Hybrid Renewable Energy System Research Articles

Conceptual hybrid energy model for different power potential scales: Technical and economic approaches

This research attempts to address the gap between the theoretical fundamentals of hybrid renewable energy systems and their practical implementation at different scales through a new Conceptual Hybrid Energy Model (COHYBEM). The main objective was to develop a multi-variable model to allow a new complete and comprehensive techno-economic analysis of the performance of possible hybrid renewable power systems at different scales. The purpose is to evaluate the influence of critical parameters by changing key parameters in the developed model and identifying their impacts. It covers big data analyses, simulation and optimization of hybrid energy solutions, combining wind, solar and hydropower energy sources with the energy storage technology of pump hydropower storage. The research also denoted the Pareto front with the increasing power installed, for the maximum efficiency and total satisfied demand by Wind + PVSolar and by Hydro converges to a higher percentage, while a minimum waste by Wind + PVSolar is also progressing towards the increasing scales. In terms of investment costs for the 243 analyzed case studies, it varies between 45 k€ to 2.1 M€, resulting in a net present value (NPV) between 18 and 600 k€ and a payback period around 6–17 years depending on the power scale analyzed.

Optimization of Solar PV System Efficiency in Bangladesh

This paper presents a comprehensive review and analysis of Sarishabari Engreen Solar Plant Ltd., a 3.3 MW grid-connected solar photovoltaic (PV) system located in Sarishabari, Jamalpur, Bangladesh. The study evaluates the plant's economic and operational performance, revealing a competitive payback period of 10.1 years and a levelized cost of energy (LCOE) of 0.11 USD/kWh. These metrics highlight the plant's financial viability, largely due to the low cost of public land used for construction. However, profitability may be challenged if similar projects require significant investments in private land acquisition. Key areas for improvement identified include optimizing the tilt angle and integrating smart automation systems. Additionally, the potential for hybrid renewable energy systems combining solar and wind power is discussed. The paper also provides actionable recommendations for future renewable projects, emphasizing the importance of advanced technologies, and supportive policies. These insights aim to inform the optimization of existing solar PV systems and guide the development of future renewable energy projects in Bangladesh, contributing to the country's sustainable energy goals.

Synergetic UPQC Application for Power Quality Enhancement in Microgrid Distribution System: SCSO Approach

Nowadays, Hybrid renewable energy systems (HRES) are increasingly being integrated into grid-connected load systems to lower losses and boost dependability. When the HRES system is connected to the grid system to satisfy needed load demand, power quality issues arise because of imbalanced load circumstances, non-linear load, and critical load. So this manuscript proposed a synergetic Unified Power Quality Conditioner (UPQC) application for power quality enhancement in microgrid distribution systems. The Sand Cat Swarm Optimization (SCSO) technique is based on the proposed sand cat swarm optimization method. The proposed strategy's primary goal is to regulate power flow, minimize harmonic distortion in both voltage and current waveforms, and maximize UPQC. By then, the proposed method's performance has been implemented into practice on the MATLAB platform and contrasted with several currently used techniques. The proposed technique displays the low Total Harmonic Distortion (THD) and operation time in all existing approaches like Moth Flame Optimization (MFO), Genetic Algorithm (GA), Salp Swarm Algorithm (SSA), Ant Lion Optimizer (ALO), Improved Bat Search Algorithm (IBSA), Lion Algorithm (LA), Artificial Bee Colony (ABC), Atom Search Optimization (ASO) and Crow Search Algorithm (CSA). The proposed method attains THD as before UPQC is 31%, after UPQC is 3%, load current is 1.42%, and load voltage is 2%. It also achieves a low operation time of 506ms and a low settling time of 0.15s compared to the existing methods. The significant improvement in power quality metrics demonstrates the effectiveness of the proposed SCSO technique.

A Methodological Framework for the development of a hybrid renewable energy system with seawater Pumped storage Hydropower system under uncertainty in Karystos, Greece

The need to minimize energy reliance and its repercussions and accretivewater scarcity necessitates research into renewable energy resources. Hybrid renewable energy systems are an apparent solution for areas and countries like Greece, especially when combined with seawater-pumped storage hydropower systems, where wind potential and topography foster such approaches. Moreover, it is essential to understand the uncertainty of the involved natural processes and incorporate their stochasticity in these hybrid systems, moving towards a more realistic approach. This system is simulated under uncertainty and has a total capacity of 31.5 MW and aims to cover the water and energy needs of Karystos, combining 9 wind turbines of 3.5 MW each, a desalination plant of 9,600 m3/day, a desalinated water tank with a capacity of 100,000 m3, a 9 MW pumping station, and a seawater pumped storage hydropower system with a 1.7 hm3 storage tank. Some promising results of this system under study are 99 % reliability for drinking water needs and 63 % and 85 % for irrigation and energy needs respectively, with the wind park contributing 54.4 % and the hydropower system 31.3 %.

