Search results for: electricity demand forecasting

Authors: Gaafar Muhammed, N. T. Ersoy

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The role of electricity in the economic development of any country is undeniable. The main goal of utilizing renewable sources in electricity generation, especially in the emerging countries, is to improve electricity access, economic development and energy sustainability. Germany’s recent transition from conventional to renewable energy technologies is overwhelming, this might not be associated with its abundant natural resources but owing to the policies in place. In line with the fast economic and technological developments recorded in recent years, Germany currently produces approximately 1059 GW of its energy from renewable sources. Hence, at the end of 2016, Germany is among the world leaders in terms of installed renewable energy capacity. As one of the most important factors that lead to renewable energy utilization in any nation is an effective policy, this study aims at examining the effect of policies on renewable energy (RE) development in Germany. Also, the study will focus on the evolution of the adopted feed-in tariff policies, as this evolution has affected the renewable energy capacity in Germany over a period of 15 years (2000 to 2015). The main contribution of the study is to establish a link between the feed-in tariff and the increase of RE in Germany’s energy mix. This is done by analyzing the characteristics of various feed-in tariff mechanisms adopted through the years. These characteristics include the feed-in-tariff rate, degression, special conditions, supported technology, etc. Then, the renewable energy development in Germany has been analyzed through the years along with the targets and the progress in reaching these targets. The study reveals that Germany’s renewable energy support policies (especially feed-in tariff) lead to several benefits and contribute towards the targets existing for renewable energy.

Keywords: feed-in tariff, Germany, policy, penewable energy

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Authors: Yanuar Tri Wahyu Saputra, Ramadhani Pamapta Putra

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Karimunjawa is one among Indonesian islands which is lacking of electricity supply. Despite condition above, Karimunjawa is an important tourism object in Indonesia's Central Java Province. Solar Power Plant is a potential technology to be applied in Karimunjawa, in order to fulfill the island's electrical supply need and to increase daily life and tourism quality among tourists and local population. This optimation modeling of Karimunjawa uses HOMER software program. The data we uses include wind speed data in Karimunjawa from BMKG (Indonesian Agency for Meteorology, Climatology and Geophysics), annual weather data in Karimunjawa from NASA, electricity requirements assumption data based on number of houses and business infrastructures in Karimunjawa. This modeling aims to choose which three system categories offer the highest financial profit with the lowest total Net Present Cost (NPC). The first category uses only PV with 8000 kW of electrical power and NPC value of $6.830.701. The second category uses hybrid system which involves both 1000 kW PV and 100 kW generator which results in total NPC of $6.865.590. The last category uses only generator with 750 kW of electrical power that results in total NPC of $ 16.368.197, the highest total NPC among the three categories. Based on the analysis above, we can conclude that the most optimal way to fulfill the electricity needs in Karimunjawa is to use 8000 kW PV with lower maintenance cost.

Keywords: Karimunjawa, renewable energy, solar power plant, HOMER

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Authors: Ali Heydarimoghim

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In this paper, the optimal placement of charging and discharging stations is done to determine the location and capacity of the stations, reducing the cost of electric vehicle owners' losses, reducing the cost of distribution system losses, and reducing the costs associated with the stations. Also, observing the permissible limits of the bus voltage and the capacity of the stations and their distance are considered as constraints of the problem. Given the traffic situation in different areas of a city, we estimate the amount of energy required to charge and the amount of energy provided to discharge electric vehicles in each area. We then introduce the electricity distribution system of the city in question. Following are the scenarios for introducing the problem and introducing the objective and constraint functions. Finally, the simulation results for different scenarios are compared.

Keywords: charging & discharging stations, hybrid vehicles, optimization, replacement

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Authors: Sahabeh Safarpour, Khiruddin Abdullah, Hwee San Lim, Mohsen Dadras

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Air pollution is a growing problem arising from domestic heating, high density of vehicle traffic, electricity production, and expanding commercial and industrial activities, all increasing in parallel with urban population. Monitoring and forecasting of air quality parameters are important due to health impact. One widely available metric of aerosol abundance is the aerosol optical depth (AOD). The AOD is the integrated light extinction coefficient over a vertical atmospheric column of unit cross section, which represents the extent to which the aerosols in that vertical profile prevent the transmission of light by absorption or scattering. Seasonal aerosol optical depth (AOD) values at 550 nm derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor onboard NASA’s Terra satellites, for the 10 years period of 2000-2010 were used to test 7 different spatial interpolation methods in the present study. The accuracy of estimations was assessed through visual analysis as well as independent validation based on basic statistics, such as root mean square error (RMSE) and correlation coefficient. Based on the RMSE and R values of predictions made using measured values from 2000 to 2010, Radial Basis Functions (RBFs) yielded the best results for spring, summer, and winter and ordinary kriging yielded the best results for fall.

