Hybrid Renewable Energy Generation Research Articles

Optimization Model of Hybrid Renewable Energy Generation for Electric Bus Charging Stations

This paper introduces a comprehensive approach for sizing grid-connected hybrid renewable energy systems tailored for electric bus fleet operations. The study involves two main steps. First, a mathematical model that optimizes the configuration of such systems by considering daily electric bus consumption, solar irradiance, wind speed, and biomass potential is formulated. The model utilizes Pareto frontier multi-objective optimization to minimize the net present cost, the cost of energy, and greenhouse gas emissions. Second, the model is rigorously applied and tested in a real-world case study in Fez, Morocco, using HOMER Pro; the case study centers on the daily energy requirements of the buses, estimated at 2.5 megawatt hours per day, with a peak demand of 345 kilowatts. Two scenarios are explored, revealing a discernible trade-off dilemma between the full hybrid renewable energy scenario (Scenario 1) and the grid-connected hybrid renewable energy scenario (Scenario 2). In Scenario 2, the grid-connected hybrid renewable energy system demonstrates a notable 42.8% reduction in the net present cost, totaling USD 984,624. Similarly, the levelized cost of energy experiences a significant decrease, reaching approximately 0.08 USD/kWh, marking a 38.1% reduction. However, this apparent economic advantage is juxtaposed with a critical consideration—an increase in greenhouse gas emissions from null to 330,418 kg/year.

Optimal location selection for a distributed hybrid renewable energy system in rural Western Australia: A data mining approach

The adverse effects of coal and gas energy production with the subsequent rapid increase in energy consumption emphasize the importance for Australia to adopt more renewable energy sources to counteract these dismissive contributions to climate change. This work presents a data mining approach for optimally selecting the best locations for installing a distributed hybrid renewable energy generation system for rural regions in Western Australia. The K-Means and K-Medoids clustering algorithms were used to divide the constructed dataset into clusters. In total, 69 locations were selected for the overall dataset, proceeding with the filtering process. The returned cluster data were graphically rendered on a Western Australia map for the region. The clustering algorithms were evaluated using the Dunn index, such that K-Means performed to a higher degree than K-Medoids, given our dataset's nature. After passing the generated clusters to HOMER software to generate the potential wind and solar energy output for each centroid, K-Medoids produced a set of locations that generated higher solar and wind energy on average. However, due to the reduced internal validation, K-Medoids might not be as valuable as K-Means, it does not cluster the data points very well, and within-cluster location energy requirements are not considered in our study.

Spatial Decision-Making under Uncertainties for Supporting the Prospection of Sites for Hybrid Renewable Energy Generation Systems

This research aims at developing methodological tools for decision makers (DMs) to determine the locations for generating sites for hybrid renewable energy systems, considering complementarity characteristics of the corresponding sources and their seasonal availability. The decision process on new sites starts using Geographic Information Systems for modeling relevant spatial criteria. The problem solution is associated with using the Slide-OWA operator, which permits one to control the inter-criteria compensation levels by adjusting pessimism and optimism parameters. After constructing multicriteria estimates for generating sites, the general scheme of multi-objective decision-making is applied in conditions of uncertainty since these estimates are subject to significant levels of uncertainty. Such a scheme is based on the possibilistic approach, which involves the construction of payoff matrices. At this point, it is possible that some alternatives cannot be distinguished based only on the criteria considered so far, or the DM may want to evaluate the alternatives from the point of view of additional considerations. For this purpose, the framework of multi-attribute decision-making models is applied by employing methods for preference modeling in a fuzzy environment. The present work results are applied to a case study of the Minas Gerais State in Brazil. These results play a strategic role for governments and investors in their decisions while considering the ability to meet a wide range of criteria.

Simulation and harmonic analysis of hybrid distributed energy generation based microgrid system using intelligent technique

Wind and solar photovoltaic (PV) based hybrid renewable energy generation are environmentally friendly and reasonable. This study describes a hybrid distributed energy generations (DEGs)-based microgrid framework where DC-DC converter, three-stage inverter with fuzzy logics control (FLC), and LC filter channel are coupled with the PV and wind energy. In India, wind and PV energies are affordable for hybrid power frameworks since they are ecological well-disposed and broadly accessible. Generally, these sources produce a fluctuating yield voltage that prompts harm to the working grid on a steady inventory. The proposed model of the hybrid-based framework is executed utilizing MATLAB/Simulink. A boost converter being associated with PV cluster is associated with the basic DC bus also a battery is used by a two-way DC to DC converter, and connected into the utility framework by a typical DC to AC inverter. Wind cluster and PV is linked with maximum power point tracking (MPPT) to produce the higher capacity to the grid, and the charging and discharging of the battery energy can be done to adjust the energy between DEGs generation and utility network. In this paper, various cases of harmonic analysis are executed on MATLAB-simulation and feasibility of proposed grid models and FLC-based intelligent control.

