Journal articles on the topic 'Renewable energy sources Computer simulation'
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Sapundzhi, Fatima. "Computer Simulation and Investigations of the Roof Mount Photovoltaic System." International Journal of Online and Biomedical Engineering (iJOE) 15, no. 12 (August 23, 2019): 88. http://dx.doi.org/10.3991/ijoe.v15i12.10869.
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The interest in the renewable energy sources is increasing due to the depletion of the conventional energy sources and the environmental pollution. In this paper we present a computer simulation and investigations of the roof mounted photovoltaic system. The results of the generated power of the 5kW built-in photovoltaic system by months over a period of 5 years are presented. Depending on the meteorological conditions, the investigated photovoltaic system generates year-round energy necessary for the needs of the household
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Razi, Muhammad, and Yousaf Ali. "Social, Environmental and Economic Impacts of Adopting Clean Energy Use." International Journal of Decision Support System Technology 11, no. 4 (October 2019): 29–49. http://dx.doi.org/10.4018/ijdsst.2019100102.
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These days, the excessive industrialization, elevated levels of pollution, and the increased energy crisis has led nations towards the use of renewable energy sources. Through the use of renewable energy sources, global warming can also be decreased, which is currently the biggest environmental issue worldwide. Pakistan, being a developing country, relies on the use of fossil fuels for the generation of electricity. The alarming increase in population, energy consumption per capita and energy wastages lead to a shortfall. To resolve this crucial issue, the alternative solutions considered include the use of renewable sources of energy such as hydro, solar and wind. The use of these renewable energy sources is governed by various environmental, economic and social parameters. The influence of these parameters on the use of renewable energy sources is studied through the use of DEMATEL and revised DEMATEL techniques.
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Antonenkov, D. V., V. Z. Manusov, P. V. Matrenin, and V. R. Kiushkina. "Adaptive optimal control of prosumer energy storage system with renewable energy sources." Omsk Scientific Bulletin, no. 173 (2020): 50–56. http://dx.doi.org/10.25206/1813-8225-2020-173-50-56.
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The prosumer can use energy storage to enhance the benefits of electricity trading by transferring buy and sell points. Improving energy efficiency is not considered from the standpoint of the entire system, but from an individual prosumer and in conditions of difficult-to-predict wind power generation. This work aims to optimize the prosumer’s electrical complex by developing a method for adapting the base of heuristic rules of the prosumer control to its parameters and climatic conditions. A method for adaptation control rules using swarm intelligence algorithms is proposed. The computer simulation has shown that the use of swarm algorithms makes it possible to increase the economic efficiency of managing the prosumer’s energy storage system by 2–4 times compared to the control rules manually constructed by an expert. It is shown that the proposed method makes it possible to automate the construction of the base of control rules
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Omar, Mohammed A., Ahmad Mayyas, and Qilun Zhou. "Energy-Aware Manufacturing Using Information Technology Tools." International Journal of Information Technology and Web Engineering 9, no. 1 (January 2014): 70–77. http://dx.doi.org/10.4018/ijitwe.2014010106.
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This manuscript discusses the implementation of information technology tools; specifically, computerized Knowledge Based Systems (KBS), in managing the energy flows, conversions, and expenditures within manufacturing environments; including renewable energy sources (namely, landfill gas). The study presents actual KBS embodiments in energy auditing, modeling, and optimization. Additionally, the text presents how IT tools can be used at a system level to integrate sustainability planning within manufacturing planning. The developed tool also addresses the question “how energy-efficient are renewable energy sources” using a novel simulation platform based on hybrid scheme.
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Kolosok, Svitlana, Yuriy Bilan, Tetiana Vasylieva, Adam Wojciechowski, and Michał Morawski. "A Scoping Review of Renewable Energy, Sustainability and the Environment." Energies 14, no. 15 (July 25, 2021): 4490. http://dx.doi.org/10.3390/en14154490.
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The article aims to identify the latest trends in research on renewable energy, sustainability and the environment. A total of 92,873 publications from 123 Scopus sources for 2020–2021 are compared using the scoping review method. The results show that the most cited works in this sample are those by authors from the Asian region. The research of these authors focuses on the security, efficiency and reliability of separate elements in energy systems. Besides, the paper considers the problems regarding COVID disease along with the renewable energy sources, perovskite and organic solar panels, nanostructured materials and high energy density. Finally, the paper analyses applications of computer science methods in research on renewable energy, sustainability and the environment. The findings evidently show that recent advancements in computer science methods were not extensively used in the discussed research domain and give a great room for novel strategies of prognosing, simulation and processes optimisation.
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Arifin, Zainal, Suyitno, Dominicus Danardono Dwi Prija Tjahjana, Mohamad Muqoffa, Singgih Dwi Prasetyo, Noval Fattah Alfaiz, and Arifin Sanusi. "Grid-connected hybrid PV-wind system simulation in urban Java." Journal Européen des Systèmes Automatisés 55, no. 4 (August 31, 2022): 477–83. http://dx.doi.org/10.18280/jesa.550406.
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This research proposes optimizing the energy harvesting system based on solar and wind energy, using the enhanced PV-Wind Turbine hybrid power grid to supply electrical energy somewhere in the city of Yogyakarta, Indonesia. The analysis was conducted by researching the possibilities of wind and solar energy and gathering data from numerous sources. To examine the available data and the economic feasibility of the proposed hybrid power system, the Hybrid Optimization Model for Electric Renewable (HOMER) program was employed. The scheme was simulated and optimized using the National Renewable Energy Laboratory's Hybrid Optimization System for Electric Renewables model (NREL). Various analyses are examined, such as Net Present Value (NPV), Energy Expenditure, Energy Output, Usage, and Excess Energy created by each component of the resultant system. The results gained via the installation of this hybrid system are fairly excellent due to monthly production optimization and minimal maintenance costs with potential investments.
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Dunkelberg, Heiko, Maximilian Sondermann, Henning Meschede, and Jens Hesselbach. "Assessment of Flexibilisation Potential by Changing Energy Sources Using Monte Carlo Simulation." Energies 12, no. 4 (February 21, 2019): 711. http://dx.doi.org/10.3390/en12040711.
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In the fight against anthropogenic climate change, the benefit of the integration of fluctuating renewable energies (wind and photovoltaics) into the electricity grid is a widely proved concept. At the same time, a fluctuating and decentralised supply of energy, especially at lower voltage levels, leads to a local discrepancy in the power balance between generation and consumption. A possible solution in connection with demand side management is the grid-oriented flexibilisation of energy demand. The present study shows how the use of an innovative hybrid-redundant high-temperature heat system (combined heat and power (CHP), power-to-heat system (PtH), gas boiler) can contribute to a flexibilisation of the electrical energy demand of plastics processing companies. In this context, the flexibilisation potential of a company is to be understood as the grid-related change of the energy supply through a change of the energy sources within the framework of the process heat supply. For this purpose, an omniscient control algorithm is developed that specifies the schedule of the individual system components. A sensitivity analysis is used to test the functionality of the control algorithm. Determination of the electrical flexibilisation potential is carried out via a comprehensive simulation study using Monte Carlo methods. For this purpose, the residual load curves of four characteristic distribution grids with a high share of renewable energies as well as heat load profiles of injection moulding machines are taken into consideration. A frequency distribution provides information on the electrical flexibilisation potential to be expected depending on the various combinations. The evaluation is carried out using a specially introduced logic, which identifies grid-relevant changes in the company's power consumption as flexibilisation potential based on a reference load curve. The results show that a reliable energy supply for production is possible despite flexibilisation. Depending on the grid under consideration, there are differences in the exploitation of the potential, which essentially depends on the installed renewable capacity. Depending on the scenario under consideration, an average of up to 1486 kWhel can be shifted in a positive direction and 1199 kWhel in a negative direction.
