Technico-economic analysis of off grid solar PV/Fuel cell energy system for residential community in desert region

A technico-economic analysis based on integrated modeling, simulation, and optimization approach is used in this study to design an off grid hybrid solar PV/Fuel Cell power system. The main objective is to optimize the design and develop dispatch control strategies of the standalone hybrid renewable power system to meet the desired electric load of a residential community located in a desert region. The effects of temperature and dust accumulation on the solar PV panels on the design and performance of the hybrid power system in a desert region is investigated. The goal of the proposed off-grid hybrid renewable energy system is to increase the penetration of renewable energy in the energy mix, reduce the greenhouse gas emissions from fossil fuel combustion, and lower the cost of energy from the power systems. Simulation, modeling, optimization and dispatch control strategies were used in this study to determine the performance and the cost of the proposed hybrid renewable power system. The simulation results show that the distributed power generation using solar PV and Fuel Cell energy systems integrated with an electrolyzer for hydrogen production and using cycle charging dispatch control strategy (the fuel cell will operate to meet the AC primary load and the surplus of electrical power is used to run the electrolyzer) offers the best performance. The hybrid power system was designed to meet the energy demand of 4500 kWh/day of the residential community (150 houses). The total power production from the distributed hybrid energy system was 52% from the solar PV, and 48% from the fuel cell. From the total electricity generated from the photovoltaic hydrogen fuel cell hybrid system, 80.70% is used to meet all the AC load of the residential community with negligible unmet AC primary load (0.08%), 14.08% is the input DC power for the electrolyzer for hydrogen production, 3.30% are the losses in the DC/AC inverter, and 1.84% is the excess power (dumped energy). The proposed off-grid hybrid renewable power system has 40.2% renewable fraction, is economically viable with a levelized cost of energy of 145 $/MWh and is environmentally friendly (zero carbon dioxide emissions during the electricity generation from the solar PV and Fuel Cell hybrid power system).     

A flower pollination optimization algorithm for an off-grid PV-Fuel cell hybrid renewable system

This research work crucially deals with a techno-economic feasibility study for off-grid solar photovoltaic fuel cell (PV/FC) hybrid systems. The hybrid renewable energy system is investigated for feeding electric to remote areas and isolated urban regions in Egypt. To achieve this goal, all the system equipment are modeled, simulated and the area under study data is gathered. The objective function is formulated depending on the total annual cost (TAC). The Flower Pollination Algorithm (FPA), as an efficient recent metaheuristic optimization method, proposed to estimate the optimum number of both PV panels and the FC/electrolyzer/H₂ storage tanks set mandatory where the least total net present value (TNPV) is reached.The loss of power supply probability (LPSP) is considered to enhance the performance of the proposed design. The effect of the variation of FC, electrolyzer, H₂ storage tanks and the PV power system initial cost on the levelized cost of energy (LCOE) is presented through a comprehensive sensitivity analysis.Through Matlab™ program, the numerical simulation results obtained by the FPA algorithm have been compared to the corresponding outcomes while using the artificial bee colony (ABC) and the Particle Swarm Optimization (PSO) techniques. According to the simulation outcomes analysis, the FPA Algorithm has the less fulfillment time and good rendering between the other algorithms. In addition, the optimum system configuration is acquired using FPA with the optimal hybridization of 27 solar PV, 28 FCs, 58 electrolyzers and 37 H₂ storage tanks for an LPSP and PEE of 1.52% and 4.68% respectively. The system TNPV is $3,244,897 with the LCOE of 0.334 $/kWh.     

Experimental investigation of power management and control of a PV/wind/fuel cell/battery hybrid energy system microgrid

This paper presents an experimental study of a standalone hybrid microgrid system. The latter is dedicated to remote area applications. The system is a compound that utilizes renewable sources that are Wind Generator (WG), Solar Array (SA), Fuel Cell (FC) and Energy Storage System (ESS) using a battery. The power electronic converters play a very important role in the system; they optimize the control and energy management techniques of the various sources. For wind and solar subsystem, the speed and Single Input Fuzzy Logic (SIFL) controllers are used respectively to harvest the maximum power point tracking (MPPT). To maintain a balance of energy in the hybrid system, an energy management strategy based on the battery state of charge (SOC) has been developed and implemented experimentally. The AC output voltage regulation was achieved using a Proportional Integral (PI) controller to supply a resistive load with constant amplitude and frequency. According to the obtained performances, it was concluded that the proposed system is very promising for potential applications in hybrid renewable energy management systems.     