Promoting developments of hydrogen production from renewable energy and hydrogen energy vehicles in China analyzing a public-private partnership cooperation scheme based on evolutionary game theory

A tripartite evolutionary game model is put forward in this study, which represents the partnership among investment companies (IC), hybrid renewable energy generation system (HREGS) and hydrogen energy vehicle users (HEVU). Aims to determine whether the three parties are willing to participate in different scenarios and find out relevant optimal behaviors to further promote the development of renewable energy hydrogen production and hydrogen vehicles. HRES cooperation needs to meet the requirements that the direct normal irradiance (DNI) is greater than 1615 W/m2, the wind speed is greater than 4.5 m/s, the annual working time is greater than 1800 h, the government subsidy is greater than $152000, and the profit distribution ratio is greater than 0.34. IC cooperation needs to meet the requirements of DNI greater than 1425 W/m2, wind speed greater than 6 m/s, annual working time greater than 1950 h, government subsidy greater than $549000, and profit distribution ratio less than 0.48. HEU cooperation needs to meet the requirements that the government subsidy is more than $29300 and the hydrogenation operation risk cost is less than $2000. This study may provide a reference for renewable energy hydrogen production industry, hydrogen vehicle industry and governments making relevant policies.

Optimal hybrid renewable energy generation planning based on BSG-starcraft radius particle swarm optimization

Optimal hybrid renewable energy generation planning based on BSG-starcraft radius particle swarm optimization

Energy Management and Power Quality Improvement of Hybrid Renewable Energy Generation System Using Coordinated Control Scheme

Energy Management and Power Quality Improvement of Hybrid Renewable Energy Generation System Using Coordinated Control Scheme

Generation of Hybrid Energy System (Solar-Wind) Supported with Battery Energy Storage

Abstract: The utilization of renewable energy is significantly important for the world because global energy consumption is increasing, while conventional energy sources are no longer sufficient to meet the energy demand, triggering energy crises. In recent years, the increasing prices of fossil fuels and concerns about the environmental consequences of greenhouse gas emissions have renewed the interest in the development of alternative energy resources. Renewable energy is now considered a more desirable source of fuel than nuclear power due to the absence of risk and disasters [1]. Considering that the major component of greenhouse gases is carbon dioxide, there is a global concern about reducing carbon emissions. In this regard, different policies could be applied to reducing carbon emissions, such as enhancing renewable energy deployment and encouraging technological innovations. There are various of renewable energy sources such as Solar, biomass, wind, hydrogen, fuel cell, nanocomposite, and supercapacitor. Each of the energy sources are suitable for specific geographical locations and can suits from region to region. However, variation in solar radiation and wind speed caused by climate and weather conditions restricts the stable operation of renewable energy systems, therefore, causing the output to fluctuate. A hybrid renewable energy generation system can be highly efficient by combining multiple renewable energy sources and is regarded as a promising solution to overcome from this issue. Hybrid solar systems are the systems combining two renewable sources of energy, like solar and wind. Then, energy is generated through solar on sunny days and when there is limited sunshine but there is wind, energy can be generated through it. The study aims to focus on generation of hybrid solar-wind power plant with the optimal contribution of renewable energy resources supported by battery energy storage technology. The motivating factor behind the hybrid solar–wind power system design is the fact that both solar and wind power exhibit complementary power profiles. Advantageous combination of solar and wind with optimal ratio will lead to clear benefits for hybrid solar-wind power plants such as smoothing of intermittent power, higher reliability, and availability. However, the potential challenges for its integration into power grids cannot be neglected. A potential solution is to utilise one of the energy storage technologies, though all of them are still very expensive for such applications, especially at large scale. Therefore, optimal capacity calculations for energy storage system are also vital to realise full benefits. Currently, battery energy storage technology is considered as one of the most promising choices for renewable power applications. However, solar-wind power technology are most suitable for off-grid services, serving the remote are without having to build or extend expensive and complicated grid infrastructure. Therefor standalone system using renewable energy sources have become a preferred option. Hence hybrid energy systems are an ideal solution since they can offer substantial improvements in performance and cost reduction and can be tailored to varying end user requirements

