Connecting Wind Turbine Generator to Distribution Power Grid--A Preload Flow Calculation Stage

A distribution grid is generally characterized by a high R/X （resistance/reactance） ratio and it is radial in nature. By design, a distribution grid system is not an active network, and it is normally designed in such a way that power flows from transmission system via distribution system to consumers. But in a situation when wind turbines are connected to the distribution grid, the power source will change from one source to two sources, in this case, network is said to be active. This may probably have an impact on the distribution grid to whenever the wind turbine is connected. The best way to know the impact of wind turbine on the distribution grid in question is by carrying out load flow analysis on that system with and without the connection of wind turbines. Two major fundamental calculations： the steady-state voltage variation at the PCC （point of common coupling） and the calculation of short-circuit power of the grid system at the POC （point of connection） are necessary before carrying out the load flow study on the distribution grid. This paper, therefore, considers these pre-load flow calculations that are necessary before carrying out load flow study on the test distribution grid. These calculations are carded out on a test distribution system.

Very Short-Term Generating Power Forecasting for Wind Power Generators Based on Time Series Analysis

In recent years, there has been introduction of alternative energy sources such as wind energy. However, wind speed is not constant and wind power output is proportional to the cube of the wind speed. In order to control the power output for wind power generators as accurately as possible, a method of wind speed estimation is required. In this paper, a technique considers that wind speed in the order of 1 - 30 seconds is investigated in confirming the validity of the Auto Regressive model (AR), Kalman Filter (KF) and Neural Network (NN) to forecast wind speed. This paper compares the simulation results of the forecast wind speed for the power output forecast of wind power generator by using AR, KF and NN.

Maximum Power Point Tracking in Variable Speed Wind Turbine Based on Permanent Magnet Synchronous Generator Using Maximum Torque Sliding Mode Control Strategy

The present study was carried out in order to track the maximum power point in a variable speed turbine by minimizing electromechanical torque changes using a sliding mode control strategy. In this strategy, first, the rotor speed is set at an optimal point for different wind speeds. As a result of which, the tip speed ratio reaches an optimal point, mechanical power coefficient is maximized, and wind turbine produces its maximum power and mechanical torque. Then, the maximum mechanical torque is tracked using electromechanical torque. In this technique, tracking error integral of maximum mechanical torque, the error, and the derivative of error are used as state variables. During changes in wind speed, sliding mode control is designed to absorb the maximum energy from the wind and minimize the response time of maximum power point tracking(MPPT). In this method, the actual control input signal is formed from a second order integral operation of the original sliding mode control input signal. The result of the second order integral in this model includes control signal integrity, full chattering attenuation, and prevention from large fluctuations in the power generator output. The simulation results, calculated by using MATLAB/m-file software, have shown the effectiveness of the proposed control strategy for wind energy systems based on the permanent magnet synchronous generator(PMSG).

Difference between grid connections of large-scale wind power and conventional synchronous generation

In China, regions with abundant wind energy resources are generally located at the end of power grids. The power grid architecture in these regions is typically not sufficiently strong, and the energy structure is relatively simple. Thus, connecting large-capacity wind power units complicates the peak load regulation and stable operation of the power grids in these regions. Most wind turbines use power electronic converter technology, which affects the safety and stability of the power grid differently compared with conventional synchronous generators. Furthermore, fluctuations in wind power cause fluctuations in the output of wind farms, making it difficult to create and implement suitable power generation plans for wind farms. The generation technology and grid connection scheme for wind power and conventional thermal power generation differ considerably. Moreover, the active and reactive power control abilities of wind turbines are weaker than those of thermal power units, necessitating additional equipment to control wind turbines. Hence, to address the aforementioned issues with large-scale wind power generation, this study analyzes the differences between the grid connection and collection strategies for wind power bases and thermal power plants. Based on this analysis, the differences in the power control modes of wind power and thermal power are further investigated. Finally, the stability of different control modes is analyzed through simulation. The findings can be beneficial for the planning and development of large-scale wind power generation farms.

