Prospects of hydrogen production potential from renewable resources in Algeria

Hydrogen production from renewable energies is a key part in the energy transition to realize a sustainable energy economy for both developed and developing nations. For Algeria, successful energy transition toward a hydrogen economy will require the establishment of its potential. This study was conducted to estimate the potential for producing hydrogen from renewable resources in Algeria. The renewable energies considered are: solar photovoltaic and wind. To accomplish this objective, first, we analyzed renewable resource data both statistically and graphically using Geographical Information System (GIS), a computer-based information system utilized to create and visualize the spatial distribution of the geographic information. Then, the study will evaluate the availability of renewable electricity production potential from these key renewable resources. The potential for the hydrogen production, via the electrolysis process with wind and solar photovoltaic electricity, is described with maps showing it per unit area in each region. Finally, the results of the estimated hydrogen potential from both resources for each region are compared and significant conclusions are drawn.     

Energy supply for water electrolysis systems using wind and solar energy to produce hydrogen: a case study of Iran

Due to acute problems caused by fossil fuels that threaten the environment, conducting research on other types of energy carriers that are clean and renewable is of great importance. Since in the past few years hydrogen has been introduced as the future fuel, the aim of this study is to evaluate wind and solar energy potentials in prone areas of Iran by the Weibull distribution function (WDF) and the Angstrom-Prescott (AP) equation for hydrogen production. To this end, the meteorological data of solar radiation and wind speed recorded at 10 m height in the time interval of 3 h in a five-year period have been used. The findings indicate that Manjil and Zahedan with yearly wind and solar energy densities of 6004 (kWh/m²) and 2247 (kWh/m²), respectively, have the greatest amount of energy among the other cities. After examining three different types of commercial wind turbines and photovoltaic (PV) systems, it becomes clear that by utilizing one set of Gamesa G47 turbine, 91 kg/d of hydrogen, which provides energy for 91 car/week, can be produced in Manjil and will save about 1347 L of gasoline in the week. Besides, by installing one thousand sets of X21-345 PV systems in Zahedan, 20 kg/d of hydrogen, enough for 20 cars per week, can be generated and 296 L of gasoline can be saved. Finally, the RETScreen software is used to calculate the annual CO₂ emission reduction after replacing gasoline with the produced hydrogen.     

A production economics analysis for quantifying the efficiency of wind turbines

We quantify the productive efficiency of a wind turbine, using power output and environmental variable data, measured either at the turbine or at a meteorological mast near the turbine. The methods described can potentially help with decision makings in asset procurement, maintenance planning, or wind turbine control optimization. The current recommendation from the International Electrotechnical Commission regarding turbine performance evaluation is to use a power curve or power coefficient. What is commonly used in practice is the average performance power curve or power coefficient. When using the power curve to quantify productive efficiency, one crucial shortcoming is the lack of a common best performance benchmark, while the power coefficient approach uses an absolute efficiency measure that is not achievable. We introduce a new approach for efficiency quantification based upon production economics' concepts which provides estimates of a best performance benchmark. Our specific approach has two main components: (a) a best performance power curve is estimated and used together with the average performance curve to show how well a turbine has performed relative to its full potential; and (b) a covariate matching procedure is developed to control for environmental influences for the comparison of turbine performances over different periods. Through a simulation study, we demonstrate that the proposed efficiency is more sensitive to potential changes in the turbine. When analyzing multi‐year wind turbine data, we observe that the turbine's efficiency is improving during the first 2 years of operation and then remains relatively constant during years 3 and 4. Copyright © 2017 John Wiley & Sons, Ltd.     

Nonlinear system identification for model-based condition monitoring of wind turbines

This paper proposes a data driven model-based condition monitoring scheme that is applied to wind turbines. The scheme is based upon a non-linear data-based modelling approach in which the model parameters vary as functions of the system variables. The model structure and parameters are identified directly from the input and output data of the process. The proposed method is demonstrated with data obtained from a simulation of a grid-connected wind turbine where it is used to detect grid and power electronic faults. The method is evaluated further with SCADA data obtained from an operational wind farm where it is employed to identify gearbox and generator faults. In contrast to artificial intelligence methods, such as artificial neural network-based models, the method employed in this paper provides a parametrically efficient representation of non-linear processes. Consequently, it is relatively straightforward to implement the proposed model-based method on-line using a field-programmable gate array.     

