Total Net Present Cost Research Articles

Techno economic analysis of optimal load scheduling approach in a standalone hybrid microgrid system

To increase the profitability of a standalone hybrid microgrid system, an optimized load scheduling strategy is required. The aim of this paper is to establish a mavin load scheduling approach for a standalone hybrid microgrid system (SHMGS) that reduces power generation costs, load shedding and achieve energy efficiency. The SHMGS includes Photovoltaics, Wind Power, Battery Energy Storage System, Diesel Generator, and Methanol Generator. A techno-economic study is carried out using HOMER Pro. Two different modes of load scheduling approach (LSA) are considered on the basis of customer comfort violation, customer behavior uncertainty, and complexity. In addition, the study looks into the effects of two different modes of load scheduling, utilizing deferrable load sections and different dispatch strategies, on the economic efficiency of the SHMGS configuration. Optimized SHMGS with the LSA (mode-2)-dataset-2 has the cost of energy 0.1694 $/kWh, total net present cost 335 792 $, annualized cost of the system 29 017 $, excess electricity 45 503 kWh/yr, and carbon emission 30 786 kg/yr.

Stochastic optimization of a hybrid photovoltaic/fuel cell/parking lot system incorporating cloud model

The interaction and optimization of electric parking lots (EPLs) with hybrid renewable energy to exchange power and improve the system load reliability has been welcomed systems in energy industry, but it is accompanied by challenges such as uncertain parameters, and also implementing the optimal energy management. This paper proposes a novel stochastic optimization framework for a hybrid energy system including photovoltaic resources, hydrogen storage based-fuel cell integrated with an EPL (PV/FC/EPL) aiming for minimization of the total net present cost (TNPC) while ensuring the maximum probability of power shortage (PPSHmax) to meet a commercial load in Tianjin, China using the real meteorological data. A new improved kepler optimization algorithm (IKOA) utilizing the golden sine strategy is applied to optimize system component sizes and EPL charge/discharge. In a deterministic scenario, the optimal system configuration ensures cost-efficiency and reliability for load supply. Also, a new stochastic modeling framework is proposed using the Cloud Model (CM) to evaluate the effect of uncertainties in irradiance, temperature, and system demand on TNPC and PPSH. Deterministic findings reveal enhanced reliability and reduced TNPC through FC and EPL overlap during power shortages, compared to systems lacking EPL. Specifically, TNPC and PPSH are $8,632,643 and 1.45 %, respectively, for PPSHmax = 2 % over 20 years of operation. However, stochastic optimization demonstrates a 10.82 % increase in TNPC and an 8.67 % decrease in PPSH compared to the deterministic model under PPSHmax = 2 %, indicating heightened cost and reduced reliability when uncertainties are considered. This underscores the efficacy of the cloud model-based stochastic approach in addressing uncertainty in hybrid system optimization. Also, it reveals fluctuations in optimal cost and reliability values with changes in cloud droplet distribution around the expected value, emphasizing the significance of stochastic modeling for robust decision-making in hybrid energy systems. Moreover, evaluating the incorporating the penalty for the system's inability to supply the load, changing the storage investment cost, and interest rate variations on the system optimization cleared considerable effect of the system cost and reliability.

Off-grid PV/biomass/DG/battery hybrid renewable energy as a source of electricity for a farm facility

Reliable, cost-effective energy systems are pivotal for sustainable development in the agricultural sector. Using the energy balance analysis of the Hybrid Optimization Model for Electric Renewable (HOMER), this study presents a techno-economic assessment of a hybrid renewable energy system for a farm facility. The energy system components considered in the analysis include solar photovoltaics, wind turbines, diesel generators, biomass, and battery storage. The results shows that ten feasible energy systems can technically power the typical farm facility, with a PV-Biomass-DG battery being the best in terms of the total net present cost. The PV-Biomass-DG-battery systems consist of 561.023 kW of PV, 88 kW of diesel generator, 10 kW of biomass, 81 kW of converter, and 584 batteries operated in a load-following mode. When the cost of energy (COE) of EA1 0.206325 $/kWh is compared to EA7 0.407681 $/kWh, a difference of $0.201356 will be saved for every kWh. Also, a comparison of the operating cost of EA1, $65,713.23 and the operating cost of EA7 $212,027.4 showed a margin of $146,314.17 being saved. Energy systems EA3 and EA4 had the lowest carbon dioxide production levels of 15.8 kg annually, respectively. The simple payback period metrics increased from EA1 to EA6 between 2.97 years to 6.99 years. The result of the study shows that adopting a low-carbon energy transition is technically and economically viable for the agricultural sector, especially in developing countries.

