Hydrogenases and photobiological hydrogen production utilizing nitrogenase system in cyanobacteria

We constructed three hydrogenase mutants from Anabaena sp. PCC 7120: ΔhupL (deficient in uptake hydrogenase), ΔhoxH (deficient in bidirectional hydrogenase), and ΔhupL/ΔhoxH (deficient in both genes), and showed that the Δhup and ΔhupL/ΔhoxH produced H₂ at a rate 4–7 times that of wild-type under optimal conditions (Appl. Microbiol. Biotechnol. 58 (2002) 618). We have studied H₂ producing activity of Δhup in more detail. H₂ producing activity of Δhup cells was moderately improved in older cultures when 1% CO₂ was added to the bubbling air. The efficiency of light energy conversion to H₂ by the ΔhupL mutant at its highest H₂ production stage was 1.0–1.6% at an actinic visible light intensity of lower than 50 W/m² under argon atmosphere, and the activity lasted for at least 35 min. At 250 W/m², H₂ producing activity gradually decreased with illumination time.     

Modelling and measurements of power losses and turbulence intensity in wind turbine wakes at Middelgrunden offshore wind farm

Understanding of power losses and turbulence increase due to wind turbine wake interactions in large offshore wind farms is crucial to optimizing wind farm design. Power losses and turbulence increase due to wakes are quantified based on observations from Middelgrunden and state‐of‐the‐art models. Observed power losses due solely to wakes are approximately 10% on average. These are relatively high for a single line of wind turbines due in part to the close spacing of the wind farm. The wind farm model Wind Analysis and Application Program (WAsP) is shown to capture wake losses despite operating beyond its specifications for turbine spacing. The paper describes two methods of estimating turbulence intensity: one based on the mean and standard deviation (SD) of wind speed from the nacelle anemometer, the other from mean power output and its SD. Observations from the nacelle anemometer indicate turbulence intensity which is around 9% higher in absolute terms than those derived from the power measurements. For comparison, turbulence intensity is also derived from wind speed and SD from a meteorological mast at the same site prior to wind farm construction. Despite differences in the measurement height and period, overall agreement is better between the turbulence intensity derived from power measurements and the meteorological mast than with those derived from data from the nacelle anemometers. The turbulence in wind farm model indicates turbulence increase of the order 20% in absolute terms for flow directly along the row which is in good agreement with the observations. Copyright © 2007 John Wiley & Sons, Ltd.     

Optimizing hybrid offshore wind farms for cost-competitive hydrogen production in Germany

Nearly 96% of the world's current hydrogen production comes from fossil-fuel-based sources, contributing to global greenhouse gas emissions. Hydrogen is often discussed as a critical lever in decarbonizing future power systems. Producing hydrogen using unsold offshore wind electricity may offer a low-carbon production pathway and emerging business model. This study investigates whether participating in an ancillary service market is cost competitive for offshore wind-based hydrogen production. It also determines the optimal size of a hydrogen electrolyser relative to an offshore wind farm. Two flexibility strategies for offshore wind farms are developed in this study: an optimal bidding strategy into ancillary service markets for offshore wind farms that build hydrogen production facilities and optimal sizing of Power-to-Hydrogen (PtH) facilities at wind farms. Using empirical European power market and wind generation data, the study finds that offshore-wind based hydrogen must participate in ancillary service markets to generate net positive revenues at current levels of wind generation to become cost competitive in Germany. The estimated carbon abatement cost of “green” hydrogen ranges between 187 EUR/tonCO₂e and 265 EUR/tonCO₂e. Allowing hydrogen producers to receive similar subsidies as offshore wind farms that produce only electricity could facilitate further cost reduction. Utilizing excess and intermittent offshore wind highlights one possible pathway that could achieve increasing returns on greenhouse gas emission reductions due to technological learning in hydrogen production, even under conditions where low power prices make offshore wind less competitive in the European electricity market.     