Design and Control of Four-Port Non-Isolated SEPIC Converter for Hybrid Renewable Energy Systems

Design and Control of Four-Port Non-Isolated SEPIC Converter for Hybrid Renewable Energy Systems

Multi-objective optimal sizing and techno-economic analysis of on- and off-grid hybrid renewable energy systems for EV charging stations

Integrating electric vehicle charging stations (EVCSs) with renewable energy systems requires the consideration of several factors during the planning stage, including environmental impact, economic viability, grid reliability, and self-sufficiency. Therefore, this study conducts a multi-objective optimal sizing of on- and off-grid hybrid renewable energy systems for EVCSs. The sizing problem is solved using the Non-dominated Sorting Genetic Algorithm (NSGA-II). Subsequently, the best suitable solutions from the obtained non-dominated solutions are selected using the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) method, prioritizing the objective functions based on diverse interests of different stakeholders (large and small private investors and governmental entities). Finally, a techno-economic analysis is made considering payback period, profitability index (PI), and internal rate of return (IRR). The results show that on-grid systems show high economic viability with payback periods between 1.98 and 7.72 years, an average PI of 5.07 and an average IRR of 23.97%. Although off-grid systems present lower economic viability with payback periods between 8.77 and 22.42 years, an average PI of 1.68 and an average IRR of 4.91%, in certain cases they reach investable levels with payback periods below 10 years, PI above 2, and IRR above the interest rate.

Performance evaluation of sustainable energy alternatives to obtain efficient hybrid energy investments

This study evaluates the synergy of coalition for hybrid renewable energy (RWB) system alternatives. In this context, the alternative sources of hybrid RWB system are examined to illustrate the impact-relation directions among them with multi SWARA based on q-ROFs and golden cut. Next, the performances of renewable alternatives are measured in terms of the synergy of coalition with game theory and Shapley value. It is concluded that solar energy is the most suitable RWB alternative for synergy to increase efficiency in investments. However, biomass does not have a significant influence on providing synergy in energy investments. Therefore, solar energy should be prioritized for hybrid energy investments. Especially with the effect of technological developments, the efficiency of solar energy investments increases significantly. Thus, solar energy investments have become quite suitable for increasing the synergy in hybrid energy projects. Furthermore, necessary research should be conducted to make biomass energy more efficient.

Multi-objective optimisation of hybrid renewable energy systems for Colombian non-interconnected zones

Colombia’s Atlantic coast wind and solar resources could enhance energy mix and self-generation. Renewable clean energy has been studied in response to fossil fuel pollution. Wind and solar photovoltaic systems have low initial, operational, and levelized energy costs. Variable wind and sun radiation may limit availability. In this regard, hybrid renewable energy systems (HRES) and energy storage have become crucial. These systems can effectively meet load demand by utilising complementary renewable resources. This study deals with sizing a wind and photovoltaic HRES with storage, using a Particle Swarm Optimisation algorithm for yearly variable resources in a non-interconnected zone in La Guajira, Colombia. The study evaluates the LCOE, probability of load loss, and the system’s CO2 emission. It develops a sensitivity analysis to determine the importance of each objective factor. From a life cycle analysis, an HRES configuration with low LCOE and environmental emission rates is associated with the size of the wind resource; the HRES configuration with minimum LCOE values is close to obtaining higher equivalent CO2e emissions. The study highlights the configuration obtained for the Colombian context, giving more importance to the environmental factor and reaching an LCOE of 0.754 USD/kWh and emission of 18.97 tCO2e/year; this configuration also increases the wind energy generation, reaching 41 % more share, compared to the configuration obtained when the economic factor is a priority.

