Local topography-induced pressure gradient effects on the wake and power output of a model wind turbine

Wind-tunnel experiments were performed to study the effect of favorable and adverse constant pressure gradients(PG)from local changes in the topography right downwind of a model wind turbine.Particle image velocimetry was used to characterize the near and intermediate wake regions.We explored five scenarios,two favorable,two adverse PG,and a case with negligible PG.Results show that the PGs induce a wake deflection and modulate the wake.They imposed a relatively small impact on the turbulence kinetic energy and kinematic shear stress but a comparatively dominant effect on the bulk flow on the flow recovery.Based on this,a simple formulation is used to describe the impact of PG on the wake.We modeled the base flow through a linearized perturbation method;the wake is obtained by solving a simplified,integrated streamwise momentum equation.This approach reasonably estimated the flow profile and PG-induced power output variations.

Big-M based MILP method for SCUC considering allowable wind power output interval and its adjustable conservativeness

In contrast to most existing works on robust unit commitment(UC),this study proposes a novel big-M-based mixed-integer linear programming(MILP)method to solve security-constrained UC problems considering the allowable wind power output interval and its adjustable conservativeness.The wind power accommodation capability is usually limited by spinning reserve requirements and transmission line capacity in power systems with large-scale wind power integration.Therefore,by employing the big-M method and adding auxiliary 0-1 binary variables to describe the allowable wind power output interval,a bilinear programming problem meeting the security constraints of system operation is presented.Furthermore,an adjustable confidence level was introduced into the proposed robust optimization model to decrease the level of conservatism of the robust solutions.This can establish a trade-off between economy and security.To develop an MILP problem that can be solved by commercial solvers such as CPLEX,the big-M method is utilized again to represent the bilinear formulation as a series of linear inequality constraints and approximately address the nonlinear formulation caused by the adjustable conservativeness.Simulation studies on a modified IEEE 26-generator reliability test system connected to wind farms were performed to confirm the effectiveness and advantages of the proposed method.

Prediction of photovoltaic power output based on different non-linear autoregressive artificial neural network algorithms

Prediction of power output plays a vital role in the installation and operation of photovoltaic modules.In this paper,two photovoltaic module technologies,amorphous silicon and copper indium gallium selenide installed outdoors on the rooftop of the University of Dodoma,located at 6.5738°S and 36.2631°E in Tanzania,were used to record the power output during the winter season.The average data of ambient temperature,module temperature,solar irradiance,relative humidity,and wind speed recorded is used to predict the power output using a non-linear autoregressive artificial neural network.We consider the Levenberg-Marquardt optimization,Bayesian regularization,resilient propagation,and scaled conjugate gradient algorithms to understand their abilities in training,testing and validating the data.A comparison with reference to the performance indices:coefficient of determination,root mean square error,mean absolute percentage error,and mean absolute bias error is drawn for both modules.According to the findings of our investigation,the predicted results are in good agreement with the experimental results.All the algorithms performed better,and the predicted power out of both modules using the Bayesian regularization algorithm is observed to exhibit good processing capabilities compared to the other three algorithms that are evident from the measured performance indices.

Decision Technique of Solar Radiation Prediction Applying Recurrent Neural Network for Short-Term Ahead Power Output of Photovoltaic System

In recent years, introduction of a renewable energy source such as solar energy is expected. However, solar radiation is not constant and power output of photovoltaic (PV) system is influenced by weather conditions. It is difficult for getting to know accurate power output of PV system. In order to forecast the power output of PV system as accurate as possible, this paper proposes a decision technique of forecasting model for short-term-ahead power output of PV system based on solar radiation prediction. Application of Recurrent Neural Network (RNN) is shown for solar radiation prediction in this paper. The proposed method in this paper does not require complicated calculation, but mathematical model with only useful weather data. The validity of the proposed RNN is confirmed by comparing simulation results of solar radiation forecasting with that obtained from other

Power output and efficiency optimization of endoreversible non-isothermal chemical engine via Lewis analogy

Compared with endoreversible heat engine with pure heat transfer and endoreversible isothermal chemical engine with pure mass transfer,endoreversible non-isothermal chemical engine(ENICE)is a more reasonable model of practical mass exchanger,solid device and chemo-electric systems.There exists heat and mass transfer(HMT)simultaneously between working fluid and chemical potential reservoir in ENICE.There is coupled HMT effect that in ENICE should be considered.There are two ways to consider this coupled effect.One is based on Onsager equations,and another is based on Lewis analogy.For the mathematical and physical description of the above HMT process,the model using Onsager equations are more appropriate in the linear HMT region not far from the equilibrium state,while that based on Lewis analogy is more appropriate in nonlinear HMT region far from the equilibrium state.Different from the previous research on the power optimization of ENICEs with Onsager equations,this paper optimizes power and efficiency of ENICE based on Lewis analogy.HMT processes are assumed to obey Newtonian heat transfer law(q∝ΔT,and T is temperature)and Fick's diffusive mass transfer law(g∝Δc,and c is concentration),respectively.Analytical results of power output and corresponding vector efficiency(η_(T)andη_(μ))of ENICE are obtained,which provide important parallel results with those based on Onsager equations.They include special cases for endoreversible Carnot heat engine with q∝ΔT and endoreversible isothermal chemical engine with g∝Δc.Adopting Lewis analogy in the modelling of ENICEs with simultaneous HMT is an important work.It provides important analytical and numerical results different from those with Onsager equations obtained previously and enriches the research contents of FTT.The research results in this paper have a certain guiding significance for the optimal designs of single irreversible NICEs,multistage NICE systems,practical mass exchangers,solid devices,chemo-electric systems,and so on.

