Hybrid Energy System Research Articles

Techno-economic optimization of a photovoltaic-wind energy-based hydrogen production system: A case study of different cities of Saudi Arabia

The study employed Hybrid Optimization of Multiple Electric Renewables software and two-hybrid energy systems configurations to ascertain the most effective approach for generating hydrogen and electrical power in the designated three cities of Dammam, Jeddah and Tabuk in Saudi Arabia. To reduce emissions of greenhouse gases, improve energy security and encourage sustainable development, this study was motivated by the need to address the urgent need to switch to renewable energy sources like solar and wind based on Saudi Arabian's Vision 2030 initiative. To achieve these objectives, this research investigates the techno-economic feasibility of producing hydrogen from renewable energy sources to promote energy independence and economic growth in the region of Saudi Arabia. The novelty of the study provides a regional view of the use of renewable energy sources for hydrogen production by concentrating on several Saudi Arabian cities. It is essential for successful energy planning and policy formation to have insights suited to unique regional settings as demonstrated in this study. According to the findings of the study, the electrical and hydrogen requirements of the selected cities in Saudi Arabia can be fulfilled using renewable energy sources, as sufficient wind speed and sunlight are available to produce renewable hydrogen. The outcomes of the study demonstrated that the electricity and hydrogen generated in the city of Dammam were found to be significantly higher than in the other two cities resulting in high hydrogen production at the city of Dammam compared to the cities of Tabuk and Jeddah. The hybrid energy system in Dammam was identified as the most practical option for fulfilling Saudi Arabia's electricity and hydrogen production requirements based on the analysis and optimization, with low net present cost, levelized cost and levelized cost of hydrogen values of $235235, 0.316 $/kWh and 4.16 $/kg, respectively. The outcome of the study suggests that incorporating a renewable energy system in Dammam may diminish the country's reliance on fossil fuels and decarbonize its transportation sector. The results of this study could be employed by members of the Saudi hydrogen industry to promote increased hydrogen production and make Saudi Arabia's energy infrastructure more resilient and sustainable.

Modeling and exergy-economy analysis of residential building energy supply systems combining torrefied biomass gasification and solar energy

A novel hybrid energy system driven by torrefied biomass gasification and solar energy is proposed for the first time, and their complementarity to enhance the system’s energy efficiency is analyzed and shown. The system mainly combines biomass torrefaction, biomass gasification subsystem, solar heat collection and absorption refrigeration technology. The effects of different operating parameters on the gasification products were studied. The economic analysis is carried out based on the theory of exergy economy. The results show that torrefaction pretreatment of biomass can significantly improve its fuel quality and gasification performance. With the increase of torrefied temperature, the volume fraction of CO2 and H2 decreased while the volume fraction of CH4 and CO increased. The economic analysis shows that the expected annual income is $72,735, and the investment recovery period is 2.89 years. Through the calculation of the energy-saving and environmental benefits, it can be concluded that the hybrid energy system can save 1.05 × 106 MJ of heat per year. This equates to about 358.26 tons of standard coal or a CO2 emission reduction of 550.59 tons, the participation of solar energy is conducive to the system emission reduction. By tuning the parameter sensitivity, the influence of biomass price change on the unit exergy cost of system products was more obvious.

Using genetic algorithm for optimal sizing of stand-alone hybrid energy system

When planning a hybrid energy system (HES) that incorporates both renewable and non-renewable energy sources—those that rely on fossil fuels—the primary considerations are the total cost of the system and the CO? emissions. In this paper, we will investigate the typical hybrid energy system (HES) that incorporates both renewable and non-renewable energy sources involving a detailed simulation process that may require specific inputs, models, and data. Then, we employed dual optimization methods: genetic algorithm (GA) and particle swarm optimization (PSO). The consequences of GA and PSO execution in the bus timetabling problem depict that the GA algorithm is better at finding the optimal solution in terms of accuracy and iteration. Additionally, the GA algorithm is also superior to the straightforwardness of the techniques used. So, in this work, we employed a Genetic Algorithm Optimization (GA)–-based optimal sizing technique for HES configurations that include sustainability wind turbines (WTs), battery storage (BS), and diesel generators (DGs). HES improved power delivery to a rural community in the Wasit Province, Iraq, situated at 46° - 36° and 32° - 31° in the country's southeastern central region. Throughout the project's 25-year lifespan, the optimization primarily aims to minimize the total cost (CT) and total CO? emissions (ECO2T). The outcomes demonstrate that the GA algorithm may, with continuous electricity supply, minimize the objectives while meeting the load demand.

