Optimization Of Hybrid Renewable Energy System Research Articles

A Case Study of Hybrid Renewable Energy System Optimization for an Island Community based on Particle Swarm Optimization

A Case Study of Hybrid Renewable Energy System Optimization for an Island Community based on Particle Swarm Optimization

On–off-Grid Optimal Hybrid Renewable Energy Systems for House Units in Iraq

This paper addresses the optimal sizing of Hybrid Renewable Energy Systems (HRESs), encompassing wind, solar, and battery systems, with the aim of delivering reliable performance at a reasonable cost. The focus is on mitigating unscheduled outages on the national grid in Iraq. The proposed On–off-grid HRES method is implemented using MATLAB and relies on an iterative technique to achieve multi-objectives, balancing reliability and economic constraints. The optimal HRES configuration is determined by evaluating various scenarios related to energy flow management, electricity prices, and land cover effects. Consumer requirements regarding cost and reliability are factored into a 2D optimization process. A battery model is developed to capture the dynamic exchange of energy among different renewable sources, battery storage, and energy demands. A detailed case study across fifteen locations in Iraq, including water, desert, and urban areas, revealed that local wind speed significantly affects the feasibility and efficiency of the HRES. Locations with higher wind speeds, such as the Haditha lake region (payback period: 7.8 years), benefit more than urban areas (Haditha city: payback period: 12.4 years). This study also found that not utilizing the battery, particularly during periods of high electricity prices (e.g., 2015), significantly impacts the HRES performance. In the Haditha water area, for instance, this technique reduced the payback period from 20.1 to 7.8 years by reducing the frequency of charging and discharging cycles and subsequently mitigating the need for battery replacement.

Capacity optimization of independent hybrid renewable energy system under different operational strategies based on improved gray wolf algorithm

Renewable energy sources such as wind and solar power exhibit strong stochasticity and volatility, resulting in decreased power supply security and sustainability. A strategically optimized hybrid renewable energy system (HRES) is crucial for maintaining stable load operations and achieving sustainable energy development. This paper introduces an energy optimization management model for an independent HRES consisting of wind turbines, photovoltaic systems, diesel generators, and energy storage units. Operational strategies focus on energy storage-led loads following diesel generator-led load prioritizations. The model aims to optimize objectives to include economic, environmental, and power supply reliability indices. A dynamic adaptive parameter approach balances the parameters of the objective function at various instances. The optimal capacity allocation of the model is solved using the improved gray wolf optimization (IGWO) algorithm. This approach incorporates the golden sine strategy, the levy flight strategy, and the dynamic inverse learning strategy into the traditional GWO algorithm. Analyzing different test functions, evaluation metrics, and actual load data indicates that the proposed algorithm excels in global optimization capabilities and search speeds. The model significantly reduces the economic and environmental costs of the HRES microgrids and improves the sustainable development of renewable energy in various scenarios.

Optimal planning and designing of microgrid systems with hybrid renewable energy technologies for sustainable environment in cities.

Although hybrid wind-biomass-battery-solar energy systems have enormous potential to power future cities sustainably, there are still difficulties involved in their optimal planning and designing that prevent their widespread adoption. This article aims to develop an optimal sizing of microgrids by incorporating renewable energy (RE) technologies for improving cost efficiency and sustainability in urban areas. Diverse RE technologies such as photovoltaic (PV) systems, biomass, batteries, wind turbines, and converters are considered for system configuration to obtain this goal. Net present cost (NPC) is this study's objective function for optimal sizing microgrid configuration. For demonstration, we assess the technical, economic factors, and atmospheric emissions of optimal hybrid renewable energy systems for Putrajaya City in Malaysia. The required solar radiation data, temperature, and wind speeds are collected from the NASA surface metrological database. From the quantitative analysis of simulations, the biomass-battery-based system has optimal economic outcomes compared to other systems with an NPC of around 1.07M$, while the cost of energy (COE) is 0.118 $/kWh. Moreover, environmentally safe nitrogen oxide emissions, carbon monoxide, and carbon dioxide concentrations exist. The grid-tied RE technology boasts cost-effectiveness, with an NPC of 348,318 $ and a COE of 0.0112 $/kWh. This study aids decision-makers in formulating policies for integrating hybrid RE systems in urban areas, promoting sustainable energy generation.