A Techno-Economic Analysis of a Hybrid Microgrid System in a Residential Area of Bangladesh: Optimizing Renewable Energy

In the face of a significant power crisis, Bangladesh is turning towards renewable energy solutions, a move supported by the government’s initiatives. This article presents the findings of a study conducted in a residential area of Pabna, Bangladesh, using HOMER (Hybrid Optimization of Multiple Energy Resources) Pro software version 3.14.2. The study investigates the feasibility and efficiency of a grid-connected hybrid power system, combining photovoltaics (PV), a biomass generator, and wind energy. The simulation produced six competing solutions, each featuring a distinct combination of energy sources. Among the configurations analyzed, the grid-connected PV–biomass generator system emerged as the most cost-effective, exhibiting the lowest COE at USD 0.0232, a total net present cost (NPC) of USD 321,798.00, and an annual operating cost of USD 6060.59. The system presents a simple payback period of 9.25 years, highlighting its economic viability. Moreover, this hybrid model significantly reduces CO2 emissions to 78,721 kg/year, compared to the 257,093 kg/year emissions from a solely grid-connected system, highlighting its environmental benefits. Sensitivity analyses further reveal that the system’s performance is highly dependent on solar irradiance, indicating that slight variations in solar input can significantly impact the system’s output. This study underscores the potential of integrating multiple renewable energy sources to address the power crisis in Bangladesh, offering a sustainable and economically viable solution while also mitigating environmental impacts.

Optimal Hybrid Renewable Energy System to Accelerate a Sustainable Energy Transition in Johor, Malaysia

As the world’s second-largest palm oil producer, Malaysia heavily depends on its extensive oil palm cultivation, which accounts for nearly 90% of the country’s lignocellulosic biomass waste. Approximately 20–22 tonnes of empty fruit bunches (EFBs) can be derived from an initial yield of 100 tonnes of fresh fruit bunches (FFBs) from oil palm trees. The average annual amount of EFBs produced in Johor is 3233 tonnes per day. Recognising that urban areas contribute significantly to anthropogenic greenhouse gas emissions, and to support Malaysia’s transition from fossil fuel-based energy to a low-carbon energy system, this research employed HOMER Pro software 3.18.3 to develop an optimal hybrid renewable energy system integrating solar and biomass (EFB) energy sources in Johor, Malaysia. The most cost-effective system (solar–biomass) consists of 4075 kW solar photovoltaics, a 2100 kW biomass gasifier, 9363 battery units and 1939 kW converters. This configuration results in a total net present cost (NPC) of USD 44,596,990 and a levelised cost of energy (LCOE) of USD 0.2364/kWh. This system satisfies the residential load demand via 6,020,427 kWh (64.7%) of solar-based and 3,286,257 kWh (35.3%) of biomass-based electricity production, with an annual surplus of 2,613,329 kWh (28.1%). The minimal percentages of unmet electric load and capacity shortage, both <0.1%, indicate that all systems can meet the power demand. In conclusion, this research provides valuable insights into the economic viability and technical feasibility of powering the Kulai district with a solar–biomass system.

Mega-scale solar-wind complementarity assessment for large-scale hydrogen production and storage (H2PS) in Algeria: A techno-economic analysis

Green hydrogen (GH2) is produced using renewable energy resources (RERs) such as solar photovoltaic (PV) and wind energy. However, relying solely on a single source, H2 production systems may encounter challenges due to the intermittent nature, time-of-day variability, and seasonal changes associated with these energies. This paper addresses the assessment of mega-scale solar-wind complementarity and the economic viability of large-scale H2 production and storage in Algeria, considering various climatic conditions. A techno-economic feasibility analysis is conducted by examining various factors, including resource complementarity, electricity and hydrogen productivity, solar and wind contributions, capacity factors (CFs), total net present cost (TNPC), the levelized cost of hydrogen (LCOH) production, and storage (LCOS). The findings reveal that among the studied locations (Tamanrasset, M'sila, Hassi R'mel, and Adrar), Tindouf ranked first in H2 production, with the highest amount at 11,267 kg and the lowest LCOH at 2.999 $/kg. Wind energy accounted for 69% (3,846,922 kWh) of the total (5,572,571 kWh), while solar energy contributed 31% (1,738,171 kWh). Economically, the LCOH-TNPC for the various locations ranged from 2.99 $/kg-77,042,696 $ to 3.70 $/kg-99,000,488 $. The total electricity-hydrogen generated is estimated at 25,840.251 MWh-529,395 kg. Wind power makes the major contribution, accounting for 63%–70%, compared to the PV system's share, ranging from 31% to 37%. Compared to relying on a single source, leveraging solar-wind complementarity presents opportunities for more consistent energy utilization and reliable hydrogen production. The obtained results are essential for decision-makers and policymakers in Algeria, indicating that the country can successfully achieve energy diversification and transition for future sustainability, and become a major player in the international hydrogen market.