A hybrid control topology for cascaded multilevel inverter with hybrid renewable energy generation subsystem

In this paper, a hybrid control topology is proposed for cascaded multilevel inverter (CMLI) with a grid-connected hybrid system involves wind and photovoltaic generation subsystem. The proposed hybrid control technique is the joint execution of Reptile Search Algorithm (RSA) and Gradient Boosting Decision Tree (GBDT) algorithm thus it is called RSA-GBDT approach. The purpose of proposed approach is to achieve load power demand and manage power regulation. Initially, the Cascade Multilevel Inverter (CMLI) is designed to obtain optimal control signal through proposed controller. The proposed control technique is utilized in two phases of the proposed system. In the first phase, RSA is used to evaluate the optimal gain parameters considering the range of source currents is also utilized to generate the optimal offline control signal data set. According to data set, in the second phase, the GBDT works and forecasts the most optimal control signals from the online CMLI. Finally, the resulting control signal is used to control CMLI's Insulated Gate Bipolar Transistor (IGBT). The proposed RSA-GBDT technique develops the operation mode for solar and wind generation system discovers the switching states of converter. The proposed control system minimizes the variation of system parameters and external disturbances. Also, the load demand is achieved and the proposed RSA-GBDT control approach is executed on MATLAB/Simulink platform and performance is analyzed.

Exploration on the feasibility of hybrid renewable energy generation in resource-based areas of China: Case study of a regeneration city

In order to explore the feasibility of hybrid renewable energy generation in resource-based areas in China, this paper takes a regeneration city as an example. The technical, economic, and environmental optimization design of the hybrid energy systems for the considered tiny village in Nanyang of Henan province are carried out using HOMER Pro software. The study demonstrates the multi-year and single-year modules of the HOMER Pro software with the advanced storage module. The load following (LF), cyclic charging (CC), and combined dispatch (CD) strategies are adopted in this study. The results indicate that the optimal photovoltaic (PV)-wind turbine (WT)-diesel generator (DG)-battery system under the CD strategy, consisting of 250 kW PV arrays, a WT, a 360 kW DG, 10 battery units, and a 150 kW converter, is the most economically viable with a total net present cost (NPC) of $1,795,558 and cost of energy of $0.378/kWh. The present worth is $5,827,278, which is the difference between the NPC of the DG system and the PV-WT-DG-battery hybrid system. From the perspective of economic and environmental, the PV-WT-battery system is the best among the studied systems. Moreover, the annual CO2 emissions of the optimal PV-WT-DG-battery system as a proposed system is 71,988 kg/year. The optimal PV-WT-DG-battery system reduces CO2 emissions by 89.4% per year compared with DG-only system. The amounts of CO2 emissions emitted from the PV-WT-DG-battery system increase with the number of years, while the renewable fraction values decrease with the number of years.

Hybrid renewable energy generation planning for isolated microgrid in Indonesia with metaheuristic approach

Wydawnictwo SIGMA-NOT wydaje czasopisma fachowe informujące swoich czytelników o najnowszych osiągnięciach naukowych i nowoczesnych rozwiązaniach technicznych w Polsce i na świecie, popularyzuje problemy techniczne oraz poszerza wiedzę i kulturę techniczną.

Development of Rose Model for Hybrid Renewable Energy Generation and Analysis of Carbon Foot Printing QOS Parameters

The risk presented by world-wide weather transformation is known and so the government panel about weather transformation prompts that guidelines need to be consider limiting world-wide median temperature boost. I expect effective strategies meant for the statistic and administration of GHG exhausts for aim for positioning and determining the accomplishment of climate change minimization activities. ‘Carbon footprints’ are progressively being acknowledged as an important signal in the arena of GHG and carbon exhausts supervision. During COVID-19 pandemic the GHG percentage dropped considerably for a moment worldwide, but there is an immense need of lowering carbon foot printing with development of new hybrid renewable energy sources. This paper presents the innovative development in the same direction by development of rose model for automation of energy plants to reach its installed capacity with identification of MPPT along with optimum ratio of demand-supply. Paper also presents the analysis of proposed developments.