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Fambri, Gabriele, Marco Badami, Dimosthenis Tsagkrasoulis, Vasiliki Katsiki, Georgios Giannakis, and Antonis Papanikolaou. "Demand Flexibility Enabled by Virtual Energy Storage to Improve Renewable Energy Penetration." Energies 13, no. 19 (October 1, 2020): 5128. http://dx.doi.org/10.3390/en13195128.
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The increasing resort to renewable energy distributed generation, which is needed to mitigate anthropogenic CO2 emissions, leads to challenges concerning the proper operation of electric distribution systems. As a result of the intrinsic nature of Renewable Energy Sources (RESs), this generation shows a high volatility and a low predictability that make the balancing of energy production and consumption difficult. At the same time, the electrification of new energy-intensive sectors (such as heating) is expected. This complex scenario paves the way for new sources of flexibility that will have more and more relevance in the coming years. This paper analyses how the electrification of the heating system, combined with an electric flexibility utilisation module, can be used to mitigate the problems related to the fluctuating production of RES. By using Power-to-Heat (P2H) technologies, buildings are able to store the overproduction of RES in the form of thermal energy for end-use according to the principle of the so-called Virtual Energy Storage (VES). A context-aware demand flexibility extraction based on the VES model and the flexibility upscale and utilisation on district-level through grid simulation and energy flow optimisation is presented in the paper. The involved modules have been developed within the PLANET (PLAnning and operational tools for optimising energy flows and synergies between energy NETworks) H2020 European project and interact under a unified co-simulation framework with the PLANET Decision Support System (DSS) for the analysis of multi-energy scenarios. DSS has been used to simulate a realistic future energy scenario, according to which the imbalance problems triggered by RES overproduction are mitigated with the optimal exploitation of the demand flexibility enabled by VES.
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Spasova, Borislava, Daisuke Kawamoto, and Yoshiyasu Takefuji. "A Study of Fuel Cell Scheduling Effect on Local Energy Markets with Heterogeneous Renewable Sources." Energies 12, no. 5 (March 5, 2019): 854. http://dx.doi.org/10.3390/en12050854.
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The study presented in this paper aims to show the impact of introducing a priority-based internal power flow management system on the local energy market of prosumers with solar panels, fuels cells and batteries. The community used for the study is based on the Open Energy Systems (OES), in which 19 autonomous subsystems, equipped with batteries, solar panels and AC grid connection are interconnected via a DC power bus. For the simulation purposes, fuel cell, modeled after Ene-Farm, is added to the original configuration. Each standalone system has internal, priority-based, agent, capable of scheduling the operating hours of the fuels cell to maximize the utilization of the generation and minimize curtailment. The energy market is based on a simplified version of the Zaraba, a continuous double auction algorithm used by the Japanese Stock Exchange, in which prosumer can submit a bid for a future timeslot. The preliminary numerical evaluation is based on the results from several simulations using different versions of the internal management system.
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Bouziane, Seif Eddine, Mohamed Tarek Khadir, and Julie Dugdale. "A collaborative predictive multi-agent system for forecasting carbon emissions related to energy consumption." Multiagent and Grid Systems 17, no. 1 (April 19, 2021): 39–58. http://dx.doi.org/10.3233/mgs-210342.
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Energy production and consumption are one of the largest sources of greenhouse gases (GHG), along with industry, and is one of the highest causes of global warming. Forecasting the environmental cost of energy production is necessary for better decision making and easing the switch to cleaner energy systems in order to reduce air pollution. This paper describes a hybrid approach based on Artificial Neural Networks (ANN) and an agent-based architecture for forecasting carbon dioxide (CO2) issued from different energy sources in the city of Annaba using real data. The system consists of multiple autonomous agents, divided into two types: firstly, forecasting agents, which forecast the production of a particular type of energy using the ANN models; secondly, core agents that perform other essential functionalities such as calculating the equivalent CO2 emissions and controlling the simulation. The development is based on Algerian gas and electricity data provided by the national energy company. The simulation consists firstly of forecasting energy production using the forecasting agents and calculating the equivalent emitted CO2. Secondly, a dedicated agent calculates the total CO2 emitted from all the available sources. It then computes the benefits of using renewable energy sources as an alternative way to meet the electric load in terms of emission mitigation and economizing natural gas consumption. The forecasting models showed satisfying results, and the simulation scenario showed that using renewable energy can help reduce the emissions by 369 tons of CO2 (3%) per day.
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Devaraj, Elangovan, Peter K. Joseph, Thundil Karuppa Raj Rajagopal, and Senthilarasu Sundaram. "Renewable Energy Powered Plugged-In Hybrid Vehicle Charging System for Sustainable Transportation." Energies 13, no. 8 (April 15, 2020): 1944. http://dx.doi.org/10.3390/en13081944.
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Energy transformation by power electronic converters is not feasible without the efficient use of renewable energy. The article tries to extend the use of renewable energy to PHEV battery charging. In PHEV, the battery is one of the major sources of stored energy. The converter used for charging these batteries is of crucial concern. The paper addresses various challenges in designing a DC to DC converter for battery charging in DC bus. An optimized converter is designed to work with renewable energy sources to accomplish a high boost ratio, low input current ripple, low output voltage ripple, high power efficiency, and high power density. A combination of two interleaved boost converters is effectively used with the overlap time switching to achieve a high voltage boost ratio in forming the DC bus. Transformer isolation is used to increase reliability and boost ratio further. The secondary side employs a series-connected voltage doubler. The converter boosts an input voltage of 24 V to a range of 300–400 V. Simulation results have been obtained for a 300 W system. Simulation results are validated by a prototype implementation for a 250 W system. The converter is studied and analyzed for steady-state and transient state characteristics and the power efficiency obtained is 92.9%.
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Mandal, Ronit. "DESIGN AND NUMERICAL SIMULATION OF A SOLAR ENERGY DRIVEN SMALL-SCALE MILK PASTEURIZATION SYSTEM." International Journal of Engineering Applied Sciences and Technology 7, no. 6 (October 1, 2022): 149–56. http://dx.doi.org/10.33564/ijeast.2022.v07i06.012.
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The conventional sources of heat generation are widely prevalent in the food industry like the electricity and usage of fossil fuels. However, they have some associated drawbacks with them like rising fuel prices, associated pollution level etc. These clearly mandate the use of renewable sources of energy like wind, hydrothermal or solar energy. Solar energy is the one of the major sources of energy, which is renewable, inexhaustible, and clean. It can significantly contribute the world energy requirement with available conversion technology. The present study is about to designing and numerical modeling a solar energy driven small-scale milk pasteurization system. The design and operating parameters were evaluated first and then computer-aideddesigning (CAD) software was used to create a 3-D diagram of the system. Then a prototype has been developed and its performance evaluation was carried out. Collector of focal length 12 cm, aperture width 31.5 cm, rim angle 131.5 ° was fabricated with a 3 m long absorber tube. The milk was passed through absorber tube at flow rate 30 L/h giving an outlet temperature of 72 °C. Computation fluid dynamics (CFD) analysis of the data showed good correlation between experimental data and simulation.
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Kumar, Jagdesh, Chethan Parthasarathy, Mikko Västi, Hannu Laaksonen, Miadreza Shafie-Khah, and Kimmo Kauhaniemi. "Sizing and Allocation of Battery Energy Storage Systems in Åland Islands for Large-Scale Integration of Renewables and Electric Ferry Charging Stations." Energies 13, no. 2 (January 9, 2020): 317. http://dx.doi.org/10.3390/en13020317.