Life cycle assessment of the offshore wind farm alpha ventus

Due to better wind conditions at sea, offshore wind farms have the advantage of higher electricity production compared to onshore and inland wind farms. In contrast, a greater material input, leading to increased energy consumptions and emissions during the production phase, is required to build offshore wind farms. These contrary effects are investigated for the first German offshore wind farm alpha ventus in the North Sea. In a life cycle assessment its environmental influence is compared to that of Germany’s electricity mix.In comparison to the mix, alpha ventus had better indicators in nearly every investigated impact category. One kilowatt-hour electricity, generated by the wind farm, was burdened with 0.137 kWh Primary Energy-Equivalent and 32 g CO₂-Equivalent, which represented only a small proportion of the accordant values for the mix. Furthermore, the offshore foundations as well as the submarine cable were the main energy intensive components. The energetic and greenhouse gas payback period was less than one year.Therefore, offshore wind power, even in deep water, is compatible with the switch to sustainable electricity production relying on renewable energies. Additional research, taking backup power plants as well as increasingly required energy storage systems into account, will allow further calculation.     

Two-dimensional simulation and critical efficiency analysis of high-temperature steam electrolysis system for hydrogen production

High-temperature steam electrolysis (HTSE) is a promising method for highly efficient large-scale hydrogen production. The HTSE process not only reduces the amount of thermodynamic electrical energy requirement but also decreases the polarization losses, which improves the overall efficiency of hydrogen production.In this paper, a two-dimensional simulation method of the efficiency of the HTSE system integrated with high-temperature gas-cooled nuclear reactor (HTGR), which changes two parameters simultaneously in a reasonable range while keeping one parameter constant, was presented. Compared with one-dimensional analysis method, the effects of electrical efficiency (η_el), electrolysis efficiency (η_es,), and thermal efficiency (η_th) on overall efficiency (η_overall) were investigated more objectively and accurately. Moreover, the critical concepts of η_es and η_th were put forward originally, which were very important to determine the optimum electrolysis voltages and operation temperatures in the actual HTSE processes. The calculated critical value of η_es was ΔG(T)/ΔH(T) and the actual η_es should be higher than the theoretically calculated one in order to maintain the high hydrogen production efficiency of HTSE system. Also, it was very interesting to find that the critical η_es was the theoretical maximum efficiency in SOFC mode. Furthermore, the critical value of η_th was equal to the value of η_el, which means the overall efficiency decreases with the η_es increasing if the η_th in the actual HTSE process is less than the critical value of η_th. Therefore, it is very important to control the η_th higher than the critical value in the actual HTSE process to get high overall system efficiency.     

Wind farm site selection from the perspective of sustainability: A novel satisfaction degree‐based fuzzy axiomatic design approach

As a clean and renewable energy resource, wind energy is the most mature, environmentally friendly, and most commercially developed new energy resource in the world. Therefore, it is of great importance to determine the best location of wind farms to ensure the sustainable development of wind energy. However, since wind farm site selection often involves multiple criteria, which include qualitative and quantitative criteria, there may be conflicts between these criteria, so wind farm site selection is a complex multi‐criteria decision‐making (MCDM) problem. Therefore, the objective of this study is to propose a novel integrated MCDM approach using a fuzzy analytic hierarchy process and satisfaction degree‐based fuzzy axiomatic design (AD) to determine the optimal onshore wind farm site under a hybrid decision information environment. First, based on the literature review and experts' opinion, the evaluation index system for wind farm site selection is built from a sustainable perspective, which includes geographic, technical, economic, social, and environmental criteria. Second, fuzzy analytic hierarchy process is applied to determine criteria weights. Third, the satisfaction degree‐based fuzzy AD is employed to evaluate and rank alternatives under a hybrid decision information environment. Finally, a case study is used to illustrate the reliability and advantages of the method proposed in this paper. In addition, the information content of each alternative is calculated by aggregating the evaluation matrix of experts, and the results are IC₁ = 0.058, IC₂ = 0.096, IC₃ = 0.16, IC₄ = ∞, IC₅ = ∞, and IC₆ = 0.226. Then the satisfaction degree of each alternative is S₁ = 0.629, S₂ = 0.545, S₃ = 0.501, S₄ = 416, S₅ = 389, and S₆ = 0.463. Thus, the best wind farm site is A₁. Moreover, the results show that the method proposed herein is flexible and can effectively deal with the wind farm site selection problem. Although this paper chooses China as a case study, the proposed method herein is also applicable to other countries or regions.     