Small-Scale Solar–Bio-Hybrid Power Generation Using Brayton and Rankine Cycles

This study conducted a detailed technical analysis of small-scale solar–bio-hybrid power generation systems using Rankine (steam turbine) and Brayton (gas turbine) cycles. Thermodynamic models were developed to characterize the state of working fluid and select the most suitable solar collection technology for individual power generation systems. Net capacity factor of power generation and utilization efficiencies of solar and biogas energy were used as parameters to evaluate energy generation and conclude the preferred system configuration. The analysis concluded that the steam turbine system has better global efficiency (67.7%) than the gas turbine system (55.7%), while the gas turbine system has better electricity generation efficiency (27.0%) than that (5.6%) of the steam turbine system. The effects of different climates on the selection of suitable hybrid systems were also investigated to delineate suitability and feasibility of different hybrid systems. In addition, the method used in this study can also be applied to investigate and optimize other small-scale hybrid renewable energy generation systems.

Research of virtual impedance layering and distributing control strategy of hybrid renewable energy microgrid

Micro-grid technology will combine hybrid renewable energy and power generation technology, clean and environmental protection, improve the utilization of renewable energy; the use of distributed generation units installed in the local characteristics of the governor from the transmission loss and cost. This paper introduced the virtual impedance into the traditional droop control, make the output impedance and line impedance of the inverter are mainly inductive, so the droop control algorithm is implemented. This paper presented a new method based on the virtual impedance to adjust the frequency and voltage of the micro-grid bus two times, to realize the two adjustment of the frequency and voltage of the micro grid. In addition, for the micro-grid power network interaction, based on PQ closed loop control method is proposed to response to the dispatching command. The simulation results show high performance of the designed control strategy.

Utilização da lógica fuzzy aplicada à energia solar

A lógica fuzzy é uma metodologia para expor dados imprecisos e qualitativos, comuns na comunicação humana, em uma sequência e forma compreensíveis pelos computadores. Esses sistemas são ferramentas poderosas, que possibilitam a expressão de conceitos que não sejam bem definidos, nos quais usualmente é empregado um nome ou adjetivo para descrevê-los. Este trabalho pretende melhorar os modelos matemáticos para as fontes renováveis de energia, por meio da utilização da teoria fuzzy. Portanto, foi realizada a modelagem de um controlador fuzzy atuando no sistema híbrido de geração de energias renováveis, com o intuito de se obter maior eficiência do sistema híbrido solar-eólico. O trabalho utilizou dados de estações meteorológicas para o desenvolvimento de simulações do sistema. Para o desenvolvimento do controlador, foi utilizado o software Matlab® no módulo Fuzzy Logic ToolBoxTM, onde foi elaborada toda a teoria fuzzy e aplicada às simulações com o controlador, tendo por objetivo melhorias na eficiência do banco de baterias do sistema.

Comparative Performance of a Hybrid Renewable Energy Generation System with Dynamic Load Demand

This article presents the modeling and simulation of a hybrid generation system, which uses solar energy generation, wind energy, and the regulation of a proton exchange membrane (PEM) cell to raise the demanded load, empowering the use of these hydride systems worldwide. This generation system was simulated for different locations in Puerto Bolivar (Colombia), Bremen (Germany), Beijing (China), and Texas (USA), for two demand profiles. The data used for the simulation was calculated using the mathematical solar model proposed by Beistow and Campbell for solar radiation. In contrast, for the wind resource evaluation, the Weibull probability distribution was used to calculate the most probable wind speed for each day, according to the historical data for each of the studied locations. Considering these data, the process transfer functions were used for tuning the control parameters for the hydrogen and oxygen production system. For the evaluation of the performance of these controllers, the indices of the absolute value of the error (IAE), the integral of the square of the error (ISE), the integral of the absolute value of the error for time (ITAE), and the integral of the square of the error for time (ITSE) were used. It was found that in the second load profile studied, better performance of the ITSE performance parameter was obtained, with stabilization times lower than those of the first profile.