Battery Energy Storage to Strengthen the Wind Generator in Integrated Power System

The wind energy generation,utilization and its grid penetration in electrical grid are increasing world-wide.The wind generated power is always fluctuating due to its time varying nature and causing stability problem.This weak interconnection of wind generating source in the electrical network affects the power quality and reliability.The localized energy storages shall compensate the fluctuating power and support to strengthen the wind generator in the power system.In this paper,it is proposed to control the voltage source inverter （VSI） in current control mode with energy storage,that is,batteries across the dc bus.The generated wind power can be extracted under varying wind speed and stored in the batteries.This energy storage maintains the stiff voltage across the dc bus of the voltage source inverter.The proposed scheme enhances the stability and reliability of the power system and maintains unity power factor.It can also be operated in stand-alone mode in the power system.The power exchange across the wind generation and the load under dynamic situation is feasible while maintaining the power quality norms at the common point of coupling.It strengthens the weak grid in the power system.This control strategy is evaluated on the test system under dynamic condition by using simulation.The results are verified by comparing the performance of controllers.

Comparative Performance of Fixed-Speed and Variable-Speed Wind Turbine Generator Systems

In the early development of the wind energy, the majority of the wind turbines have been operated at constant speed. Subsequently, the number of variable-speed wind turbines installed in wind farms has increased. In this paper, a comparative performance of fixed and variable speed wind generators with Pitch angle control has been presented. The first is based on a squirrel cage Induction Generator （IG） of 315 kW rated power, connected directly to the grid. The second incorporated a Permanent Magnet Synchronous Generator （PMSG） of 750 kW rated power. The performances of each studied wind generator are evaluated by simulation works and variable speed operation is highlighted as preferred mode of operation.

An Optimal Dynamic Generation Scheduling for a Wind-Thermal Power System

In this paper, a dynamic generation scheduling model is formulated, aiming at minimizing the costs of power generation and taking into account the constraints of thermal power units and spinning reserve in wind power integrated systems. A dynamic solving method blended with particle swarm optimization algorithm is proposed. In this method, the solution space of the states of unit commitment is created and will be updated when the status of unit commitment changes in a period to meet the spinning reserve demand. The thermal unit operation constrains are inspected in adjacent time intervals to ensure all the states in the solution space effective. The particle swarm algorithm is applied in the procedure to optimize the load distribution of each unit commitment state. A case study in a simulation system is finally given to verify the feasibility and effectiveness of this dynamic optimization algorithm.

Non-dominated sorting culture differential evolution algorithm for multi-objective optimal operation of Wind-Solar-Hydro complementary power generation system

Due to the intermittency and instability of Wind-Solar energy and easy compensation of hydropower, this study proposes a Wind-Solar-Hydro power optimal scheduling model. This model is aimed at maximizing the total system power generation and the minimum ten-day joint output. To effectively optimize the multi-objective model, a new algorithm named non-dominated sorting culture differential evolution algorithm(NSCDE) is proposed. The feasibility of NSCDE was verified through several well-known benchmark problems. It was then applied to the Jinping Wind-Solar-Hydro complementary power generation system. The results demonstrate that NSCDE can provide decision makers a series of optimized scheduling schemes.

New energy power generation-wind power generation

This paper introduced the status quo of wind power and wind power generation technology. Focusing on the introduction of wind power generating system ibrational self-consistent field（VSCF）, program implementation included Alternating Current （AC）-Direct Current （DC）-AC conversion system, magnetic field modulation generator system, doubly-fed generator system etc. Among these, doubly-fed generator system is the trend. Where to build the wind farm is very important, so a perfect site is needed. Wind power generation will have a bright future. As long as the wind power can be linked to the grid in large scale.

Wind Generator Stabilization with Doubly-Fed Asynchronous Machine

This paper investigates the function of doubly-fed asynchronous machine(DASM)with emphasis placed on its ability to the stabilization of the power system including wind generators.P(active power)and Q(reactive power)compensation from DASM can be regulated independently through secondary-excitation controlling.Simulation results by power system computer aided design(PSCAD)show that DASM can restore the wind-generator system to a normal operating condition rapidly even following severe transmission-line failures.Comparison studies have also been performed between wind turbine pitch control and proposed method.