Numerical study of a hybrid system of solar panels, a diesel generator, and a wind turbine using a battery system

This paper gives an overall quantitative analysis of a hybrid renewable energy system (HRES) incorporating solar photovoltaic system, wind system, diesel generator and battery storage system. The system is aimed at coordination the management of the energy resources for providing the off-grid or remote facilities. The best intervention is thus to increase the consumption of renewable energy sources to minimize the reliance on diesel generators. The findings show that the hybrid system is capable of supplying different levels of power, which is pumped from the solar PV panels at maximum of 30.38 kW for the photovoltaic system at maximum solar intensity, and the wind power system to a maximum of 3213 kW of power generation under standard wind potential. The diesel generator serves a backup power source, which ranges from 91.24 kW and 864 at a rate of 250 kW during high activity and 5 kW during high-demand periods. Battery storage integration has a crucial part in matching the short-term supply-demand imbalance problem. The study suggests that the hybrid system reduces diesel use, emissions, and improves energy sustainability making the system a worthy proposition for remote areas. The findings therefore affirm the use of hybrid systems in off grid electrification since they operate economically and are eco-friendly.

Optimization of a hybrid renewable energy system for off-grid residential communities using numerical simulation, response surface methodology, and life cycle assessment

This paper presents an optimized hybrid renewable energy system tailored for off-grid residential communities, integrating wind, solar, and hydrogen technologies to meet electricity, cooling, heating, and water needs. The proposed optimization methodology combines numerical simulation, response surface methodology (RSM), and life cycle assessment (LCA), ensuring robust performance across diverse conditions. Key components include fuel cells, reverse osmosis systems, heat pumps, photovoltaic/thermal solar collectors, wind turbines, and hydrogen generation systems. The optimization process targets critical variables such as PVT panel area, the number of wind turbines, and fuel cell power. The optimal configuration was found to include 24 small-scale wind turbines, 159.46 m2 of PVT collectors, and 79.73 kW of fuel cell power. This configuration generated surplus electricity with net electricity usage (NEU) values of −123084.27 kWh/year in New York, −224245.29 kWh/year in Forks, and −215949.30 kWh/year in Santa Barbara. Additionally, the optimized systems achieved a significant reduction in life cycle cost (LCC), with Forks showing the lowest LCC at 304428.97 USD. The environmental impact was also minimized using the novel optimization approach, with the optimized systems achieving negative 100-year global warming potential (GWP100) values, indicating a net reduction in greenhouse gas emissions.

Techno-economic and environmental analysis of biogas-based hybrid renewable energy systems: A case study for a small-scale livestock farm

Biogas technology offers a significant benefit in enabling energy generation from distributed sources of biomass through its easy scalability. This study aimed to conduct the technical, economic, and environmental analysis of biogas-based hybrid renewable energy systems in a small-scale livestock farm located in the rural area of the Central Anatolia region in Türkiye. The HOMER software was used to analyze a total of five scenarios. These scenarios are hybrid combinations of a biogas generator, PV panels and wind turbines. The hybrid scenarios were evaluated by comparing them to each other and to the base scenario, which only has a grid connection. The optimal system has been determined to be the grid-connected Biogas/PV panel hybrid configuration, with an energy cost of 0.0688 $/kWh and a net present cost of $70,777. The optimal system has a renewable fraction of 89.9 % and a CO2 emissions mitigation potential of 13,066 kg/year compared to the base scenario. Furthermore, sensitivity analysis for various input parameters such as grid sellback rate, interest rate and load demand was performed to assess the impact of changes in these parameters on the system. Sensitivity analysis results show that increased grid sellback rates can significantly enhance financial metrics and reduce the payback period from 13.13 years to 6.63 years.

A Photovoltaic and Wind-Powered Electric Vehicle with a Charge Equalizer

This research aims at proposing an alternative to improve the efficiency of electric vehicles (EVs) and reduce greenhouse gas (GHG) emissions in the context of electric mobility. A photovoltaic and wind hybrid energy system was installed in a Chok S2 electric vehicle. In addition, a charge equalization system was included to balance and maximize the performance of each of the EV’s five batteries connected in series. The results show a 20% improvement in vehicle efficiency after conducting tests on a 17 km Andean route. The photovoltaic system generated 535 W, while the wind system generated 135 W/s at a speed of 45 km/h. These findings highlight the potential of hybrid renewable energy systems to improve the efficiency and range of electric vehicles.