Performance analysis of three-phase solar PV, BESS, and Wind integrated UPQC for power quality improvement

UPQC (Unified Power Quality Conditioner) is indeed a Versatile power conditioner which could be utilized to adjust for a variety of power supply voltage disturbances, rectify voltage fluctuation, and minimize harmonic load current in accessing the power source. To ensure a continuous power supply. We are making use of UPQC technology in combination with shunt and series AFC (Active filter compensators) to counteract power quality problems resulting from grid harmonics and nonlinear loads. Therefore, the focus of this research is to analyze the UPQC's system performance under swell and sag with the variation of solar irradiation and temperature. To achieve these two distinct cases of PV system like temperature-25 °C, irradiance-700 W/m2, and temperature-45 °C, irradiance-800 W/m2, are considered respectively. The implementation of the FOPI controller purposes to bolster power quality of 3-phase HESS (hybrid energy storage system), which includes an integrated UPQC for outstanding performance. In order to manage harmonics resulting from non-linear loads and reduce grid power quality issues, the UPQC model integrates both shunt and series AFC. In the case of extended voltage interruptions, the integrated UPQC with BESS, wind and PV can effectively resolve power quality concerns. The UPQC shunt compensator efficiently harnesses power from HES (hybrid energy systems), whereas the series compensator acts as a guardian, protecting the load from power quality issues originating in the grid. In order to regulate the voltage of the DC connection at a desired level, the aim of this article is to develop a FOPI controller with isodamping properties. In particular, a novel hybrid algorithm called the Enhanced Seagull with Rooster Update (ES-RU) Algorithm, which combines the ideas of Chicken Swarm Optimization (CSO) and Seagull Optimization algorithm (SOA), optimally tunes the gain of the FOPI controller. For optimal performance, the FOPI controller's gain parameters (Kp, Ki, λ) are finely tuned using an Enhanced Seagull with Rooster Update (ES-RU) Algorithm. As a consequence, the performance of the adopted and extant models is examined during sag and swell conditions with respect to source voltage and load voltage and compared with other conventional models like PI, FF, CS and SG, respectively for both cases like temperature-25 °C, irradiance 700 W/m2, and temperature-45°C, irradiance-800 W/m2, correspondingly. The overshot and total harmonic distortion (THD) of the proposed ES-RU is superior to the existing models like PI, FF, CS and SG.

A Hybrid Energy System Based Ev Charging Station with Advanced Controller for Grid Power Quality Regulation

A solar photovoltaic array, battery energy storage, diesel generator, grid-based island are four sources and electric vehicles (EVs) are loads in grid-connected and DG-connected modes are continuously charged. There is a Charging Station (CS)/Battery charger. The primary function of Charging Station is to charge an EV battery using a solar PV array and Battery energy storage (BES). The Charging Station will intelligently utilise the energy from the grid or DG set even if the battery is empty and the power of the PV system is not accessible. The power of DG units is constantly pulled to run at 80%–85% load in order to ensure excellent fuel efficiency at all load circumstances. In the absence of a mechanical governor, CS also regulates the voltage and frequency of the generator and accumulator. Additionally, it ensures that even with non-linear loads, the power taken from the mains or DG set has unity power factor. The grid/generator voltage and the common link voltage are synced to provide continuous charging. A PI, fuzzy logic controller and ANN is also used to analyse and reduce overall harmonic distortion on the Grid. Charging Station also manages active/reactive power transfers from cars to the grid, residences, and other vehicles to increase operational efficiency. There are tools for CS operation analysis and simulation.