Optimization of turbine design in wind farms with multiple hub heights,using exact analytic gradients and structural constraints

Wind farms are generally designed with turbines of all the same hub height. If wind farms were designed with turbines of different hub heights, wake interference between turbines could be reduced, lowering the cost of energy (COE). This paper demonstrates a method to optimize onshore wind farms with two different hub heights using exact, analytic gradients. Gradient‐based optimization with exact gradients scales well with large problems and is preferable in this application over gradient‐free methods. Our model consisted of the following: a version of the FLOw Redirection and Induction in Steady‐State wake model that accommodated three‐dimensional wakes and calculated annual energy production, a wind farm cost model, and a tower structural model, which provided constraints during optimization. Structural constraints were important to keep tower heights realistic and account for additional mass required from taller towers and higher wind speeds. We optimized several wind farms with tower height, diameter, and shell thickness as coupled design variables. Our results indicate that wind farms with small rotors, low wind shear, and closely spaced turbines can benefit from having two different hub heights. A nine‐by‐nine grid wind farm with 70‐meter rotor diameters and a wind shear exponent of 0.08 realized a 4.9% reduction in COE by using two different tower sizes. If the turbine spacing was reduced to 3 diameters, the reduction in COE decreased further to 11.2%. Allowing for more than two different turbine heights is only slightly more beneficial than two heights and is likely not worth the added complexity.     

Active wake control: An approach to optimize the lifetime operation of wind farms

The wind turbines within a wind farm impact each other's power production and loads through their wakes. Wake control strategies, aiming to reduce wake effects, receive increasing interest by both the research community and the industry. A number of recent simulation studies with high fidelity wake models indicate that wake mitigation control is a very promising concept for increasing the power production of a wind farm and/or reducing the fatigue loading on wind turbines' components. The purpose of this paper is to study the benefits of wake mitigation control in terms of lifetime power production and fatigue loading on several existing full‐scale commercial wind farms with different scale, layouts, and turbine sizes. For modeling the wake interactions, Energy Research Centre of the Netherlands' FarmFlow software is used: a 3D parabolized Navier‐Stokes code, including a k‐? turbulence model. In addition, an optimization approach is proposed that maximizes the lifetime power production, thereby incorporating the fatigue loads into the optimization criterion in terms of a lifetime extension factor.     

Wake effect in wind farm performance: Steady-state and dynamic behavior

The aim of this paper is to evaluate the impact of the wake effect on both the steady-state operation and dynamic performance of a wind farm and provide conclusions that can be used as thumb rules in generic assessments where the full details of the wind farms are unknown. A simplified explicit model of the wake effect is presented, which includes: the cumulative impact of multiple shadowing, the effects of wind direction and the wind speed time delay. The model is implemented in MATLAB^® and then integrated into a power system simulation package to describe the wake effect and its impact on a wind farm, particularly in terms of the wake coefficient and overall active power losses. Results for two wind farm layouts are presented to illustrate the importance of wind turbine spacing and the directionality of wind speeds when assessing the wake effect during steady-state operation and dynamic behavior.     

An evaluation of the predictive accuracy of wake effects models for offshore wind farms

Wake losses are perceived as one of the largest uncertainties in energy production estimates (EPEs) for new offshore wind projects. In recent years, significant effort has been invested to improve the accuracy of wake models. However, it is still common for a standard wake loss uncertainty of 50% to be assumed in EPEs for new offshore wind farms. This paper presents a body of evidence to support reducing that assumed uncertainty. It benchmarks the performance of four commonly used wake models against production data from five offshore wind farms. Three levels of evidence are presented to substantiate the performance of the models:

• Case studies, i.e. efficiencies of specific turbines under specific wind conditions;
• Array efficiencies for the wind farm as a whole for relatively large bins of wind speed and direction; and
• Validation wake loss, which corresponds to the overall wake loss within the proportion of the annual energy production where validation is possible.