Development of a Full Parameterized FE-modeling Tool for Efficient Vibration Investigations on End Windings of Turbo- and Hydro-Generators

End windings of generators are excited to vibrations due to electromagnetic forces which can cause severe damage and noise. To avoid this, it is important to predict the natural frequencies and modes of the end windings with finite elements. Due to the complex structure and unknown boundary conditions, the conventionally calculation of stator end windings has been very difficult and time consuming up to now. This paper describes the development of a full parameterized modeling tool, which allows a quick calculation of natural frequencies during the design phase of the generator. To keep the computing time low, it is important to find a way to get exact calculation results without detailed modeling of all pans. Additionally, special attention was paid to the active part, which has been replaced by spring-damper elements, and the determination of their stiffness via experimental modal analysis combined with finite element calculations.

Power Delivery Studies of Windbelt Generators with Different Architectures

Windbelt generators have been proposed as small, green power sources for battery charging applications. Some of the reported results lack detailed information about how key parameters influence the output power of the generator. In this work, we built prototypes with different architectures to study the voltage generation and power delivery as functions of belt tension, length, and electrical load at various wind speeds. We also studied the maximum power delivery conditions before the breakdown of the belt oscillation occurs. Our results are obtained from windbelt generators with two types of architectures： a conventional design with an adjustable belt that uses weight for tension control, and a revised design with a belt oscillation perpendicular to the coil axis. We have concluded that the breakdown of the belt oscillation at lower output resistances is a primary bottleneck that will limit windbelt systems to only very low power applications.

Rolling Generation Dispatch Based on Ultra-short-term Wind Power Forecast

The power systems economic and safety operation considering large-scale wind power penetration are now facing great challenges, which are based on reliable power supply and predictable load demands in the past. A rolling generation dispatch model based on ultra-short-term wind power forecast was proposed. In generation dispatch process, the model rolling correct not only the conventional units power output but also the power from wind farm, simultaneously. Second order Markov chain model was utilized to modify wind power prediction error state (WPPES) and update forecast results of wind power over the remaining dispatch periods. The prime-dual affine scaling interior point method was used to solve the proposed model that taken into account the constraints of multi-periods power balance, unit output adjustment, up spinning reserve and down spinning reserve.

Analysis and Control of a Three-Phase Switched Reluctance Wind Generator

This paper deals with various aspects of modeling, simulation, analysis, and control ofa SRG （switched reluctance generator） in different modes of operation. Excitation method of such a generator is shortly described. The output power of the SRG is controlled so that it can track the maximum output power of a wind turbine drive applications. Also, the output generator voltage is stabilized under either load or wind speed variations. Basic operational characteristics of a three-phase 6/4 SRG are developed through experimental observation. Meanwhile, the real-time operation was implemented in a DSP （digital signal processor） environment. The simulation of the complete system model has been obtained using the Matlab/Simulink software. A good agreement between experimental and simulation results has been observed which supports the validity of the proposed analysis.

A Long-Range Generalized Predictive Control Algorithm for a DFIG Based Wind Energy System

This paper presents a new Long-range generalized predictive controller in the synchronous reference frame for a wind energy system doubly-fed induction generator based. This controller uses the state space equations that consider the rotor current and voltage as state and control variables, to execute the predictive control action. Therefore, the model of the plant must be transformed into two discrete transference functions, by means of an auto-regressive moving average model, in order to attain a discrete and decoupled controller, which makes it possible to treat it as two independent single-input single-output systems instead of a magnetic coupled multiple-input multiple-output system. For achieving that, a direct power control strategy is used, based on the past and future rotor currents and voltages estimation. The algorithm evaluates the rotor current predictors for a defined prediction horizon and computes the new rotor voltages that must be injected to controlling the stator active and reactive powers. To evaluate the controller performance, some simulations were made using Matlab/Simulink. Experimental tests were carried out with a small-scale prototype assuming normal operating conditions with constant and variable wind speed profiles. Finally, some conclusions respect to the dynamic performance of this new controller are summarized.