Keywords: aerosol optical depth, MODIS, spatial interpolation techniques, Radial Basis Functions

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Authors: Ehsanolah Assareh, Mojtaba Biglari, Mojtaba Nedaei

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Sanar village in north of Iran is a remote region with difficult access to electricity, grid and water supply. Thus the aim of this research is to evaluate the potential of wind as a power source either for electricity generation or for water pumping. In this study the statistical analysis has been performed by Weibull distribution function. The results show that the Weibull distribution has fitted the wind data very well. Also it has been demonstrated that wind speed at 40 m height is ranged from 1.75 m/s in Dec to 3.28 m/s in Aug with average value of 2.69 m/s. In this research, different wind speed characteristics such as turbulence intensity, wind direction, monthly air temperature, humidity wind power density and other related parameters have been investigated. Finally it was concluded that the wind energy in the Sanar village may be explored by employing modern wind turbines that require very lower start-up speeds.

Keywords: wind energy, wind turbine, weibull, Sanar village, Iran

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Authors: Joselito Medina-Marin, Maria G. Serna-Diaz, Juan C. Seck-Tuoh-Mora, Norberto Hernandez-Romero, Irving Barragán-Vite

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Wind speed forecasting is an important issue for planning wind power generation facilities. The accuracy in the wind speed prediction allows a good performance of wind turbines for electricity generation. A model based on artificial neural networks is presented in this work. A dataset with atmospheric information about air temperature, atmospheric pressure, wind direction, and wind speed in Pachuca, Hidalgo, México, was used to train the artificial neural network. The data was downloaded from the web page of the National Meteorological Service of the Mexican government. The records were gathered for three months, with time intervals of ten minutes. This dataset was used to develop an iterative algorithm to create 1,110 ANNs, with different configurations, starting from one to three hidden layers and every hidden layer with a number of neurons from 1 to 10. Each ANN was trained with the Levenberg-Marquardt backpropagation algorithm, which is used to learn the relationship between input and output values. The model with the best performance contains three hidden layers and 9, 6, and 5 neurons, respectively; and the coefficient of determination obtained was r²=0.9414, and the Root Mean Squared Error is 1.0559. In summary, the ANN approach is suitable to predict the wind speed in Pachuca City because the r² value denotes a good fitting of gathered records, and the obtained ANN model can be used in the planning of wind power generation grids.

Keywords: wind power generation, artificial neural networks, wind speed, coefficient of determination

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Authors: Kurias George, Ildefonso Cuesta Romeo, Clara Salueña Pérez, Jordi Sole Olle

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With the growing prevalence of wind energy there is a need, for modeling techniques to evaluate the impact of wind farms on meteorology and oceanography. This study presents an approach that utilizes the WRF (Weather Research and Forecasting )with that include a Wind Farm Parametrization model to simulate the dynamics around Parc Tramuntana project, a offshore wind farm to be located near the Gulf of Roses off the coast of Barcelona, Catalonia. The model incorporates parameterizations for wind turbines enabling a representation of the wind field and how it interacts with the infrastructure of the wind farm. Current results demonstrate that the model effectively captures variations in temeperature, pressure and in both wind speed and direction over time along with their resulting effects on power output from the wind farm. These findings are crucial for optimizing turbine placement and operation thus improving efficiency and sustainability of the wind farm. In addition to focusing on atmospheric interactions, this study delves into the wake effects within the turbines in the farm. A range of meteorological parameters were also considered to offer a comprehensive understanding of the farm's microclimate. The model was tested under different horizontal resolutions and farm layouts to scrutinize the wind farm's effects more closely. These experimental configurations allow for a nuanced understanding of how turbine wakes interact with each other and with the broader atmospheric and oceanic conditions. This modified approach serves as a potent tool for stakeholders in renewable energy, environmental protection, and marine spatial planning. environmental protection and marine spatial planning. It provides a range of information regarding the environmental and socio economic impacts of offshore wind energy projects.

Keywords: weather research and forecasting, wind turbine wake effects, environmental impact, wind farm parametrization, sustainability analysis

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Authors: Jeremy Faludi, Zhongyin Hu, Shahd Alrashed, Christopher Braunholz, Suneesh Kaul, Leulekal Kassaye

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Environmental impacts of six 3D printers using various materials were compared to determine if material choice drove sustainability, or if other factors such as machine type, machine size, or machine utilization dominate. Cradle-to-grave life-cycle assessments were performed, comparing a commercial-scale FDM machine printing in ABS plastic, a desktop FDM machine printing in ABS, a desktop FDM machine printing in PET and PLA plastics, a polyjet machine printing in its proprietary polymer, an SLA machine printing in its polymer, and an inkjet machine hacked to print in salt and dextrose. All scenarios were scored using ReCiPe Endpoint H methodology to combine multiple impact categories, comparing environmental impacts per part made for several scenarios per machine. Results showed that most printers’ ecological impacts were dominated by electricity use, not materials, and the changes in electricity use due to different plastics was not significant compared to variation from one machine to another. Variation in machine idle time determined impacts per part most strongly. However, material impacts were quite important for the inkjet printer hacked to print in salt: In its optimal scenario, it had up to 1/38th the impacts coreper part as the worst-performing machine in the same scenario. If salt parts were infused with epoxy to make them more physically robust, then much of this advantage disappeared, and material impacts actually dominated or equaled electricity use. Future studies should also measure DMLS and SLS processes / materials.