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The stringent emission rules set by international maritime organisation and European Directives force ships and harbours to constrain their environmental pollution within certain targets and enable them to employ renewable energy sources. To this end, harbour grids are shifting towards renewable energy sources to cope with the growing demand for an onshore power supply and battery-charging stations for modern ships. However, it is necessary to accurately size and locate battery energy storage systems for any operational harbour grid to compensate the fluctuating power supply from renewable energy sources as well as meet the predicted maximum load demand without expanding the power capacities of transmission lines. In this paper, the equivalent circuit battery model of nickel–cobalt–manganese-oxide chemistry has been utilised for the sizing of a lithium-ion battery energy storage system, considering all the parameters affecting its performance. A battery cell model has been developed in the Matlab/Simulink platform, and subsequently an algorithm has been developed for the design of an appropriate size of lithium-ion battery energy storage systems. The developed algorithm has been applied by considering real data of a harbour grid in the Åland Islands, and the simulation results validate that the sizes and locations of battery energy storage systems are accurate enough for the harbour grid in the Åland Islands to meet the predicted maximum load demand of multiple new electric ferry charging stations for the years 2022 and 2030. Moreover, integrating battery energy storage systems with renewables helps to increase the reliability and defer capital cost investments of upgrading the ratings of transmission lines and other electrical equipment in the Åland Islands grid.
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Sayed, Khairy, Ahmed G. Abo-Khalil, and Ali S. Alghamdi. "Optimum Resilient Operation and Control DC Microgrid Based Electric Vehicles Charging Station Powered by Renewable Energy Sources." Energies 12, no. 22 (November 7, 2019): 4240. http://dx.doi.org/10.3390/en12224240.
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This paper introduces an energy management and control method for DC microgrid supplying electric vehicles (EV) charging station. An Energy Management System (EMS) is developed to manage and control power flow from renewable energy sources to EVs through DC microgrid. An integrated approach for controlling DC microgrid based charging station powered by intermittent renewable energies. A wind turbine (WT) and solar photovoltaic (PV) arrays are integrated into the studied DC microgrid to replace energy from fossil fuel and decrease pollution from carbon emissions. Due to the intermittency of solar and wind generation, the output powers of PV and WT are not guaranteed. For this reason, the capacities of WT, solar PV panels, and the battery system are considered decision parameters to be optimized. The optimized design of the renewable energy system is done to ensure sufficient electricity supply to the EV charging station. Moreover, various renewable energy technologies for supplying EV charging stations to improve their performance are investigated. To evaluate the performance of the used control strategies, simulation is carried out in MATLAB/SIMULINK.
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Bassil, Chirine, Hussein EL GHOR, Jawad Khalife, and Nizar Hamadeh. "A New Clustering Routing Protocol for Homogeneous Wireless Sensor Networks Powered by Renewable Energy Sources." Scalable Computing: Practice and Experience 21, no. 4 (December 20, 2020): 637–48. http://dx.doi.org/10.12694/scpe.v21i4.1787.
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The technology of wireless sensor networks (WSNs) is in constant development and it made great progress in many applications. One of the most popular problems in WSNs is the limited energy storage power at every sensor node. This paper aims to propose and develop a new distributed clustering algorithm for energy harvesting wireless sensor networks denoted by DEH-WSN (Energy Harvesting for Distributed Clustering Wireless Sensor Networks Protocol) that relies on matching between clustering and energy harvesting in a distributed topology. DEH-WSN uses initial and residual energy capacity of the nodes to choose cluster heads. Simulation results prove that the proposed method increases network lifetime and the effective throughput.
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Li, Jeremy (Zheng). "Computer-Aided Design, Modeling and Simulation of a New Solar Still Design." Modelling and Simulation in Engineering 2011 (2011): 1–5. http://dx.doi.org/10.1155/2011/903721.
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The clean and pure drinking water is important in today's life but current water sources are usually brackish with bacteria that cannot be used for drinking. About 78% of water available in the sea is salty, 21% of water is brackish, and only 1% of water is fresh. Distillation is one of the feasible processes applied to water purification, and it requires the energy inputs, such as solar radiation. Water is evaporated in this distillation process and water vapor can be separated and condensed to pure water. Now, with the change from conventional fuels to renewable and environment friendly fuels sources, the modern technology allows to use the abundant energy from the sun. It is better to use solar energy to process the water desalination since it is more economical than the use of conventional energies. The main focus of this paper is applying computer-aided modeling and simulation to design a less complex solar water distillation system. The prototype of this solar still system is also built to verify its feasibility, functionality, and reliability. The computational simulation and prototype testing show the reliability and proper functionality of this solar water distillation system.
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Andrychowicz, Mateusz. "Comparison of the Use of Energy Storages and Energy Curtailment as an Addition to the Allocation of Renewable Energy in the Distribution System in Order to Minimize Development Costs." Energies 13, no. 14 (July 21, 2020): 3746. http://dx.doi.org/10.3390/en13143746.
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This paper presents a comparison of the efficiency of energy storage and energy curtailment as an addition to the allocation of renewable energy in the distribution system in order to minimize development costs using a Mixed Integer-Linear Programming (MILP). Energy sources and energy storages are selected, sized and allocated under operational circumstances such as grid congestions and weather conditions. Loads and power units are modeled by daily consumption and generation profiles respectively, to reflect the intermittent character of renewable generation and consumption of energy. The optimization is carried out for a one-year time horizon using twenty-four representative days. The method is verified on three main simulation scenarios and three sub-scenarios for each of them, allowing for the comparison of the efficiency of each used tool. The main scenarios differ in their share of energy from renewable energy sources (RES) in total consumption. In the sub-scenarios, different tools (RES sizing and allocation, energy storages (ES) sizing and allocation and energy curtailment) are used. The results of this research confirm that energy curtailment is a more efficient additional tool for RES sizing and allocation than energy storages. This method can find practical application for Distribution System Operators in elaborating grid development strategies.
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Shao, Lei, Xu Zhou, Ji Li, Hongli Liu, and Xiaoqi Chen. "Microgrids as Flexible and Network-Connected Grid Assets in Active Distribution Systems." Journal of Electrical and Computer Engineering 2018 (July 24, 2018): 1–7. http://dx.doi.org/10.1155/2018/6079617.
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The functionalities of microgrids are detailed and thereby expanded in active distribution systems. A versatile and coordinated operation among multiple microgrids is proposed to facilitate the integration of renewable energy sources (RES) in modern distribution grids. Particularly, to meet the requirements of high penetration level of renewables (e.g., photovoltaics and small hydro), more than one networked controlled microgrids are deployed simultaneously in different locations of a distribution system. Therefore, local RES can be aggregated in each microgrids. In order to satisfy the latest standards in terms of renewable energy integration (i.e., IEEE Std. 1547 Rev), an optimal operation strategy is designed to coordinate the operation of multiple microgrids. A simulation model is implemented in MATLAB to validate the proposed networked microgrids and the corresponding operation strategy.
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Hasan, A. S. M. Mominul. "Electric Rickshaw Charging Stations as Distributed Energy Storages for Integrating Intermittent Renewable Energy Sources: A Case of Bangladesh." Energies 13, no. 22 (November 22, 2020): 6119. http://dx.doi.org/10.3390/en13226119.
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This exploratory research outlines an opportunity for increasing renewable energy share in Bangladesh by using electric rickshaws (e-rickshaws) as a catalyst. The overall objective of this research is to show how to utilise an existing opportunity, such as e-rickshaws, as energy storage options for integrating renewable energy sources. It proposes a grid-connected local energy system considering a battery swapping and charging station (BSCS) for e-rickshaws as a community battery energy storage (CBESS). This system was simulated using the HOMER Pro software. The simulation results show that such systems can help communities significantly reduce their dependency on the national grid by integrating solar PV locally. The proposed BSCS also shows an opportunity for battery demand reduction and circular battery management for electric rickshaws. The research also discusses the economies of scale of the proposed method in Bangladesh, and pathways for implementing microgrids and smart energy systems. The innovative concepts presented in this research will start a policy-level dialogue in Bangladesh for utilising local opportunities to find an alternative energy storage solution and provide momentum to the researchers for further studies.