The most important result for predicting annual energy production is the validation wake loss. The other levels of evidence demonstrate that this result is not unduly reliant on cancellation of errors between wind speed and/or wind direction bins. All of the root‐mean‐squared errors in validation wake loss are substantially lower than the 50% uncertainty commonly assumed in EPEs; indeed, even the maximum errors are below 25%. It is therefore concluded that there is a good body of evidence to support reducing this assumed uncertainty substantially, to a proposed level of 25%. Copyright © 2015 John Wiley & Sons, Ltd.     

Prospects of wind farm development in Saudi Arabia

This paper presents the energy output of wind farms in terms of unadjusted energy, gross energy, renewable energy delivered, specific yield and wind farm capacity factor. The analysis also includes the comparison of energy output from two methods: (i) the RETScreen model and (ii) the actual frequency and wind turbine power curve. The energy output analysis is done using three wind energy conversion systems of rated capacity 600, 1000, and 1500 kW. The study is performed for 30 MW installed capacity wind farms at five coastal locations in Saudi Arabia.Furthermore, the RETScreen software is also used to perform the economical feasibility study of the wind farms at these locations. The study concludes that of the five wind parks, Yanbo and Dhahran are the only two sites where wind park development is economically feasible. Finally, wind park development at Yanbo will result in a reduction in greenhouse gases of 31369, 23601, and 26087 tons each year, corresponding to 1500, 1000, and 600 kW machine wind parks, respectively. On the other hand, at Dhahran, installation of wind machines of 1500, 1000, and 600 kW sizes will reduce the GHGs by 26183, 19247, and 21533 tons per year.     

Power output variations of co-located offshore wind turbines and wave energy converters in California

The electric power generation of co-located offshore wind turbines and wave energy converters along the California coast is investigated. Meteorological wind and wave data from the National Buoy Data Center were used to estimate the hourly power output from offshore wind turbines and wave energy converters at the sites of the buoys. The data set from 12 buoys consists of over 1,000,000 h of simultaneous hourly mean wind and wave measurements. At the buoys, offshore wind farms would have capacity factors ranging from 30% to 50%, and wave farms would have capacity factors ranging from 22% to 29%. An analysis of the power output indicates that co-located offshore wind and wave energy farms generate less variable power output than a wind or wave farm operating alone. The reduction in variability results from the low temporal correlation of the resources and occurs on all time scales. Aggregate power from a co-located wind and wave farm achieves reductions in variability equivalent to aggregating power from two offshore wind farms approximately 500 km apart or two wave farms approximately 800 km apart. Combined wind and wave farms in California would have less than 100 h of no power output per year, compared to over 1000 h for offshore wind or over 200 h for wave farms alone. Ten offshore farms of wind, wave, or both modeled in the California power system would have capacity factors during the summer ranging from 21% (all wave) to 36% (all wind) with combined wind and wave farms between 21% and 36%. The capacity credits for these farms range from 16% to 24% with some combined wind and wave farms achieving capacity credits equal to or greater than a 100% wind farm because of their reduction in power output variability.     

Some aspects of fluctuating vertical wind shears

Fluctuating vertical shears of wind speed have been measured using anemometers on an array of towers. The statistical distributions of these shears are compared with formulas proposed by Fichtl and good agreement is found. A comparison of Fichtl's formula for σ_Δu, the standard deviation of the fluctuating shears, with a more empirical one proposed by Ramsdell shows that the latter is consistent with the former under the proper conditions. The probability of occurrence of extreme shears in speed is discussed. Fluctuating shears two or more times larger than the mean values are shown to occur frequently, and their likelihood increases as the mean measuring height increases if Δz is held fixed. These results are applicable for slightly unstable to neutral conditions over level, homogeneous terrain, and in the surface boundary layers. The normal distribution gives a useful lower bound on shear values. Probabilities of extreme shears as function of are given. σ_Δu is also shown to be affected by τ, the averaging time used for the shear measurements. Increasing τ from 0.2 to 4 sec can decrease σ_Δu by 25 per cent or more. The effects of τ on the probability of extreme events is shown.     

