Sizing methodology for hybrid systems based on multiple renewable power sources integrated to the energy management strategy

This work presents a design methodology for a hybrid energy system based on multiple renewable power sources and bioethanol. The new concept of generation consists on having multiple power sources such as a PEM fuel cell system fed by the hydrogen produced by a bioethanol reformer and wind-solar sources working all together supervised by the energy management system. The necessary heating for the bioethanol reforming reaction can be provided by the renewable sources to enhance the efficiency of the hydrogen production. It is worth noting that, from the power balance as well as backup point of views, the hybrid system is equipped with energy storage devices. An optimal sizing methodology integrated with the energy management strategy is proposed here for designing the overall hybrid system. The suggested approach is based on genetic algorithms, using historical climate data and load demands over a period of one year. Several simulation results are given to show the methodology performance in terms of loss of power supply probability (LPSP), costs and bioethanol consumption.     

Design and techno-economical optimization for stand-alone hybrid power systems with multi-objective evolutionary algorithms

The optimal design of the hybrid energy system can significantly improve the economical and technical performance of power supply. However, the problem is formidable because of the uncertain renewable energy supplies, the uncertain load demand, the nonlinear characteristics of some components, and the conflicting techno-economical objectives. In this work, the optimal design of the hybrid energy system has been formulated as a multi-objective optimization problem. We optimize the techno-economical performance of the hybrid energy system and analyse the trade-offs between the multi-objectives using multi-objective genetic algorithms. The proposed method is tested on the widely researched hybrid PV-wind power system design problem. The optimization seeks the compromise system configurations with reference to three incommensurable techno-economical criteria, and uses an hourly time-step simulation procedure to determine the design criteria with the weather resources and the load demand for one reference year. The well-known efficient multi-objective genetic algorithm, called NGAS-II (the fast elitist non-dominated sorting genetic algorithm), is applied on this problem. A hybrid PV-wind power system has been designed with this method and several methods in the literature. The numerical results demonstrate that the proposed method is superior to the other methods. It can handle the optimal design of the hybrid energy system effectively and facilitate the designer with a range of the design solutions and the trade-off information. For this particular application, the hybrid PV-wind power system using more solar panels achieves better technical performance while the one using more wind power is more economical. Copyright © 2006 John Wiley & Sons, Ltd.     

Optimization of control strategies for stand-alone renewable energy systems with hydrogen storage

This paper presents a novel strategy, optimized by genetic algorithms, to control stand-alone hybrid renewable electrical systems with hydrogen storage. The strategy optimizes the control of the hybrid system minimizing the total cost throughout its lifetime. The optimized hybrid system can be composed of renewable sources (wind, PV and hydro), batteries, fuel cell, AC generator and electrolyzer. If the renewable sources produce more energy than the one required by the loads, the spare energy can be used either to charge the batteries or to produce H₂ in the electrolyzer. The control strategy optimizes how the spare energy is used. If the amount of energy demanded by the loads is higher than the one produced by the renewable sources, the control strategy determines the most economical way to meet the energy deficit. The optimization of the various system control parameters is done using genetic algorithms. This paper explains the strategy developed and shows its application to a PV–diesel–battery–hydrogen system.     

Real-time energy management in an off-grid smart home: Flexible demand side control with electric vehicle and green hydrogen production

A real-time energy management system for an off-grid smart home is presented in this paper. The primary energy sources for the system are wind turbine and photovoltaics, with a fuel cell serving as a supporting energy source. Surplus power is used to generate hydrogen through an electrolyzer. Data on renewable energy and load demand is gathered from a real smart home located in the Yildiz Technical University Smart Home Laboratory. The aim of the study is to reduce hydrogen consumption and effectively utilize surplus renewable energy by managing controllable loads with fuzzy logic controller, all while maintaining the user's comfort level. Load shifting and tuning are used to increase the demand supplied by renewable energy sources by 10.8% and 13.65% from wind turbines and photovoltaics, respectively. As a result, annual hydrogen consumption is reduced by 7.03%, and the average annual efficiency of the fuel cell increases by 4.6%     

Energy storage and control optimization for an electric vehicle

Two big issues involving electric vehicles are energy supply and power management control. To deal with the energy supply problem, this paper proposes the application of a hybrid energy source system, composed of battery pack and ultracapacitor bank. The power management control between the energy supplies was defined by a fuzzy logic with inference rules optimized through genetic algorithm. The genetic algorithm optimizes lower and upper limits of membership functions aiming to reduce the hybrid energy source system total mass while maximizing the electric vehicle drive range and performance. Through the Pareto frontier, we found the best trade‐off solution.     