Potential of renewable hydrogen production for energy supply in Hong Kong

Hong Kong is highly vulnerable to energy and economic security due to the heavy dependence on imported fossil fuels. The combustion of fossil fuels also causes serious environmental pollution. Therefore, it is important to explore the opportunities for clean renewable energy for long-term energy supply. Hong Kong has the potential to develop clean renewable hydrogen energy to improve the environmental performance. This paper reviews the recent development of hydrogen production technologies, followed by an overview of the renewable energy sources and a discussion about potential applications for renewable hydrogen production in Hong Kong. The results show that although renewable energy resources cannot entirely satisfy the energy demand in Hong Kong, solar energy, wind power, and biomass are available renewable sources for significant hydrogen production. A system consisting of wind turbines and photovoltaic (PV) panels coupled with electrolyzers is a promising design to produce hydrogen. Biomass, especially organic waste, offers an economical, environmental-friendly way for renewable hydrogen production. The achievable hydrogen energy output would be as much as 40% of the total energy consumption in transportation.     

Investigation of the socio-economic feasibility of installing wind turbines to produce hydrogen: Case study

The objective of this study is to socially and economically investigate installation of wind turbines in Iran in order to produce hydrogen using its electricity. Due to adequate condition of wind blow in Manjil, Zabol, and Ardebil, these cities were chosen as the case studies and sample society. To scrutinize the acceptance of wind power among the sample members, first, data was gathered through questionnaires and analyzed by Partial Least Squares (PLS) approach to Structural Equations Modeling (SEM). The results showed that the first hypothesis (H1), positive effect of financial condition of households on wind power acceptance, was rejected with the coefficient of 1.184. On the other hand, the second hypothesis (H2) was approved with a meaningful coefficient of 3.159, that is, the social awareness of wind energy has a positive effect on its acceptance as an electricity generating source. Costs and Incomes Chart was utilized to estimate the payback period of investing in the wind power site project. Five wind turbines with different nominal capacities were tested and the results showed that the payback period for Manjil is shorter than that of others’ in a way that for turbines with 5, 30, 50, 60 and 100 kW nominal capacity is 3.1, 2.4, 2.3, 1.9, 2.6 years respectively. Finally, Hummer H25.0–60 KW wind turbine was selected due to its payback time which was less than other turbines to estimate the amount of hydrogen produced. The results showed that with installing one set of this turbine in Manjil, Zabol, and Ardebil 7.12, 5.82 and 5.72 ton hydrogen per year will be produced, respectively.     

Dynamic planning,conversion, and management strategy of different renewable energy sources: A Sustainable Solution for Severe Energy Crises in Emerging Economies

Green hydrogen energy is a natural substitute for fuel-based energy and it increases a country's long-term energy safety. Pakistan has been a victim of a severe energy crisis for the past few decades. In this context, this research addresses green hydrogen generation and renewable energy supply (i.e., wind, solar, biomass, public waste, geothermal and small hydropower) as an alternate energy source in Pakistan. The assessment is carried out through a two-step framework (i.e., Fuzzy-AHP and non-parametric DEA). Results show that Pakistan has abundant renewable power capacity from wind, which the light-duty transport in the country can opt. Almost 4.89 billion gallons of fuel are consumed annually in Sindh, whereas Punjab uses up around 6.92 billion gallons of fuel annually, which need to be substituted with 1.63 billion kg and 2.31 billion kg of wind-produced hydrogen, respectively. It has been discovered that solar and wind energy attain the same criterion of weights (i.e., 0.070) in-line with the commercial potential criterion. Besides, wind-generated power is ideal for green hydrogen generation in Pakistan, and the subsequent choice for green hydrogen energy is small hydropower and solar, which are also good for green hydrogen generation in the country. Hence, this research offers a solid recommendation for the use of wind energy, which is ideal for the production of Green Hydrogen energy in the country.     