Optimal Control and Optimization of Grid-Connected PV and Wind Turbine Hybrid Systems Using Electric Eel Foraging Optimization Algorithms.

This paper presents a comprehensive exploration of a hybrid energy system that integrates wind turbines with photovoltaics (PVs) to address the intermittent nature of electricity production from these sources. The necessity for such technology arises from the sporadic nature of electricity generated by PV cells and wind turbines. The envisioned outcome is an emissions-free, more efficient alternative to traditional energy sources. A variety of optimization techniques are utilized, specifically the Particle Swarm Optimization (PSO) algorithm and Electric Eel Foraging Optimization (EEFO), to achieve optimal power regulation and seamless integration with the public grid, as well as to mitigate anticipated loading issues. The employed mathematical modeling and simulation techniques are used to assess the effectiveness of EEFO in optimizing the operation of grid-connected PV and wind turbine hybrid systems. In this paper, the optimization methods applied to the system's architecture are described in detail, providing a clear understanding of the intricate nature of the approach. The efficacy of these optimization strategies is rigorously evaluated through simulations of diverse operating scenarios using MATLAB/SIMULINK. The results demonstrate that the proposed optimization strategies are not only capable of precisely and swiftly compensating for linked loads, but also effectively controlling the energy supply to maintain the load's power at the desired level. The findings underscore the potential of this hybrid energy system to offer a sustainable and reliable solution for meeting power demands, contributing to the advancement of clean and efficient energy technologies. The results demonstrate the capability of the proposed approach to improve system performance, maximize energy yield, and enhance grid integration, thereby contributing to the advancement of renewable energy technologies and sustainable energy systems.

Optimal design and analysis of a grid‐connected hybrid renewable energy system using HOMER Pro: A case study of Tumbatu Island, Zanzibar

AbstractThis study addresses the pressing issue of quality electricity access in remote regions, with a specific focus on Tumbatu Island in Tanzania. Most studies on quality improvement concentrate on low‐voltage distribution lines and leave high‐voltage (HV) transmission lines behind. It is essential to address quality issues in HV lines due to their critical role in electricity transmission and distribution infrastructure. The objective of the study is to improve the voltage profile on the island's HV transmission line by identifying the optimal hybrid energy system comprising solar PV, wind turbine, and battery technologies. The study begins by presenting the total power demand and consumption on Tumbatu Island, which are important factors in designing an efficient energy system. The findings reveal a power demand of 7173 kW and a consumption of 28540 kWh/day, with an average scaled value of 1507.9 and 6000 kWh/day. To achieve the desired voltage profile improvement, the research incorporates HOMER Pro software for simulating and analyzing various hybrid system configurations. Essential input parameters, such as costs, resources, technology components, and load, are considered in the simulation process. The software generates a ranked list of options based on the system's net present cost (NPC). The simulation results demonstrate that the integration of solar PV, wind turbine, and HV lines provides a substantial improvement in the voltage profile, increasing it from 29.6 to 31.23 kV during peak demand periods. This solution proves to be the most economically viable, with the lowest NPC of $4,003,851 and a relatively short payback period of 3.79 years. In addition, a sensitivity analysis is performed to identify the most influential parameter in the system's performance. Wind speed is found to have the greatest impact, emphasizing its significance in the design and operation of the hybrid energy system. The implementation of this optimal hybrid renewable energy system on Tumbatu Island will not only improve the voltage profile and meet the island's energy needs but also shall contribute to global efforts in reducing pollution and the cost of electricity to the Tumbatu Island population. Moreover, it addresses the current and future demands for clean energy, underlining its importance in achieving sustainable and accessible electricity in sub‐Saharan Africa and beyond.