Sustainable rural electrification: Energy-economic feasibility analysis of autonomous hydrogen-based hybrid energy system

Pakistan has endured a severe power shortage for the past decade, with an installed capacity insufficient to meet the escalating demand. This dire situation results in catastrophic power breakdowns lasting 12 h in cities and 18 h in rural areas daily, and unfortunately, the outlook indicates it may worsen over time. The energy deficit is taking a toll on the country's overall economy, causing significant damage. This study focuses on designing a rural hybrid renewable energy system (HRES) to provide stable power to a remote village in Pakistan's Bannu district. The proposed HRES includes photovoltaic panels (PV), fuel cells (FC), and a biogas generator (BG). This paper addresses Pakistan's power shortage crisis and offers an economically viable solution through the rural HRES design, ensuring a sustainable and resilient energy future. Robustness, sensitivity, and breakeven analyses confirm the system's viability and ability to provide the community with uninterrupted electricity. The research demonstrates a cost of energy (COE) of $0.41/kWh and a total net present cost (TNPC) of $199,081 for the HRES. Additionally, the study compares the performance of the proposed system with state-of-the-art alternatives.

Sustainable in-situ steam injection approach for shale oil extraction in Xinjiang, China: A technical and economic analysis

This work proposes a microgrid system for in-situ steam heating extraction of oil shale utilizing renewable energy sources. This system is designed for high efficiency and promises significant cost savings. This work couples the underground in-situ steam injection heating model and the microgrid system model to analyze the system's energy-saving and economics. Due to the technical and economic importance of Xinjiang oil shale in Northwest China, it is chosen as a case study to investigate the feasibility of the proposed method. The effect of steam temperature, pressure, and renewable resources at the oil shale extraction location on the economics of the system is examined. The results show that using renewable energy power is superior to hybrid and conventional power supply methods in terms of economy and energy efficiency. Moreover, renewable energy resulted in a 12.38 % reduction in the total net present cost (NPC) when the steam temperature increased by 40 °C. The total NPC of the project can be reduced by 28.61 % when the pressure of superheated steam is decreased by 4.0 MPa. The results indicate that the solar resource at the oil shale extraction location significantly impacts the system's economics. The study provides a theoretical basis for the economic analysis of oil shale steam injection extraction technology.

Techno-economic evaluation and improved sizing optimization of green hydrogen production and storage under higher wind penetration in Aqaba Gulf