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Alhamrouni, Ibrahim, Mohamed Salem, Younes Zahraoui, Basilah Ismail, Awang Jusoh, and Tole Sutikno. "Multi-input interleaved DC-DC converter for hybrid renewable energy applications." Bulletin of Electrical Engineering and Informatics 11, no. 3 (June 1, 2022): 1765–78. http://dx.doi.org/10.11591/eei.v11i3.3779.
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The increasing demand for hybrid energy systems based on renewable energy sources has enabled the new dimension for multi-input converter (MIC). Various topologies have been introduced over the last decade. However, most of these topologies have several drawbacks in terms of design complexity or efficiency. Therefore, this research aims to introduce a multi-input DC-DC converter for hybrid renewable energy applications. The proposed multi-input converter is able to hybridize different sources such as solar PV array and PEMFC. Analysis and simulation have been carried out for the double input two-phase interleaved converter in operating the boost mode. The proposed converter is designed in matlab simulink by using interleaved boost converter method to achieve a boosted and smoothened output. The proposed topology has shown a remarkable performance in terms of output voltage boosting, voltage ripple reduction as well as enhanced efficiency through interleaved boosting technique. From the simulation results, it can be observed that the proposed converter can gain high efficiency which is higher than 97%. The obtained results have been validated with previously published works and the proposed technique has been proven to yield compatible and improved outcomes.
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Liu, Lei, Hidehito Matayoshi, Mohammed Lotfy, Manoj Datta, and Tomonobu Senjyu. "Load Frequency Control Using Demand Response and Storage Battery by Considering Renewable Energy Sources." Energies 11, no. 12 (December 5, 2018): 3412. http://dx.doi.org/10.3390/en11123412.
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Renewable energy sources (RESs), as clean, abundant, and inexhaustible source of energy, have developed quickly in recent years and played more and more important roles around the world. However, RESs also have some disadvantages, such as the weakness of stability, and by the the estimated increase of utilizing RESs in the near future, researchers began to give more attention to these issues. This paper presents a novel output power fluctuate compensation scheme in the small-scale power system, verifying the effect of output power control using storage battery, demand-response and RESs. Four scenarios are considered in the proposed approach: real-time pricing demand-response employment, RESs output control use and both of demand-response and RESs output control implementation. The performance of the proposed control technique is investigated using the real 10-bus power system model of Okinawa island, Japan. Moreover, the system stability is checked using the pole-zero maps for all of the control loops associated with the proposed scheme. The robustness and effectiveness of the proposed method was verified by simulation using Matlab ® /Simulink ® .
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Patnaik, Samarjit, Manas Ranjan Nayak, and Meera Viswavandya. "Smart deployment of energy storage and renewable energy sources for improving distribution system efficacy." AIMS Electronics and Electrical Engineering 6, no. 4 (2022): 397–417. http://dx.doi.org/10.3934/electreng.2022024.
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<abstract><p>Climate change, global warming, the depletion of fossil fuels, and rising energy demand are the main forces behind the increase in renewable energy sources. However, the unpredictability of power output from these renewable energy sources presents distribution system integration issues such as limited feeder capacity, unstable voltage, and network power loss. This study analyses the African vulture optimisation algorithm to determine the best allocation of distribution generators, with an emphasis on reducing the ageing of distribution transformers and delaying investment in feeders. The optimization technique provides faster global convergence and outperforms existing bio-inspired algorithms verified with benchmark uni-modal functions as a result of a larger crossover between the exploration and exploitation phases. The key aim is to decrease active power loss while simultaneously enhancing security margin and voltage stability. The IEEE 69-bus RDS system is utilised to validate the case studies for appropriate allocation of photovoltaic, wind turbine generation, and battery energy storage systems units, as well as offering the ideal energy management approach. During simulation, uncertainty on the characteristics of renewable energy source is accounted for. The results demonstrate the efficacy of the proposed algorithm with a substantial improvement in voltage profile, the benefit of lower CO2 emissions, an increase in security margin of up to 143%, and the advantage of extending the feeder investment deferral period by more than 50 years. In addition, the distribution transformer ageing acceleration factor improves significantly in the case of an increase in load demand.</p></abstract>
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Yılmaz, İbrahim Halil, and Mehmet Sait Söylemez. "Design and computer simulation on multi-effect evaporation seawater desalination system using hybrid renewable energy sources in Turkey." Desalination 291 (April 2012): 23–40. http://dx.doi.org/10.1016/j.desal.2012.01.022.
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Abdulmula, Ahmed, Kamaruzzaman Sopian, Norasikin Ahmad Ludin, Lim Chin Haw, Abdelnaser Elbreki, Fayez Aldawi, and Hazim Moria. "Micropower system optimization for the telecommunication towers based on various renewable energy sources." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 2 (April 1, 2022): 1069. http://dx.doi.org/10.11591/ijece.v12i2.pp1069-1076.
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This study investigates the technical and cost-effective performance of options renewable energy sources to develop a green off-grid telecommunication tower to replace diesel generators in Malaysia. For this purpose, the solar, wind, pico-hydro energy, along with diesel generators, were examined to compare. In addition, the modeling of hybrid powering systems was conducted using hybrid optimization model for energy (HOMER) simulation based on techno-economic analysis to determine the optimal economically feasible system. The optimization findings showed that the hybrid high-efficiency fixed photovoltaic (PV) system with battery followed by 2 kW pico-hydropower and battery are the optimal configurations for powering off-grid telecommunication towers in Malaysia with the lowest net present cost (NPC) and cost of energy (COE). These costs of NPC and COE are more down than diesel generator costs with battery by 17.45%, 16.45%, 15.9%, and 15.5%, respectively. Furthermore, the economic evaluation of the high-efficiency solar fixed PV panels system annual cash flow compared to the diesel generator with the battery system indicated a ten-year payback period.
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Morais, Hugo, Tiago Pinto, and Zita Vale. "Adjacent Markets Influence Over Electricity Trading—Iberian Benchmark Study." Energies 13, no. 11 (June 1, 2020): 2808. http://dx.doi.org/10.3390/en13112808.
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This paper presents a study on the impact of adjacent markets on the electricity market, realizing the advantages of acting in several different markets. The increased use of renewable primary sources to generate electricity and new usages of electricity such as electric mobility are contributing to a better and more rational way of living. The investment in renewable technologies for the distributed generation has been creating new opportunities for owners of such technologies. Besides the selling of electricity and related services (ancillary services) in energy markets, players can participate and negotiate in other markets, such as the carbon/CO2 market, the guarantees of origin market, or provide district heating services selling of steam and hot water among others. These market mechanisms are related to the energy market, originating a wide market strategy improving the benefits of using distributed generators. This paper describes several adjacent markets and how do they complement the electricity market. The paper also shows how the simulation of electricity and adjacent markets can be performed, using an electricity market simulator, and demonstrates, based on market simulations using real data from the Iberian market, that the participation in various complementary markets can enable power producers to obtain extra profits that are essential to cover the production costs and facilities maintenance. The findings of this paper enhance the advantages for investment on energy production based renewable sources and more efficient technologies of energy conversion.
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Asgher, Urooj, Muhammad Rasheed, Ameena Al-Sumaiti, Atiq Rahman, Ihsan Ali, Amer Alzaidi, and Abdullah Alamri. "Smart Energy Optimization Using Heuristic Algorithm in Smart Grid with Integration of Solar Energy Sources." Energies 11, no. 12 (December 14, 2018): 3494. http://dx.doi.org/10.3390/en11123494.