Transfer Strategy for Power Output Estimation of Wind Farm at Planning Stage Based on a SVR Model

The conventional wind farm(WF)power generation modelling method highly relies on wind hindcast produced by record time-series data or numerical weather modelling.However,estimating production at future sites is challenging in the absence of local wind monitoring.To address this,a data-driven WF modelling and model transfer strategy is proposed in this work.It considers the challenge of how to transpose metered data from existing operational WFs to sites that might feature as a prospective site for a new WF.By modelling 14 WFs distributed across Scotland using a machine learning(ML)approach,this study proved it was possible to effectively model metered production at a site using modelled wind speed and direction.In addition,this study also found when the latitude difference between two WFs is less than 0.2 degrees and the distance is less than 5o km,two WFs in non-mountainous areas can share an ML model.The results of the shared ML model remain superior to the results of the given power curve from manufacturers,after adjusting the results by the ratio of the power curve in these two WFs.The WF model transfer strategy investigated in this work offered a novel approach to transposing WF production estimates to new sites and appeared to offer better value than simple power curves,which is of importance at the early planning stage for site selection,although it would likely not fully replace detailed micro-siting modelling which are well established in the industry.Index Terms-Machine learning,model transfer strategy,power curve,power output estimation,wind farm.

Performance Improvement of Artificial Neural Network Model in Short-term Forecasting of Wind Farm Power Output

Due to the low dispatchability of wind power,the massive integration of this energy source in power systems requires short-term and very short-term wind power output forecasting models to be as efficient and stable as possible.A study is conducted in the present paper of potential improvements to the performance of artificial neural network(ANN)models in terms of efficiency and stability.Generally,current ANN models have been developed by considering exclusively the meteorological information of the wind farm reference station,in addition to selecting a fixed number of time periods prior to the forecasting.In this respect,new ANN models are proposed in this paper,which are developed by:varying the number of prior 1-h periods(periods prior to the forecasting hour)chosen for the input layer parameters;and/or incorporating in the input layer data from a second weather station in addition to the wind farm reference station.It has been found that the model performance is always improved when data from a second weather station are incorporated.The mean absolute relative error(MARE)of the new models is reduced by up to 7.5%.Furthermore,the longer the forecasting horizon,the greater the degree of improvement.

Droop Control Method to Achieve Maximum Power Output of Photovoltaic for Parallel Inverter System

In general,the power distribution of a parallel inverter is achieved by the use of droop control in a microgrid system,which consists of PV inverters and non-regeneration energy source inverters without energy storage devices in an islanded mode.If the shared load power is no more than the available maximum PV inverter output power,then there is a power waste for the PV inverter.In addition,due to the intermittency of PV sources,the system may become unstable if the shared load power is more than the available maximum power output of the PV(MPO-PV)inverter.Therefore,in order to avoid power waste and potential instability caused by insufficient PV power by traditional droop control,this paper recommends an improved droop control scheme to maximize the power output of PV units.As required by the load,the remaining power is composed of the other inverters,which can effectively improve the utilization rating of renewable energy sources and system stability.At the same time,according to the system stability analysis based on small signal modeling,it has been designed around the droop coefficients of the improved droop control loop.In the end,the simulation and experimental results show that the suggested scheme has a varied validity and robustness.

Analysis on Output Power for Multi-direction Piezoelectric Vibration Energy Harvester

To predict the performance of multi-direction piezoelectric vibration energy harvester,an equation for calculating its output power is obtained based on elastic mechanics theory and piezoelectricity theory.Experiments are performed to verify theoretical analysis.When the excitation direction is along Y direction,a maximal output power about 0.139 mW can be harvested at a resistive load of 65kΩ and an excitation frequency of 136 Hz.Theoretical analysis agrees well with experimental results.Furthermore,the performance of multi-direction vibration energy harvester is experimentally tested.The results show that the multi-direction vibration energy harvester can harvest perfect energy as the excitation direction changes in XY plane,YZ plane,XZ plane and body diagonal plane of the harvester.

Thermodynamic performance of Dual-Miller cycle(DMC) with polytropic processes based on power output, thermal efficiency and ecological function

This study reports a new model of an air standard Dual-Miller cycle(DMC) with two polytropic processes and heat transfer loss.The two reversible adiabatic processes which could not be realized in practice are replaced with two polytropic processes in order to more accurately reflect the practical working performance. The heat transfer loss is taken into account. The expressions of power output, thermal efficiency, entropy generation rate(EGR) and ecological function are addressed using finite-time thermodynamic theory. Through numerical calculations, the influences of compression ratio, cut-off ratio and polytropic exponent on the performance are thermodynamically analyzed. The model can be simplified to other cycle models under specific conditions, which means the results have an certain universality and may be helpful in the design of practical heat engines. It is shown that the entropy generation minimization does not always lead to the best system performance.