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).     

On-line fuzzy energy management for hybrid fuel cell systems

Fuel Cell Hybrid Vehicles (FCHV) can reach near zero emission by removing the conventional internal combustion from the vehicle powertrain. Nevertheless, before seeing competitive and efficient FCHV on the market, at market prices, different technical, economic, and social challenges should be overcome. A typical hybrid fuel cell powertrain combines a fuel cell stack and a dedicated energy storage system along with their necessary power converters. Energy storage systems are used in order to enhance the well-to-wheel efficiency and thus reducing the hydrogen consumption. An efficient management of power flows on the vehicle, allows optimizing the recovery of energy braking. Moreover, working in the fuel cell maximum efficiency leads to reduced thermal losses and thus to the downsizing of the heat exchangers. This paper presents an enhanced control of the power flows on a FCHV in order to reduce the hydrogen consumption, by generating and storing the electrical energy only at the most suitable moments on a given driving cycle. While the off-line optimization-based on dynamic programming algorithm offers the necessary optimal comparison reference on a known demand, the proposed strategy which can be implemented on-line, is based on a fuzzy logic decision system. The fine tuning of the fuzzy system parameters (mainly the membership functions and the gains), is made using a genetic algorithm and the fuzzy supervisor shows performing results for different load profiles.     

H2 Optimization and Fuel Cells Application on Electrical Distribution System and Its Commercial Viability in Australia

Conventional energy technologies are not environmentally friendly, are not renewable, and also the cost of using fossil and nuclear fuels will go higher and higher (anecdotal evidence suggests that consumers will be paying three times their current bill 5 years from now). Therefore, renewable energy sources will play important roles in electricity generation. This paper highlights the advantages of renewable technologies, like future prospects for the poor population, being environmentally friendly, and also available in abundance. This paper points outs the factors seeking hydrogen energy and fuel cell technology to eradicate environmental disasters. This paper is significant as it looks into optimal utilization of renewable energy sources with major emphasis on H₂ optimization and fuel cells application utilizing cogeneration technology. This paper discusses the multiple hydrogen production pathways from different sources, including renewable and nonrenewable sources, H₂ safety, and also barriers to use of hydrogen energy. This paper recommends different types of quantitative and qualitative methods for optimal energy planning, and different types of fuel cells are also discussed. This paper explains a hybrid system inclusive of renewable energy, with its types and benefits. Finally, this paper concludes that Australia could switch from conventional fossil fuel technology to hybrid energy inclusive of renewable energy.     

A comprehensive method for optimal power management and design of hybrid RES-based autonomous energy systems

The power management strategy (PMS) plays an important role in the optimum design and efficient utilization of hybrid energy systems. The power available from hybrid systems and the overall lifetime of system components are highly affected by PMS. This paper presents a novel method for the determination of the optimum PMS of hybrid energy systems including various generators and storage units. The PMS optimization is integrated with the sizing procedure of the hybrid system. The method is tested on a system with several widely used generators in off-grid systems, including wind turbines, PV panels, fuel cells, electrolyzers, hydrogen tanks, batteries, and diesel generators. The aim of the optimization problem is to simultaneously minimize the overall cost of the system, unmet load, and fuel emission considering the uncertainties associated with renewable energy sources (RES). These uncertainties are modeled by using various possible scenarios for wind speed and solar irradiation based on Weibull and Beta probability distribution functions (PDF), respectively. The differential evolution algorithm (DEA) accompanied with fuzzy technique is used to handle the mixed-integer nonlinear multi-objective optimization problem. The optimum solution, including design parameters of system components and the monthly PMS parameters adapting climatic changes during a year, are obtained. Considering operating limitations of system devices, the parameters characterize the priority and share of each storage component for serving the deficit energy or storing surplus energy both resulted from the mismatch of power between load and generation. In order to have efficient power exploitation from RES, the optimum monthly tilt angles of PV panels and the optimum tower height for wind turbines are calculated. Numerical results are compared with the results of optimal sizing assuming pre-defined PMS without using the proposed power management optimization method. The comparative results present the efficacy and capability of the proposed method for hybrid energy systems.     