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Smart grid (SG) vision has come to incorporate various communication technologies, which facilitate residential users to adopt different scheduling schemes in order to manage energy usage with reduced carbon emission. In this work, we have proposed a residential load management mechanism with the incorporation of energy resources (RESs) i.e., solar energy. For this purpose, a real-time electricity price (RTP), energy demand, user preferences and renewable energy parameters are taken as an inputs and genetic algorithm (GA) has been used to manage and schedule residential load with the objective of cost, user discomfort, and peak-to-average ratio (PAR) reduction. Initially, RTP is used to reduce the energy consumption cost. However, to minimize the cost along with reducing the peaks, a combined pricing model, i.e., RTP with inclining block rate (IBR) has been used which incorporates user preferences and RES to optimally schedule load demand. User comfort and cost reduction are contradictory objectives, and difficult to maximize, simultaneously. Considering this trade-off, a combined pricing scheme is modelled in such a way that users are given priority to achieve their objective as per their requirements. To validate and analyze the performance of the proposed algorithm, we first propose mathematical models of all utilized loads, and then multi-objective optimization problem has been formulated. Furthermore, analytical results regarding the objective function and the associated constraints have also been provided to validate simulation results. Simulation results demonstrate a significant reduction in the energy cost along with the achievement of both grid stability in terms of reduced peak and high comfort..
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Mahmoud, Fayza S., Ashraf M. Abdelhamid, Ameena Al Sumaiti, Abou-Hashema M. El-Sayed, and Ahmed A. Zaki Diab. "Sizing and Design of a PV-Wind-Fuel Cell Storage System Integrated into a Grid Considering the Uncertainty of Load Demand Using the Marine Predators Algorithm." Mathematics 10, no. 19 (October 10, 2022): 3708. http://dx.doi.org/10.3390/math10193708.
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In this paper, the utility grid is integrated with hybrid photovoltaic (PV)/wind/fuel cells to overcome the unavailability of the grid and the single implementation of renewable energy. The main purpose of this study is smart management of hydrogen storage tanks and power exchange between the hybrid renewable energy and the grid to minimize the total cost of the hybrid system and load uncertainties. PV and wind act as the main renewable energy sources, whereas fuel cells act as auxiliary sources designed to compensate for power variations and to ensure continuous power flow to the load. The grid is considered a backup system that works when hybrid renewable energy and fuel cells are unavailable. In this study, the optimal size of the components of the hybrid energy system is introduced using two methods: the marine predators’ algorithm (MPA) and the seagull optimization algorithm (SOA). The optimal sizing problem is also run accounting for the uncertainty in load demand. The results obtained from the proposed optimization are given with and without uncertainty in load demand. The simulation results of the hybrid system without uncertainty demonstrate the superiority of the MPA compared with SOA. However, in the case of load uncertainty, the simulation results (the uncertainty) are given using the MPA optimization technique with +5%, +10%, and +15% uncertainty in load, which showed that the net present cost and purchase energy are increased with uncertainty.
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Oliveira, Rosana Cavalcante de, Rogerio Diogne de Souza e. Silva, and Maria Emília De Lima Tostes. "A methodology for analysis of cogeneration projects using oil palm biomass wastes as an energy source in the Amazon." DYNA 82, no. 190 (May 11, 2015): 105–12. http://dx.doi.org/10.15446/dyna.v82n190.43298.
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In the search for strategies to mitigate climate change, the promotion of renewable energy is a major challenge worldwide, particularly for developing countries such as Brazil and Colombia, which aim to diversify their power grids by using unconventional renewable energy sources. One of the main obstacles is the development of innovative projects. Increasing oil palm cultivation in the Amazon region for the food and biodiesel industries is producing a large volume of biomass. The present study outlines a methodology for analysis of renewable energy projects based on identification of environmental, economic, and social sustainability criteria and indicators (C&I) for the oil palm production chain. This methodology was then used to develop a computer simulation model in the RETScreen® International software environment for financial viability and risk analysis.
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Bâra, Adela. "Mix-generation optimization for electricity market simulation." Scientific Bulletin of Naval Academy XXIII, no. 1 (July 15, 2020): 180–85. http://dx.doi.org/10.21279/1454-864x-20-i1-023.
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Owning several types of generating units requires an optimized schedule to cover the negotiated bilateral contracts. This approach will lead to a better electricity market strategy and benefits for an electricity producer. In this paper, we will simulate the operation of five different generators including generators based on Renewable Energy Sources (such as wind turbines and photovoltaic panels) that belong to an electricity producer. The five generators are modelled considering the specificity of their type and primary energy source. For instance, for renewable energy sources, we will consider the 24-hour generation forecast. The objective function of the optimization process is to obtain an optimal loading of generators, while the constraints are related to the capacity and performance of the generators. The output consisting in a generating unit optimized operation schedule will be further used for day-ahead or balancing market bidding process. Hence, the producer will be able to adequately bid on the future electricity markets knowing the commitment of generators for negotiated bilateral contracts market. The simulations are tested for more than five generators considering the connection to a relational database where more data for generators is stored.
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Abdulgalil, Mohammed Atta, Muhammad Khalid, and Fahad Alismail. "Optimal Sizing of Battery Energy Storage for a Grid-Connected Microgrid Subjected to Wind Uncertainties." Energies 12, no. 12 (June 23, 2019): 2412. http://dx.doi.org/10.3390/en12122412.
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In this paper, based on stochastic optimization methods, a technique for optimal sizing of battery energy storage systems (BESSs) under wind uncertainties is provided. Due to considerably greater penetration of renewable energy sources, BESSs are becoming vital elements in microgrids. Integrating renewable energy sources in a power system together with a BESS enhances the efficiency of the power system by enhancing its accessibility and decreasing its operating and maintenance costs. Furthermore, the microgrid-connected BESS should be optimally sized to provide the required energy and minimize total investment and operation expenses. A constrained optimization problem is solved using an optimization technique to optimize a storage system. This problem of optimization may be deterministic or probabilistic. In case of optimizing the size of a BESS connected to a system containing renewable energy sources, solving a probabilistic optimization problem is more effective because it is not possible to accurately determine the forecast of their output power. In this paper, using the stochastic programming technique to discover the optimum size of a BESS to connect to a grid-connected microgrid comprising wind power generation, a probabilistic optimization problem is solved. A comparison is then produced to demonstrate that solving the problem using stochastic programming provides better outcomes and to demonstrate that the reliability of the microgrid improves after it is connected to a storage system. The simulation findings demonstrate the efficacy of the optimum sizing methodology proposed.
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Nazir, Muhammad Shahzad, Sami ud Din, Wahab Ali Shah, Majid Ali, Ali Yousaf Kharal, Ahmad N. Abdalla, and Padmanaban Sanjeevikumar. "Optimal Economic Modelling of Hybrid Combined Cooling, Heating, and Energy Storage System Based on Gravitational Search Algorithm-Random Forest Regression." Complexity 2021 (May 13, 2021): 1–13. http://dx.doi.org/10.1155/2021/5539284.
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The hybridization of two or more energy sources into a single power station is one of the widely discussed solutions to address the demand and supply havoc generated by renewable production (wind-solar/photovoltaic (PV), heating power, and cooling power) and its energy storage issues. Hybrid energy sources work based on the complementary existence of renewable sources. The combined cooling, heating, and power (CCHP) is one of the significant systems and shows a profit from its low environmental impact, high energy efficiency, low economic investment, and sustainability in the industry. This paper presents an economic model of a microgrid (MG) system containing the CCHP system and energy storage considering the energy coupling and conversion characteristics, the effective characteristics of each microsource, and energy storage unit is proposed. The random forest regression (RFR) model was optimized by the gravitational search algorithm (GSA). The test results show that the GSA-RFR model improves prediction accuracy and reduces the generalization error. The detail of the MG network and the energy storage architecture connected to the other renewable energy sources is discussed. The mathematical formulation of energy coupling and energy flow of the MG network including wind turbines, photovoltaic (PV), CCHP system, fuel cell, and energy storage devices (batteries, cold storage, hot water tanks, and so on) are presented. The testing system has been analysed under load peak cutting and valley filling of energy utilization index, energy utilization rate, the heat pump, the natural gas consumption of the microgas turbine, and the energy storage unit. The energy efficiency costs were observed as 88.2% and 86.9% with heat pump and energy storage operation comparing with GSA-RFR-based operation costs as 93.2% and 93% in summer and winter season, respectively. The simulation results extended the rationality and economy of the proposed model.
