Oxy‐fuel combustion technology: current status,applications, and trends

The increased level of emissions of carbon dioxide into the atmosphere due to burning of fossil fuels represents one of the main barriers toward the reduction of greenhouse gases and the control of global warming. In the last decades, the use of renewable and clean sources of energies such as solar and wind energies has been increased extensively. However, due to the tremendously increasing world energy demand, fossil fuels would continue in use for decades which necessitates the integration of carbon capture technologies (CCTs) in power plants. These technologies include oxycombustion, pre‐combustion, and post‐combustion carbon capture. Oxycombustion technology is one of the most promising carbon capture technologies as it can be applied with slight modifications to existing power plants or to new power plants. In this technology, fuel is burned using an oxidizer mixture of pure oxygen plus recycled exhaust gases (consists mainly of CO₂). The oxycombustion process results in highly CO₂‐concentrated exhaust gases, which facilitates the capture process of CO₂ after H₂O condensation. The captured CO₂ can be used for industrial applications or can be sequestrated. The current work reviews the current status of oxycombustion technology and its applications in existing conventional combustion systems (including gas turbines and boilers) and novel oxygen transport reactors (OTRs). The review starts with an introduction to the available CCTs with emphasis on their different applications and limitations of use, followed by a review on oxycombustion applications in different combustion systems utilizing gaseous, liquid, and coal fuels. The current status and technology readiness level of oxycombustion technology is discussed. The novel application of oxycombustion technology in OTRs is analyzed in some details. The analyses of OTRs include oxygen permeation technique, fabrication of oxygen transport membranes (OTMs), calculation of oxygen permeation flux, and coupling between oxygen separation and oxycombustion of fuel within the same unit called OTR. The oxycombustion process inside OTR is analyzed considering coal and gaseous fuels. The future trends of oxycombustion technology are itemized and discussed in details in the present study including: (i) ITMs for syngas production; (ii) combustion utilizing liquid fuels in OTRs; (iii) oxy‐combustion integrated power plants and (iv) third generation technologies for CO₂ capture. Techno‐economic analysis of oxycombustion integrated systems is also discussed trying to assess the future prospects of this technology. Copyright © 2017 John Wiley & Sons, Ltd.     

Fracture mechanics approach for failure of adhesive joints in wind turbine blades

Composite components of wind turbine blade are assembled with adhesive. In order to assess structural integrity of blades it is needed to investigate fracture of joints. In this study, finite element analysis based on fracture mechanics was conducted to characterize failure of adhesive joint for wind turbine blade. The cohesive zone model as proposed fracture mechanics approach was verified through the comparison of numerical results with experimental data. Finite element models of wind turbine were developed to predict damage initiation and propagation. Numerical results based on fracture mechanics showed that failure was initiated in the edge of the adhesive bond line due to high level of shear stress prior to reaching the extreme design loading and propagated progressively.     

Hydro-thermal-wind scheduling employing novel ant lion optimization technique with composite ranking index

A solution to the combined hydro-thermal-wind scheduling problem of multi reservoir cascaded hydro plants is presented employing a novel ant lion optimization (ALO) algorithm. Five objectives, cost, various emissions and power loss, are simultaneously optimized. The optimal schedules of thermal, hydro and wind power (WP) units are determined for continuously varying load subject to a large number of practical operational constraints. The effect of reserve and penalty coefficients and WP uncertainty is also investigated for the multi-objective (MO) problem. The newly proposed ALO algorithm has unique features like random walk, roulette wheel, and boundary shrinking. These operations provide a judicious balance between exploration and exploitation, and create a powerful optimization technique for complex real-world problems.Finding the best compromise solution (BCS) is a tedious task when multiple objectives are involved. A composite ranking index (CRI) is proposed as a performance metrics for MO problems. The CRI helps the decision maker in ranking the large number of Pareto-optimal solutions. The developed model is tested on three standard systems, having a mix of hydro, thermal and wind generators. The performance is found to be superior to published results and comparable with established algorithms like artificial bee colony (ABC) and differential evolution (DE).     

Nonlinear PI control for variable pitch wind turbine

Wind turbine uses a pitch angle controller to reduce the power captured above the rated wind speed and release the mechanical stress of the drive train. This paper investigates a nonlinear PI (N-PI) based pitch angle controller, by designing an extended-order state and perturbation observer to estimate and compensate unknown time-varying nonlinearities and disturbances. The proposed N-PI does not require the accurate model and uses only one set of PI parameters to provide a global optimal performance under wind speed changes. Simulation verification is based on a simplified two-mass wind turbine model and a detailed aero-elastic wind turbine simulator (FAST), respectively. Simulation results show that the N-PI controller can provide better dynamic performances of power regulation, load stress reduction and actuator usage, comparing with the conventional PI and gain-scheduled PI controller, and better robustness against of model uncertainties than feedback linearization control.     