A novel adaptative maximum power point tracking algorithm for small wind turbines

A novel maximum power point tracking algorithm for small wind turbines is proposed. The solution presented here is an adaptive intelligent algorithm that uses a new advanced perturb and observe method to search for the optimum relationship of the system for tracking the maximum power point even under variable wind conditions. The validity of the proposed algorithm is analysed and the design procedure is presented. Its main virtue resides in its capability to adapt to changes in the turbine and in the surrounding environment, even under variable wind conditions, improving the efficiency of the system. The experimental results confirm the validity of the proposed algorithm.     

Model‐based fault detection for generator cooling system in wind turbines using SCADA data

In this work, an early fault detection system for the generator cooling of wind turbines is presented and tested. It relies on a hybrid model of the cooling system. The parameters of the generator model are estimated by an extended Kalman filter. The estimated parameters are then processed by an appropriate statistical change detection algorithm in order to detect faults in the cooling system. To validate the method, it has been tested on 3 years of historical data from 43 turbines. During the testing period, 16 faults occurred; 15 of these were detected by the developed method, and one false alarm was issued. This is an improvement compared with the current system that gives 15 detections and more than 10 false alarms. In some cases, the method detects the fault a long time before the turbine reports an alarm. A further advantage of the method is that it is based on supervisory control and data acquisition data that are available for the operator of all modern turbines. Thereby, the method can be implemented without the need to modify or install additional components in the turbines. Copyright © 2015 John Wiley & Sons, Ltd.     

Opportunities and challenges for thermally driven hydrogen production using reverse electrodialysis system

Ongoing and emerging renewable energy technologies mainly produce electric energy and intermittent power. As the energy economy relies on banking energy, there is a rising need for chemically stored energy. We propose heat driven reverse electrodialysis (RED) technology with ammonium bicarbonate (AmB) as salt for producing hydrogen. The study provides the authors’ perspective on the commercial feasibility of AmB RED for low grade waste heat (333 K–413 K) to electricity conversion system. This is to our best of knowledge the only existing study to evaluate levelized cost of energy of a RED system for hydrogen production. The economic assessment includes a parametric study, and a scenario analysis of AmB RED system for hydrogen production. The impact of various parameters including membrane cost, membrane lifetime, cost of heating, inter-membrane distance and residence time are studied. The results from the economic study suggests, RED system with membrane cost less than 2.86 €/m², membrane life more than 7 years and a production rate of 1.19 mol/m²/h or more are necessary for RED to be economically competitive with the current renewable technologies for hydrogen production. Further, salt solubility, residence time and inter-membrane distance were found to have impact on levelized cost of hydrogen, LCH. In the present state, use of ammonium bicarbonate in RED system for hydrogen production is uneconomical. This may be attributed to high membrane cost, low (0.72 mol/m²/h) hydrogen production rate and large (1,281,436 m²) membrane area requirements. There are three scenarios presented the present scenario, market scenario and future scenario. From the scenario analysis, it is clear that membrane cost and membrane life in present scenario controls the levelized cost of hydrogen. In market scenario and future scenario the hydrogen production rate (which depends on membrane properties, inter-membrane distance etc.), the cost of regeneration system and the cost of heating controls the levelized cost of hydrogen. For a thermally driven RED system to be economically feasible, the membrane cost not more than 20 €/m²; hydrogen production rate of 3.7 mol/m²/h or higher and cost of heating not more than 0.03 €/kWh for low grade waste heat to hydrogen production.     