An ultra-low power output capacitor-less low-dropout regulator with slew-rate-enhanced circuit

An ultra-low power output-capacitorless low-dropout(LDO) regulator with a slew-rate-enhanced(SRE)circuit is introduced. The increased slew rate is achieved by sensing the transient output voltage of the LDO and then charging(or discharging) the gate capacitor quickly. In addition, a buffer with ultra-low output impedance is presented to improve line and load regulations. This design is fabricated by SMIC 0.18 μm CMOS technology. Experimental results show that, the proposed LDO regulator only consumes an ultra-low quiescent current of 1.2 μA.The output current range is from 10 μA to 200 m A and the corresponding variation of output voltage is less than 40 m V. Moreover, the measured line regulation and load regulation are 15.38 m V/V and 0.4 m V/m A respectively.

Optimal Output Power Control of Switched Reluctance Generator at a Constant Speed

In order to control the output power of a switched reluctance generator(SRG)at a constant speed,the output power of SRG is theoretically analyzed by using freewheeling control.First,through a theoretical analysis,a finite element simulation and an experiment,it was verified that the output power of SRG cannot be improved by using freewheeling control with a single pulse control method(SPCM).Then,the maximum output power can be obtained by optimizing the turn off angles of SPCM at a constant speed,and at the same time,the formula of the optimal turn-off angle was presented,which meets the criterion for the output power maximization.Finally,numerical simulation and experimental results demonstrated the validity of the theoretical analysis.

Controlling the output power of soft switching arc welding inverter by two-stage continuous PWM method

The full bridge zero voltage zero current switching(FB-ZVZCS),which could adjust the output power by keeping the duty ratio of lagging leg constant and changing the duty ratio of leading leg,was a common circuit of soft switching arc welding inverter power source.However,when the duty ratio of leading leg was reduced to zero,the output power stayed the constant value instead of becoming zero.The working status and waveforms of some major parameters were studied in this paper while the duty ratio of leading leg was zero.It was concluded that the minimum output power of soft switching inverter was related to the charging voltage of parallel capacitors,and the output power also could be reduced by reducing the duty ratio of lagging leg.A novel two-stage continuous PWM control method that could switch working-mode between full bridge and half bridge was put forward in this paper.This kind of control method could further reduce the output power of soft switching inverter in order to meet the requirement of low heat input of sheet metal welding.

Mathematical modeling of output power in RF-excited CO_2 waveguide lasers

Theoretical analysis model has been established for CO 2 laser to describe the process of dynamic emission in the electrooptically Q switched laser .The electron excitation and the energy transfer of vibration level and the rotational relaxation of rotational levels are described. The comparison between this model and a set of coupled rat equations model are discussed.

Experimental Study of Buffer Gas Flow Rate Effect on Output Power of a Copper Vapor Laser

A copper vapor laser with active medium length of 60 cm and bore of 16 mm has been operated and optimized using different buffer gases to investigate the effect of the gas flow rates on the output power. It is found that there is a special optimum gas flow rate associated with the type of buffer gas.

微生物燃料电池工作原理及产电性能提升策略

微生物燃料电池(MFC)是一种解决其他能源在环境方面不足的新技术,目前低能量输出是MFC实际应用的关键瓶颈。基于MFC工作原理,提出微生物活性差、电子迁移阻力、质子传输阻力及阴极还原反应缓慢是MFC能量输出的限制因素,并从以下5个方面综述了提升MFC产电性能策略:调节pH和选择最佳盐度,加强微生物代谢活性;改性阳极材料,降低电子迁移阻力;增强电解液电导率、优化隔膜材料及缩短电极间距减小质子传输阻力;制备高效阴极催化剂和选择优异电子受体加快阴极还原反应速率;改进MFC反应器构型,提高整体产电性能。未来,可在合成新型阴极催化剂、降低膜污染、优化微生物生长环境、制备优异的电极材料和改进MFC反应器配置5个方面开展重点研究。

Resilient Fixed-Order Distributed Dynamic Output Feedback Load Frequency Control Design for Interconnected Multi-Area Power Systems

The paper proposes a novel H∞ load frequency control(LFC) design method for multi-area power systems based on an integral-based non-fragile distributed fixed-order dynamic output feedback(DOF) tracking-regulator control scheme. To this end, we consider a nonlinear interconnected model for multiarea power systems which also include uncertainties and timevarying communication delays. The design procedure is formulated using semi-definite programming and linear matrix inequality(LMI) method. The solution of the proposed LMIs returns necessary parameters for the tracking controllers such that the impact of model uncertainty and load disturbances are minimized. The proposed controllers are capable of receiving all or part of subsystems information, whereas the outputs of each controller are local. These controllers are designed such that the resilient stability of the overall closed-loop system is guaranteed. Simulation results are provided to verify the effectiveness of the proposed scheme. Simulation results quantify that the distributed(and decentralized) controlled system behaves well in presence of large parameter perturbations and random disturbances on the power system.