Optimizing hybrid energy systems for remote communities in Asia’s least developed countries

In least-developed countries (LDCs), electricity shortages are the primary barrier to economic and social growth. Some remote areas in LDC rely on diesel-based systems. However, renewable energy must be taken into account for generating electricity because of the uncertainty of diesel fuel prices and the emissions of carbon dioxide. Hybrid energy systems (HES) are becoming increasingly popular, which is unsurprising given the rapid advancement of renewable energy technologies, which have made them the preferred method to respond to the current unreliable electricity supply, reduce the impact of global warming that occurs from electricity production, and contribute to cost reduction. This study explores the feasibility of utilizing a combination of solar PV, wind energy, and battery systems with the existing diesel generator in four different locations in Cambodia, Laos, Myanmar, and Bangladesh. Hybrid optimization multiples for electric renewables (HOMER) is used as a tool for techno-economic analysis and finding the possible combination of solar PV, wind, diesel, and battery. The multi-criteria decision-making (MCDM) technique was used to verify all configurations obtained from HOMER’s results. This approach considers environmental, economic, and technological factors by utilizing the AHP, TOPSIS, EDAS, and PROMETHEEE II techniques. The results show that PV/diesel with batteries is the optimum solution. This hybrid system comprises 89% PV penetration, a cost of electricity (COE) of 0.257 $/kWh, an initial capital cost (IC) of $244,277, and a net present cost (NPC) of $476,216 for a case study in Cambodia. Furthermore, this system can reduce almost 51,005 kg/year of carbon dioxide compared to a diesel-only system, while the cost of electricity is reduced.

Integration and performance analysis of optimal large-scale hybrid PV and pump hydro storage system based upon floating PV for practical application

The widespread use of green energy sources creates a significant demand for energy storage. Hybrid floating photovoltaic (FPV) and pumped hydro storage (PHS) represent one of the most dependable and cost-effective solutions, which uses the PV system on the water body combined with a pair of lakes with different heights. This study focuses on the load side as well as the PHS capacity factor and aims to lower the cost of energy (COE) by raising the PHS capacity factor. Since building a PHS requires a significant upfront investment, doing so will also lower the COE and enable the acquisition of PHS for large-scale power production, which will guarantee power access in large cities. To simulate the FPV-PHS system, the multi-objective genetic algorithm (MOGA) is employed. Sufficient power management is a prerequisite for achieving system reliability in the best possible hybrid energy system design and implementation. Considering the 60-year system lifespan, the net present cost (NPC) analysis shows that, out of all the communities evaluated, the FPV-PHS system has the lowest NPC and COE. For the optimal configuration (FPV (Block A) 105 MW, PHS 80 MW, FPV (Block B) 357 MW, and the current hydropower plant), the expected NPC and energy costs for implementing the hybrid energy system (HRS) at the chosen location are $44,737,613 and $40/MWh, respectively. The existing FPV system spans 4.65 km2 and lowers the evaporation fraction by 17,279,400 m3. The hybrid FPV-PHS system reduces annual CO2 emissions by 581,830 tons. Our research reveals that a hybrid floating PV and pump storage hydropower system offers more steady clean electricity, implying a great significance for power grid infrastructure.

Design of Intelligent Hybrid Energy Ambulatory Surgical Center Ship in Efficient Way

An Ambulatory Surgical Center (ASC), also known as an outpatient surgery center, is a medical facility that provides same-day surgical procedures to patients who do not require an overnight stay in a hospital. ASCs are equipped with state-of-the-art medical equipment and staffed by highly trained healthcare professionals, including surgeons, anaesthesiologists and nurses. There are many areas along the river where people do not have easy access to any surgery. They have to go far to get this service, for which they do not even take the service. This research is for them. This research will ensure their basic medical services. The contribution of this research, this world-class surgical ship goes to ensure the basic medical needs of poor people in remote areas where good healthcare is not available. Another great contribution that will surprise the world is that no conventional fuel is needed to ensure this healthcare service. So undoubtedly this research has a great contribution in the global energy crisis. To ensure efficient ambulatory surgical center (ASC) ship, conducting site assessment, sizing the hybrid system appropriately, selecting the right components, improving hybrid energy system design, implement intelligent system is important. And these are the scope of our research. A detailed analysis of all possible aspects has shown that using intelligent hybrid energy ships instead of conventional ships improves the quality of service. Long lasting service is achieved with low energy consumption, sustainability and no pollution even without compromising performance. In this research details of ASC will be critically discussed.