On shore wind farms designed for hydrogen production present a promising avenue for maximizing the utilization of wind energy, achieving decarbonization and energy security objectives across various sectors. However, existing understanding of these systems, particularly in terms of economic and technical considerations, remains challenging. Hence, this paper introduces a comprehensive numerical modeling aimed at assessing the feasibility of hydrogen production from onshore wind farms for the arid costal community south of Aqaba Gulf, Saudi Arabia. This model incorporates formulas to compute wind power output, electrolyzer plant sizing, and hydrogen generation based on fluctuating wind speeds. The objective is to identify the optimal setup for a hydrogen station fueled by high wind resources, while also evaluating its economic feasibility and reliable capacity to reduce hydrogen production cost and minimize carbon emissions. The results show that the optimal Onshore Wind-Hydrogen System (OWHS) consists of 26 units of WT (each is 6.15 MW), Alkaline Electrolyzers plant with a capacity of 120 MW, and a group of hydrogen storage tanks of total size of 300 tones. The hydrogen demand and the subsidiary electric needs are successfully met with the 160 MW of wind generation capacity installed within the system with negligible capacity shortage and unmet demand. The employed set of alkaline electrolyzers has a total rated capacity of 120 MW and can stay in operation for 7335 h/yr to produce a total annual amount of 8,214,152 kg/yr of green hydrogen. The proposed system generates hydrogen with a moderate price since the LCOH obtained is found 5.26 $/kg which falls within the global range that varies from 4 to 6 $/kg. Moreover, the CO2 mitigation of the designated OWHS reaches 3343.72 Mt. with a corresponding $133,748 carbon credit gain. The sensitivity analysis shows that the total net present cost (TNPC) is highly sensitive to wind speed, hydrogen cost, and hydrogen demand but less so to inflation and discount rates. The TNPC increases by 22 % with a 5 % decrease in wind speed, as well as reducing hydrogen costs by 25 % and 50 % decreases TNPC by 14.63 % and 29.26 %, respectively. While, increasing hydrogen demand by 20 % and 40 % raises TNPC by 30.3 % and 51.4 %, respectively. This study aims to assist stakeholders and policymakers in refining onshore wind‑hydrogen systems to economically fulfill the requirements of hydrogen production for the arid costal community in Saudi Arabia.

Strategic operation of electric vehicle in residential microgrid with vehicle-to-home features

The urgent need for innovative energy solutions to facilitate the transition to renewable energy and electric vehicles (EVs) is particularly critical in developing countries, where high emissions and grid reliability challenges persist. This study investigates an off-grid residential renewable energy system with stationary storage like battery and hydrogen, alongside an EV as mobile storage. A bi-level optimization framework is established considering stationary and mobile energy storage options and a strategy is proposed to implement Vehicle-to-Home (V2H) in off-gird settings. Three cases are studied, with optimal component sizing determined using an optimization tool integrated with MATLAB. Firstly, to determine the most cost-effective stationary storage alternative, Case 1 uses hydrogen and Case 2 employs a battery as storage. Then Case 3 integrates the optimal stationary storage with mobile storage using V2H technology enabling the EV to support household energy needs during peak times. Results highlight that combining stationary and mobile storage (Case 3) offers a 15.92% reduction in Total Net Present Cost (TNPC) and a 13.9% reduction in Levelized Cost of Energy (LCOE) compared with stationary storage alone. This off-grid system (Case 3) also outperforms the conventional grid economically and environmentally, offering 2.13× TNPC reduction and 7,813 kg/yr carbon emissions mitigation.

Economic and strategic challenges in microgrid integration: Insights from operational dynamics and renewable energy potential

With the integration of a large number of microgrids in the power distribution network operation, economic and strategic challenges arise. To address these challenges, this research provides a comprehensive investigation into the operational, economic, and strategic dynamics of microgrids. Through careful data analysis, the study interprets the complications of microgrid responses to seasonal changes. It also investigates energy consumption patterns and production dynamics. The detailed analysis of microgrid configurations reveals the unique attributes and challenges of PV, wind, and hydropower microgrids. Moreover, the research explains the financial implications of microgrid integration, from setup costs to potential ROI. It is also examining the cooperative relationship between microgrids and conventional grids. Key findings highlight that solar microgrids contribute 3.2% to 5.3%, wind microgrids provide 5.9% to 7.4%, and hydropower microgrids contribute 24.4% of total power. Energy purchase peaks at 850,000 kWh in August and declines to 580,000 kWh in May. 170,000 kWh of energy is sold back to the grid in May. Moreover, the grid energy costs reduced from $0.178 kWh to $0.30 kWh. The total net present cost of the system is achieved at $37,880,023.33. Renewable energy production ranges from 480 kW to 2,300 kW, with a penetration level reaching 160%.

Enviro-economic and optimal hybrid energy system: Photovoltaic–biogas–hydro–battery system in rural areas of Pakistan