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.

Optimal Sizing of Hybrid Renewable Energy System Using Two-Stage Stochastic Programming

Stochastic programming has become increasingly vital in energy applications, especially in the context of the growing need for renewable energy solutions. This paper presents a significant advancement in this field by introducing an efficient and robust algorithm for optimally sizing hybrid renewable energy systems. Utilizing a two-stage stochastic programming approach, the proposed algorithm addresses the challenges posed by the unpredictability of renewable energy sources. The proposed solution leverages the three-block alternating direction method of multipliers (ADMM), a cutting-edge technique that facilitates parallel computation and enhances computational efficiency. The distinctiveness of this method lies in its ability to solve complex stochastic optimization problems without compromising the mathematical integrity of the model. This is achieved by applying first-order optimality conditions, ensuring both robustness and efficacy. To demonstrate the practical applicability and superiority of the algorithm, a case study was conducted in a rural area of South Africa. The proposed algorithm was applied to design an optimal hybrid renewable energy system, and its performance was compared against traditional methods such as progressive hedging and Monte Carlo techniques. Results affirm the superiority of the approach, saving approximately 8.16% capital cost when compared to progressive hedging. In addition, the proposed algorithm outperforms the Monte Carlo method both in terms of CPU time and the number of cost function evaluations.

Efficient integration of photo voltaic and hydro energy technologies for sustainable power generation in rural areas: A case study

This research aims to provide an efficient and cost-effective renewable energy supply. It assesses the potential for photovoltaic (PV) and hydro energy in Pirthala, Haryana, India, using HOMER Pro® v3.14.2. A Hybrid renewable energy system (HRES) can continuously power 855 homes. The optimal HRES configuration comprises well-optimized PV modules, hydro turbines, converters, and batteries. The top four configurations were selected based on criteria such as net present cost (NPC) and cost of energy production (COE). The most effective HRES configuration involves a 3461-kW solar array, a 98.1 kW hydro turbine, 304 lithium-ion batteries of 100 kWh, and a 2785-kW converter, achieving a 100 % integration of renewable energy. This ideal HRES was thoroughly assessed regarding economic, technical, and renewable energy considerations. The results and the optimized HRES configuration can serve as a valuable reference for similar initiatives in rural areas, contributing to adopting renewable energy sources and enhancing energy access and reliability.

Performance and Techno-Economic Analysis of Optimal Hybrid Renewable Energy Systems for the Mining Industry in South Africa

This paper presents an exploration of the potential of hybrid renewable energy systems (HRESs), combining floating solar photovoltaics (FPV), wind turbines, and vanadium redox flow (VRF) battery energy storage systems (BESSs) to expedite the transition from conventional to renewable energy for the mining sector in South Africa. The feasibility study assesses how to enhance the overall efficiency and minimize greenhouse gas emissions from an economic standpoint by using the Hybrid Optimization of Multiple Energy Resources (HOMER) grid software version 1.11.1 and PVsyst version 7.4. Furthermore, the BESS Covariance Matrix Adaptation Evolution Strategy (CMA-ES) dispatch algorithm is proposed to make the most of the battery storage capacity and capability, aligning it with the dynamic energy demand and supply patterns of an HRES. The proposed HRES includes a highly efficient SFPV with a performance ratio of 0.855 and an annual energy production of 15,835 MWh; a wind turbine (WT) operating for 2977 h annually, achieving a 25% wind penetration rate; and a dynamic VRF-BESS with a 15,439 kWh life throughput and a 3 s dispatch response time. This HRES has a CapEx of R172 million, a 23.5% Internal Rate of Return (IRR), and an investment payback period of 4.9 years. It offers a low Levelized Cost of Energy (LCoE) at 4.27 R/kWh, a competitive Blended Cost of Energy (BCoE) at 1.91 R/kWh, and a positive net present cost (NPC), making it economically advantageous without external subsidies. Moreover, it annually reduces CO2 emissions by 1,715,468 kg, SO2 emissions by 7437 kg, and NOx emissions by 3637 kg, contributing to a significant environmental benefit.