Co-production of electricity and hydrogen from wind: A comprehensive scenario-based techno-economic analysis

The aim of this study is to investigate the economic prospects of producing electricity and hydrogen using wind energy under different scenarios. For this, the most essential criteria to investors including Levelized Cost of Wind-generated Electricity (LCOWE), Levelized Cost of Wind-based Hydrogen (LCOWH), payback period, and rate of return are examined. Technical and environmental impacts are factored into the LCOWE formulation to obtain comprehensive insight. Owing to the uncertain nature of future, five degradation rates concerned with wind turbine performance and five likely rates as to the future value of money are investigated under the scenarios of I) utilizing wind electricity to replace fuel oil electricity, II) to replace natural gas electricity and III) without considering environmental penalties. The results indicate that LCOWE would be in the range of 0.0325–0.0755 $/kWh, while the corresponding LCOWH being in the range of 1.375–1.59 $/kg. Moreover, payback period of the related LCOWE and LCOWH would be in the range of 2.55–9.48 yr during the lifetime of wind power plant and 3.91–8.41 yr during that of hydrogen production system, respectively. The corresponding rate of return pertinent to the above-mentioned ones would be respectively in the range of 14.15–23.54% and of 9.87–21.55%.     

Utilization of machine‐learning algorithms for wind turbine site suitability modeling in Iowa,USA

Because of the current shift away from fossil fuels and toward renewable energy sources, it is necessary to plan for the installation of new infrastructure to meet the demand for clean energy. Traditional methods for determining wind turbine site suitability suffer from the selection of arbitrary criteria and model parameters by experts, which may lead to a degree of uncertainty in the models produced. An alternative empirically based methodology for building a wind turbine siting model for the state of Iowa is presented in the study. We employ ‘ecological niche’ principles traditionally utilized to model species allocation to develop a new multicriteria, spatially explicit framework for wind turbine placement. Using information on suitability conditions at existing turbine locations, we incorporate seven variables (wind speed, elevation, slope, land cover, distance of infrastructure and settlements, and population density) into two machine‐learning algorithms [maximum entropy method (Maxent) and Genetic Algorithm for Rule Set Prediction (GARP)] to model suitable areas for installation of wind turbines. The performance of this method is tested at the statewide level and a six‐county region in western Iowa. Maxent and GARP identified areas in the Northwest and North Central regions of Iowa as the optimum location for new wind turbines. Information on variable contributions from Maxent illuminates the relative importance of environmental variables and its scale‐dependent nature. It also allows validating existing assumptions about the relationship between variables and wind turbine suitability. The resultant models demonstrate high levels of accuracy and suggest that the presented approach is a possible methodology for developing wind turbine siting applications. Copyright © 2014 John Wiley & Sons, Ltd.     

Dynamic model of wind energy conversion systems with PMSG-based variable-speed wind turbines for power system studies

In order to study the impact of a wind farm on the dynamics of the power system, a significant issue is to develop appropriate equivalent models that allow characterizing the dynamics of all individual wind turbine generators (WTGs) composing the park. In this sense, with the advance of power electronics, direct-driven permanent magnet synchronous generators (PMSGs) have drawn increased interest to wind turbine manufacturers due to their advantages over other variable-speed WTGs. These include the possibility of multi-pole design with a gearless construction that offers slow speed operation and reduced maintenance since no brushes are used, elimination of the excitation system, full controllability for maximum wind power extraction and grid interface, and easiness in accomplishing fault-ride through and grid support. In this way, this paper presents a comprehensive dynamic equivalent model of a wind farm with direct-driven PMSG wind turbines using full-scale converters and its control scheme. The proposed simplified modelling is developed using the state-space averaging technique and is implemented in the MATLAB/Simulink environment. The dynamic performance of the wind farm and its impact on the power system operation is evaluated using the phasor simulation method.     