Multi-objective optimization of a photovoltaic/wind/diesel pumping system with water tank in the Adrar region

Irrigating the remote regions of southern Algeria, which generally use diesel generators, with clean, environmentally-friendly energy is a challenge. Taking into account the solar and wind potential of the Adrar region, a renewable system using both sources seems more cost-effective. The realization of hybrid renewable energy systems takes into account several technical, economic and environmental aspects. This study consists in finding an efficient and adequate energy supply for the irrigation of one hectare of date palm in the Adrar region. It proposes a mathematical modelling for the given problem in different possible models, for this, we used the basic concepts of multi-objective optimization (bi-objective), and the adaptation of the concept of genetic algorithms to find solutions. The theoretical foundations discussed in this research have enabled us to design and implement a software that optimizes the hybrid pumping system used for the irrigation of date palms by minimizing the total cost and reducing CO2 emissions produced by the diesel group.

Economic assessment of efficient hydrogen production-based hybrid renewable energy system: OOA-RBFNN approach

Economic assessment of efficient hydrogen production-based hybrid renewable energy system: OOA-RBFNN approach

CRITIC-TOPSIS Method

The increasing demand for electricity has driven the development of hybrid renewable energy systems (HRES) in developing countries and remote areas. HRES combines various renewable energy sources to overcome the limitations of each source by utilizing their respective strengths. Although HRES has advantages such as flexibility and low pollution, the development of renewable energy needs to consider environmental impacts and principles of sustainable development. This study aims to find the optimal configuration of a hybrid renewable energy system in the new capital region of Indonesia, namely IKN Nusantara in East Kalimantan province. We conducted a geospatial approach and literature review to gather relevant information, such as solar radiation data, hydropower potential, and biomass potential. We utilized the hybrid optimization model for electric renewables (HOMER) software to design the HRES, and we optimized the results using the multi-criteria decision-making (MCDM) method. The experimental results show that the combination of PV and hydro is the optimal configuration in terms of energy and environmental aspects, with a relative closeness value of 0.675 compared to the ideal solution. Therefore, the implementation of MCDM to evaluate and determine the best configuration of HRES in the IKN Nusantara region is worth considering for further research and development.

Techno-economic analysis of a hybrid energy system for electrification using an off-grid solar/biogas/battery system employing HOMER: A case study in Vietnam

The electrification of off-grid /island villages is a critical step towards improving the techno-economic circumstances of rural regions and the overall general growth of the country. However, consistent supply from a single source is not possible in these areas. Thus, a hybrid renewable energy system performs better in these conditions. The research challenge now is to identify the optimal combinations of HRES from the available resources in a specific village site that can supply the power demand sustainably and to determine whether this is a cost-effective option. The present work is an endeavour to develop a sustainable and dynamic energy demand-supply model using HOMER Pro energy software in a specified off-grid rural site in Vietnam. The research presents four unique configurations of a combined energy system for Vietnam's island settlements, incorporating biomass-based biogas facilities, photovoltaic panels, lithium-ion batteries, and converters. Homer Pro was used for optimization and design, focusing on key performance measures such as cost of energy, net present cost, initial cost, operating cost, renewable fraction, and carbon emissions. The best HES system layout includes a 100-kW biomass-based generator, 2.62 kW photovoltaic installation, 10 lithium-ion batteries, and a 6.31 kW converter, producing 100 % renewable energy. The system's low cost of energy ($0.48), and net present cost ($25,730.89) make it an economically viable alternative, while its low CO2 emissions demonstrate its commitment to reducing greenhouse gas emissions.

Use of Triboelectric Nanogenerators in Advanced Hybrid Renewable Energy Systems for High Efficiency in Sustainable Energy Production: A Review

Renewable energy is the best choice for clean and sustainable energy development. A single renewable energy system reveals an intermittent disadvantage during the energy production process due to the effects of weather, season, day/night, and working environment. A generally hybrid renewable energy system (HRES) is an energy production scheme that is built based on a combination of two or more single renewable energy sources (such as solar energy, wind power, hydropower, thermal energy, and ocean energy) to produce electrical energy for energy consumption, energy storage, or a power transmission line. HRESs feature the outstanding characteristics of enhancing energy conversion efficiency and reducing fluctuations during the energy production process. Triboelectric nanogenerator (TENG) technology transduces wasted mechanical energies into electrical energy. The TENG can harvest renewable energy sources (such as wind, water flow, and ocean energy) into electricity with a sustainable working ability that can be integrated into an HRES for high power efficiency in sustainable renewable energy production. This article reviews the recent techniques and methods using HRESs and triboelectric nanogenerators (TENGs) in advanced hybrid renewable energy systems for improvements in the efficiency of harvesting energy, sustainable energy production, and practical applications. The paper mentions the benefits, challenges, and specific solutions related to the development and utilization of HRESs. The results show that the TENG is a highly potential power source for harvesting energy, renewable energy integration, application, and sustainable energy development. The results are a useful reference source for developing HRES models for practical applications and robust development in the near future.