Optimal sizing of stand-alone hybrid systems based on PV/WT/FC by using several methodologies

This paper presents a comparative study of four sizing methods for a stand-alone hybrid generation system integrating renewable energies (photovoltaic panels and wind turbine) and backup and storage system based on battery and hydrogen (fuel cell, electrolyzer and hydrogen storage tank). Two of them perform a technical sizing. In one case, the sizing is based on basic equations, and in the other case, an optimal technical sizing is achieved by using Simulink Design Optimization. The other two methods perform an optimal techno-economical sizing by using the hybrid system optimization software HOMER and HOGA, respectively. These methods have been applied to design a stand-alone hybrid system which supplies the load energy demand during a year. A MATLAB-Simulink model of the hybrid system has been used to simulate the performance of hybrid system designed by each method for the stand-alone application under study in this work. The results are reported and discussed in the paper.     

Optimization of the photovoltaic-hydrogen supply system of a stand-alone remote-telecom application

Hydrogen is considered as the optimal carrier for the surplus energy storage from renewable resources. Although hydrogen and its application in fuel cell is considered as a high-cost energy system, some cost-efficient solutions have been found for their use in stand-alone applications, which usually depend on the variability of renewable sources that have to be oversized in order to reduce their dependence on external energy sources. This paper shows the results from the simulation of several alternatives of introducing hydrogen technologies to increase the independence of a remote-telecom application fed by photovoltaic panels. Hydrogen is obtained by electrolysis and it is used in a fuel cell when the renewable energy source is not enough to maintain the stand-alone application. TRNSYS simulation environment has been used for evaluating the proposed alternatives. The results show that the best configuration option is that considering the use of hydrogen as a way to storage the surplus of radiation and the management system can vary the number of photovoltaic panels assigned to feed the hydrogen generation, the batteries or the telecom application.     

A review of fuel cell based hybrid power supply architectures and algorithms for household appliances

Nowadays, renewable power system solutions are widely investigated for residential applications. Grid-connected systems including energy storage elements are designed. Advanced research is actually focused on improving the reliability and energy density of renewable systems reducing the whole utility cost. Source and load modeling, power architectures and algorithms are only a few topics to be addressed. Designers have to carefully deal with each subtopic prior to design efficient renewable energy systems. In the literature, each topic is separately discussed and the lack of a unique reference guide is clear to power electronics designers. In this paper, each design step including source and load modeling, hybrid supply architectures and power algorithms, is carefully addressed. A review of existing solutions is presented. The correlation between each topic is deeply analyzed. Guidelines for system design are given. This paper can be referenced as a detailed review of renewable energy system design issues and solutions.     

Standalone hybrid system energy management optimization for remote village considering methane production from livestock manure

Recently, many efforts have been done to overcome increasing fuel consumption. One of the vital solutions is utilization of standalone renewable energy resources hybrid systems. This paper attempts to develop a cost-effective methodology to ascertain optimal design and energy management for a remote village. Different energy resources such as wind and solar, fuel cell, and energy storage systems are employed to satisfy total demands including agriculture, residential, school, and health center. Different hydrogen production methods are proposed to verify the efficiency of the developed methodology. In the proposed village, different waste types such as rice husk, maize straw, livestock, and residential wastes are used to generate the required hydrogen for fuel cells to generate electricity. The main objective of the proposed methodology is minimizing the total cost of the village including total costs of each Distributed Generation (DG), cost of natural gas consumption, penalty for interruption the demands, and cost of CO₂ emission. A Particle Swarm Optimization (PSO) algorithm is employed to solve the optimization problem by minimizing the total system costs while the customers required Loss of Power Supply Probability (LPSP) is satisfied. The suggested hybrid system not only increases the renewable energy penetration but also decreases the natural gas consumption. The results achieved in the course of the present study depict that utilization of energy produced from different types of wastes plays a significant role in conserving fossil fuels and overcoming the fossil fuels depletion. It is concluded from the results that there is about a 17.46% reduction in natural gas consumption when all available waste is utilized. In addition, considering 100% availability for the animal manure reduces the natural gas consumption by reformer from 2.373 to 1.605 million liters which means reduction of the natural gas consumption is 32.35%. The results conclude that H₂ produced by livestock waste is dominating among available wastes. However, there is about 18% reduction in the Cost of Energy (COE), when 100% availability is considered for this type of waste.     