A new method for spatial allocation of turbines in a wind farm based on lightning protection efficiency

Existing studies of the spatial allocation of wind farms are typically based on turbine power generation efficiency and rarely consider the damage caused by lightning strikes. However, lightning damage seriously affects the economic performance of wind farms because of the high cost of repairing or replacing damaged blades. This paper proposes a method for the spatial optimization of multiple turbines based on lightning protection dependability. Firstly, the lightning protection efficiency of turbine blade protection systems is analyzed by combining the physical mechanisms of lightning leader progression with a conventional electro‐geometric model to develop an electro‐geometric model of turbine blades (EGMTB). Then, the optimized spatial allocation of multiple turbines in a wind farm is investigated using the EGMTB. The results are illustrated from an example wind farm with 1.5 MW turbines, which shows that the optimal spacing between two turbines perpendicular to the prevailing wind direction L_⊥ is 4R‐6R, where R is the length of a turbine blade. This spacing is shown to effectively shield turbine blades from lightning damage over a wide range of lightning currents (>26‐60 kA). Note that, the suggested L_⊥ will be smaller considering the influence of lightning polarity as it takes more difficulty developing upward leader (UL) in the condition of positive lightning striking. Experiments verify the effectiveness and correctness of this method.     

A simple analytical wind park model considering atmospheric stability

The analytical top‐down wind park model by Emeis and Frandsen 1 is enhanced by consistently making both the downward momentum flux and the momentum loss at the rough surface dependent on atmospheric stability. Specifying the surface roughness underneath the turbines in a wind farm in the model gives the opportunity to investigate principal differences between onshore and offshore wind parks, because the roughness length of the sea surface is two to three orders of magnitude lower than the roughness length of land surfaces. Implications for the necessary distance between single turbines in offshore wind farms and the distance between neighbouring wind parks are computed. It turns out from the model simulations that over smooth surfaces offshore the wind speed reduction at hub height in a wind farm is larger than over rough onshore surfaces given the same density of turbines within the park. Mean wind profiles within the park are also calculated from this model. Offshore wind farms must have a larger distance between each other in order to avoid shadowing effects of the upstream farm. Copyright © 2009 John Wiley & Sons, Ltd.     

An analysis of energy use and input costs for cotton production in Turkey

The aim of this study was to determine direct input energy and indirect energy in per hectare in cotton production and compare with input costs. The study also sought to analyse the effect of farm size. Data were collected from sixty five farmers using a face to face questionnaire. The sample farms were selected through a stratified random sampling technique. The results revealed that cotton production consumed a total of 49.73 GJha⁻¹ of which diesel energy consumption was 31.1% followed by fertilizer and machinery energy. Output–input energy ratio and energy productivity were 0.74 and 0.06 kg of cotton MJ⁻¹, respectively. Cost analysis showed that net return per kilogram of seed cotton was insufficient to cover costs of production in the research area. The most important cost items were labour, machinery costs, land rent and pesticide costs. Large farms were more successful in energy productivity, use efficiency and economic performance. It was concluded that energy management at farm level could be improved to give more efficient and economic use of energy.     

Electricity generation from the first wind farm situated at Ras Ghareb, Egypt

Egypt is one of the Red Sea and Mediterranean countries having windy enough areas, in particular along the coasts. The coastal location Ras Ghareb on the Red Sea has been investigated in order to know the wind power density available for electricity generation. To account for the wind potential variations with height, a new simple estimating procedure was introduced. This study has explicitly demonstrated the presence of high wind power density nearly 900 kW/m² per year at 100 m of altitude for this region. Indeed, the seasonal wind powers available are comparable to and sometimes higher than the power density in many European cities for wind electricity applications like Vindeby (Denmark) and also America.New technical analysis for wind turbine characteristics have been made using three types of commercial wind turbines possessing the same rotor diameter and rated power to choice the best wind machine suitable for Ras Ghareb station. As per the decreasing the cut-in wind speed for the wind turbine used, the availability factor increases for a given generator. That it could produce more energy output throughout the year for the location.The aim of this research, was to predict the electrical energy production with the cost analysis of a wind farm 150 MW total power installed at Ras Ghareb area using 100 wind turbines model (Repower MD 77) with 1.5 MW rated power. Additionally, this paper developed the methodology for estimating the price of each kWh electricity from the wind farms. Results show that this wind park will produce maximum energy of 716 GWh/year. The expected specific cost equal to 1.5 € cent/kWh is still less than and very competitive price with that produced from the wind farms in Great Britain and Germany and at the international markets of wind power. The important result derived from this study encourages several wind parks with hundreds of megawatts can be constructed at Ras Ghareb region.     