To satisfy the electricity needs of a village in Tangi, northwest Pakistan, the present research can design and evaluate the environmental and economical aspects of an optimal hybrid photovoltaic-biogas-hydropower-battery energy sustainable system (PV-BG-HP-BESS). This framework integrates various renewable energy sources, delivering a modern, efficient approach to sustainable energy solutions. The HOMER Pro software is utilized to optimize the most economical and effective hybrid energy system. The results showed that the proposed hybrid system comprising 91.4 kWp PV modules, 19.6 kW hydropower, a 50 kW biogas generator (BG), 36 batteries, and a 60.6 kW converter was the most economical choice. This system, which used the cyclic charging (CC) method, had a cost of energy (COE) of 0.0728 $/kWh and a total net present cost (NPC) of $152,242. The suggested hybrid energy system for rural areas of Pakistan includes photovoltaic (PV), biogas (BG), hydro, and battery components to provide a dependable and sustainable power supply. This system minimizes the need for expensive fossil fuels while simultaneously minimizing environmental impact by lowering pollutants and greenhouse gas emissions. The system's annual electricity production is 294,782 kWh, with PV leads at 59.4%, BG at 6.02%, and hydro at 34.6%, ensuring uninterrupted power generation even in remote areas. The unmet load, extra electricity, and capacity shortage illustrate the reliability of the system and make it possible to address rural electrification challenges while supporting sustainable development and economic growth. Moreover, the outcomes of the proposed hybrid system dominate the previous studies in multiple objectives, including cost and sensitivity analysis, when compared.

Feasibility analysis of hybrid photovoltaic, wind, and fuel cell systems for on–off‐grid applications: A case study of housing project in Bangladesh

AbstractThis study investigates the viability of hybrid photovoltaic (PV), wind, and fuel cell (FC) systems for on‐grid and off‐grid operations for the Ashrayan‐3 housing project in Bangladesh, with an increased focus on sustainable energy solutions. Motivated by the issue of the delivery of proper and sustainable energy services to remote locations, we conducted an extensive analysis of load demand and found that an average daily demand of 46,176.65 kWh exists, with a peak load of 4852.8 kW. In this research, the HOMER software has been used to make a simulation of five different hybrid system configurations with differing mixes of renewable technologies. From the analyses, the systems based 100% on renewable resources suffer more initial capital costs, with a total net present cost increase of up to 20%, in comparison to conventional systems. On the other hand, the systems give much lower operational costs and cost of energies (COEs) of a minimum of $0.0253/kWh, reported from the on‐grid PV‐based system. On the other hand, the off‐grid PV–FC–wind turbine system showed a COE of $0.286/kWh, along with a decrease in CO2 emissions by about 15,000 kg/year, showing a 30% decrease, compared with on‐grid systems. The results form a basis for the conclusion that such hybrid renewable energy systems are both economically and environmentally feasible. They can reduce COEs by up to 70% in off‐grid systems. This proves that the quality of life and energy security in developing regions will be highly increased, supporting the goals of sustainable development.

AN EFFICIENT STUDY OF PV/WIND/BATTERY/ELECTROLYZER/H2-TANK/FC FOR A REMOTE AREA ELECTRIFICATION

With the rapid development of the use of renewable energy systems, it is becoming more and more important to combine different sources into hybrid renewable energy systems. Many parameters in hybrid renewable energy systems must be optimized to effectively size hybrid system components to achieve economic, technical, and design goals practically. This paper focuses on the optimal configuration of off-grid hybrid renewable energy systems (HRES). The system consists of a photovoltaic (PV), wind turbine (WT) and battery bank (BB), fuel cell (FC) with hydrogen tank (H2-tank), and electrolyzer (Elect). The optimal size of the proposed HRES component is achieved using a novel meta-heuristic technique called the whale optimization algorithm (WOA). WOA improves the optimal configuration of HRES to produce the best minimum value of the fitness function, which converges to the global optimal solution after several iterations. The proposed WOA is used to solve the multi-objective optimization problem of the cost of energy (COE) in $/kWh and the total net present cost (TNPC) in $. Two recent algorithms, particle swarm optimization (PSO) and gray wolf optimizer (GWO), have also been implemented in this work to demonstrate the effectiveness of the proposed algorithm.

Techno-economic optimization and Strategic assessment of sustainable energy solutions for Powering remote communities

The purpose of this research is to identify the optimal configuration of a diesel generator with a hybrid renewable energy system that can sustainably meet the energy demands of a rural area. Some of the main challenges of using diesel generators to supply the required electric load in remote areas are the high operating cost, unmet electric load, carbon dioxide emissions, very high total net cost, and the quality of electricity. This study, which combined diesel generators with renewable resources, accurately analyzed eight different system outputs from the hybrid optimization of multiple energy resources software. The analysis considered factors such as site-specific conditions, fuel costs, and solar radiation levels. The software prefers a load following strategy over a cycle charging strategy. This load following strategy involves combining a diesel generator with renewable energy sources, specifically configured as a combination of photovoltaic cells, a diesel generator, a wind turbine, and a battery. This configuration, with a total net cost of approximately $180,065.43 and a levelized cost of energy of $0.32, is identified as the most effective configuration chosen. Operating cost, carbon dioxide emission, and total net present cost are reduced by 53.17 %, 60.46 %, and 30.02 %, respectively. It highlighted the combination of diesel generator with renewable energies and their role in promoting environmental sustainability. By providing 100 % of the load demand, it increased the quality of electricity such that the unmet electric load is reduced to zero.