Keywords: 3D printing, additive manufacturing, sustainability, life-cycle assessment, design for environment

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Authors: Claudio L. M. Souza, Milton Erthal, Aldo Shimoya, Elias R. Goncalves, Igor C. Rangel, Allysson R. T. Tavares, Elias G. Figueira

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The process of choosing a region for the implementation of wind farms involves factors such as the wind regime, economic viability, land value, topography, and accessibility. This work presents results obtained by multi-criteria decision analysis, and it establishes a hierarchy, regarding the installation of wind farms, among geopolicy regions in the state of ‘Rio de Janeiro’, Brazil: ‘Regiao Norte-RN’, ‘Regiao dos Lagos-RL’ and ‘Regiao Serrana-RS’. The wind regime map indicates only these three possible regions with an average annual wind speed of above of 6.0 m/s. The method applied was the Analytical Hierarchy Process-AHP, designed to prioritize and rank the three regions based on four criteria as follows: 1) potential of the site and average wind speeds of above 6.0 ms-¹, 2) average land value, 3) distribution and interconnection to electric network with the highest number of electricity stations, and 4) accessibility with proximity and quality of highways and flat topography. The values of energy generation were calculated for wind turbines 50, 75, and 100 meters high, considering the production of site (GWh/Km²) and annual production (GWh). The weight of each criterion was attributed by six engineers and by analysis of Road Map, the Map of the Electric System, the Map of Wind Regime and the Annual Land Value Report. The results indicated that in 'RS', the demand was estimated at 2,000 GWh, so a wind farm can operate efficiently in 50 m turbines. This region is mainly mountainous with difficult access and lower land value. With respect to ‘RL’, the wind turbines have to be installed at a height of 75 m high to reach a demand of 6,300 GWh. This region is very flat, with easy access, and low land value. Finally, the ‘NR’ was evaluated as very flat and with expensive lands. In this case, wind turbines with 100 m can reach an annual production of 19,000 GWh. In this Region, the coast area was classified as of greater logistic, productivity and economic potential.

Keywords: AHP, renewable energy, wind energy

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Authors: Marita Pigłowska, Beata Kurc, Paweł Daszkiewicz

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Railway vehicles are divided into two groups: traction (powered) vehicles and wagons. The traction vehicles include locomotives (line and shunting), railcars (sometimes referred to as railbuses), and multiple units (electric and diesel), consisting of several or a dozen carriages. In vehicles with diesel traction, fuel energy (petrol, diesel, or compressed gas) is converted into mechanical energy directly in the internal combustion engine or via electricity. In the latter case, the combustion engine generator produces electricity that is then used to drive the vehicle (diesel-electric drive or electric transmission). In Poland, such a solution dominates both in heavy linear and shunting locomotives. The classic diesel drive is available for the lightest shunting locomotives, railcars, and passenger diesel multiple units. Vehicles with electric traction do not have their own source of energy -they use pantographs to obtain electricity from the traction network. To determine the competitiveness of the hydrogen propulsion system, it is essential to understand how it works. The basic elements of the construction of a railway vehicle drive system that uses hydrogen as a source of traction force are fuel cells, batteries, fuel tanks, traction motors as well as main and auxiliary converters. The compressed hydrogen is stored in tanks usually located on the roof of the vehicle. This resource is supplemented with the use of specialized infrastructure while the vehicle is stationary. Hydrogen is supplied to the fuel cell, where it oxidizes. The effect of this chemical reaction is electricity and water (in two forms -liquid and water vapor). Electricity is stored in batteries (so far, lithium-ion batteries are used). Electricity stored in this way is used to drive traction motors and supply onboard equipment. The current generated by the fuel cell passes through the main converter, whose task is to adjust it to the values required by the consumers, i.e., batteries and the traction motor. The work will attempt to construct a fuel cell with unique electrodes. This research is a trend that connects industry with science. The first goal will be to obtain hydrogen on a large scale in tube furnaces, to thoroughly analyze the obtained structures (IR), and to apply the method in fuel cells. The second goal is to create low-energy energy storage and distribution station for hydrogen and electric vehicles. The scope of the research includes obtaining a carbon variety and obtaining oxide systems on a large scale using a tubular furnace and then supplying vehicles. Acknowledgments: This work is supported by the Polish Ministry of Science and Education, project "The best of the best! 4.0", number 0911/MNSW/4968 – M.P. and grant 0911/SBAD/2102—B.K.

