power plants (e.g. coal power plants) and to reduce the losses. In fact, it is not a cost-effective solution, because these power plants exhibit some shutdown and startup costs. Moreover, they require certain time for shutdown and also need enough pause before starting up again, increasing inefficiency in the whole power network. Hence, there is always a trade-off between avoiding negative electricity prices, and the startup costs of power plants. To exploit this trade-off and to increase the profit of a power plant, two main contributions are made: 1) introducing retrofit technology for state of art coal power plant; 2) proposing optimal control strategy for a power plant by exploiting different flexibility features. These flexibility features include: improving ramp rate of power plant, reducing startup time and lowering minimum load. While, the control strategy is solved as mixed integer linear programming (MILP), ensuring optimal solution for the profit maximization problem. Extensive comparisons are made considering pre and post-retrofit coal power plant having the same efficiencies under different electricity price scenarios. It concludes that if the power plant must remain in the market (providing services), more flexibility reflects direct economic advantage to the plant operator.

Keywords: discrete optimization, power plant flexibility, profit maximization, unit commitment model

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Authors: Bryan Jefry Sabillon, Arlex Molina Cedillo

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Currently, the raise in the demand of electrical energy as a consequence of the development of technology and population growth, as well as some projections made by ‘La Agencia Internacional de la Energía’ (AIE) and research institutes, reveal alarming data about the expected raise of it in the next few decades. Because of this, something should be made to raise the awareness of the rational and efficient usage of this resource. Because of the global concern of providing electrical energy to isolated areas, projects consisting of energy generation using renewable resources are commonly carried out. On a socioeconomically and cultural point of view, it can be foreseen a positive impact that would result for the society to have this resource. This article is focused on the great potential that Honduras shows, as a country that is looking forward to produce renewable energy due to the crisis that it’s living nowadays. Because of this, we present a detailed research that exhibits the main necessities that the rural communities are facing today, to allay the negative aspects due to the scarcity of electrical energy. We also discuss which should be the type of electrical generation method to be used, according to the disposition, geography, climate, and of course the accessibility of each area. Honduras is actually in the process of developing new methods for the generation of energy; therefore, it is of our concern to talk about renewable energy, the exploitation of which is a global trend. Right now the countries’ main energetic generation methods are: hydrological, thermic, wind, biomass and photovoltaic (this is one of the main sources of clean electrical generation). The use of these resources was possible partially due to the studies made by the organizations that focus on electrical energy and its demand, such as ‘La Cooperación Alemana’ (GIZ), ‘La Secretaria de Energía y Recursos Naturales’ (SERNA), and ‘El Banco Centroamericano de Integración Económica’ (BCIE), which eased the complete guide that is to be used in the protocol to be followed to carry out the three stages of this type of projects: 1) Licences and Permitions, 2) Fincancial Aspects and 3) The inscription for the Protocol in Kyoto. This article pretends to take the reader through the necessary information (according to the difficult accessibility that each zone might present), about the best option of electrical generation in zones that are totally isolated from the net, pretending to use renewable resources to generate electrical energy. We finally conclude that the usage of hybrid systems of generation of energy for small remote communities brings about a positive impact, not only because of the fact of providing electrical energy but also because of the improvements in education, health, sustainable agriculture and livestock, and of course the advances in the generation of energy which is the main concern of this whole article.

Keywords: energy, isolated, renewable, accessibility

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Authors: Furkan Ozkan, M. Selcuk Arslan, Hatice Mercan