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Żelazna, Agnieszka, Artur Pawłowski, and Agata Zdyb. "Green designing of solar hot water systems using computer simulations." MATEC Web of Conferences 252 (2019): 05017. http://dx.doi.org/10.1051/matecconf/201925205017.
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Solar thermal installations are one of the popular types of renewable energy sources. This paper presents the comparison of the considered design variants of the typical solar hot water installation on the basis of Life Cycle Assessment. The simulations and the design criteria included:- optimal angle of inclination and orientation of collectors for the selected location (simulations in GetSolar),- optimal type of collectors (simulations in SimaPro).Life cycle analysis of solar hot water systems shows that this technology has the potential to reduce the environmental impact of hot water preparation while compared to the conventional energy sources. However, the optimisation criteria used for green designing in the life cycle perspective can significantly improve the environmental balance of the analysed technologies.
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Singh, Mayank, and Rakesh Jha. "Object-Oriented Usability Indices for Multi-Objective Demand Side Management Using Teaching-Learning Based Optimization." Energies 12, no. 3 (January 24, 2019): 370. http://dx.doi.org/10.3390/en12030370.
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This paper proposes Object-Oriented Usability Indices (OOUI) for multi-objective Demand Side Management (DSM). These indices quantify the achievements of multi-objective DSM in a power network. DSM can be considered as a method adopted by utilities to shed some load during peak load hours. Usually, there are service contracts, and the curtailments or dimming of load are automatically done by service providers based on contract provisions. This paper formulates three indices, namely peak power shaving, renewable energy integration, and an overall usability index. The first two indices indicate the amount of peak load shaving and integration of renewable energy, while the third one combines the impact of both indices and quantifies the overall benefit achieved through DSM. The application of the proposed indices is presented through simulation performed in a grid-tied microgrid environment for a multi-objective DSM formulation. The adopted microgrid structure consists of three units of diesel generators and two renewable energy sources. Simulation has been done using MATLAB software. Teaching-Learning-Based Optimization (TLBO) is adopted as the optimization tool due to its simplicity and independency of algorithm-specific control parameters. Five different cases of renewable energy availability with results validate the efficiency of the proposed approach. The results indicate the usefulness in determining the suitable condition regarding DSM application.
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D’Agostino, Diana, Luigi Mele, Francesco Minichiello, and Carlo Renno. "The Use of Ground Source Heat Pump to Achieve a Net Zero Energy Building." Energies 13, no. 13 (July 3, 2020): 3450. http://dx.doi.org/10.3390/en13133450.
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Currently, ground source heat pump (GSHP) technology is being studied, as the use of the ground as a source of renewable energy allows significant energy savings to be obtained. Therefore, it is useful to quantify how these savings help to achieve the energy balance of a Net Zero Energy Building (NZEB) compared to an air source heat pump or a condensing boiler coupled to a chiller. This paper assesses how these savings affect the number of photovoltaic panels installed on the roof of a building to obtain the NZEB target. The study is conducted by dynamic simulation for a building used as a bed and breakfast, virtually placed in two Italian towns. The energy savings and reduction of CO2 emissions, the percentage of renewable energy used, and the photovoltaic surface needed are assessed. Finally, the discounted payback period is calculated. The results show that the GSHP, unlike the systems to which it is compared, allows an NZEB to be obtained by balancing yearly energy consumption with energy production systems which only use on-site renewable energy sources (by exploiting the surface available on the roof) for both of the climatic conditions considered. GSHP also allows primary energy requests equal to or less than 57 kWh/m2 to be obtained.
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Hasan, Ghanim Thiab, Ali Hlal Mutlaq, and Mohammad Omar Salih. "Investigate the optimal power system by using hybrid optimization of multiple energy resources software." Indonesian Journal of Electrical Engineering and Computer Science 26, no. 1 (April 1, 2022): 9. http://dx.doi.org/10.11591/ijeecs.v26.i1.pp9-19.
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Increasing the effects of global pollution and the availability of renewable energy sources has push many countries to use reasonable energy sources such as wind and solar energy. This paper presents a case study of evaluating a hybrid renewable energy system by using a hybrid optimization of multiple energy resources (HOMER) software program based on the entered data available from the net for the considered location. The hybrid system consisting of a wind turbine, a photovoltaic system, a battery and a diesel generator. The simulation results are presented in a graphical curves n HOMER software. The obtained results indicate that by using the HOMER simulation program, the optimal design of the hybrid electrical power system for the considered location can be achieved which can help the designer to decide the types and number of the competent required for conducting the intending hybrid electrical power system which results in optimum output power in addition to reducing the overall operating costs.
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Figaj, Rafał, Maciej Żołądek, and Wojciech Goryl. "Dynamic Simulation and Energy Economic Analysis of a Household Hybrid Ground-Solar-Wind System Using TRNSYS Software." Energies 13, no. 14 (July 8, 2020): 3523. http://dx.doi.org/10.3390/en13143523.
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The adoption of micro-scale renewable energy systems in the residential sector has started to be increasingly diffused in recent years. Among the possible systems, ground heat exchangers coupled with reversible heat pumps are an interesting solution for providing space heating and cooling to households. In this context, a possible hybridization of this technology with other renewable sources may lead to significant benefits in terms of energy performance and reduction of the dependency on conventional energy sources. However, the investigation of hybrid systems is not frequently addressed in the literature. The present paper presents a technical, energy, and economic analysis of a hybrid ground-solar-wind system, proving space heating/cooling, domestic hot water, and electrical energy for a household. The system includes vertical ground heat exchangers, a water–water reversible heat pump, photovoltaic/thermal collectors, and a wind turbine. The system with the building is modeled and dynamically simulated in the Transient System Simulation (TRNSYS) software. Daily dynamic operation of the system and the monthly and yearly results are analyzed. In addition, a parametric analysis is performed varying the solar field area and wind turbine power. The yearly results point out that the hybrid system, compared to a conventional system with natural gas boiler and electrical chiller, allows one to reduce the consumption of primary energy of 66.6%, and the production of electrical energy matches 68.6% of the user demand on a yearly basis. On the other hand, the economic results show that that system is not competitive with the conventional solution, because the simple pay back period is 21.6 years, due to the cost of the system components.
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Fadil, Hassan El, Abdelhafid Yahya, Mustapha Oulcaid, Leila Ammeh, and Fouad Giri. "Output feedback nonlinear control of power system under large penetration of renewable energy sources." International Journal of Modelling, Identification and Control 31, no. 4 (2019): 337. http://dx.doi.org/10.1504/ijmic.2019.099825.
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Skouros, Ioannis, and Athanasios Karlis. "A Study on the V2G Technology Incorporation in a DC Nanogrid and on the Provision of Voltage Regulation to the Power Grid." Energies 13, no. 10 (May 23, 2020): 2655. http://dx.doi.org/10.3390/en13102655.