Analysis of Hybrid Ship Machinery System with Proton Exchange Membrane Fuel Cells and Battery Pack

As marine traffic is contributing to pollution, and most vessels have predictable routes with repetitive load profiles, to reduce their impact on environment, hybrid systems with proton exchange membrane fuel cells (PEMFC-s) and battery pack are a promising replacement. For this purpose, the new approach takes into consideration an alternative to diesel propulsion with the additional benefit of carbon neutrality and increase of system efficiency. Additionally, in the developed numerical model, control of the PEMFC–battery hybrid energy system with balance of plant is incorporated with repowering existing vessels that have two diesel engines with 300 kWe. The goal of this paper is to develop a numerical model that analyzes and determines an equivalent hybrid ship propulsion system for a known traveling route. The developed numerical model consists of an interconnected system with the PEMFC stack and a battery pack as power sources. The numerical model was developed and optimized to meet the minimal required power demand for a successful route, which has variable loads and sees ships sail daily six times along the same route—in total 54 nautical miles. The results showed that the equivalent hybrid power system consists of a 300 kWe PEMFC stack and battery pack with 424 kWh battery and state of charge varying between 20 and 87%. To power this new hybrid power system, a hydrogen tank of 7200 L holding 284.7 kg at pressure of 700 bar is required, compared to previous system that consumed 1524 kg of diesel and generated 4886 kg of CO2.

Supplying hydrogen for green steel through renewable energy sources: A case study of Turkiye

Steel is the most common industrial material worldwide due to its numerous applications, high strength and recyclability. Steel production involves alloying iron with various amounts of carbon and other elements to produce thousands of different grades and types of steel for various purposes. However, the intensive use of carbon in steel production is one of the factors contributing to global climate change. To use of hydrogen and renewable energy sources in steel production has emerged as a significant solution to reduce carbon emissions. The aim of this study is to obtain green hydrogen for the production of green steel. The focus is on utilizing offshore wind energy as a renewable energy source to give us the energy we need to electrolyze seawater. The study uses the seas of Turkiye for case analysis. In this paper, an integrated Multi-criteria decision-making method is used to integrate hybrid energy systems and their application for green industry and to select a location for a power generation plant. The study is a new contribution to the literature in terms of its scope. Green steel's location selection is addressed for the first time in the literature. The weights of the criteria are determined by employing the Best-Worst Method (BWM) as a multi-criteria decision-making technique, and the alternatives are evaluated using the Analytic Hierarchy Process (AHP). By using the BWM method, decision makers can have a clear understanding of the evaluation range for pairwise comparisons of criteria, which reduces potential biases. According to the study, the northern part of the Aegean Sea in Turkiye is the most suitable alternative for green steel production, with offshore wind energy being used for hydrogen production. The study also revealed that the most important main criterion for this hybrid system is “natural factors”, and the sub-criteria are “wind speed and power density” by far compared to other sub-criteria. The fact that the area determined for the facility is suitable for construction and the possibility that the customer of the energy produced is other industrial establishments here is the most important indicator that the methods applied give good results.

Energy, economic and environmental (3E) analyses of solar photovoltaic and fuel cell based hybrid energy system for a developing country: a worldwide approach to sustainable energy

Energy, economic and environmental (3E) analyses of solar photovoltaic and fuel cell based hybrid energy system for a developing country: a worldwide approach to sustainable energy

Analysis of the influence of electric flywheel and electromechanical flywheel on electric vehicle economy

Improving energy utilization efficiency to extend the range of vehicle is the common issue concerned by various forms of electric vehicles. In order to reveal the influence of electric flywheel and electromechanical flywheel on vehicle economy, two kinds of hybrid energy systems are studied. Firstly, based on the operating characteristics of the two types of flywheels, the topology schemes of the two hybrid energy systems are designed. On this basis, to make full use of the advantages of electric flywheel and electromechanical flywheel, energy management strategies based on wavelet algorithm and logic threshold are designed. Finally, economy tests of the two hybrid energy systems are conducted. Results show that compared with the single energy scheme with lithium battery, under CLTC, as the control motor of the electric flywheel operates under high speed and low torque range frequently, the energy consumption improvement of lithium battery is not enough to compensate for the flywheel energy loss. The net loss of the lithium battery-electric flywheel energy system increases by 2.61%. Profit from efficiency improvement of lithium battery system, increase of regenerative energy recovery and better efficiency of main drive motor, the net loss of the lithium battery-electromechanical flywheel energy system decreases by 6.44%.