An artificial neural network‐based condition monitoring method for wind turbines,with application to the monitoring of the gearbox

Major failures in wind turbines are expensive to repair and cause loss of revenue due to long downtime. Condition‐based maintenance, which provides a possibility to reduce maintenance cost, has been made possible because of the successful application of various condition monitoring systems in wind turbines. New methods to improve the condition monitoring system are continuously being developed. Monitoring based on data stored in the supervisory control and data acquisition (SCADA) system in wind turbines has received attention recently. Artificial neural networks (ANNs) have proved to be a powerful tool for SCADA‐based condition monitoring applications. This paper first gives an overview of the most important publications that discuss the application of ANN for condition monitoring in wind turbines. The knowledge from these publications is utilized and developed further with a focus on two areas: the data preprocessing and the data post‐processing. Methods for filtering of data are presented, which ensure that the ANN models are trained on the data representing the true normal operating conditions of the wind turbine. A method to overcome the errors from the ANN models due to discontinuity in SCADA data is presented. Furthermore, a method utilizing the Mahalanobis distance is presented, which improves the anomaly detection by considering the correlation between ANN model errors and the operating condition. Finally, the proposed method is applied to case studies with failures in wind turbine gearboxes. The results of the application illustrate the advantages and limitations of the proposed method. Copyright © 2017 John Wiley & Sons, Ltd.     

Feasibility assessment of wind energy resources in Malaysia based on NWP models

There is a common belief that countries located in the doldrums with prevailing monotonous weather, characterized by light winds, cannot harness the wind for feasible energy production. This paper reexamines such a belief and presents a novel approach to assess the techno-economic potential of wind turbine generator sites in Malaysia, which lies in the equatorial, low wind speed doldrums. Dissimilar to other techniques that account for planetary-scale winds only, a numerical weather prediction (NWP) prospecting tool for mesoscale winds is used to forecast the wind characteristics. Potential sites from the forecasting studies are further investigated for economic feasibility by using a commercial wind turbine generator and a financial analysis method. From the economic analysis, it is found that unlike what is widely touted, there is an actual potential of wind energy in Malaysia, manifested through the several economically viable wind turbine generating sites.     

Prioritizing of wind farm locations for hydrogen production: A case study

Many advantages of renewable energies, especially wind energy, such as abundance, permanence, and lack of pollution has encouraged many industrialized and developing countries to focus more on these clean and economic sources of energy. Identifying a good location that is suitable for the construction of a wind farm is one of the important initial steps in harnessing wind energy which is assessed this study. The purpose of this study is to prioritize and rank 13 cities of Fars province in Iran, in terms of their suitability for the construction of a wind farm. Six important criteria were used to prioritize and rank the cities. Wind power density is the most important criterion among these criteria which is calculated by obtaining the 3-h wind speed data between 2004 and 2013. DEA (Data Envelopment Analysis) method is used for prioritizing and ranking cities, and then AHP (Analytical Hierarchy Process), and FTOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) methods are used to assess the validity of results. It is concluded that Izadkhast city is the suggested location for the construction of wind farm. The utilizing a wind-hydrogen energy conversion system will result in a substantial amount of hydrogen production (averagely 21.9 ton/year) when a 900 kW wind turbine is installed in this location.     

Design,modelling and optimal power and hydrogen management strategy of an off grid PV system for hydrogen production using methanol electrolysis

Hydrogen used as an energy carrier and chemical element can be produced by several processes such as gasification of coal and biomass, steam reforming of fossil fuel and electrolysis of water. Each of these methods has its own advantage and disadvantage. Electrolysis process is seen as the best option for quick hydrogen production. Hydrogen generation by methanol electrolysis process (MEP) gained much attention since it guarantees high purity gas and can be compatible with renewable energies. Furthermore, due to its very low theoretical potential (0.02 V), MEP can save more than 65% of electrical energy required to produce 1 kg of hydrogen compared to water electrolysis process (WEP). Electrolytic hydrogen production using solar photovoltaic (PV) energy is positioned to become as one of the preferred options due to the harmful environmental impacts of widely used methane steam reforming process and also since the prices of PV modules are more competitive.In this paper, hydrogen production by MEP using PV energy is investigated. A design of an off grid PV/battery/MethElec system is proposed. Mathematical models of each component of the system are presented. Semi-empirical relationship between hydrogen production rate and power consumption at 80 °C and 4 M concentration is developed. Optimal power and hydrogen management strategy (PHMS) is designed to achieve high system efficiency and safe operation. Case studies are carried out on two tilts of PV array: horizontal and tilted at 36° using measured meteorological data of solar irradiation and ambient temperature of Algiers site. Simulation results reveal great opportunities of hydrogen production using MEP compared to the WEP with 22.36 g/m² d and 24.38 g/m² d of hydrogen when using system with horizontal and tilted PV array position, respectively.     