Keywords: railway, hydrogen, fuel cells, hybrid vehicles

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Authors: Piotr Kacejko, Lukasz Grabowski, Zdzislaw Kaminski

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This paper discusses a model of fuel consumption and on-board electricity generation. Rapid changes in speed result in a constantly changing kinetic energy accumulated in a bus mass and an increased fuel consumption due to hardly recuperated kinetic energy. The model is based on the results achieved from chassis dynamometer, airport and city street researches. The verified model was applied to simulate the on-board electricity generation during the Japanese JE05 Emission Test Cycle. The simulations were performed for several values of vehicle mass and electrical load applied to on-board devices. The research results show that driving dynamics has an impact on a consumption of fuel to drive alternators.

Keywords: city bus, heavy duty vehicle, Japanese JE05 test cycle, power generation

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Authors: Masood Sattari

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Using fuel cell technology to generate electricity for large commercial and industrial sites is a growing segment in the fuel cell industry. The installation of these systems involves design, permitting, procurement of long-lead electrical equipment, and construction involving multiple utilities. The installation of each fuel cell system requires the same amount of coordination as the construction of a new structure requiring a foundation, gas, water, and electricity. Each of these components provide variables that can delay and possibly eliminate a new project. As the manufacturing process and efficiency of fuel cell systems improves, so must the installation methods to prevent a ‘bottle-neck’ in the installation phase of the deployment. Installation methodologies to install the systems vary among companies and this paper will examine the methodologies, describe the benefits and drawbacks for each, and provide guideline for the industry to improve overall installation efficiency.

Keywords: construction, installation, methodology, procurement

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Authors: Olusola Olorunfemi Bamisile, Mustafa Dagbasi, Serkan Abbasoglu

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Feasibility of an Energy Audit program is the main aim of this paper. LEDs are used to replace Sodium Vapor lamps and High Pressured Mercury Vapor lamps that are currently used for the street lighting system in Turkish Republic of Northern Cyprus. 44% of the fossil fuels imported into Turkish Republic of Northern Cyprus are used for electricity generation which makes the reduction in the consumption of electricity very important. This project will save as much as 40,206,210 kWh on site annually and 121,837,000 kWh can be saved from source. The economic environmental and fossil fuels saving of this project is also evaluated.

Keywords: energy conservation management, LEDs, sodium vapor, high pressure mercury vapor, life cycle costing

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Authors: Nangialai Yousufzai, Eysosiyas Etana, Ikuo Sugiyama

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Kabul population has been growing continually since 2001 and reaching six million in 2025 due to the rapid inflow from the neighboring countries. As a result of the population growth, lack of living facilities supported by infrastructure services is becoming serious in social and economic aspects. However, about 70% of the city is still occupied illegally and the government has little information on the infrastructure demands. To improve this situation, land readjustment is one of the powerful development tools, because land readjustment does not need a high governmental budget of itself. Instead, the method needs cooperation between stakeholders such as landowners, developers and a local government. So it is becoming crucial for both government and citizens to implement land readjustment for providing tidy urban areas with enough public services to realize more livable city as a whole. On the contrary, the traditional land readjustment tends to spend a long time until now to get consensus on the new plan between stakeholders. One of the reasons is that individual land area (land parcel) is decreased due to the contribution to public such as roads/parks/squares for improving the urban environment. The second reason is that the new plan is difficult for dwellers to imagine new life after the readjustment. Because the paper-based plan is made by an authority not for dwellers but for specialists to precede the project. This paper aims to shorten the time to realize quick consensus between stakeholders. The first improvement is utilizing questionnaire(s) to assess the demand and preference of the landowners. The second one is utilizing 3D model for dwellers to visualize the new environment easily after the readjustment. In additions, the 3D model is reflecting the demand and preference of the resident so that they could select a land parcel according to their sense value of life. The above-mentioned two improvements are carried out after evaluating total land prices of the new plans to select for maximizing the project value. The land price forecasting formula is derived from the current market ones in Kabul. Finally, it is stressed that the rapid consensus-building of land readjustment utilizing ICT and open data analysis is essential to redevelop slums and illegal occupied areas in Kabul.

Keywords: land readjustment, consensus building, land price formula, 3D simulation

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Authors: Seyedomid Fatemi

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The walls of the building, as the main intermediary between the outside and the inside of the building, play an important role in controlling the environmental conditions and ensuring the comfort of the residents, thus reducing the heating and cooling loads. Therefore, the use of suitable materials is considered one of the simplest and most effective ways to reduce the heating and cooling loads of the building, which will also save energy. Therefore, in order to achieve the goal of the research "Ranking of optimal materials for building walls," optimal materials for building walls in a temperate and humid climate (case example: Sari city) from the perspective of embodied energy, waste of electricity and gas energy, cost and reuse been investigated to achieve sustainable architecture. In this regard, using information obtained from Sari Municipality, design components have been presented by experts using the Delphi method. Considering the criteria of experts' opinions (cost and reuse), the amount of embodied energy of the materials, as well as the amount of waste of electricity and gas of different materials of the walls, with the help of the AHP weighting technique and finally with the TOPSIS technique, the best type of materials in the order of 1- 3-D Panel 2-ICF-, 3-Cement block with pumice, 4-Wallcrete block, 5-Clay block, 6-Autoclaved Aerated Concrete (AAC), 7-Foam cement block, 8-Aquapanel and 9-Reinforced concrete wall for use in The walls of the buildings were proposed in Sari city.