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Electric vehicles are becoming increasingly popular asa sustainable alternative to traditional combustion engine vehicles. However, to fully realize the potential of EVs in reducing environmental impact and energy consumption, efficient control strategies are essential. This study explores the application of green wave control using model predictive control for electric vehicles, coupled with energy consumption modeling using neural networks. The use of MPC allows for real-time optimization of the vehicles’ energy consumption while considering dynamic traffic conditions. By leveraging neural networks for energy consumption modeling, the EV's performance can be further enhanced through accurate predictions and adaptive control. The integration of these advanced control and modeling techniques aims to maximize energy efficiency and range while navigating urban traffic scenarios. The findings of this research offer valuable insights into the potential of green wave control for electric vehicles and demonstrate the significance of integrating MPC and neural network modeling for optimizing energy consumption. This work contributes to the advancement of sustainable transportation systems and the widespread adoption of electric vehicles. To evaluate the effectiveness of the green wave control strategy in real-world urban environments, extensive simulations were conducted using a high-fidelity vehicle model and realistic traffic scenarios. The results indicate that the integration of model predictive control and energy consumption modeling with neural networks had a significant impact on the energy efficiency and range of electric vehicles. Through the use of MPC, the electric vehicle was able to adapt its speed and acceleration profile in realtime to optimize energy consumption while maintaining travel time objectives. The neural network-based energy consumption modeling provided accurate predictions, enabling the vehicle to anticipate and respond to variations in traffic flow, further enhancing energy efficiency and range. Furthermore, the study revealed that the green wave control strategy not only reduced energy consumption but also improved the overall driving experience by minimizing abrupt acceleration and deceleration, leading to a smoother and more comfortable ride for passengers. These results demonstrate the potential for green wave control to revolutionize urban transportation by enhancing the performance of electric vehicles and contributing to a more sustainable and efficient mobility ecosystem.

Keywords: electric vehicles, energy efficiency, green wave control, model predictive control, neural networks

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Authors: Hamed Saremi, Shahla Saremi

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In this study, control and management of construction projects is evaluated through developing a dynamic model in which some means are used in order to evaluating planning assumptions and reviewing the effectiveness of some project control policies based on previous researches about time, cost, project schedule pressure management, source management, project control, adding elements and sub-systems from cost management such as estimating consumption budget from budget due to costs, budget shortage effects and etc. using sensitivity analysis, researcher has evaluated introduced model that during model simulation by VENSIM software and assuming optimistic times and adding information about doing job and changes rate and project is forecasted with 373 days (2 days sooner than forecasted) and final profit $ 1,960,670 (23% amount of contract) assuming 15% inflation rate in year and costs rate accordance with planned amounts and other input information and final profit.

Keywords: dynamic planning, cost, time, performance, project management

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Authors: Dehong Li, Yuchen Chen, Alireza Kaboorani, Denis Rodrigue, Xiaodong (Alice) Wang

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Utilizing solar energy for thermal energy storage has emerged as an appealing option for lowering the amount of energy that is consumed by buildings. Due to their high heat storage density, and non-corrosive and non-polluting properties, alcohols can be a good alternative to petroleum-derived paraffin phase change materials (PCMs). In this paper, ternary eutectic PCMs with suitable phase change temperatures were designed and prepared using lauryl alcohol (LA), cetyl alcohol (CA), stearyl alcohol (SA), and xylitol (X). The differential scanning calorimetry (DSC) results revealed that the phase change temperatures of LA-CA-SA, LA-CA-X, and LA-SA-X were 20.52°C, 20.37°C, and 22.18°C, respectively. The latent heat of phase change of the ternary eutectic PCMs was all stronger than that of the paraffinic PCMs at roughly the same temperature. The highest latent heat was 195 J/g. It had good thermal energy storage capacity. The preparation mechanism was investigated using Fourier-transform Infrared Spectroscopy (FTIR), and it was found that the ternary eutectic PCMs were only physically mixed among the components. Ternary eutectic PCMs had a simple preparation process, suitable phase change temperature, and high energy storage density. They are suitable for low-temperature architectural packaging applications.

Keywords: thermal energy storage, buildings, phase change materials, alcohols

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Authors: Mohamed Sifan, Brabha Nagaratnam, Julian Thamboo, Keerthan Poologanathan