Design and simulation of the PV/PEM fuel cell based hybrid energy system using MATLAB/Simulink for greenhouse application

In this study, design and optimization of the hybrid renewable energy system consisting of Photovoltaic (PV)/Electrolyzer/Proton Exchange Membrane Fuel Cell (PEMFC) was investigated to provide electricity and heat for Greenhouse in ?anl?urfa (Turkey). The coupling of a photovoltaic system with PEMFC was preferred to supply continuous production of electric energy throughout the year. Additionally, produced heat from PEMFC was used to heating of the greenhouse by micro cogeneration application. The MATLAB/Simulink was applied to the design and optimization of the proposed hybrid system. In the designed system, solar energy was selected to produce the Hydrogen (H₂) required to run the electrolyzer. In cases where the solar energy is not sufficient and cannot meet the electricity requirement for the electrolyzer; the H₂ requirement for the operation of the PEMFC was met from the H₂ storage tanks and energy continuity was ensured. The electrolyzer was designed for H₂ demand of the 3 kW PEMFC which were met the greenhouse energy requirement. PEMFC based hybrid system has 48% electrical and 45% thermal efficiencies. According to optimization results obtained for the proposed hybrid system, the levelized cost of energy was found 0.117 $/kWh. The obtained results show the proposed PV/Electrolyzer/PEMFC hybrid power system provides an applicable option for powering stand-alone application in a self-sustainable expedient.     

Considering uncertainty in the optimal energy management of renewable micro-grids including storage devices

This paper proposes a new probabilistic framework based on 2m Point Estimate Method (2m PEM) to consider the uncertainties in the optimal energy management of the Micro Girds (MGs) including different renewable power sources like Photovoltaics (PVs), Wind Turbine (WT), Micro Turbine (MT), Fuel Cell (FC) as well as storage devices. The proposed probabilistic framework requires 2m runs of the deterministic framework to consider the uncertainty of m uncertain variables in the terms of the first three moments of the relevant probability density functions. Therefore, the uncertainty regarding the load demand forecasting error, grid bid changes and WT and PV output power variations are considered concurrently. Investigating the MG problem with uncertainty in a 24 h time interval with several equality and inequality constraints requires a powerful optimization technique which could escape from the local optima as well as premature convergence. Consequently, a novel self adaptive optimization algorithm based on θ-Particle Swarm Optimization (θ-PSO) algorithm is proposed to explore the total search space globally. The θ-PSO algorithm uses the phase angle vectors to update the velocity/position of particles such that faster and more stable convergence is achieved. In addition, the proposed self adaptive modification method consists of three sub-modification methods which will let the particles choosel the modification method which best fits their current situation. The feasibility and satisfying performance of the proposed method is tested on a typical grid-connected MG as the case study.     

Optimal energy management system for stand-alone wind turbine/photovoltaic/hydrogen/battery hybrid system with supervisory control based on fuzzy logic

This paper presents a novel hourly energy management system (EMS) for a stand-alone hybrid renewable energy system (HRES). The HRES is composed of a wind turbine (WT) and photovoltaic (PV) solar panels as primary energy sources, and two energy storage systems (ESS), which are a hydrogen subsystem and a battery. The WT and PV panels are made to work at maximum power point, whereas the battery and the hydrogen subsystem, which is composed of fuel cell (FC), electrolyzer and hydrogen storage tank, act as support and storage system. The EMS uses a fuzzy logic control to satisfy the energy demanded by the load and maintain the state-of-charge (SOC) of the battery and the hydrogen tank level between certain target margins, while trying to optimize the utilization cost and lifetime of the ESS. Commercial available components and an expected life of the HRES of 25 years were considered in this study. Simulation results show that the proposed control meets the objectives established for the EMS of the HRES, and achieves a total cost saving of 13% over other simpler EMS based on control states presented in this paper.     