Techno-economic optimization of hydrogen generation through hybrid energy system: A step towards sustainable development

The present study aims to design and optimize a Hybrid Renewable Energy System (HRES) to facilitate a remote community's electricity and hydrogen load demand at Dungri, Uttarakhand, India. The methodology includes an assessment of energy demand, local resource availability, and the nature of the inhabitant. The findings shows techno-economically an optimal HRES, consisting of 90 kW PV, 25 kW Bio-generator, 30 kW electrolyser, 15 kW hydrogen tank, 10 kWh storage and a 30 kW converter with Net present value (NPV) of Rs. 78.4 lakhs, cost of energy (COE) as Rs. 7.61/kWh and cost of hydrogen (COH) Rs. 330/kg. Annual electricity generation is of 250641 kWh/year and yearly average hydrogen generation of 1838 kg through electricity consumption of 80462 kWh/year and can be utilized for 26280 km/year of operation of hydrogen fuelled buses. Furthermore, sensitivity analysis reveals that, rise in the hydrogen load, boost up the system's NPV and COE, whereas,the COH reduces. Amount of annual CO2 emission and avoided are 53.9 kg, 209.12 t, respectively. Moreover, it infers that the proposed system serves isolated rural communities with high-quality energy and satisfies local hydrogen fuel demand in the transportation sector in economically viable manner and achieves the SDG 7 & 8.

Multiple energy resources integration in the food industry: A technoeconomic analysis

This study focuses on exploring sustainable energy solutions for the industrial sector, with a particular emphasis on meeting the electrical and thermal needs of the local bakery industry. Several alternative energy sources were proposed in this study, including solar irradiation, and the utilization of agricultural residues (such as olive tree pruning and residues of tomato crop). An anaerobic digestion (AD) reactor, a photovoltaic (PV) system, wind turbines (WT), a gasification system, and a combined heat and power (CHP) unit were used as parts of the developed hybrid renewable energy system (HRES). The objective was to optimize the system's performance by considering renewable energy sources (RES) penetration, energy cost, and ecological footprint.Furthermore, this investigation identified research gaps in the supply of thermal energy demand using renewable energy sources in an industrial setting and evaluated the integration of waste-to-energy technologies in HOMER Pro. Through modelling, optimization, and evaluation, different HRES configurations were assessed to determine the most cost-effective and optimal system for the bakery industry. The optimal suggested HRES showed a 65% reduction (from 0.4362 €/kWh to 0.1533 €/kWh) in the levelized cost of electricity (LCOE). Gasification achieved better results than AD, with the addition of a gasifier leading to a 40% decrease in the LCOE. The renewable fraction for the optimal HRES was 87.9%. There was a reduction in carbon dioxide emissions by 63%, while the HRES had a payback time of 3.17 years. Overall, the findings of this study show that utilizing local biomass and waste can play a significant role in the energy transition, leading to cost reduction and improved economic performance.

Techno-economic analysis of optimal hybrid renewable energy systems – A case study for a campus microgrid

People are becoming more aware of the benefits of renewable energy. In recent years, a lot of research deals with the use of energy systems during on-grid or off-grid conditions, however, grid-connected systems may cause a power crisis to the grid. With the addition of renewable components, it is hard for the grid to keep balance. In hybrid systems, contradiction between net present cost (NPC) and excess electricity, unmet load, and capacity shortage always appears. Excess electricity, unmet load, and capacity shortage appear when the demand and supply are unbalanced, indicating the underutilization of energy. In this paper, we aim to overcome the aforementioned contradiction by conducting a case study for the first time on the implementation of a Hybrid Renewable Energy System (HRES) for a university campus in Selangor, Malaysia. Four different designs of HRES are proposed and compared. They are the Wind-Biogas-Battery System (Design A), Wind-Biogas-PV-Battery System (Design B), Wind-Biogas-Hydrogen Module-Battery System (Design C), Wind-Biogas-Diesel Generator-Battery System (Design D). The most optimal system will be selected based on the evaluation of three main criteria, i.e., cost analysis, electricity production analysis, and gas emission analysis.