Hybrid off-grid energy systems optimal sizing with integrated hydrogen storage based on deterministic balance approach

The transition to sustainable power infrastructure necessitates integrating various renewable energy sources efficiently. Our study introduces the deterministic balanced method (DBM) for optimizing hybrid energy systems, with a particular focus on using hydrogen for energy balance. The DBM translates the sizing optimization problem into a deterministic one, significantly reducing the number of iterations compared to state-of-the-art methods. Comparative analysis with HOMER Pro demonstrates a strong alignment of results, with deviations limited to a 5% margin, confirming the precision of our method in sizing determinations. Utilizing solar and wind data, our research includes a case study of Cairo International Airport, applying the DBM to actual energy demands.

Optimal design and economic analysis of a stand-alone integrated solar hydrogen water desalination system case study agriculture farm in Kairouan Tunisia

In the contemporary global discourse on environmental and developmental issues, the dual challenges of sustainable green energy and water supply stand paramount. These elements are vitally intertwined with the socio-economic vitality of the world. Notably, regions plagued by freshwater scarcity are increasingly turning to desalination which consists of a reliable and unconventional water source. The intersection of renewable energy with desalination and water purification processes presents a compelling synergy. This approach is particularly pertinent in areas where freshwater shortages coexist with abundant solar energy availability. Additionally, these technologies boast the advantage of low operational and maintenance costs. This paper delves into the design, optimization and financial analysis of a novel, standalone hybrid energy system, integrating photovoltaic and fuel cell technologies, for an agriculture farm situated in Kairouan, Tunisia. Unlike conventional systems, this model foregoes battery storage in favour of hydrogen storage, generated through water electrolysis powered by solar energy. This system harnesses solar energy for direct electrical power generation and hydrogen gas production. A segment of the generated electricity is allocated to electrolysis for green hydrogen production. In times of solar unavailability, the stored hydrogen is reconverted to electricity via a fuel cell. An intriguing aspect of this system is the utilization of saline well water, which, due to its high salt content, necessitates purification through desalination to prevent damage to the electrolysis unit and to render it suitable for agricultural irrigation.

Techno-Economic Performance and Sensitivity Analysis of an Off-Grid Renewable Energy-Based Hybrid System: A Case Study of Kuakata, Bangladesh

Hybrid renewable energy sources (HRES) are increasingly being utilized to meet global energy demands, particularly in rural areas that rely on diesel generators and are disconnected from the utility grid, due to their environmental and human health benefits. This study investigates the performance of an off-grid, hybrid PV/diesel generator/battery system for a decentralized power plant in Kuakata, Bangladesh, meeting a load demand of 3000 kWh/day with a 501.61 kW peak load demand. HOMER Pro (hybrid optimization model for electric renewable) software (version 3.11) was used to simulate and optimize system operations utilizing real-time solar radiation and load profile data from that location. This study also includes a sensitivity analysis of the off-grid HRES system under different electrical load demands, project longevity, and derating variables. The results reveal that CO2 emissions have potentially decreased by more than 30% and over 10 tons per year, respectively, when compared to traditional power plants. The optimized system’s net present cost (NPC) was determined to be around USD 5.19 million, with a cost of energy (COE) of USD 0.367 per kWh per unit with a 100% renewable component. Furthermore, the current study’s findings are compared to previous research that has resulted in an economical hybrid renewable energy system with an affordable COE. The hybrid energy system under consideration might also be applicable to other parts of the world with comparable climate conditions.