Power quality enhancement of grid-connected fuel cell using evolutionary computing techniques

Fuel Cell (FC), as a type of new renewable energy sources grid-connected at Point of Common Coupling (PCC), is introduced in this study. This article presents the power quality improvement of the FC integrated to the power network through a chopper and an inverter using the conventional PI controller. Two PI controllers, tuned by three recent different evolutionary computing techniques namely Harmony Search (HS), Modified Flower Pollination Algorithm (MFPA) and Electromagnetic Field Optimization (EFO) methods are considered. The two PI controllers are used for driving the inverter connected the on-grid FC in order to govern the PCC voltage between the FC and the power network. These two controllers are exploited to drive the power and the current regulators at different voltage sag and swell conditions. The three optimization methods are compared to the Particle Swarm Optimization (PSO) with regards to voltage profile, power quality and execution time.Simulation results, using Matlab/Simulink^?, show the significance of the three optimization techniques in regulating the voltage at PCC with reduced harmonics during the system voltage sag and swell conditions when compared to the PSO. Through the numerical analysis, the superiority of MFPA method among the different optimization metaheuristic techniques is highlighted particularly for enhanced dynamic voltage response purposes.     

The importance of detailed data utilization on the performance evaluation of a grid-independent hybrid renewable energy system

In this study, a multi-source hybrid power system consisting of wind turbine (WT), photovoltaic (PV) solar unit, proton exchange membrane (PEM) FC and battery is proposed. The WT and PV generation systems are considered as the main power sources for utilizing the available renewable energy. The FC system is proposed as the back-up generation combined with electrolyzer unit and battery picks up the fast load transients and ripples. In such a hybrid system, energy management plays an important role for the overall system performance and durability. From this perspective, a fuzzy logic based intelligent controller is considered in this study. Besides, a detailed minute-scale meteorological and load demand data is utilized in the simulation process and the importance of utilization of such detailed data is presented. This detailed analysis may be valuable for evaluating the feasibility of grid-independent hybrid renewable energy units for upcoming power systems.     

Techno‐economic optimization of hybrid power system using genetic algorithm

This paper presents an optimum sizing methodology to optimize the hybrid energy system (HES) configuration based on genetic algorithm. The proposed optimization model has been applied to evaluate the techno‐economic prospective of the HES to meet the load demand of a remote village in the northern part of Saudi Arabia. The optimum configuration is not achieved only by selecting the combination with the lowest cost but also by finding a suitable renewable energy fraction that satisfies load demand requirements with zero rejected loads. Moreover, the economic, technical and environmental characteristics of nine different HES configurations were investigated and weighed against their performance. The simulation results indicated that the optimum wind turbine (WT) selection is not affected only by the WT speed parameters or by the WT rated power but also by the desired renewable energy fraction. It was found that the rated speed of the WT has a significant effect on optimum WT selection, whereas the WT rated power has no consistent effect on optimal WT selection. Moreover, the results clearly indicated that the HES consisting of photovoltaics (PV), WT, battery bank (Batt) and diesel generator (DG) has superiority over all the nine systems studied here in terms of economical and environmental performance. The PV/Batt/DG hybrid system is only feasible when wind resource is very limited and solar energy density is high. On the other hand, the WT/Batt/DG hybrid system is only feasible at high wind speed and low solar energy density. It was also found that the inclusion of batteries reduced the required DG and hence reduced fuel consumption and operating and maintenance cost. Copyright © 2014 John Wiley & Sons, Ltd.     