Hierarchical fuzzy control of low-energy building systems

A hierarchical fuzzy supervisory controller is described that is capable of optimizing the operation of a low-energy building, which uses solar energy to heat and cool its interior spaces. The highest level fuzzy rules choose the most appropriate set of lower level rules according to the weather and occupancy information; the second level fuzzy rules determine an optimal energy profile and the overall modes of operation of the heating, ventilating and air-conditioning system (HVAC); the third level fuzzy rules select the mode of operation of specific equipment, and assign schedules to the local controllers so that the optimal energy profile can be achieved in the most efficient way. Computer simulation is used to compare the hierarchical fuzzy control scheme with a supervisory control scheme based on expert rules. The performance is evaluated by comparing the energy consumption and thermal comfort.     

Review of hydrogen technologies based microgrid: Energy management systems,challenges and future recommendations

With the significant development of renewable energy sources in recent years, integrating energy storage systems within a renewable energy microgrid is getting more attention as a promising future hybrid energy system configuration. Recently, hydrogen systems are being considered a promising energy storage option that utilised electrolysers to produce and store hydrogen when energy is surplus and re-supply it into microgrids using fuel cells in energy shortage scenarios. To control the energy flow within such hybrid energy systems, designing an energy management system should be considered a critical task, that allows the technical and economic optimal operation of microgrids. This study presents a comprehensive review and analysis of different energy management systems for hydrogen technologies-based microgrids, including the strategies’ objectives, constraints and techniques as well as the optimisation methods and simulation tools. In addition, an insightful discussion of the existing challenges and suggestions for the future research direction has been given.     

Modeling and performance analysis of renewable hydrogen energy hub connected to an ac/dc hybrid microgrid

This paper proposes a system modeling and performance analysis of a renewable hydrogen energy hub (RHEH) connected to an ac/dc hybrid microgrid (MG). The proposed RHEH comprises a photovoltaic (PV)-based renewable energy source (RES) as the primary source, a proton exchange membrane fuel cell (PEMFC) as the secondary power source, and a proton exchange membrane electrolyzer (PEMELZ) that can generate and store hydrogen in a hydrogen tank. All these resources are directly connected at the dc bus of the ac/dc microgrids. The PEMFC operates and utilizes the hydrogen from the hydrogen tank when the energy generated by RES cannot meet the load demand. A coordinated power flow control approach has been developed for the RHEH to mitigate the mismatch between generation and demand in the ac/dc microgrid and produce renewable hydrogen when renewable power is in excess. The paper also proposes a modified hybrid Perturb & Observe-Particle Swarm Optimization (Hybrid PO-PSO) algorithm to ensure the maximum power point tracking (MPPT) operation of the PV and the PEMFC. The operation of the proposed RHEH is validated through simulations under various critical conditions. The results show that the proposed RHEH is effective to maintain the system power balance and can provide power-to-hydrogen and hydrogen-to-power when required.     

Comparative analysis of different grid-independent hybrid power generation systems for a residential load

Demand of electricity is rising all over the world, both in developing and developed countries due to escalation in world population and economic growth. The exploitation of renewable energy is imperative to mitigate energy crisis and to avoid the environmental downfall. The stochastic nature of many renewable energy sources sets techno-economic and functional limitations in their application for covering most types of energy needs. These limitations can be surmounted if a renewable and a conventional energy source are combined to formulate a hybrid generation power system.This paper examines the techno-economic feasibility of four hybrid power generation systems applied to cover the demand of a typical off-grid residence for a 20 years period. Each one of these hybrid power solutions should involve at least one renewable energy source technology and be able to cover all load needs. Four applications are investigated for each hybrid system, accounting to different geographical areas in Greece with diverse solar and aeolic profile. A comparative analysis is followed to set off the optimal solution based on a minimal total cost criterion.     