Multi-objective size optimization and economic analysis of a hydrogen-based standalone hybrid energy system for a health care center

The main contribution of this study is the multi-objective size optimization of a standalone hybrid energy system (HES) to supply the electricity demand of a health care center in Kerman province, south of Iran, in which fuel cell, photovoltaic, and diesel generator produces electricity, while the combination of electrolyzer and hydrogen tank is the storage system. The non-dominated sorting genetic algorithm II (NSGA-II) is applied to find the Pareto front of optimal solutions, where the loss of power supply probability (LPSP) and total net present cost (TNPC) are the objective functions. The results show that considering operating reserve and uncertainty, the TNPC increases 30.50% compared to the base load. Moreover, the fuel cell has a smaller share of energy production, which is due to the high cost of the storage system, while about 50% of the demand load is provided by DG in the cold seasons. The sensitivity analysis reveals that TNPC decreases by 8.93% for a 50% reduction of the storage system cost, while increases by 24.55% for a 50% increase in the fuel cost. Moreover, AHP/TOPSIS-based multi-criteria decision-making is implemented to find the best solution according to the opinions of three different managers/experts, which shows that the HES with LPSP = 0.2503% and TNPC = 2.1038 × 106 $ is the best solution in which uncertainties and operating reserve are also considered.

A power dispatch allocation strategy to produce green hydrogen in a grid-integrated offshore hybrid energy system

A dedicated grid-tied offshore hybrid energy system for hydrogen production is a promising solution to unlock the full benefit of offshore wind and solar energy and realize decarbonization and sustainable energy security targets in electricity and other sectors. Current knowledge of these offshore hybrid systems is limited, particularly in the integration, component control, and allocation aspects. Therefore, a grid-integrated analytical model with a power dispatch allocation strategy between the grid and electrolyzer for the co-production of hydrogen from the offshore hybrid energy system is developed in this paper. While producing hydrogen, the proposed offshore hybrid energy system supplies a percentage of its capacity to the onshore grid facility, and the amount of the electricity is quantified based on the electricity market price and available total offshore generation. The detailed controls of each component are discussed. A case study considers a hypothetical hybrid offshore energy system of 10 MW situated in a potential offshore off the NSW of Australia based on realistic metrological data. A grid-scale proton-exchange membrane electrolyzer stack is used and a model predictive power controller is implemented on the distributed hydrogen generation scheme. The model is helpful for the assessment or optimization of both the economics and feasibility of the dedicated offshore hybrid energy farm for hydrogen production systems.

Optimal Design of Grid-Connected Hybrid Renewable Energy System Considering Electric Vehicle Station Using Improved Multi-Objective Optimization: Techno-Economic Perspectives

Electric vehicle charging stations (EVCSs) and renewable energy sources (RESs) have been widely integrated into distribution systems. Electric vehicles (EVs) offer advantages for distribution systems, such as increasing reliability and efficiency, reducing pollutant emissions, and decreasing dependence on non-endogenous resources. In addition, vehicle-to-grid (V2G) technology has made EVs a potential form of portable energy storage, alleviating the random fluctuation of renewable energy power. This paper simulates the optimal design of a photovoltaic/wind/battery hybrid energy system as a power system combined with an electric vehicle charging station (EVCS) using V2G technology in a grid-connected system. The rule-based energy management strategy (RB-EMS) is used to control and observe the proposed system power flow. A multi-objective improved arithmetic optimization algorithm (MOIAOA) concept is proposed to analyze the optimal sizing of the proposed system components by calculating the optimal values of the three conflicting objectives: grid contribution factor (GCF), levelled cost of electricity (LCOE), and energy sold to the grid (ESOLD). This research uses a collection of meteorological data such as solar radiation, temperature, and wind speed captured every ten minutes for one year for a government building in Al-Najaf Governorate, Iraq. The results indicated that the optimal configuration of the proposed system using the MOIAOA method consists of eight photovoltaic modules, two wind turbines, and thirty-three storage batteries, while the fitness value is equal to 0.1522, the LCOE is equal to 2.66 × 10−2 USD/kWh, the GCF is equal to 7.34 × 10−5 kWh, and the ESOLD is equal to 0.8409 kWh. The integration of RESs with an EV-based grid-connected system is considered the best choice for real applications, owing to their remarkable performance and techno-economic development.