Dynamic modeling and sizing optimization of stand-alone photovoltaic power systems using hybrid energy storage technology

Economic and environmental concerns over fossil fuels encourage the development of photovoltaic (PV) energy systems. Due to the intermittent nature of solar energy, energy storage is needed in a stand-alone PV system for the purpose of ensuring continuous power flow. Three stand-alone photovoltaic power systems using different energy storage technologies are studied in this paper. Key components including PV modules, fuel cells, electrolyzers, compressors, hydrogen tanks and batteries are modeled in a clear way so as to facilitate the evaluation of the power systems. Based on energy storage technology, a method of ascertaining minimal system configuration is designed to perform the sizing optimization and reveal the correlations between the system cost and the system efficiency. The three hybrid power systems, i.e., photovoltaic/battery (PV/Battery) system, photovoltaic/fuel cell (PV/FC) system, and photovoltaic/fuel cell/battery (PV/FC/Battery) system, are optimized, analyzed and compared. The obtained results indicate that maximizing the system efficiency while minimizing system cost is a multi-objective optimization problem. As a trade-off solution to the problem, the proposed PV/FC/Battery hybrid system is found to be the configuration with lower cost, higher efficiency and less PV modules as compared with either single storage system.     

Multi-objective operation management of a renewable MG (micro-grid) with back-up micro-turbine/fuel cell/battery hybrid power source

As a result of today’s rapid socioeconomic growth and environmental concerns, higher service reliability, better power quality, increased energy efficiency and energy independency, exploring alternative energy resources, especially the renewable ones, has become the fields of interest for many modern societies. In this regard, MG (Micro-Grid) which is comprised of various alternative energy sources can serve as a basic tool to reach the desired objectives while distributing electricity more effectively, economically and securely. In this paper an expert multi-objective AMPSO (Adaptive Modified Particle Swarm Optimization algorithm) is presented for optimal operation of a typical MG with RESs (renewable energy sources) accompanied by a back-up Micro-Turbine/Fuel Cell/Battery hybrid power source to level the power mismatch or to store the surplus of energy when it’s needed. The problem is formulated as a nonlinear constraint multi-objective optimization problem to minimize the total operating cost and the net emission simultaneously. To improve the optimization process, a hybrid PSO algorithm based on a CLS (Chaotic Local Search) mechanism and a FSA (Fuzzy Self Adaptive) structure is utilized. The proposed algorithm is tested on a typical MG and its superior performance is compared to those from other evolutionary algorithms such as GA (Genetic Algorithm) and PSO (Particle Swarm Optimization).     

Bacterial Foraging Algorithm based solar PV parameter estimation

The abundance and non-polluting nature of solar energy has aroused the interest of many researchers. This worldwide attention of photovoltaic panels has led to the need of generating accurate model for solar photovoltaic (PV) module before proceeding to the installation part. However, accurate modeling of solar PV characteristics is difficult; since the manufacturer’s datasheet provides only four values such as V_mp, I_mp, V_oc, and I_sc. Further, for accurate modeling precise estimation of model parameters at different environmental conditions are very essential. On the other hand, optimization technique is a very powerful tool to obtain solutions to complex non-linear problems. Hence, in this paper, Bacterial Foraging Algorithm is proposed to model the solar PV characteristics accurately. A new equation has been evolved to determine the values of V_oc, V_mp accurately; since these values decides the closeness of the simulated characteristics. Model parameters are extracted for three different types of solar PV panels. A systematic evaluation and performance comparison of Bacterial Foraging Algorithm with other optimization techniques such as Genetic Algorithm and Artificial Immune System has been done and the best computational technique is derived based on performance criteria such as accuracy, consistency, speed of convergence and absolute error. Extensive computations are carried out for the proposed method, as well as for Genetic Algorithm and Artificial Immune System to substantiate the findings.     