Techno-economic impact analysis for renewable energy-based hydrogen storage integrated grid electric vehicle charging stations in different potential locations of Malaysia

This study investigates the techno-economic impacts analysis of renewable energy-based hybrid energy storage system integrated grid electric vehicles charging station (EVCS) in Malaysia. Focusing on three potential locations namely Pulau Pinang, Johor Bharu and Kuala Terengganu, the research aims to address the increasing electricity demand from the expanding electric vehicle (EV) infrastructure while mitigating grid instability issues caused by sudden load surges, increased electrical losses, and overload of high voltage devices that leads to power quality issues. Using the HOMER Pro platform, the study models and optimises an EVCS configuration-based hybrid energy storage system that incorporates renewable energy sources (RES) such as photovoltaic (PV), wind turbines (WT), lithium-ion (Li-ion) batteries, hydrogen (H2) tank, fuel cell (FC) and electrolysers considering various geographical and meteorological conditions. The hybrid energy storage configuration offers a long-term energy storage solution, surpassing current batteries' capabilities while providing a stable electricity supply for a sustainable EVCS system. The results demonstrated favourable outcomes, with the total Net Present Cost (NPC) ranging from $1.4 million to $3.4 million across all locations, and the Cost of Energy (COE) ranging from $0.03/kWh to $0.16/kWh. These findings suggest that the optimization methodology is adaptable for implementation in diverse locations with different meteorological conditions. This innovation is beneficial for developing renewable-based EVCS infrastructures, which can support economic growth in Malaysia. In addition, the study emphasizes the necessity of advanced control algorithms to manage power quality issues during peak demand and suggests future field trials to validate the system's real-world performance. Additionally, the optimized EVCS-based hybrid energy storage system contributes to reducing carbon dioxide (CO2) emissions, promoting a cleaner environment and an eco-friendly energy ecosystem.

Optimal sizing of grid connected multi-microgrid system using grey wolf optimization

Renewable distributed energy resources (DERs) offer a promising and environmentally sustainable solution for providing energy. Nowadays, there has been significant attention in wind, solar Photovoltaic (PV), and hydrogen-based fuel cell (FC) systems due to their ability to provide cost-effective energy to replace conventional generations. However, the intermittent nature of renewable energy sources presents challenges and operational issues for fully renewable energy systems. To address this, integrating energy storage systems and effectively managing uncertainties related to both load and generation resources are crucial for mitigating such challenges. This paper proposes a hybrid grid-connected PV-wind-FC generation-based Multi-microgrid (MMG) system integrated with a Battery Energy Storage System (BESS) to meet the entire load demand of the adopted MMG-based IEEE 14-bus system. The aim is to ensure cost-effectiveness and enable energy trading with the main grid by optimizing system configurations. The study incorporates stochastic analysis to handle uncertainties related to load, meteorological data, and energy prices to optimize the configuration of DERs and BESS in the MMGs. A Grey Wolf Optimization (GWO) algorithm is employed to determine the optimal sizing of the proposed grid-connected MMG. The proposed algorithm has reduced the NPC from $431.796 million to $428.832 million and LCOE to 0.267$/kWh when load and generation data uncertainty and dynamic energy price has considered. The robustness of the proposed approach is evaluated by comparing results with those obtained using Particle Swarm Optimization (PSO) and JAYA algorithms. The GWO method demonstrates superior performance, resulting in lower total Net Present Cost (NPC), lower system capacity, and a lower Levelized Cost of Energy (LCOE) compared to its counterparts. Moreover, the GWO algorithm exhibits the fastest convergence, indicating its accuracy and robustness compared to PSO and JAYA algorithms.