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Ultra high performance concrete (UHPC) is a type of cementitious material known for its exceptional strength, ductility, and durability. However, its production is often associated with high costs due to the significant amount of cementitious materials required and the use of fine powders to achieve the desired strength. The aim of this research is to explore the feasibility of developing cost-effective UHPC mixes using locally available materials. Specifically, the study aims to investigate the use of coarse limestone sand along with other sand types, namely, basalt sand, dolomite sand, and river sand for developing UHPC mixes and evaluating its performances. The study utilises the particle packing model to develop various UHPC mixes. The particle packing model involves optimising the combination of coarse limestone sand, basalt sand, dolomite sand, and river sand to achieve the desired properties of UHPC. The developed UHPC mixes are then evaluated based on their workability (measured through slump flow and mini slump value), compressive strength (at 7, 28, and 90 days), splitting tensile strength, and microstructural characteristics analysed through scanning electron microscope (SEM) analysis. The results of this study demonstrate that cost-effective UHPC mixes can be developed using locally available materials without the need for silica fume or fly ash. The UHPC mixes achieved impressive compressive strengths of up to 149 MPa at 28 days with a cement content of approximately 750 kg/m³. The mixes also exhibited varying levels of workability, with slump flow values ranging from 550 to 850 mm. Additionally, the inclusion of coarse limestone sand in the mixes effectively reduced the demand for superplasticizer and served as a filler material. By exploring the use of coarse limestone sand and other sand types, this study provides valuable insights into optimising the particle packing model for UHPC production. The findings highlight the potential to reduce costs associated with UHPC production without compromising its strength and durability. The study collected data on the workability, compressive strength, splitting tensile strength, and microstructural characteristics of the developed UHPC mixes. Workability was measured using slump flow and mini slump tests, while compressive strength and splitting tensile strength were assessed at different curing periods. Microstructural characteristics were analysed through SEM and energy dispersive X-ray spectroscopy (EDS) analysis. The collected data were then analysed and interpreted to evaluate the performance and properties of the UHPC mixes. The research successfully demonstrates the feasibility of developing cost-effective UHPC mixes using locally available materials. The inclusion of coarse limestone sand, in combination with other sand types, shows promising results in achieving high compressive strengths and satisfactory workability. The findings suggest that the use of the particle packing model can optimise the combination of materials and reduce the reliance on expensive additives such as silica fume and fly ash. This research provides valuable insights for researchers and construction practitioners aiming to develop cost-effective UHPC mixes using readily available materials and an optimised particle packing approach.

Keywords: cost-effective, limestone powder, particle packing model, ultra high performance concrete

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Authors: Saleh Gareh, B. C. Kok, H. H. Goh

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Piezoelectric energy harvesting has advantages over other alternative sources due to its large power density, ease of applications, and capability to be fabricated at different scales: macro, micro, and nano. This paper presents an electromechanical-traffic model for roadway compression-based piezoelectric energy harvesting system. A two-degree-of-freedom (2-DOF) electromechanical model has been developed for the piezoelectric energy harvesting unit to define its performance in power generation under a number of external excitations on road surface. Lead Zirconate Titanate (PZT-5H) is selected as the piezoelectric material to be used in this paper due to its high Piezoelectric Charge Constant (d) and Piezoelectric Voltage Constant (g) values. The main source of vibration energy that has been considered in this paper is the moving vehicle on the road. The effect of various frequencies on possible generated power caused by different vibration characteristics of moving vehicle has been studied. A single unit of circle-shape Piezoelectric Cymbal Transducer (PCT) with diameter of 32 mm and thickness of 0.3 mm be able to generate about 0.8 mW and 3 mW of electric power under 4 Hz and 20 Hz of excitation, respectively. The estimated power to be generated for multiple arrays of PCT is approximately 150 kW/ km. Thus, the developed electromechanical-traffic model has enormous potential to be used in estimating the macro scale of roadway power generation system.

Keywords: piezoelectric energy harvesting, cymbal transducer, PZT (lead zirconate titanate), 2-DOF

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Authors: Abdalla Ahmad Obeidat

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Developing efficient hydrogen storage materials is critical to advancing clean energy technologies, particularly for applications in fuel cells and renewable energy systems. This study explores materials for hydrogen storage through Density Functional Theory (DFT) calculations, addressing one of the most significant challenges in sustainable energy: the safe and efficient storage and release of hydrogen. Our research provides an in-depth analysis of various candidate compounds' structural and electronic properties, aiming to identify materials with enhanced hydrogen storage capacities. By investigating adsorption mechanisms and optimizing key material properties, we aim to contribute to developing high-performance hydrogen storage solutions. The findings from this work have the potential to impact the field of hydrogen fuel technology significantly, offering insights and advancements that support the transition to sustainable energy systems.