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Currently, environmental and climate change issues raise a lot of concerns related to conventional vehicles and renewable energy generation methods. Thus, more and more researchers around the world focus on the development and deployment of Renewable Energy Sources (RES). Additionally, due to the technological advancements in power electronics and electrical batteries, Electrical Vehicles (EVs) are becoming more and more popular. In addition, according to the Vehicle-to-Grid (V2G) operation, the EV batteries can provide electrical energy to the power grid. In this way, many ancillary services can be provided. A Direct Current (DC) nanogrid can be composed by combining the aforementioned technologies. Nanogrids present high efficiency and provide a simple interaction with renewable energy sources and energy storage devices. Firstly, the present study describes the design considerations of a DC nanogrid as well as the control strategies that have to be applied in order to make the V2G operation feasible. Furthermore, the provision of voltage regulation toward the power grid is investigated though the bidirectional transfer of active and reactive power between the DC nanogrid and the power grid. Afterwards, the voltage regulation techniques are applied in an Alternating Current (AC) radial distribution grid are investigated. The proposed system is simulated in Matlab/Simulink software and though the simulation scenarios the impact of the voltage regulation provided by the DC nanogrid is investigated.
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Rahman, Syed, Irfan Khan, Khaliqur Rahman, Sattam Al Otaibi, Hend I. Alkhammash, and Atif Iqbal. "Scalable Multiport Converter Structure for Easy Grid Integration of Alternate Energy Sources for Generation of Isolated Voltage Sources for MMC." Electronics 10, no. 15 (July 25, 2021): 1779. http://dx.doi.org/10.3390/electronics10151779.
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This paper presents a novel, scalable, and modular multiport power electronic topology for the integration of multiple resources. This converter is not only scalable in terms of the integration of multiple renewable energy resources (RES) and storage devices (SDs) but is also scalable in terms of output ports. Multiple dc outputs of a converter are designed to serve as input to the stacking modules (SMs) of the modular multilevel converter (MMC). The proposed multiport converter is bidirectional in nature and superior in terms of functionality in a way that a modular universal converter is responsible for the integration of multiple RES/SDs and regulates multiple dc output ports for SMs of MMC. All input ports can be easily integrated (and controlled), and output ports also can be controlled independently in response to any load variations. An isolated active half-bridge converter with multiple secondaries acts as a central hub for power processing with multiple renewable energy resources that are integrated at the primary side. To verify the proposed converter, a detailed design of the converter-based system is presented along with the proposed control algorithm for managing power on the individual component level. Additionally, different modes of power management (emulating the availability/variability of renewable energy sources (RES)) are exhibited and analyzed here. Finally, detailed simulation results are presented in detail for the validation of the proposed concepts and design process.
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POPA, C. "Review of renewable energy sources and offshore wind turbine technology." Scientific Bulletin of Naval Academy XIV, no. 2 (December 15, 2021): 8–22. http://dx.doi.org/10.21279/1454-864x-21-i2-001.
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This paper is a state-of-the-art that aims to highlight all the new developments for wind renewable energy sources, wind turbine system, vertical axis wind turbine and the included components to find the best solution for an offshore vertical axis wind turbine that supplies ships with energy in the outer harbor. This review could help to understand the potential future choices in the design of vertical-axes wind turbine in order to reduce pollution in marine environment.
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Masompe, K. B., T. Madiba, T. S. Bungu, and F. T. Kadinda. "Smart Grid Method for the Lubumbashi Distribution Network Based on Provision of Renewable Energy Resources." Journal of Solar Energy Research Updates 9 (August 13, 2022): 16–26. http://dx.doi.org/10.31875/2410-2199.2022.09.03.
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Abstract: The development of smart grids (SG) in the electrical network is the subject of many studies nowadays. This new technology seems to be as an additional tool and the perfect solution which the D.R. Congo could use to achieve the objectives of the efficient management of electrical energy, electrical network security, and the inclusion of renewable energy sources. The rise of these new networks brings together many economic issues.
This study is essentially focused on the incapability of the National Electricity Company (SNEL) which still retains the monopoly of production and distribution of energy to individuals, industries and mining companies. The incorporation of a system of control and management of the two-ways energy flow between the sources of electricity production and users via an intelligent distribution network, considering several specific constraints and performance required, will allow us to highlight the influence of intelligence in a distribution network as complex as that of the city of Lubumbashi. This study reviews the challenges of renewable energies in the environment of the city of Lubumbashi, the modeling of the distribution network, the introduction of intelligence control in the network and simulation using computer tools to see the contribution of these results to the entire electrical system. Finally, the integration of new renewable energy sources associated with its monitoring system is planned to stabilize this network by increasing the efficiency of the system with 25 percent in power quality.
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Corlu, Canan G., Rocio de la Torre, Adrian Serrano-Hernandez, Angel A. Juan, and Javier Faulin. "Optimizing Energy Consumption in Transportation: Literature Review, Insights, and Research Opportunities." Energies 13, no. 5 (March 2, 2020): 1115. http://dx.doi.org/10.3390/en13051115.
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From airplanes to electric vehicles and trains, modern transportation systems require large quantities of energy. These vast amounts of energy have to be produced somewhere—ideally by using sustainable sources—and then brought to the transportation system. Energy is a scarce and costly resource, which cannot always be produced from renewable sources. Therefore, it is critical to consume energy as efficiently as possible, that is, transportation activities need to be carried out with an optimal intake of energetic means. This paper reviews existing work on the optimization of energy consumption in the area of transportation, including road freight, passenger rail, maritime, and air transportation modes. The paper also analyzes how optimization methods—of both exact and approximate nature—have been used to deal with these energy-optimization problems. Finally, it provides insights and discusses open research opportunities regarding the use of new intelligent algorithms—combining metaheuristics with simulation and machine learning—to improve the efficiency of energy consumption in transportation.
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Hu, Shubo, Feixiang Peng, Zhengnan Gao, Changqiang Ding, Hui Sun, and Wei Zhou. "Sample Entropy Based Net Load Tracing Dispatch of New Energy Power System." Energies 12, no. 1 (January 8, 2019): 193. http://dx.doi.org/10.3390/en12010193.
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The high-proportion of renewable energies is gradually becoming one of the main power supply sources and bringing strong uncertainties to the power grid. In this paper, a sample entropy (SampEn) based net load tracing dispatch strategy with a specific thermal generating mode is proposed. In this strategy, renewable energies are fully and preferentially consumed by electric loads, turned to net loads, to maximize the utilization of renewable energies. SampEn theory is utilized to evaluate the complexity of net load time series, based on which, the traditional power generators trace the complexity of the net load flexibly. According to the SampEn, a specific generating model of thermal generators is determined and the cooperation between thermal generators and pumped storage is realized, aiming at reducing the ramp power of thermal generators and increasing the throughput of pumped storage. The experiment simulation is developed on the 10-unit test system. Results show that the ramping power of the thermal generators are reduced 43% and 13% in the two cases together with the throughput of pumped storage is increased 44% and 27% on the premise that the economy of the system is maintained and renewable energies are fully consumed. Therefore, the efficiency and reasonability of the proposed dispatch strategy are confirmed.
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Csuka, Zoltán, Jozef Matušov, Peter Hlbočan, Zuzana Kolková, and Marta Murgašová. "Optimal Design of Battery Storage Systems for RES Using Simulation Methods." MATEC Web of Conferences 369 (2022): 01009. http://dx.doi.org/10.1051/matecconf/202236901009.
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The use of battery storage systems (BSS) is an increasingly common topic in the context of the operation of various types of renewable energy sources (RES). One of the applications may be to solve the problem of energy-free operation of small hydropower plants, where quite specific requirements are placed on the design of the BSS. In the context of optimal BSS design for a given application, this paper discusses the computer analysis capabilities that are essential in the design and performance verification phase of a BSS. The paper presents the possibilities of simulation methods in the field of electrical analysis of cell current load during charging and discharging processes, thermal analysis related to the selection of a suitable cooling system with respect to the operating mode of the battery system.
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Chen, Li, Jian Shen, Bin Zhou, Qingsong Wang, and Giuseppe Buja. "Quantitative Analysis on the Proportion of Renewable Energy Generation Based on Broadband Feature Extraction." Applied Sciences 12, no. 21 (November 3, 2022): 11159. http://dx.doi.org/10.3390/app122111159.