Keywords: optimum materials, building walls, moderate and humid climate, sustainable architecture, AHP-TOPSIS technique

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Authors: Rewadee Anuwattana, Pattamaphorn Phuangngamphan, Narumon Soparatana, Supinya Sutthima, Worapong Pattayawan, Saroj Klangkongsub, Songkiat Roddang, Pluek Wongpanich

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The leachate wastewater is high contaminant water; hence it needs to be treated. The objective of this research was to determine the Chemical Oxygen Demand (COD) concentration, Phosphate (PO₄³⁻), Ammonia (NH₃) and color in leachate wastewater in the landfill area. The experiments were carried out in the optimum condition by pH, the Fenton reagent dosage (concentration of dosing Fe²⁺ and H₂O₂). The optimum pH is 3, the optimum [Fe²⁺]/[COD] and [H₂O₂]/[COD₀] = 0.03 and 0.03, respectively. The Biochemical Oxygen Demand (BOD₅)/Chemical Oxygen Demand (COD) ratio can be adjusted to 1 for landfill leachate wastewater (BOD₅/COD = 0.11). From the results, the Fenton process shall be investigated further to achieve the removal of phosphates in addition to COD and color.

Keywords: landfill leachate treatment, open dumpsite, Fenton process, wastewater treatment

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Authors: Roghieh A. Biroon, Zoleikha Abdollahi

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The recent growth of renewables, e.g., solar panels, batteries, and electric vehicles (EVs) in residential and small commercial sectors, has potential impacts on the stability and operation of power grids. Considering approximately 50 percent share of the residential and the commercial sectors in the electricity demand market, the significance of these impacts, and the necessity of addressing them are more highlighted. Utilities and power system operators should manage the renewable electricity sources integration with power systems in such a way to extract the most possible advantages for the power systems. The most common effect of high penetration level of the renewables is the reverse power flow in the distribution feeders when the customers generate more power than their needs. The reverse power flow causes voltage rise and thermal issues in the power grids. To overcome the voltage rise issues in the distribution system, several techniques have been proposed including reducing transformers short circuit resistance and feeder impedance, installing autotransformers/voltage regulators along the line, absorbing the reactive power by distributed generators (DGs), and limiting the PV and battery sizes. In this study, we consider a medium-scale battery energy storage to manage the power energy and address the aforementioned issues on voltage deviation and power loss increase. We propose an optimization algorithm to find the optimum size and location for the battery. The optimization for the battery location and size is so that the battery maintains the feeder voltage deviation and power loss at a certain desired level. Moreover, the proposed optimization algorithm controls the charging/discharging profile of the battery to absorb the negative power flow from residential and commercial customers in the feeder during the peak time and sell the power back to the system during the off-peak time. The proposed battery regulates the voltage problem in the distribution system while it also can play frequency regulation role in islanded microgrids. This battery can be regulated and controlled by the utilities or a third-party ancillary service provider for the utilities to reduce the power system loss and regulate the distribution feeder voltage and frequency in standard level.

Keywords: ancillary services, battery, distribution system and optimization

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Authors: Javier Sandoval Bustamante, Pardis Sheikhzadeh, Vijayanarasimha Hindupur Pakka

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In the pursuit of achieving net-zero carbon emissions, the integration of low carbon technologies into electricity distribution networks is paramount. This paper delves into the critical assessment of how the integration of low carbon technologies, such as heat pumps, electric vehicle chargers, and photovoltaic systems, impacts the infrastructure and operation of electricity distribution networks. The study employs rigorous methodologies, including power flow analysis and headroom analysis, to evaluate the feasibility and implications of integrating these technologies into existing distribution systems. Furthermore, the research utilizes Local Area Energy Planning (LAEP) methodologies to guide local authorities and distribution network operators in formulating effective plans to meet regional and national decarbonization objectives. Geospatial analysis techniques, coupled with building physics and electric energy systems modeling, are employed to develop geographic datasets aimed at informing the deployment of low carbon technologies at the local level. Drawing upon insights from the Local Energy Net Zero Accelerator (LENZA) project, a comprehensive case study illustrates the practical application of these methodologies in assessing the rollout potential of LCTs. The findings not only shed light on the technical feasibility of integrating low carbon technologies but also provide valuable insights into the broader transition towards a sustainable and electrified energy future. This paper contributes to the advancement of knowledge in power electrical engineering by providing empirical evidence and methodologies to support the integration of low carbon technologies into electricity distribution networks. The insights gained are instrumental for policymakers, utility companies, and stakeholders involved in navigating the complex challenges of energy transition and achieving long-term sustainability goals.