Keywords: hydrogen storage, density functional theory, electronic, thermal stability

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Authors: S. Jayasinghe, R. B. N. Dissanayake

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Optimization modelling together with the Network models and Linear Programming techniques is a powerful tool in problem solving and decision making in real world applications. This study developed a mathematical model to optimize the net profit by minimizing the transportation cost. This model focuses the transportation among decentralized production plants to a centralized distribution centre and then the distribution among island wide agencies considering the customer satisfaction as a requirement. This company produces basically 9 types of food items with 82 different varieties and 4 types of non-food items with 34 different varieties. Among 6 production plants, 4 were located near the city of Mawanella and the other 2 were located in Galewala and Anuradhapura cities which are 80 km and 150 km away from Mawanella respectively. The warehouse located in the Mawanella was the main production plant and also the only distribution plant. This plant distributes manufactured products to 39 agencies island-wide. The average values and average amount of the goods for 6 consecutive months from May 2013 to October 2013 were collected and then average demand values were calculated. The following constraints are used as the necessary requirement to satisfy the optimum condition of the model; there was one source, 39 destinations and supply and demand for all the agencies are equal. Using transport cost for a kilometer, total transport cost was calculated. Then the model was formulated using distance and flow of the distribution. Network optimization and linear programming techniques were used to originate the model while excel solver is used in solving. Results showed that company requires total transport cost of Rs. 146, 943, 034.50 to fulfil the customers’ requirement for a month. This is very much less when compared with data without using the model. Model also proved that company can reduce their transportation cost by 6% when distributing to island-wide customers. Company generally satisfies their customers’ requirements by 85%. This satisfaction can be increased up to 97% by using this model. Therefore this model can be used by other similar companies in order to reduce the transportation cost.

Keywords: mathematical model, network optimization, linear programming

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Authors: Mehrzad Soltani, Pegah Rezaei

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In the endeavor to construct cities that are not only thriving but also environmentally responsible, effective urban planning and architectural design assume paramount significance. The focal point of this pursuit is the harnessing of urban renewable energy. By embracing sustainable practices such as the integration of solar panels into the urban landscape and the establishment of smart grids, cities are poised to confront head-on the dual challenge of surging energy demands and pressing environmental concerns. Urban renewable energy solutions offer a multifaceted approach to these issues. Firstly, they usher in a clean and sustainable source of energy, reducing the cities' ecological footprint while ensuring a continuous power supply. This transition to eco-friendly energy is also intrinsically linked to enhanced spatial utilization, thereby streamlining the efficiency of urban areas. Moreover, it spurs the adoption of sustainable transportation alternatives, diminishing the reliance on fossil fuels and mitigating air pollution. However, the significance of integrating renewable energy solutions transcends the realm of urban sustainability. It embodies a holistic approach towards creating cities that harmoniously coexist with the natural environment while catering to the needs and aspirations of their inhabitants. In essence, prioritizing sustainability in urban planning and architectural design has evolved from a choice to a necessity, one that not only safeguards the cities' well-being but also fosters a better quality of life for their residents. Thus, it is imperative that we acknowledge the transformative potential of these innovations as we pave the way towards the cities of the future.

Keywords: sustainability, smart grids, solar panel, urban planning, environmental concerns

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Authors: Bazilah Ismail, Muhammad Mat Naain, Ibrahim Alhamrouni, Lilik Jamilatul Awalin, Fadi Albatsh, Mohd Fairuz Abdul Hamid

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Rapid depletion and prices of the conventional energy sources have stimulated the development of the renewable energy source (RES). Due to the unpredicted and intermittent nature of RES, the hybrid renewable energy system (HRES) is the best solution to complement the nature of the respective sources, and the combination of the wind and solar energy is rapidly gaining popularity. The significant challenges on the operation and planning of the grid system with a high HRES penetration has become an important subject since the location of HRES plant give impact towards the existing system. This paper aims to propose the location of the grid connected Wind-PV hybrid plant (WPHP) based on load flow and voltage stability indices study. Several case studies are carried out using IEEE 14 bus system, and the system is modeled and tested in DigSILENT PowerFactory.