Prediction of the wind turbine performance by using BEM with airfoil data extracted from CFD

Blade element momentum (BEM) theory with airfoil data is a widely used technique for prediction of wind turbine aerodynamic performance, but the reliability of the airfoil data is an important factor for the prediction accuracy of aerodynamic loads and power. The airfoil characteristics used in BEM codes are mostly based on 2D wind tunnel measurements of airfoils with constant span. Due to 3D effects, a BEM code using airfoil data obtained directly from 2D wind tunnel measurements will not yield the correct loading and power. As a consequence, 2D airfoil characteristics have to be corrected before they can be used in a BEM code. In this article, we consider the MEXICO (Model EXperiments In Controlled cOnditions) rotor where airfoil data are extracted from CFD (Computational Fluid Dynamics) results. The azimuthally averaged velocity is used as the sectional velocity to define the angle of attack and the coefficient of lift and drag is determined by the forces on the blade. The extracted airfoil data are put into a BEM code without further corrections, and the calculated axial and tangential forces are compared to both computations using BEM with Shen's tip loss correction model and experimental data. The comparisons show that the recalculated forces by using airfoil data extracted from CFD have good agreements with the experiment.     

Bidding strategy of wind-thermal energy producers

This paper presents a stochastic mixed-integer linear programming approach for solving the self-scheduling problem of a price-taker thermal and wind power producer taking part in a pool-based electricity market. Uncertainty on electricity price and wind power is considered through a set of scenarios. Thermal units are modelled by variable costs, start-up costs and technical operating constraints, such as: forbidden operating zones, ramp up/down limits and minimum up/down time limits. An efficient mixed-integer linear program is presented to develop the offering strategies of the coordinated production of thermal and wind energy generation, having as a goal the maximization of profit. A case study with data from the Iberian Electricity Market is presented and results are discussed to show the effectiveness of the proposed approach.     

Tidal turbine array optimisation using the adjoint approach

Oceanic tides have the potential to yield a vast amount of renewable energy. Tidal stream generators are one of the key technologies for extracting and harnessing this potential. In order to extract an economically useful amount of power, hundreds of tidal turbines must typically be deployed in an array. This naturally leads to the question of how these turbines should be configured to extract the maximum possible power: the positioning and the individual tuning of the turbines could significantly influence the extracted power, and hence is of major economic interest. However, manual optimisation is difficult due to legal site constraints, nonlinear interactions of the turbine wakes, and the cubic dependence of the power on the flow speed. The novel contribution of this paper is the formulation of this problem as an optimisation problem constrained by a physical model, which is then solved using an efficient gradient-based optimisation algorithm. In each optimisation iteration, a two-dimensional finite element shallow water model predicts the flow and the performance of the current array configuration. The gradient of the power extracted with respect to the turbine positions and their tuning parameters is then computed in a fraction of the time taken for a flow solution by solving the associated adjoint equations. These equations propagate causality backwards through the computation, from the power extracted back to the turbine positions and the tuning parameters. This yields the gradient at a cost almost independent of the number of turbines, which is crucial for any practical application. The utility of the approach is demonstrated by optimising turbine arrays in four idealised scenarios and a more realistic case with up to 256 turbines in the Inner Sound of the Pentland Firth, Scotland.     

Validation of a three-dimensional viscous–inviscid interactive solver for wind turbine rotors

MIRAS is a newly developed computational model that predicts the aerodynamic behavior of wind turbine blades and wakes subject to unsteady motions and viscous effects. The model is based on a three-dimensional panel method using a surface distribution of quadrilateral singularities with a Neumann no penetration condition. Viscous effects inside the boundary layer are taken into account through the coupling with the quasi-3D integral boundary layer solver Q³UIC. A free-wake model is employed to simulate the vorticity released by the blades in the wake. In this paper the new code is validated against measurements and/or CFD simulations for five wind turbine rotors, including three experimental model rotors [20–22], the 2.5 MW NM80 machine [23] and the NREL 5 MW virtual rotor [24]. Such a broad set of operational conditions and rotor sizes constitutes a very challenging validation matrix, with Reynolds numbers ranging from 5.0⋅10⁴ to 1.2⋅10⁷.     

Open loop wind turbine emulator

A new wind turbine emulator (WTE) is presented, which is able to simulate the turbine power curves without using a closed loop control system. The state of the art emulators use DC or AC motors, closed loop controlled by processors with the turbine power curves recorded. The presented emulator has a DC voltage source, a power resistor and a DC motor with independent excitation. The motor power curve has a shape similar to a wind turbine power curve for a given wind speed; the wind speed variations can be emulated by the variations of the DC voltage source. The open loop emulator is completely different and new, because it works in open loop and does not require the presence of a processor.The following elements are included: the theoretical foundations of the emulator, the emulator power curves adjustment procedure to simulate a commercial wind turbine and the experimental tests.     

Online multi-step prediction for wind speeds and solar irradiation: Evaluation of prediction errors

We propose a general method for predicting multiple steps ahead of our target system and estimating simultaneously the prediction errors in a real time. The requirement of the proposed method is that we have a time series of the target system. We demonstrate the method by artificial data, real wind speed data, and real solar irradiation data.