Modeling,design, and optimization of a cost‐effective and reliable hybrid renewable energy system integrated with desalination using the division algorithm

People in the Middle East are facing the problem of freshwater shortages. This problem is more intense for a remote region, which has no access to the power grid. The use of seawater desalination technology integrated with the generated energy unit by renewable energy sources could help overcome this problem. In this study, we refer a seawater reverse osmosis desalination (SWROD) plant with a capacity of 1.5 m³/h used on Larak Island, Iran. Moreover, for producing fresh water and meet the load demand of the SWROD plant, three different stand‐alone hybrid renewable energy systems (SAHRES), namely wind turbine (WT)/photovoltaic (PV)/battery bank storage (BBS), PV/BBS, and WT/BBS are modeled and investigated. The optimization problem was coded in MATLAB software. Furthermore, the optimized results were obtained by the division algorithm (DA). The DA has been developed to solve the sizing problem of three SAHRES configurations by considering the object function's constraints. These results show that this improved algorithm has been simpler, more precise, faster, and more flexible than a genetic algorithm (GA) in solving problems. Moreover, the minimum total life cycle cost (TLCC = 243 763$), with minimum loss of power supply probability (LPSP = 0%) and maximum reliability, was related to the WT/PV/BBS configuration. WT/PV/BBS is also the best configuration to use less battery as a backup unit (69 units). The batteries in this configuration have a longer life cycle (maximum average of annual battery charge level) than two other configurations (93.86%). Moreover, the optimized results have shown that utilizing the configuration of WT/PV/BBS could lead to attaining a cost‐effective and green (without environmental pollution) SAHRES, with high reliability for remote areas, with appropriate potential of wind and solar irradiance.     

Analysis of off-grid hybrid wind turbine/solar PV water pumping systems

While many remote water pumping systems exist (e.g. mechanical windmills, solar photovoltaic, wind-electric, diesel powered), few combine both the wind and solar energy resources to possibly improve the reliability and the performance of the system. In this paper, off-grid wind turbine (WT) and solar photovoltaic (PV) array water pumping systems were analyzed individually and combined as a hybrid system. The objectives were to determine: (1) advantages or disadvantages of using a hybrid system over using a WT or a solar PV array alone; (2) if the WT or solar PV array interfered with the output of the other; and (3) which hybrid system was the most efficient for the location. The WT used in the analysis was rated at 900 W alternating current (AC). There were three different solar PV arrays analyzed, and they were rated at 320, 480, and 640 W direct current (DC). A rectifier converted the 3-phase variable voltage AC output from the WT to DC before combining it with the solar PV array DC output. The combined renewable energies powered a single helical pump. The independent variable used in the hybrid WT/PV array analysis was in units of W/m². The peak pump efficiency of the hybrid systems at Bushland, TX occurred for the 900 W WT combined with the 640 W PV array. The peak pump efficiencies at a 75 m pumping depth of the hybrid systems were: 47% (WT/320 W PV array), 51% (WT/480 W PV array), and 55% (WT/640 W PV array). Interference occurred between the WT and the different PV arrays (likely due to voltage mismatch between WT and PV array), but the least interference occurred for the WT/320 W PV array. This hybrid system pumped 28% more water during the greatest water demand month than the WT and PV systems would have pumped individually. An additional controller with a buck/boost converter is discussed at end of paper for improvement of the hybrid WT/PV array water pumping system.     

A reliable methodology based on mine blast optimization algorithm for optimal sizing of hybrid PV-wind-FC system for remote area in Egypt

In this paper, a reliable methodology incorporated mine blast algorithm (MBA) is applied to solve the optimal sizing of a hybrid system consisting of photovoltaic modules, wind turbines and fuel cells (PV/WT/FC) to meet a certain load of remote area in Egypt. The main objective of the optimal sizing process is to achieve the minimum annual cost of the system with load coverage. The sizing process is performed optimally based on real measured data for solar radiation, ambient temperature and wind velocity recorded by the solar radiation and meteorological station located at national research institute of astronomy and geophysics, Helwan city, Egypt. Three other meta-heuristic optimization techniques, particle swarm optimization, cuckoo search and artificial bee colony are applied to solve the problem and the results are compared with those obtained by the proposed methodology. A power management strategy that regulates the power flow between each system component is also presented. The obtained results show that; applying the proposed methodology will save about 24.8% in the annual total cost of the proposed system compared with PSO, 8.956% compared with CS and 11.5576% compared with ABC. The proposed algorithm based on MBA is candidate for solving the presented optimization problem of optimal sizing the hybrid PV/WT/FC system.     