Missing interpolation model for wind power data based on the improved CEEMDAN method and generative adversarial interpolation network

Randomness and fluctuations in wind power output may cause changes in important parameters(e.g.,grid frequency and voltage),which in turn affect the stable operation of a power system.However,owing to external factors(such as weather),there are often various anomalies in wind power data,such as missing numerical values and unreasonable data.This significantly affects the accuracy of wind power generation predictions and operational decisions.Therefore,developing and applying reliable wind power interpolation methods is important for promoting the sustainable development of the wind power industry.In this study,the causes of abnormal data in wind power generation were first analyzed from a practical perspective.Second,an improved complete ensemble empirical mode decomposition with adaptive noise(ICEEMDAN)method with a generative adversarial interpolation network(GAIN)network was proposed to preprocess wind power generation and interpolate missing wind power generation sub-components.Finally,a complete wind power generation time series was reconstructed.Compared to traditional methods,the proposed ICEEMDAN-GAIN combination interpolation model has a higher interpolation accuracy and can effectively reduce the error impact caused by wind power generation sequence fluctuations.

Physics-Informed AI Surrogates for Day-Ahead Wind Power Probabilistic Forecasting with Incomplete Data for Smart Grid in Smart Cities

Due to the high inherent uncertainty of renewable energy,probabilistic day-ahead wind power forecasting is crucial for modeling and controlling the uncertainty of renewable energy smart grids in smart cities.However,the accuracy and reliability of high-resolution day-ahead wind power forecasting are constrained by unreliable local weather prediction and incomplete power generation data.This article proposes a physics-informed artificial intelligence(AI)surrogates method to augment the incomplete dataset and quantify its uncertainty to improve wind power forecasting performance.The incomplete dataset,built with numerical weather prediction data,historical wind power generation,and weather factors data,is augmented based on generative adversarial networks.After augmentation,the enriched data is then fed into a multiple AI surrogates model constructed by two extreme learning machine networks to train the forecasting model for wind power.Therefore,the forecasting models’accuracy and generalization ability are improved by mining the implicit physics information from the incomplete dataset.An incomplete dataset gathered from a wind farm in North China,containing only 15 days of weather and wind power generation data withmissing points caused by occasional shutdowns,is utilized to verify the proposed method’s performance.Compared with other probabilistic forecastingmethods,the proposed method shows better accuracy and probabilistic performance on the same incomplete dataset,which highlights its potential for more flexible and sensitive maintenance of smart grids in smart cities.

Enhancement of Wind Energy Conversion Using Axial Flux Generator

This paper investigates the application of the axial flux machine (AFM) to the wind energy conversion systems (WECS) to obtain high power and torque at reduced cost. By developing mathematical equations using the phase and active transformations, the three-phase model is transformed to two-phase equations by making both the stator and rotor as reference frames, finally converting to arbitrary reference frame, which is useful for the modelling of the axial flux machine. The torque, current, and voltage equations are expressed to improve the simulation reliability. Based on the developed equations, the mathematical model for the axial flux machine is developed using the MATLAB/Simulink. Starting with the axial flux motor model, when the load on the motor increases, how the parameters like torque, current, and speed of the motor vary are explored in this paper. Then for the axial flux generator model, when the wind speed exceeds the rated speed how the torque, line voltages, currents, power and speed of the generator behave are investigated and presented in this paper. The developed model in this paper could be extended to a twin-rotor axial flux synchronous machine, which will lead to the development of more efficient WECS.

PI-MPC Frequency Control of Power System in the Presence of DFIG Wind Turbines

For the recent expansion of renewable energy applications, Wind Energy System (WES) is receiving much interest all over the world. However, area load change and abnormal conditions lead to mismatches in frequency and scheduled power interchanges between areas. These mismatches have to be corrected by the LFC system. This paper, therefore, proposes a new robust frequency control technique involving the combination of conventional Proportional-Integral (PI) and Model Predictive Control (MPC) controllers in the presence of wind turbines (WT). The PI-MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. A frequency response dynamic model of a single-area power system with an aggregated generator unit is introduced, and physical constraints of the governors and turbines are considered. The proposed technique is tested on the single-area power system, for enhancement of the network frequency quality. The validity of the proposed method is evaluated by computer simulation analyses using Matlab Simulink. The results show that, with the proposed PI-MPC combination technique, the overall closed loop system performance demonstrated robustness regardless of the presence of uncertainties due to variations of the parameters of governors and turbines, and loads disturbances. A performance comparison between the proposed control scheme, the classical PI control scheme and the MPC is carried out confirming the superiority of the proposed technique in presence of doubly fed induction generator (DFIG) WT.