Technical and economic analysis of a hybrid PV/wind energy system for hydrogen refueling stations

In recent years, the construction of hydrogen refueling stations (HRSs) has been in full swing. However, irrational configuration and design can increase the operation and maintenance costs of HRSs and reduce their overall energy conversion efficiency. This paper introduces the configuration optimization of a hybrid PV/wind energy system for hydrogen refueling stations. Firstly, the distribution of hydrogen refueling demand of hydrogen fuel cell vehicles (HFCVs) in different time periods was simulated by the Monte Carlo method according to the driving rules of HFCVs. Then a model of renewable energy HRS was established in Homer, the purpose is to provide energy supply service for HFCVs through hydrogen production by electrolysis of water from renewable energy generation. Based on this, a load demand response model is developed. Finally, the best system configuration under different scenarios is obtained with the objective of minimizing the total net present cost (NPC). Through simulation calculations, the results show that the system configuration is more economically feasible after considering the demand response. The best system configuration was a grid-connected system containing a 548 kW PV, 1040 kW WT, 600 kW electrolyzer, and 600 kg hydrogen tanks This renewable energy system has the lowest NPC of $8,351,442 and produces 40,000 kg of green hydrogen annually. The sensitivity analysis also shows that with the advancement of hydrogen energy development and technology, the system will bring multiple benefits such as environmental protection and economic benefits in the future.

Optimal technoeconomic reliability‐oriented design of islanded multicarrier microgrids with electrical and hydrogen energy storage systems considering emission concerns

AbstractAlthough several studies have been performed on energy systems, there is a gap in examining the impact of energy storage systems (ESSs) technologies on the technoeconomic design of optimal multicarrier microgrids (MCMGs), considering environmental concerns. This paper aims to address this research gap by developing an optimal technoeconomic reliability‐oriented design of MCMGs, specifically focusing on battery storage systems (BSSs) and hydrogen storage systems (HSSs). The study was applied to MCMG at an actual MCMG, using HOMER Pro software. Additionally, a reliability‐oriented sensitivity analysis is conducted to understand the effects of reliability constraints, such as desired maximum capacity shortage, on the performance of various ESS technologies. One of the main contributions is analyzing the HSS and BSS from different viewpoints, such as cost, emission, and other technical–economic features for MCMGs. The comparative test results show that if a highly reliable MCMG is desired, the BSS‐based MCMG is the more practical option in terms of technoeconomic indices. However, regardless of reliability constraints, the HSS‐based MCMGs offer better environmental conditions. The total net present cost of the HSS‐based MCMG is 1.68% higher than the BSS‐based one, while it has 17.99% less CO2 emissions, while the HSS one has 17.99% less CO2 emissions.

An optimal sizing framework of a microgrid system with hydrogen storage considering component availability and system scalability by a novel approach based on quantum theory

This paper introduces an innovative framework for optimizing a hybrid photovoltaic-wind system with integrated hydrogen storage, taking into account component availability and system scalability. The primary objective is to minimize the total net present cost (TNPC) while enhancing system reliability based on the Loss of Power Supply probability (LPSP). The decision variables include the determination of the number of photovoltaic (PV) panels, wind turbines (WTs), hydrogen storage mass, fuel cell capacity, electrolyzer capacity, and inverter capacity. To achieve this optimization, the Quantum Beluga Whale Optimization (QBWO) algorithm is employed, which is an improved version of the Beluga Whale Optimization (BWO) algorithm. QBWO overcomes some limitations of BWO by incorporating principles from quantum theory and addressing challenges related to the scarcity of population diversity and stagnation in local optima. Simulations were conducted for scenarios involving WT/FC, PV/FC, and PV/WT/FC systems. The results indicate that within a microgrid context, the PV/WT/FC configuration proves to be the most cost-effective approach for supplying local loads. Under certain conditions, it achieved the best TNPC with 0.8176 M$, Levelized Cost of Energy (LCOE) with 0.264 $/kWh, and LPSP with 0.04687. However, considering components availability and system scalability changes indicate a significant effect on the system cost and reliability. Overall, this framework provides a precise method for designing energy systems, considering factors such as electricity generation costs and reliability enhancements in the face of uncertainties. QBWO outperforms original BWO, Particle Swarm Optimization (PSO), and Crow Search Algorithm (CSA) by achieving lower design costs and improved reliability. This study contributes to developing environmentally friendly electrification plans and provides valuable insights for power investments in energy-deprived Southwest Morocco.