Keywords: energy planning, energy systems, digital twins, power flow analysis, headroom analysis

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Authors: Muhammad Usman Sardar, Muhammad Haroon Nadeem, Shahbaz Ahmad, Ashiq Hussain

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The marketing of solar photovoltaic energy systems has one of the monetary settlements to address the higher rate to pay in advance with the purchase of two decades worth of electricity services. To deploy solar photovoltaic technologies and energy setups in areas, it’s important to create a system of credit that can ensure the availability of subsidized capital and commercial conditions for the society. Meanings of energy in developing countries like Pakistan were strongly prompted by marketable interests and industrialization trend influences within their culture. It’s going to be essential to prepare the concerned proceeding models of energy development strategies. This paper discuss the impact and share of environmental friendly solar photo-voltaic energy, researching to find the most appropriate alternate solutions for balance the energy demand and supply and current progressive position in different countries regarding to development and deployment. Based on the literature reviews, its presence found that most beneficial and concerning policies have implemented in several countries around the globe.

Keywords: photovoltaic marketing and pricing, renewable energy technology, solar photovoltaic, SPV

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Authors: Sirilak Areerachakul

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Water quality has initiated serious management efforts in many countries. Artificial Neural Network (ANN) models are developed as forecasting tools in predicting water quality trend based on historical data. This study endeavors to automatically classify water quality. The water quality classes are evaluated using 6 factor indices. These factors are pH value (pH), Dissolved Oxygen (DO), Biochemical Oxygen Demand (BOD), Nitrate Nitrogen (NO3N), Ammonia Nitrogen (NH3N) and Total Coliform (T-Coliform). The methodology involves applying data mining techniques using multilayer perceptron (MLP) neural network models. The data consisted of 11 sites of Saen Saep canal in Bangkok, Thailand. The data is obtained from the Department of Drainage and Sewerage Bangkok Metropolitan Administration during 2007-2011. The results of multilayer perceptron neural network exhibit a high accuracy multilayer perception rate at 94.23% in classifying the water quality of Saen Saep canal in Bangkok. Subsequently, this encouraging result could be combined with GIS data improves the classification accuracy significantly.

Keywords: artificial neural network, geographic information system, water quality, computer science

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Authors: Dušan Bojović, Wei Huang, Zdravko Stojanović, Jovan Ilić

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In an era of ever-growing electricity generation from renewable energy sources, namely wind and solar, a need for reliable energy storage and intensive balancing of the electric power system gains significance. For decades, pump storage hydroelectric power plants have proven to be an important asset regarding the storage of generated electricity. However, with the increasing overall share of wind and solar in electric systems at large, the importance of electric grid stability keeps growing. A large pump storage project, the Bistrica Pump Storage Plant (PSP), is currently under development in Serbia. The Bistrica PSP will be designed as a 600+ MW power plant, which is envisaged as a significant contributor to the Serbian power grid stability as more and more renewable energy sources are implemented over time. PSP Bistrica is seen as a strategically important project on the green agenda path of the Electric Power Industry of Serbia as a necessary pre-condition for the safe implementation of other renewable energy sources. The importance of such a plant would also play an important role in reducing the electricity production from coal, i.e., thermoelectric power plants. During the project’s development, various techniques and technologies are evaluated for the purpose of determining the optimum (the most profitable) solution. Over the course of this paper, these technologies – such as frequency-regulated pump turbines and ternary sets will be presented, with a detailed explanation of their possible application within the Bistrica PSP project and their relative advantages/disadvantages in this particular case.

Keywords: hydraulic turbines, pumped storage, renewable energy, competing technologies

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Authors: Leila Jafari, Viliam Makis

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In this paper, the joint optimization of the economic manufacturing quantity (EMQ), safety stock level, and condition-based maintenance (CBM) is presented for a partially observable, deteriorating system subject to random failure. The demand is stochastic and it is described by a Poisson process. The stochastic model is developed and the optimization problem is formulated in the semi-Markov decision process framework. A modification of the policy iteration algorithm is developed to find the optimal policy. A numerical example is presented to compare the optimal policy with the policy considering zero safety stock.

Keywords: condition-based maintenance, economic manufacturing quantity, safety stock, stochastic demand

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Authors: Dylber Qema

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Driven by recent developments in technology and the growing concern about the sustainability and environmental impact of conventional fuel use, the possibility of producing clean and sustainable energy in significant quantities from renewable energy sources has sparked interest all over the world. Solar energy is one of the sources for the generation of electricity, with no emissions or environmental pollution. The electricity produced by photovoltaics can supply a home or business and can even be sold or exchanged with the grid operator. A very positive effect of using photovoltaic modules is that they do not produce greenhouse gases and do not produce chemical waste, unlike all other forms of energy production. Photovoltaics are becoming one of the largest investments in the field of renewable generating units. Improving the reliability of the electric power system is one of the most important impacts of the installation of photovoltaics (PV). Renewable energy sources are so large that they can meet the energy demands of the whole world, thus enabling sustainable supply as well as reducing local and global atmospheric emissions. Albania is rated by experts as one of the most favorable countries in Europe for the production of electricity from solar panels. But the country currently produces about 1% of its energy from the sun, while the rest of the needs are met by hydropower plants and imports. Albania has very good characteristics in terms of solar radiation (about 1300–1400 kW/m2). Solar energy has great potential and is a permanent source of energy with greater economic efficiency. Photovoltaic energy is also seen as an alternative, as long periods of drought in Albania have produced crises and high costs for securing energy in the foreign market.