Keywords: hybrid renewable energy system, wind farm, photovoltaic system, voltage stability and load flow

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Authors: Dina K. Badawy, Dina M. Ibrahim, Alsayed A. Sallam

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Distributed database is a collection of logically related databases that cooperate in a transparent manner. Query processing uses a communication network for transmitting data between sites. It refers to one of the challenges in the database world. The development of sophisticated query optimization technology is the reason for the commercial success of database systems, which complexity and cost increase with increasing number of relations in the query. Mariposa, query trading and query trading with processing task-trading strategies developed for autonomous distributed database systems, but they cause high optimization cost because of involvement of all nodes in generating an optimal plan. In this paper, we proposed a modification on the autonomous strategy K-QTPT that make the seller’s nodes with the lowest cost have gradually high priorities to reduce the optimization time. We implement our proposed strategy and present the results and analysis based on those results.

Keywords: autonomous strategies, distributed database systems, high priority, query optimization

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Authors: C. Vrekos, C. Evagelides, N. Samarinas, G. Arampatzis

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As known, the water energy is a renewable and clean source of energy. Energy production from hydropower has been the first, and still is today a renewable source used to generate electricity. The optimal location and sizing of a small hydropower plant is a very important issue in engineering design which encourages investigation. The aim of this paper is to present a formula that can be utilized for locating the position of a small hydropower plant although there is a high dependence on economic, environmental, and social parameters. In this paper, the economic and technical side of the problem is considered. More specifically, there is a critical terrain slope that determines if the plant should be located at the end of the slope or not. Of course, this formula can be used for a first estimate and does not include detailed economic analysis. At the end, a case study is presented for the location of a small hydropower plant in order to demonstrate the validity of the proposed formula.

Keywords: critical terrain slope, economic analysis, hydropower plant locating, renewable energy

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Authors: Domenico M. Mongelli, Michele De Carli, Laura Carnieletto, Filippo Busato

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Europe's dependence on imported fossil fuels has been particularly highlighted by the Russian invasion of Ukraine. Limiting this dependency with a massive replacement of fossil fuel boilers with heat pumps for building heating is the goal of this work. Therefore, with the aim of diversifying energy sources and evaluating the potential use of heat pump technologies for residential buildings with a view to decarbonization, the quantitative reduction in the consumption of fossil fuels was investigated in all regions of Europe through the use of heat pumps. First, a general overview of energy consumption in buildings in Europe has been assessed. The consumption of buildings has been addressed to the different uses (heating, cooling, DHW, etc.) as well as the different sources (natural gas, oil, biomass, etc.). The analysis has been done in order to provide a baseline at the European level on the current consumptions and future consumptions, with a particular interest in the future increase of cooling. A database was therefore created on the distribution of residential energy consumption linked to air conditioning among the various energy carriers (electricity, waste heat, gas, solid fossil fuels, liquid fossil fuels, and renewable sources) for each region in Europe. Subsequently, the energy profiles of various European cities representative of the different climates are analyzed in order to evaluate, in each European climatic region, which energy coverage can be provided by heat pumps in replacement of natural gas and solid and liquid fossil fuels for air conditioning of the buildings, also carrying out the environmental and economic assessments for this energy transition operation. This work aims to make an innovative contribution to the evaluation of the potential for introducing heat pump technology for decarbonization in the air conditioning of buildings in all climates of the different European regions.

Keywords: heat pumps, heating, decarbonization, energy policies

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Authors: Ahmed Amrani, Oussama Allali, Amira Ben Hamida, Felix Defrance, Stephanie Morland, Eva Pineau, Thomas Lacroix

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The energy planning process is a very complex task that involves several stakeholders and requires the consideration of several local and global factors and constraints. In order to optimize and simplify this process, we propose a tool-based iterative approach applied to district heating planning. We build our tool with the collaboration of a French territory using actual district data and implementing the European incentives. We set up an iterative process including data visualization and analysis, identification and extraction of information related to the area concerned by the operation, design of sustainable planning scenarios leveraging local renewable and recoverable energy sources, and finally, the evaluation of scenarios. The last step is performed by a dynamic digital twin replica of the city. Territory’s energy experts confirm that the tool provides them with valuable support towards sustainable energy planning.