Integrating hydrogen into a hybrid system to meet a laboratory's electricity demand

Providing quality electricity to improve the living conditions of rural and urban populations in Africa, particularly in Cameroon, represents a challenging but achievable task. Indeed, Cameroon has the second largest hydrographic network in Central Africa, and thanks to this network, over 90% of electricity comes from aging hydroelectric dams that cause permanent power outages. The desire to take advantage of other benefits that nature has given this country has directed this work towards renewable energies. Thanks to the HOMER Pro software, a renewable energy hybrid system with hydrogen gas serving as storage and energy vector was adopted. Photovoltaic panels and wind turbines are proposed as primary energy sources for the permanent, low-cost supply of the IRAD laboratory at the University of Maroua. The software proposes three systems, one with the wind turbine as the only primary source, and considered as the most optimal. It has an energy cost equal to $0.0633, an NPC of $20330, and an initial capital of $8500. The other two systems are hybrids with a renewable fraction equal to 100%, and a load distribution strategy that is the charge cycle (CC) like the first system. The first less expensive hybrid system has an energy cost and an NPC respectively of $0.0778 and $24986. As for the second hybrid system, it has an NPC and an energy cost respectively of $26195 and $0.0778. Hydrogen fully plays its role as an energy vector and storage in all three systems. A sensitivity analysis was conducted in this work to ensure that the system proposed for the laboratory can also be adapted in the 9 other regions of the country. It appears that the values of wind resources, solar radiation, and temperature have a significant impact on the energy cost. The cities of Yaoundé and Ebolowa, displaying respective wind speeds of 2.07 m/s and 1.76 m/s, are recognized for having the lowest wind speeds in the country, which hinders the overall energy production and profitability of the system. The hybrid system suggested for these cities proves to be expensive, with energy costs exceeding the standard electricity price set by the energy distribution and marketing organization in the country.

Configuration optimization and performance analysis of hybrid PV/wind systems in building groups

Distributed hybrid renewable energy is a promising technology for addressing environmental and energy issues, and its performance and system configuration play an essential role in the application. However, the contribution of energy sharing among buildings in building groups to the matching performance has yet to be fully explored. This study established a joint MATLAB-TRNSYS optimization model for the hybrid PV/wind building system to investigate the matching performance of energy consumption in building groups and energy production in PV/wind systems. The optimal system configuration for three objectives, technical, economic, and environmental, was also studied using the multi-objective particle swarm algorithm. Several factors influencing system performance and configuration were considered: renewable energy hybrid, a hybrid of different buildings, intensity of energy use and energy resource, and economic parameters. The results reveal that a hybrid system outperforms a single system, particularly a PV system with a smaller roof area and less installed capacity. Additionally, wind turbines contribute more to system performance than PV panels. Mixing buildings with different heights and functions could also improve system performance by renewable energy sharing in most instances, except multi-story office buildings. Increasing wind resources improves system performance more than solar resources, and increasing energy use intensity negatively impacts system performance for residential buildings but is beneficial for office buildings. Higher grid prices and feed-in tariffs can bring more economic benefits. This study revealed the contribution of energy sharing among different buildings, which could support better application of distributed hybrid renewable energy systems in complex urban environments.

Optimization of renewable energy hybrid power plant in the state of Karnataka, India

This paper proposes a methodology on reliability and cost minimization of the electricity produced by Renewable energy sources. The approach is to use Hybrid Renewable Energy Systems, which involves integrating various renewable sources. The objective of this study is to address these challenges by HRES method in the state of Karnataka. In Karnataka, there has been large scale curtailment of renewable energy generation due to the various structural issues. This study would give a solution to reliability and cost related issues faced by this state. For the study a Mathematical Model has been developed using Feed Forward Neural Network (FNN) and Chemical Reaction Optimization algorithms. Chemical reaction Optimization model is chosen to remove biases of the Artificial Neural Network Model of FNN. This model will be used to simulate interaction between Hybrid Renewable Energy Systems. The result of the study will provide a power system with high & optimized renewable energy output in the state of Karnataka, India which will be reliable and cost effective.