Energy, Economic, and Environmental Evaluation of a Proposed Solar-Wind Power On-grid System Using HOMER Pro®: A Case Study in Colombia

The electrical sector in the Caribbean region of Colombia is currently facing problems that affect its reliability. Many thermo-electric plants are required to fill the gap and ensure energy supply. This paper thus proposes a hybrid renewable energy generation plant that could supply a percentage of the total energy demand and reduce the environmental impact of conventional energy generation. The hybrid plant works with a photovoltaic (PV) system and wind turbine systems, connected in parallel with the grid to supply a renewable fraction of the total energy demand. The investigation was conducted in three steps: the first stage determined locations where the energy system was able to take advantage of renewable sources, the second identified a location that could work more efficiently from an economic perspective, and finally, the third step estimated the number of PV solar panels and wind turbines required to guarantee optimal functioning for this location using, as a main method of calculation, the software HOMER pro® for hybrid optimization with multiple energy resources. The proposed system is expected to not only limit environmental impacts but also decrease total costs of electric grid consumption from thermoelectric plants. The simulations helped identify Puerto Bolivar, Colombia, as the location where the hybrid plant made the best use of non-conventional resources of energy. However, Rancho Grande was found to offer the system more efficiency, while generating a considerable amount of energy at the lowest possible cost. An optimal combination was also obtained—441 PV arrays and 3 wind turbines, resulting in a net present cost (NPC) of $11.8 million and low CO2 production of 244.1 tons per year.

An Efficient Reactive Power Dispatch Method for Hybrid Photovoltaic and Superconducting Magnetic Energy Storage Inverters in Utility Grids

The intermittent property and increased grid restrictions have become the most critical elements for increasing penetration levels of clean renewable energy sources (RESs). Smart inverters with combined RESs integration and reactive power support for utility grids have recently found widespread applications due to their techno-economic benefits. In smart inverters, the distribution-static compensator (DSTATCOM) functionality is inherently integrated to the RESs inverters. However, optimized reactive power-sharing between these inverters has become a big issue for the control systems of utility grids. There are numerous existing attempts presented in the literature for addressing these challenges, although they disadvantage low efficiency, uneven sharing, complex implementations, and/or costly added devices. Therefore, this paper proposes an efficient reactive power dispatch method between hybrid renewable energy generation and energy storage systems. The proposed method enhances the energy efficiency of the utility grid by adopting the reactive power share between interfacing inverters according to the estimated power losses. Besides, the proposed method enhances the reliability of smart inverters by relieving their thermal stresses through adopting their reactive power share according to the estimated power losses. The hybrid photovoltaic (PV) generation with superconducting magnetic energy storage (SMES) systems is selected as a case study for validating the new proposed reactive power dispatch method. The results, comprehensive discussions, and performance comparisons have verified the superior performance of the new proposed reactive power dispatch method.

Potential Analysis of Hybrid Renewable Energy Systems for Self-Sufficient Residential Use in Germany and the Czech Republic

Independence from the power grid can be pursued by achieving total self-sufficient electricity supply. Such an energy supply model might be particularly interesting for settlements located in rural areas where enough space is available for energy generation installations. This article evaluates how and at what cost electricity demand of residential users across Germany and the Czech Republic could be covered by hybrid renewable energy generation systems consisting of photovoltaics, micro-generation wind turbines and batteries. High-resolution reanalysis data are used to calculate necessary system sizes over a large area by simultaneously accounting for the temporal variability of renewable energy. For every potential location in the research area, the hybrid system requirements for clusters of 50 self-sufficient single-family houses are calculated. The results indicate no general trend regarding the size of the respective technologies, although larger areas where PV-wind power complementarity enables lowering the total system costs and required storage capacities were determined. Assuming that the cluster of households could be constituted and depending on the location, the total installation and operation costs for the proposed systems for a lifetime of 20 years range between EUR 1.8 Million and EUR 5 Million without considering costs of financing. Regions with the lowest costs were identified mainly in the south of Germany.

Battery Charge Management for Hybrid PV/Wind/Fuel Cell with Storage Battery

Hybrid renewable electric energy generation system become essential to the most of electric networks and the stand-alone systems like the water pumping and telecommunication systems. The renewable sources usually required storage system due to change in the power outputs during the day. Due to increase in demand of using batteries, the charging process of battery system needed to be well managed through an adaptive controlled energy managing system. In this paper a standalone system using photovoltaic, wind generation, fuel cell and storage batteries are contributed in supplying the desired load and the charging balance of batteries is achieved by using AI techniques to enhance battery charging controller performance. The main goal of this paper is to design and implement an integrated smart artificial controller, this controller is responsible for controlling both the battery charge voltage using the boost converter and the other controller is to control the charging current of the battery through DC to DC converter using (ANFIS) and (GA) techniques. This study is implemented using MATLAB /Simulink and the results are presented to show the applicability and effieciency of the proposed technique.