Keywords: climate change, data management, decision support, digital twin, district heating, energy planning, renewables, smart city

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Authors: A. Roukbi, B. Draoui

Abstract:

Due to the high cost and the environmental problems caused by the conventional air-conditioning systems, various researches are being increasingly focused on thermal comfort in the building sector integrating renewable energy sources, particularly solar energy. For that purpose, this study aims to present a modeling and performance analysis of a direct air-cooled Water/LiBr absorption chiller. The chiller is considered to be coupled to a small residential building at an arid zone situated in south Algeria. The system is modeled with TRNSYS simulation program. The main objective is to study the feasibility of the chosen system in arid zones and to apply a simplified method to predict the performance of the system by mean of the characteristic equation approach tacking in account the influence of the climatic conditions of the considered site, the collector area and storage volume of the hot water tank on the performance of the installation. First, the results of the system modeling are compared with an experimental data from the open literature and the developed model is then validated. In another hand, a parametric study is performed to analyze the performance of the direct air-cooled absorption chiller at the operating conditions of interest for the present study. Thus, the obtained results has shown that the studied system can present a good alternative for cooling systems in arid zones since the cooling load is roughly in phase with solar availability.

Keywords: absorption chiller, air-cooled, arid zone, thermal comfort

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Authors: Andres F. Ramirez, Carlos F. Valencia

Abstract:

The increasing interest in renewable energies strategies application and the path for diminishing the use of carbon related energy sources have encouraged the development of novel strategies for integration of solar energy into the electricity network. A correct inclusion of the fluctuating energy output of a photovoltaic (PV) energy system into an electric grid requires improvements in the forecasting and simulation methodologies for solar energy potential, and the understanding not only of the mean value of the series but the associated underlying stochastic process. We present a methodology for synthetic generation of solar irradiance (shortwave flux) and air temperature bivariate time series based on copula functions to represent the cross-dependence and temporal structure of the data. We explore the advantages of using this nonlinear time series method over traditional approaches that use a transformation of the data to normal distributions as an intermediate step. The use of copulas gives flexibility to represent the serial variability of the real data on the simulation and allows having more control on the desired properties of the data. We use discrete zero mass density distributions to assess the nature of solar irradiance, alongside vector generalized linear models for the bivariate time series time dependent distributions. We found that the copula autoregressive methodology used, including the zero mass characteristics of the solar irradiance time series, generates a significant improvement over state of the art strategies. These results will help to better understand the fluctuating nature of solar energy forecasting, the underlying stochastic process, and quantify the potential of a photovoltaic (PV) energy generating system integration into a country electricity network. Experimental analysis and real data application substantiate the usage and convenience of the proposed methodology to forecast solar irradiance time series and solar energy across northern hemisphere, southern hemisphere, and equatorial zones.

Keywords: copula autoregressive, solar irradiance forecasting, solar energy forecasting, time series generation

Procedia PDF Downloads 323

Authors: Johnson Adafin, James O. B. Rotimi, Suzanne Wilkinson, Abimbola O. Windapo

Abstract:

An aspect of client expenditure management that requires attention is the level of accuracy achievable in design-stage elemental cost planning. This has been a major concern for construction clients and practitioners in New Zealand (NZ). Pre-tender estimating inaccuracies are significantly influenced by the level of risk information available to estimators. Proper cost planning activities should ensure the production of a project’s likely construction costs (initial and final), and subsequent cost control activities should prevent unpleasant consequences of cost overruns, disputes and project abandonment. If risks were properly identified and priced at the design stage, observed variance between design-stage elemental cost plans (ECPs) and final tender sums (FTS) (initial contract sums) could be reduced. This study investigates the variations between design-stage ECPs and FTS of construction projects, with a view to identifying risk factors that are responsible for the observed variance. Data were sourced through interviews, and risk factors were identified by using thematic analysis. Access was obtained to project files from the records of study participants (consultant quantity surveyors), and document analysis was employed in complementing the responses from the interviews. Study findings revealed the discrepancies between ECPs and FTS in the region of -14% and +16%. It is opined in this study that the identified risk factors were responsible for the variability observed. The values obtained from the analysis would enable greater accuracy in the forecast of FTS by Quantity Surveyors. Further, whilst inherent risks in construction project developments are observed globally, these findings have important ramifications for construction projects by expanding existing knowledge on what is needed for reasonable budgetary performance and successful delivery of construction projects. The findings contribute significantly to the study by providing quantitative confirmation to justify the theoretical conclusions generated in the literature from around the world. This therefore adds to and consolidates existing knowledge.