Supervisory Control of Solar-Wind-Biomass-Fuel Cell Energy System for Optimal Performance

Generating electricity through a hybrid renewable energy system (HRES) plays a crucial role in achieving the sustainable development goal of affordable and clean energy (SDG 7). However, designing an optimal HRES is challenging due to the fluctuating demand and intermittent nature of renewable energy sources (RES). In recent times, hybrid hydrogen-battery energy storage technologies have garnered significant attention as they offer a pathway to a sustainable HRES with zero net emissions. This research paper introduces a rule-based algorithm and a metaheuristic optimization technique called Levy Flight Algorithm (LFA) for the energy management strategy (EMS) of an independent HRES. The EMS aims to establish a sequence for power delivery among the different components within the microgrid. The LFA is employed to optimize this EMS. To account for the variability and unpredictability of renewable energy sources, the proposed EMS is evaluated across four scenarios: winter, spring, summer, and autumn. These scenarios are derived from a stochastic model of RES. The results of the evaluation demonstrate that the energy management strategy implemented to control the HRES has successfully established an environmentally friendly energy system.

Energy, economics and environmental (3E's) analysis of a solar-assisted HRES through demand side management.

The limitation of renewable energy is its fluctuation with time, season, and peak load demand. Hence, most of the research was carried using demand side management to reduce the actual consumption load to lower the peak load. This will also hamper the basic energy need of the facility. Therefore, the objective of the present study is to model a hybrid renewable energy system (HRES) to attain the specific consumption of a community health centre (CHC) in Yomcha, Arunachal Pradesh, with load shedding. The optimization of HRES is performed on HOMER® Pro software along with the demand side management algorithm and a maximum annual capacity shortage of 5%. Three different cases were compared based on feasibility, economics, and environmental basis to estimate the performance of the HRES. The results show that the proposed model is appropriate for the CHC over the previously proposed system. Moreover, HRES with (design-side management) DSM will reduce the overall cost and increase efficiency and reliability with an net present value of Rs. 3013482 and a cost of energy of Rs. 5.42/kW, renewable fraction 78%, internal rate of return 70%, return of investment 66%, and payback period of 1.4 years. Moreover, it reduces emissions, controls overloading during peak hours, and decreases load shifting. The study also supports the sustainable development goal (SDG)-7 set by the United Nation SDG Committee.

Techno-economic study and the optimal hybrid renewable energy system design for a hotel building with net zero energy and net zero carbon emissions

The tourism sector is a key source of national income, and the use of renewable energy resources promotes green and sustainable tourism. In addition, ensuring a reliable supply and efficient use of clean energy is a primary objective of Egypt's Vision 2030, as it has a significant impact on the sustainable development and growth of the tourism sector in Egypt. Net-zero energy buildings (NZEBs) are a promising decarbonization effort as they reduce energy consumption while increasing the share of renewable energy. Therefore, it is worth investigatingthe opportunities for NZEBs applications in tourism sector. This paper presents an optimization analysis of a hotel’s grid-connected hybrid renewable energy system (HRES) based on its technical, economical, and environmental prospects. Seven scenarios are considered for on-site generation to match the energy requirements of the specific hotel building. The proposed hybrid systems incorporate photovoltaic (PV), wind turbine (WT), and biogas generators into a grid-connected system for supplying power to a tourist hotel. The size of the microgrid system is optimized to decrease the net present cost (NPC) and levelized cost of electricity (LCOE). The results reveal that the PV/wind grid-connected system, with renewable energy generators consisting of 143 kW of photovoltaic modules and one 20 kW wind turbine with a hub height of 18 m, has the lowest NPC and LCOE. This hybrid energy system has a net present cost of 388 k$, which is significantly lower compared to the electricity grid's cost of 873 k$. The electricity price of the proposed HRES, at 2.1 ¢/kWh, is highly competitive with Egypt's retail electricity prices of 6.9 ¢/kWh. Moreover, grid-connected HRES can lower the pressure on the electricity grid arising from the feed-in of electricity from HRES. Furthermore, the proposed HRES will help slow climate change by reducing GHG emissions and fossil fuel usage. Finally, this study will provide valuable guidance for the practical application of NZEBs in Egypt as well as similar global zones.