A novel methodology for scrutiny of autonomous hybrid renewable energy system

The optimal design of a hybrid system with different configurations including renewable generation is presented in this paper. A novel multi‐objective function consisting of 6 different objectives of hybrid system is reported using GA, PSO, and TLBO to decide the optimal configurations of parameters. The technical (loss of power supply probability, renewable factor), economical (cost of energy, penalty and fuel consumption), and social (job creation, human development index, and particular matter) features are investigated as objectives simultaneously for optimal design of hybrid system. The different objective indices namely cost of energy, loss of power supply probability, particular matter, human development index, job creation, and renewable factor indices are considered. The newly invented particular matter factor for design consideration of hybrid system directly shows the human health impacts, while pollutant emission is measured in the hybrid system design. The optimum values of objective indices are decided on the basis of the minimum value of multi‐objective function. The distinct cases from I to VI of hybrid system are examined for optimal configuration including different combinations of PV, wind, biomass, diesel generator, and battery bank. The resulting analysis of each case reveals that the performance of TLBO is better than PSO, and PSO is better than GA in all respect through new multi‐objective function and found case I is more efficient solution.     

Techno-economical evaluation of a hydrogen refuelling station powered by Wind-PV hybrid power system: A case study for İzmir-Çeşme

Hydrogen fuelling station is an infrastructure for the commercialisation of hydrogen energy utilising fuel cells, particularly, in the automotive sector. Hydrogen fuel produced by renewable sources such as the solar and wind energy can be an alternative fuel to depress the use of fuels based on fossil sources in the transport sector for sustainable clean energy strategy in future. By replacing the primary fuel with hydrogen fuel produced using renewable sources in road transport sector, environmental benefits can be achieved. In the present study, techno-economic analysis of hydrogen refuelling station powered by wind-photovoltaics (PV) hybrid power system to be installed in ?zmir-Çe?me, Turkey is performed. This analysis is carried out to a design of hydrogen refuelling station which is refuelling 25 fuel cell electric vehicles on a daily basis using hybrid optimisation model for electric renewable (HOMER) software. In this study, National Aeronautics and Space Administration (NASA) surface meteorology and solar energy database were used. Therefore, the average wind speed during the year was assessed to be 5.72 m/s and the annual average solar irradiation was used to be 5.08 kW h/m²/day for the considered site. According to optimisation results obtained for the proposed configuration, the levelised cost of hydrogen production was found to be US $7.526–7.866/kg in different system configurations. These results show that hydrogen refuelling station powered by renewable energy is economically appropriate for the considered site. It is expected that this study is the pre-feasibility study and obtained results encougare the hydrogen refuelling station to be established in Turkey by inventors or public institutions.     

A dynamic MOPSO algorithm for multiobjective optimal design of hybrid renewable energy systems

In this paper, a dynamic multiobjective particle swarm optimization (DMOPSO) method is presented for the optimal design of hybrid renewable energy systems (HRESs). The main goal of the design is to minimize simultaneously the total net present cost (NPC) of the system, unmet load, and fuel emission. A DMOPSO‐simulation based approach has been used to approximate a worthy Pareto front (PF) to help decision makers in selecting an optimal configuration for an HRES. The proposed method is examined for a case study including wind turbines, photovoltaic (PV) panels, diesel generators, batteries, fuel cells, electrolyzer, and hydrogen tanks. Well‐known metrics are used to evaluate the generated PF. The average spacing and diversification metrics obtained by the proposed approach are 1386 and 4656, respectively. Additionally, the set coverage metric value shows that at least 67% of Pareto solutions obtained by DMOPSO dominate the solutions resulted by other reported algorithms. By using a sensitivity analysis for the case study, it is found that if the PV panel and wind turbine capital cost are decreased by 50%, the total NPC of the system would be decreased by 18.8 and 3.7%, respectively. Copyright © 2014 John Wiley & Sons, Ltd.