Performance analysis of various hybrid renewable energy systems using battery,hydrogen, and pumped hydro‐based storage units

The aim of this research is to analyze the techno‐economic performance of hybrid renewable energy system (HRES) using batteries, pumped hydro‐based, and hydrogen‐based storage units at Sharurah, Saudi Arabia. The simulations and optimization process are carried out for nine HRES scenarios to determine the optimum sizes of components for each scenario. The optimal sizing of components for each HRES scenario is determined based on the net present cost (NPC) optimization criterion. All of the nine optimized HRES scenarios are then evaluated based on NPC, levelized cost of energy, payback period, CO₂ emissions, excess electricity, and renewable energy fraction. The simulation results show that the photovoltaic (PV)‐diesel‐battery scenario is economically the most viable system with the NPC of US$2.70 million and levelized cost of energy of US$0.178/kWh. Conversely, PV‐diesel‐fuel cell system is proved to be economically the least feasible system. Moreover, the wind‐diesel‐fuel cell is the most economical scenario in the hydrogen‐based storage category. PV‐wind‐diesel‐pumped hydro scenario has the highest renewable energy fraction of 89.8%. PV‐wind‐diesel‐pumped hydro scenario is the most environment‐friendly system, with an 89% reduction in CO₂ emissions compared with the base‐case diesel only scenario. Overall, the systems with battery and pumped hydro storage options have shown better techno‐economic performance compared with the systems with hydrogen‐based storage.     

Reliability of wind turbines modeled by a Poisson process with covariates,unobserved heterogeneity and seasonality

Reliability of wind turbines is analyzed with the use of an easily interpretable mathematical model based on a Poisson process, which takes into account jointly observable differences between turbines described by covariates (type of turbine, size of turbine, harshness of environment, installation date and seasonal effects) as well as unobservable differences modeled by a standard frailty approach known from survival analysis. The introduced model is applied to failure data from the WMEP database, and the fit of the model is checked. The paper demonstrates the usefulness of the model for determination of critical factors of wind turbine reliability, with potential for prediction for future installations. In particular, the model's ability to take into account unobserved heterogeneity is demonstrated. The model can easily be adapted for use with different datasets or for analysis of other repairable systems than wind turbines. Copyright © 2016 John Wiley & Sons, Ltd.     

Evaluation of hydrogen production by wind energy for agricultural and industrial sectors

Wind power potential by itself is not a good indicator of the suitability of a region for wind power generation for different purposes. Economic attractiveness is a better indicator in this regard as it stimulates the involvement of private businesses in this sector. Naturally, the shorter is the payback period or the time required to reach profitability, the more attractive will be the project. Considering the high wind energy potential of some regions of Iran, this study evaluates the wind energy available for generating electricity as well as hydrogen by industrial and agricultural sectors in four cities of Ardebil province, namely Ardebil, Khalkhal, Namin, and Meshkinshahr, and then conducts an econometric analysis accordingly. Wind power potentials are evaluated using the energy pattern factor and Weibull distribution function based on 5-year meteorological data of the studied regions. Economic evaluations are performed based on the present worth of incomes and costs, which are estimated for two models of wind turbines with 3.5 and 100 KW rated power. Results indicate that the cities of Namin and Ardebil with wind power densities of respectively 261.68 and 258.99 W/m² have the best condition. The economic analysis conducted for turbines shows that for Ardebil, installation of the 3.5 KW and 100 KW turbines will have a payback period of 13 and 5 years, respectively. For Khalkhal, Namin, and Meshkinshahr, the only feasible option is installation of the 100 KW turbine, which would result in a payback period of respectively 10.2, 6.1 and 8.7 years. Then it is investigated how much hydrogen can be gained if these private sectors invest in producing hydrogen using nominated wind turbines.