Keywords: accuracy, design-stage, elemental cost plan, final tender sum

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Authors: Marko Batic, Nikola Tomasevic, Sanja Vranes

Abstract:

One of the strongholds in the ubiquitous efforts related to the energy conservation and energy efficiency improvement is represented by the retrofit of high energy consumers in buildings. In general, HVAC systems represent the highest energy consumers in buildings. However they usually suffer from mal-operation and/or malfunction, causing even higher energy consumption than necessary. Various Fault Detection and Diagnosis (FDD) systems can be successfully employed for this purpose, especially when it comes to the application at a single device/unit level. In the case of more complex systems, where multiple devices are operating in the context of the same building, significant energy efficiency improvements can only be achieved through application of comprehensive FDD systems relying on additional higher level knowledge, such as their geographical location, served area, their intra- and inter- system dependencies etc. This paper presents a comprehensive FDD system that relies on the utilization of common knowledge repository that stores all critical information. The discussed system is deployed as a test-bed platform at the two at Fiumicino and Malpensa airports in Italy. This paper aims at presenting advantages of implementation of the knowledge base through the utilization of ontology and offers improved functionalities of such system through examples of typical queries and reasoning that enable derivation of high level energy conservation measures (ECM). Therefore, key SPARQL queries and SWRL rules, based on the two instantiated airport ontologies, are elaborated. The detection of high level irregularities in the operation of airport heating/cooling plants is discussed and estimation of energy savings is reported.

Keywords: airport ontology, knowledge management, ontology modeling, reasoning

Procedia PDF Downloads 537

Authors: Shwadhin Sharma, Monica Perez, Vinita Patel, Tyler Kuwatani, Siobhan Scott

Abstract:

The purpose of this research is to explain and analyze why the Internet of Things (IoT) is an emerging technology trend. The aspects of this research paper include an overview of IoT, what research has already been done, the benefits, implications, and our own perspectives on the trend in order to thoroughly analyze how the trend of IoT will make an impact on society. Through the identification of what makes IoT important, it is concluded that IoT will have a tremendous impact for the whole world. Technology is never going to go away, it is going to get smarter and have the potential to change the world.

Keywords: internet of things, enablers of IoT, cost of IoT, benefits of IoT

Procedia PDF Downloads 357

Authors: M. Capocelli, A. Caputo, M. De Falco, D. Mazzei, V. Piemonte

Abstract:

This paper presents the experimental results and the related modeling of a thermal energy storage (TES) facility, ideated and realized by ENEA and realizing the thermocline with an innovative geometry. Firstly, the thermal energy exchange model of an equivalent shell & tube heat exchanger is described and tested to reproduce the performance of the spiral exchanger installed in the TES. Through the regression of the experimental data, a first-order thermocline model was also validated to provide an analytical function of the thermocline, useful for the performance evaluation and the comparison with other systems and implementation in simulations of integrated systems (e.g. power plants). The experimental data obtained from the plant start-up and the short-cut modeling of the system can be useful for the process analysis, for the scale-up of the thermal storage system and to investigate the feasibility of its implementation in actual case-studies.

Keywords: CSP plants, thermal energy storage, thermocline, mathematical modelling, experimental data

Procedia PDF Downloads 329

Authors: S. Kumchoo

Abstract:

The result of suggestion for low energy diet (1,000-1,200 kcal) in obese women to the effect on body weight, waist circumference and body mass index (BMI) in this experiment. Quisi experimental research was used for this study and it is a One-group pretest-posttest designs measurement method. The aim of this study was body weight, waist circumference and body mass index (BMI) reduction by using low energy diet (1,000-1,200 kcal) in obese women, the result found that in 15 of obese women that contained their body mass index (BMI) ≥ 30, after they obtained low energy diet (1,000-1,200 kcal) within 2 weeks. The data were collected before and after of testing the results showed that the average of body weight decrease 3.4 kilogram, waist circumference value decrease 6.1 centimeter and the body mass index (BMI) decrease 1.3 kg.m² from their previous body weight, waist circumference and body mass index (BMI) before experiment started. After this study, the volunteers got healthy and they can choose or select some food for themselves. For this study, the research can be improved for data development for forward study in the future.

Keywords: body weight, waist circumference, low energy diet, BMI

Procedia PDF Downloads 388