Keywords: capacity, ministry of tourism and environment, obstacles, photovoltaic energy, sustainable

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Authors: Heather Wyman-Pain, Yuankai Bian, Furong Li

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The decreasing use of fossil fuel power stations has a negative effect on the stability of the electricity systems in many countries. Nuclear power stations have traditionally provided minimal ancillary services to support the system but this must change in the future as they replace fossil fuel generators. This paper explains the development of the four most popular reactor types still in regular operation across the world which have formed the basis for most reactor development since their commercialisation in the 1950s. The use of nuclear power in four countries with varying levels of capacity provided by nuclear generators is investigated, using the primary frequency response provided by generators as a measure for the electricity networks stability, to assess the need for nuclear generators to provide additional support as their share of the generation capacity increases.

Keywords: frequency control, nuclear power generation, power system stability, system inertia

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Authors: Elizabeth Spink

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The United Nations' Sustainable Development Goal 6 sets a target for safe and affordable drinking water for all. Developing country governments aiming to achieve this goal often face significant challenges when trying to service last mile customers, particularly those in peri-urban and rural areas. Expansion of water networks often requires high connection fees from households, and demand for connections may be low if there are cheaper substitute sources of water available. This research studies the effect of the availability of substitute sources of water on demand for individual water connections in Livingstone, Zambia, using an event study analysis of metering campaigns. Metering campaigns reduce the share of a household's neighbors that can provide free water to the household if their water connection becomes disconnected due to nonpayment. The results show that household payments in newly metered regions increase by 10 percentage points in the months following metering events, with a decrease in disconnections of 6 percentage points for low-income households. To isolate the effect of changes in a household's substitution possibilities, a similar analysis is conducted among households that neighbor the metered region. These results show mixed evidence of the impact of substitutes on payment behavior and disconnections. The results suggest that metering may be effective in increasing household demand for individual water connections primarily through a lower monthly cost burden for newly metered households.

Keywords: piped-water access, water demand, water utilities, water sharing

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Authors: Sajeesh Sulaiman, Gomathisankar A., Aravind Devaraj, Aswin R., Vijay Kumar G., Rachana Raj

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Wind turbines are the next big answer to the emerging and ever-growing demand for electricity, and this need is increasing day by day. These high mast structures, whether on land or on the sea, has also become one of the big sources of electromagnetic interferences (EMI) in the not so distant past. With the emergence of the AC-AC converter and drawing of large power cables through the wind turbine towers has made this clean and efficient source of renewable energy to become one of the culprits in creating electromagnetic interference. This paper will present the sources of such EMIs, a comparison of radiated emissions (both electric and magnetic field) patterns in wind turbine towers for both onshore and offshore wind turbines and close look into the IEC 61400-40 (new standard for EMC design on wind turbine). At present, offshore wind turbines are tested in onshore facilities. This paper will present the anomaly in results for offshore wind turbines when tested in onshore, which the existing standards and the upcoming standards have failed to address.

Keywords: emissions, electric field, magnetic field, wind turbine, tower, standards and regulations

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Authors: Ahmed Aljudaya, Derek Ingham, Lin Ma, Kevin Hughes, Mohammed Pourkashanian

Abstract:

Researchers, power companies, and state politicians have given concentrated solar power (CSP) much attention due to its capacity to generate large amounts of electricity whereas overcoming the intermittent nature of solar resources. The Linear Fresnel Reflector (LFR) is a well-known CSP technology type for being inexpensive, having a low land use factor, and suffering from low optical efficiency. The LFR was considered a cost-effective alternative option to the Parabolic Trough Collector (PTC) because of its simplistic design, and this often outweighs its lower efficiency. The LFR has been found to be a promising option for directly producing steam to a thermal cycle in order to generate low-cost electricity, but also it has been shown to be promising for indirect steam generation. The purpose of this important analysis is to compare the annual performance of the Direct Steam Generation (DSG) and Indirect Steam Generation (ISG) of LFR power plants using molten salt and other different Heat Transfer Fluids (HTF) to investigate their technical and economic effects. A 50 MWe solar-only system is examined as a case study for both steam production methods in extreme weather conditions. In addition, a parametric analysis is carried out to determine the optimal solar field size that provides the lowest Levelized Cost of Electricity (LCOE) while achieving the highest technical performance. As a result of optimizing the optimum solar field size, the solar multiple (SM) is found to be between 1.2 – 1.5 in order to achieve as low as 9 Cent/KWh for the direct steam generation of the linear Fresnel reflector. In addition, the power plant is capable of producing around 141 GWh annually and up to 36% of the capacity factor, whereas the ISG produces less energy at a higher cost. The optimization results show that the DSG’s performance overcomes the ISG in producing around 3% more annual energy, 2% lower LCOE, and 28% less capital cost.