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With the massive access of distributed renewable energy sources, many uncertain renewable energy power components have been added to the low-voltage lines in substations in addition to the loads of definite classification. From the perspective of economy and cleanliness, it is necessary to quantitatively analyze the renewable energy share among them and improve the power quality level of users. For the power quality information at low-voltage feeders, this paper proposes a quantitative analysis algorithm based on improved wavelet energy entropy and LSTM neural network. The method is based on wavelet transform, based on sym8 wavelet basis function; it divides the long time sequence into equal-length small time sequences, calculates each feature component obtained from wavelet transform decomposition separately, then borrows the concept of information entropy to find its energy entropy. After obtaining the energy entropy sequence of each feature component, it then borrows the concept of kurtosis to weighted differentiation of each energy entropy sequence to highlight the feature information and finally, uses the LSTM neural network to classify the power quality information of different renewable energy sources to determine to which interval segment they belong. By building a simulation model to simulate the actual data in the field, the percentage of renewable energy can be quantitatively analyzed efficiently and accurately.
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Łukaszewski, Artur, Łukasz Nogal, and Marcin Januszewski. "The Application of the Modified Prim’s Algorithm to Restore the Power System Using Renewable Energy Sources." Symmetry 14, no. 5 (May 16, 2022): 1012. http://dx.doi.org/10.3390/sym14051012.
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The recent trends in the development of power systems are focused on the Self-Healing Grid technology fusing renewable energy sources. In the event of a failure of the power system, automated distribution grids should continue to supply energy to consumers. Unfortunately, there are currently a limited number of algorithms for rebuilding a power system with renewable energy sources. This problem is possible to solve by implementing restoration algorithms based on graph theory. This article presents the new modification of Prim’s algorithm, which has been adapted to operate on a power grid containing several power sources, including renewable energy sources. This solution is unique because Prim’s algorithm is ultimately dedicated to single-source graph topologies, while the proposed solution is adapted to multi-source topologies. In the algorithm, the power system is modeled by the adjacency matrices. The adjacency matrixes for the considered undirected graphs are symmetric. The novel logic is based on the original method of determining weights depending on active power, reactive power and active power losses. The developed solution was verified by performing a simulation on a test model of the distribution grid powered by a renewable energy source. The control logic concept was compared with the reference algorithms, which were chosen from the ideas representing available approaches based on graph theory present in the scientific publications. The conducted research confirmed the effectiveness and validity of the novel restoration strategy. The presented algorithm may be applied as a restoration logic dedicated to power distribution systems.
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Alvarez-Diazcomas, Alfredo, Héctor López, Roberto V. Carrillo-Serrano, Juvenal Rodríguez-Reséndiz, Nimrod Vázquez, and Gilberto Herrera-Ruiz. "A Novel Integrated Topology to Interface Electric Vehicles and Renewable Energies with the Grid." Energies 12, no. 21 (October 26, 2019): 4091. http://dx.doi.org/10.3390/en12214091.
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Electric Vehicles (EVs) are an alternative to internal combustion engine cars to reduce the environmental impact of transportation. It is common to use several power sources to achieve the requirements of the electric motor. A proper power converter and an accurate control strategy need to be utilized to take advantage of the characteristics of every source. In this paper is presented a novel topology of a multiple-input bidirectional DC-DC power converter to interface two or more sources of energy with different voltage levels. Furthermore, it can be used as a buck or a boost in any of the possible conversion of energy. It is also possible to independently control the extracted power in each source and any combination of the elements of the system can be used as source and destiny for a transfer. Finally, the interaction with the grid is possible. The operation, analysis and design of the converter are presented with different modes of power transfer. Simulation results are shown where the theoretical analysis of the converter is validated.
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Montoya, Oscar Danilo, Walter Gil-González, Luis Grisales-Noreña, César Orozco-Henao, and Federico Serra. "Economic Dispatch of BESS and Renewable Generators in DC Microgrids Using Voltage-Dependent Load Models." Energies 12, no. 23 (November 26, 2019): 4494. http://dx.doi.org/10.3390/en12234494.
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This paper addresses the optimal dispatch problem for battery energy storage systems (BESSs) in direct current (DC) mode for an operational period of 24 h. The problem is represented by a nonlinear programming (NLP) model that was formulated using an exponential voltage-dependent load model, which is the main contribution of this paper. An artificial neural network was employed for the short-term prediction of available renewable energy from wind and photovoltaic sources. The NLP model was solved by using the general algebraic modeling system (GAMS) to implement a 30-node test feeder composed of four renewable generators and three batteries. Simulation results demonstrate that the cost reduction for a daily operation is drastically affected by the operating conditions of the BESS, as well as the type of load model used.
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Magni, Chiara, Alessia Arteconi, Konstantinos Kavvadias, and Sylvain Quoilin. "Modelling the Integration of Residential Heat Demand and Demand Response in Power Systems with High Shares of Renewables." Energies 13, no. 24 (December 15, 2020): 6628. http://dx.doi.org/10.3390/en13246628.
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The EU aims to become the world’s first climate-neutral continent by 2050. In order to meet this target, the integration of high shares of Renewable Energy Sources (RESs) in the energy system is of primary importance. Nevertheless, the large deployment of variable renewable sources such as wind and photovoltaic power will pose important challenges in terms of power management. For this reason, increasing the system flexibility will be crucial to ensure the security of supply in future power systems. This work investigates the flexibility potential obtainable from the diffusion of Demand Response (DR) programmes applied to residential heating for different renewables penetration and power system configuration scenarios. To that end, a bottom-up model for residential heat demand and flexible electric heating systems (heat pumps and electric water heaters) is developed and directly integrated into Dispa-SET, an existing unit commitment optimal dispatch model of the power system. The integrated model is calibrated for the case of Belgium and different simulations are performed varying the penetration and type of residential heating technologies, installed renewables capacity and capacity mix. Results show that, at country level, operational cost could be reduced up to €35 million and curtailment up to 1 TWh per year with 1 million flexible electric heating systems installed. These benefits are significantly reduced when nuclear power plants (non-flexible) are replaced by gas-fired units (flexible) and grow when more renewable capacity is added. Moreover, when the number of flexible heating systems increases, a saturation effect of the flexibility is observed.
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Dosano, Rodel D., Nemia H. Mabaquiao, Godelyn Gallega-Hisole, Regin A. Cabacas, and In-Ho Ra. "A Novel Approach for Determining Distributed Generations Penetration Level Using Least Square Minimization (LSM) Curve Fitting." Journal of Advanced Computational Intelligence and Intelligent Informatics 20, no. 6 (November 20, 2016): 1004–12. http://dx.doi.org/10.20965/jaciii.2016.p1004.
Full textAbstract:
With the publicized benefits offered by renewable energy resources, more and more households embrace the utilization of stand-alone installations ranging from small to medium scale systems. In literature, several studies provide insights on the effects of integration of renewable energy (RE) resources to the distribution systems but have inadequacy of considering the penetration levels. Moreover, RE cost reductions, increasing costs of traditional energy sources, and Renewable Portfolio Standards have created the possibility of significant increase of penetration levels of distributed RE generation being installed on distribution systems. To aid in the evaluation and assist with these expansions, new analysis tools are needed. In particular, new RE high-penetration analysis tools and procedures need to be developed and integrated with existing conventional methods. This paper presents a simulation based study on distribution system with and without integration of RE sources. It takes into account of the impending effects of these RE integrations in the distribution system. This paper emphasizes a novel method of determining the penetration level of Distributed Generation using least square minimization (LSM) method. The studies were tested using IEEE 123 bus distribution test feeder and actual data from an existing distribution system to verify the effectiveness and robustness of the proposed approach.