Optimum hybrid renewable energy system design for on and off grid buildings: Hotel, education and animal hospital building case

Optimum design of hybrid renewable systems is essential for the efficient utilization of the renewable sources and uninterruptible energy supply. The size and backup capacity of the system are effected by the hourly energy demand profile of the building.In this study, optimal design of PV/wind/battery/diesel hybrid renewable energy system (HRES) for the electrification of a hotel building (HB), education building and animal hospital (AH) for on and off grid cases are evaluated to compare buildings with different demand profiles. The hourly electricity consumption of the buildings is measured during January 2023. Nonlinear swarm optimization algorithm was used to minimize the system cost of electricity (COE) and maximize the renewable fraction.Optimal off-grid HRES found to include PV and wind turbine together. AH represented the most stable and highest hourly demand which resulted in minimum COE (0.18 $/kWh and 0.321 $/kWh) for on and off grids.Then annual electricity consumptions of the buildings are equalized to compare buildings with the same annual but different hourly load. On-grid HB found to have minimum COE (0.177 $/kWh) due to the closer hourly demand profile on weekends and weekdays then other buildings. Therefore, on-grid HRES configurations are found to be more cost effective in buildings utilized seven days of the week. However, in off-grid case minimum COE (0.321 $/kWh) was obtained for AH and maximum was found for HB which was due to the peak demands. The result shows that buildings with sudden increases require high battery capacity which results in high COE.

Optimal design and development of renewable based multi‐energy system for village sustainability: A case study simulation

AbstractThe primary objective of this article is the design and development of the optimal hybrid renewable energy (HRE) system for rural communities through village‐owned resources. The optimal performance and economic analysis is carried out with a suitable multi‐energy generation configuration model simulation. Based on the simulation outcomes the feasibility report of the proposed HRE system is to be considered for the investor's decision‐making process. The complete analysis has been planned with three important phases such as pre assessment stage, simulation and optimization stage, and evaluation stages. This real conducted case study has expressed many interesting facts about the integration of renewable resources toward meeting the rural energy requirements with economical and smooth manners. The proposed configuration is capable to generate net annual energy of 89,822 kWh/year with CoE (cost of energy) of Rs. 8.102. In addition, the proposed HRE system is reducing the CO2 impact on the environment by nearly 3.5% with an excess energy capacity of 6688 kWh/year.

Optimal Design of a Hybrid Off-Grid Renewable Energy System Using Techno-Economic and Sensitivity Analysis for a Rural Remote Location

Due to the lack of grid power availability in rural areas, hybrid renewable energy sources are integrated with microgrids to distribute reliable power to remote locations. This optimal hybrid system is created using a solar photovoltaic system, wind turbine, diesel generator, battery storage system, converter, electrolyzer and hydrogen tank to provide uninterrupted power and meet different load demands of different communities in Doddipalli village, Chittoor, Andhra Pradesh, India. Optimization and techno-economic analysis are performed to design the proposed system using HOMER Software. Various configurations are obtained from the software among which the best four combinations are considered for case studies. This research article aims to design the optimal hybrid renewable energy system, wherein the design consists of PV/BS (1476 kW-solar PV, 417 batteries, electrolyser-200 kW, hydrogen tank-20 kg and 59.6 kW-converter) by comparing the minimum net present cost (NPC: $7.01 M), levelized cost of energy (LCOE: 0.244 $/kWh), and the high renewable fraction (RF: 84.1%). In this research, the proposed system would be more economical when solar energy becomes the primary source and is integrated with the battery. This research also presents a sensitivity analysis of the off-grid HRES system with various electrical load demands, project lifetime, and derating factors.