偏远岛礁可再生能源开发利用技术经济分析

为了优化偏远岛礁能源保障模式,通过分析柴油发电和可再生能源发电的分项费用特点,分别建立了这两种发电模式的费用表达式,并给出了可再生能源发电投资回收期和寿命期内节省费用的计算公式。以南海岛礁为例分析了太阳能和风能资源状况、柴油运输费用特点,以示例的形式探讨了光伏设备投资回收期与运输费用之间的关系,以及节省费用数额与运行时间之间的关系。研究表明,在偏远岛礁开发利用太阳能和风能资源在经济上具有可行性;岛礁距离越远,可再生能源设备投资回收期越短,节省的费用越多;在南海岛礁光伏发电设备投资回收期一般不超过8 a。     

Techno-economic analysis of photovoltaic-hydrogen refueling station case study: A transport company Tunis-Tunisia

This paper sheds the light on the future of green hydrogen in Tunisia. So, a detailed economic assessment and evaluation of the Levelized Hydrogen Cost (LHC) and the Net Profit (NP) of a Photovoltaic (PV) Hydrogen Refueling Station (HRS) are presented and discussed. Tunisia is characterized by its high PV potential which makes the production of electricity from solar energy an effective alternative source. However, due to the regulations and issues related to the connection of medium PV scale to the power grid, the energy produced from renewable sources (RS) is still less than 3% of the total produced electricity. On the other hand, the price of hydrocarbon fuels is still increasing. The gap between production and total demand in hydrocarbons has created a deficit in the primary energy balance. Therefore, the production of hydrogen from solar energy for refueling Fuel Cell Vehicles (FCV)s consists of a promising solution to boost the development of the country, reduce hydrocarbon fuels consumption, and protect the environment. The sizing of a small PV-HRS to produce 150 kg of hydrogen per day shows the necessity to install PV systems with a total Direct Current (DC) capacity of 1.89 MWp. The Initial Cost (IC) analysis shows that while the PV system cost represents 48.5% of the total IC, the IC of electrolysers represents 41%. The storage system cost is approximately equal to 3.2% of the total IC. The LHC is equal to 3.32€/kg with a total IC of 2.34 million €.     

Optimization and sensitivity analysis of a PV/Wind/Diesel hybrid system for a rural community in the pacific

This work looks at the feasibility of a standalone hybrid power generation system for providing power to a rural community in the Pacific Islands. The optimization and sensitivity analysis of a proposed PV/Wind/Diesel hybrid System is performed together with economic analysis. We have used HOMER, a sizing and optimization tool for distributed power system, developed by National Renewable Energy Laboratory (NREL) for our analysis. The sensitivity analysis was done using wind speed data and diesel price as variables. An Ice storage facility having a corrected mean daily load of 60 kWh/day was considered as the stand-alone load. The life cycle cost analysis was done for a number of scenarios with different renewable energy contribution to the total electricity produced.     

Dynamic modeling of a photovoltaic hydrogen fuel cell hybrid system

The objective of this paper is to mathematically model a stand-alone renewable power system, referred to as “Photovoltaic–Fuel Cell (PVFC) hybrid system”, which maximizes the use of a renewable energy source. It comprises a photovoltaic generator (PV), a water electrolyzer, a hydrogen tank, and a proton exchange membrane (PEM) fuel cell generator. A multi-domain simulation platform Simplorer is employed to model the PVFC hybrid systems. Electrical power from the PV generator meets the user loads when there is sufficient solar radiation. The excess power from the PV generator is then used for water electrolysis to produce hydrogen. The fuel cell generator works as a backup generator to supplement the load demands when the PV energy is deficient during a period of low solar radiation, which keeps the system's reliability at the same level as for the conventional system. Case studies using the present model have shown that the present hybrid system has successfully tracked the daily power consumption in a typical family. It also verifies the effectiveness of the proposed management approach for operation of a stand-alone hybrid system, which is essential for determining a control strategy to ensure efficient and reliable operation of each part of the hybrid system. The present model scheme can be helpful in the design and performance analysis of a complex hybrid-power system prior to practical realization.