Keywords: concentrated solar power, levelized cost of electricity, linear Fresnel reflectors, steam generation

Procedia PDF Downloads 91

Authors: Farid Khosravikia, Patricia Clayton

Abstract:

The main objective of this work is to evaluate the advantages and disadvantages of various machine learning techniques in two key steps of seismic hazard and risk assessment of different types of structures. The first step is the development of ground-motion models, which are used for forecasting ground-motion intensity measures (IM) given source characteristics, source-to-site distance, and local site condition for future events. IMs such as peak ground acceleration and velocity (PGA and PGV, respectively) as well as 5% damped elastic pseudospectral accelerations at different periods (PSA), are indicators of the strength of shaking at the ground surface. Typically, linear regression-based models, with pre-defined equations and coefficients, are used in ground motion prediction. However, due to the restrictions of the linear regression methods, such models may not capture more complex nonlinear behaviors that exist in the data. Thus, this study comparatively investigates potential benefits from employing other machine learning techniques as statistical method in ground motion prediction such as Artificial Neural Network, Random Forest, and Support Vector Machine. The results indicate the algorithms satisfy some physically sound characteristics such as magnitude scaling distance dependency without requiring pre-defined equations or coefficients. Moreover, it is shown that, when sufficient data is available, all the alternative algorithms tend to provide more accurate estimates compared to the conventional linear regression-based method, and particularly, Random Forest outperforms the other algorithms. However, the conventional method is a better tool when limited data is available. Second, it is investigated how machine learning techniques could be beneficial for developing probabilistic seismic demand models (PSDMs), which provide the relationship between the structural demand responses (e.g., component deformations, accelerations, internal forces, etc.) and the ground motion IMs. In the risk framework, such models are used to develop fragility curves estimating exceeding probability of damage for pre-defined limit states, and therefore, control the reliability of the predictions in the risk assessment. In this study, machine learning algorithms like artificial neural network, random forest, and support vector machine are adopted and trained on the demand parameters to derive PSDMs for them. It is observed that such models can provide more accurate estimates of prediction in relatively shorter about of time compared to conventional methods. Moreover, they can be used for sensitivity analysis of fragility curves with respect to many modeling parameters without necessarily requiring more intense numerical response-history analysis.

Keywords: artificial neural network, machine learning, random forest, seismic risk analysis, seismic hazard analysis, support vector machine

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Authors: Laidi Maamar, Achwak Madani, Abdellah El Ahdj Abdellah

Abstract:

The aim of this work is to use Support Vector regression (SVR) combined with dragonfly, firefly, Bee Colony and particle swarm Optimization algorithm to predict global solar radiation on horizontal surfaces in some cities in Algeria. Combining these optimization algorithms with SVR aims principally to enhance accuracy by fine-tuning the parameters, speeding up the convergence of the SVR model, and exploring a larger search space efficiently; these parameters are the regularization parameter (C), kernel parameters, and epsilon parameter. By doing so, the aim is to improve the generalization and predictive accuracy of the SVR model. Overall, the aim is to leverage the strengths of both SVR and optimization algorithms to create a more powerful and effective regression model for various cities and under different climate conditions. Results demonstrate close agreement between predicted and measured data in terms of different metrics. In summary, SVM has proven to be a valuable tool in modeling global solar radiation, offering accurate predictions and demonstrating versatility when combined with other algorithms or used in hybrid forecasting models.

Keywords: support vector regression (SVR), optimization algorithms, global solar radiation prediction, hybrid forecasting models

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Authors: Shoaib Yousaf

Abstract:

The main purpose of this research is to the empirical investigation of the bullwhip effect under sensitivity analysis in the two-tier supply chain. The simulation modeling technique has been applied in this research as a research methodology to see the sensitivity analysis of the bullwhip effect in the rice industry of Pakistan. The research comprises two case studies that have been chosen as a sample. The results of this research have confirmed that reduction in production delay reduces the bullwhip effect, which conforms to the time compressing paradigm and the significance of the reduction in production delay to lessen demand amplification. The result of this research also indicates that by increasing the value of time to adjust inventory decreases the bullwhip effect. Furthermore, by decreasing the value of alpha increases the damping effect of the exponential smoother, it is not surprising that it also reduces the bullwhip effect. Moreover, by reducing the value of time to work in progress also reduces the bullwhip effect. This research will help practitioners and operation managers to reduces the major costs of their products in three ways. They can reduce their i) inventory levels, ii) better utilize their capacity and iii) improve their forecasting techniques. However, this study is based on two tier supply chain, while in reality the supply chain has got many tiers. Hence, future work will be extended across more than two-tier supply chains.

Keywords: bullwhip effect, rice industry, supply chain dynamics, simulation, sensitivity analysis

Procedia PDF Downloads 118