Grid connected hybrid renewable energy systems for urban households in Djibouti: An economic evaluation

The cost of electricity produced by thermal power plants in Republic of Djibouti is relatively high at about $0.32/kWh. This is due to its dependence on imported oil coupled with fluctuating oil prices. Consequently, the customer pays a high electricity bill. However, Djibouti is endowed with indigenous renewable energy resources such as a good solar irradiance of 5.92 kWh/ m2 day, a potential geothermal energy estimated up to 1000 MW, and few sites with annual wind speed higher than 6 m/s. The goal of this paper is, therefore, to assess an economic evaluation of different grid connected hybrid renewable energy systems to a residential urban house located in Tadjourah city (11.7913° N, 42.8796° E) in the North-Eastern part of Djibouti to reduce the cost of electricity from the grid. To reach this objective, a powerful software tool called HOMER (Hybrid Optimization Model for Electric Renewables) has been used to find the optimum hybrid energy system using real wind and solar irradiation data. The results obtained from this study show that the best economical suited combination of hybrid renewable energy system is a PV-Wind grid connected system. This study shows also that potentially the indigenous renewable energy contribution, in Tadjourah, can be as much as 77 % with 47 % of solar and 30% of Wind energy. The Net Present Cost, the Levelized Cost of Energy, and the operating cost of the optimal HRES are $337, $0.002/kWh and $1,025/year, respectively. When compared with the average cost of grid-only connection of $0.32/kWh, the optimal hybrid renewable energy system is more economical and will save 51 % of the cost that the customer must pay when using only the electricity from the grid.

Standalone Hybrid Renewable Energy System Optimization Using Linear Programming

Standalone Hybrid Renewable Energy System Optimization Using Linear Programming

Optimal Sizing of a Hybrid Renewable Energy System: A Socio-Techno-Economic-Environmental Perspective

Abstract Unprecedented power outages and load shedding significantly impact power supply reliability in a power distribution network. Furthermore, extending grid availability to far-flung regions with higher distribution losses is not economically viable. Therefore, a hybrid renewable energy system (HRES) is developed, and its socio-techno-economic-environmental (STEE) viability in supplying reliable electricity to the village is being examined in this paper. STEE factor-based multi-target optimization and sizing technique are designed using the homer pro software. The factors considered are namely social (land cost, human progress index, and employment generation factor), technical (unmet load, renewable energy portion, duty factor, and excess energy factor), economical (annualized cost of system, cost of energy, and total net present cost), and environmental (carbon emission and particulate matter). Three HRES setups are investigated, with various combinations of photovoltaic (PV), wind turbine (WT), battery (BAT), biogas generator (BG), and diesel generator (DG) and the optimal configuration is selected by STEE performance analysis. Compared to other evaluated setups, the HRES design with PV–WT–BAT–BG–DG is optimal for a consistent power supply. A sensitivity analysis for the optimal setup’s macro-economic variables and component costs is performed to achieve a more feasible optimal setup. Furthermore, the optimal setup’s cost of energy (0.1813 $/kW h) is lower than that of the most recent study in the literature. The closeness of the hybrid optimization of multiple electric renewables (HOMER) results (cost of energy (0.1813 $/kW h), unmet load (2.86 kW h/year)) and particle swarm optimization results (cost of energy (0.1799 $/kW h), unmet load (2.60 kW h/year)) for the optimal HRES setup supports the validity of the HOMER method used in this investigation.