Review of research on autonomous wind farms and solar parks and their feasibility for commercial loads in hot regions

In the wake of rising cost of oil and fears of its exhaustion coupled with increased pollution, the governments world-wide are deliberating and making huge strides to promote renewable energy sources such as solar–photovoltaic (solar–PV) and wind energy. Integration of diesel systems with hybrid wind–PV systems is pursued widely to reduce dependence on fossil-fuel produced energy and to reduce the release of carbon gases that cause global climate change. Literature indicates that commercial/residential buildings in the Kingdom of Saudi Arabia (KSA) consume an estimated 10–40% of the total electric energy generated. The study reviews research work carried out world-wide on wind farms and solar parks. The work also analyzes wind speed and solar radiation data of East-Coast (Dhahran), KSA, to assess the technical and economic potential of wind farm and solar PV park (hybrid wind–PV–diesel power systems) to meet the load requirements of a typical commercial building (with annual electrical energy demand of 620,000 kWh). The monthly average wind speeds range from 3.3 to 5.6 m/s. The monthly average daily solar global radiation ranges from 3.61 to 7.96 kWh/m². The hybrid systems simulated consist of different combinations of 100 kW wind machines, PV panels, supplemented by diesel generators. NREL (and HOMER Energy's) HOMER software has been used to perform the techno-economic study. The simulation results indicate that for a hybrid system comprising of 100 kW wind capacity (37 m hub-height) and 40 kW of PV capacity together with 175 kW diesel system, the renewable energy fraction (with 0% annual capacity shortage) is 36% (24% wind + 12% PV). The cost of generating energy (COE, $/kWh) from this hybrid wind–PV–diesel system has been found to be 0.154 $/kWh (assuming diesel fuel price of 0.1$/L). The study exhibits that for a given hybrid configuration, the number of operational hours of diesel generators decreases with increase in wind farm and PV capacity. Attention has also been focused on wind/PV penetration, un-met load, excess electricity generation, percentage fuel savings and reduction in carbon emissions (relative to diesel-only situation) of different hybrid systems, cost break-down of wind–PV–diesel systems, COE of different hybrid systems, etc.     

Temperature-dependent study of the radiative losses in double-quantum well solar cells

Quantum well solar cells (QWSC) have been proposed as a way to achieve a higher efficiency than conventional homogeneous cells. A key quantity for understanding the potential of the QWSC is the spatial variation of the quasi-Fermi level separation (Δφ_F) which is directly linked to the radiative losses. For the first time we have successfully measured Δφ_F in asymmetric double QW (DQW) p–i–n diodes in the AlGaAs/GaAs system at temperatures between 200 and 295 K. We have made several significant observations: (1) radiative losses through the QW decrease with increasing temperature and are clearly below the detailed balance-based predictions at room temperature. (2) Δφ_F is not the same in both wells which contradicts the assumption made by some researchers. (3) Δφ_F shows a dependence on the separation between the two QWs at low temperatures.     

A new transparently insulated, bifacially irradiated solar flat-plate collector

A new type of transparently insulated flat-plate collector was developed. It reaches higher efficiencies at low irradiation values or high operating temperatures than any other collector type known. Both sides of its absorber are covered with transparent insulation material and both sides are irradiated. Thus, the heat losses of the collector related to the total absorber area are distinctly reduced. An optical efficiency of η₀ = 0.72 and a temperature dependent U-value of U(ΔT) = (0.95 + 0.0076 ΔTK⁻¹) W m⁻² K⁻¹ were measured with an outdoor test facility. The bifacial-absorber collector is considered to be the best option for the DHW system of the energetically self-sufficient solar house in Freiburg because of its outstanding winter performance.