Transient Stability Preventive Control of Wind Farm Connected Power System Considering the Uncertainty

To address uncertainty as well as transient stability constraints simultaneously in the preventive control of windfarm systems, a novel three-stage optimization strategy is established in this paper. In the first stage, the probabilisticmulti-objective particle swarm optimization based on the point estimate method is employed to cope with thestochastic factors. The transient security region of the system is accurately ensured by the interior point methodin the second stage. Finally, the verification of the final optimal objectives and satisfied constraints are enforcedin the last stage. Furthermore, the proposed strategy is a general framework that can combine other optimizationalgorithms. The proposed methodology is tested on the modified WSCC 9-bus system and the New England 39-bussystem. The results verify the feasibility of the method.

GNN Representation Learning and Multi-Objective Variable Neighborhood Search Algorithm for Wind Farm Layout Optimization

With the increasing demand for electrical services,wind farm layout optimization has been one of the biggest challenges that we have to deal with.Despite the promising performance of the heuristic algorithm on the route network design problem,the expressive capability and search performance of the algorithm on multi-objective problems remain unexplored.In this paper,the wind farm layout optimization problem is defined.Then,a multi-objective algorithm based on Graph Neural Network(GNN)and Variable Neighborhood Search(VNS)algorithm is proposed.GNN provides the basis representations for the following search algorithm so that the expressiveness and search accuracy of the algorithm can be improved.The multi-objective VNS algorithm is put forward by combining it with the multi-objective optimization algorithm to solve the problem with multiple objectives.The proposed algorithm is applied to the 18-node simulation example to evaluate the feasibility and practicality of the developed optimization strategy.The experiment on the simulation example shows that the proposed algorithm yields a reduction of 6.1% in Point of Common Coupling(PCC)over the current state-of-the-art algorithm,which means that the proposed algorithm designs a layout that improves the quality of the power supply by 6.1%at the same cost.The ablation experiments show that the proposed algorithm improves the power quality by more than 8.6% and 7.8% compared to both the original VNS algorithm and the multi-objective VNS algorithm.

A Chaotic Local Search-Based Particle Swarm Optimizer for Large-Scale Complex Wind Farm Layout Optimization

Wind energy has been widely applied in power generation to alleviate climate problems.The wind turbine layout of a wind farm is a primary factor of impacting power conversion efficiency due to the wake effect that reduces the power outputs of wind turbines located in downstream.Wind farm layout optimization(WFLO)aims to reduce the wake effect for maximizing the power outputs of the wind farm.Nevertheless,the wake effect among wind turbines increases significantly as the number of wind turbines increases in the wind farm,which severely affect power conversion efficiency.Conventional heuristic algorithms suffer from issues of low solution quality and local optimum for large-scale WFLO under complex wind scenarios.Thus,a chaotic local search-based genetic learning particle swarm optimizer(CGPSO)is proposed to optimize large-scale WFLO problems.CGPSO is tested on four larger-scale wind farms under four complex wind scenarios and compares with eight state-of-the-art algorithms.The experiment results indicate that CGPSO significantly outperforms its competitors in terms of performance,stability,and robustness.To be specific,a success and failure memories-based selection is proposed to choose a chaotic map for chaotic search local.It improves the solution quality.The parameter and search pattern of chaotic local search are also analyzed for WFLO problems.

Wind farm active power dispatching algorithm based on Grey Incidence

This study proposes a wind farm active power dispatching(WFAPD) algorithm based on the grey incidence method, which does not rely on an accurate mathematical model of wind turbines. Based on the wind turbine start-stop data at different wind speeds, the weighting coefficients, which are the participation degrees of a variable speed system and a variable pitch system in power regulation, are obtained using the grey incidence method. The incidence coefficient curve is fitted by the B-spline function at a full range of wind speeds, and the power regulation capacity of all wind turbines is obtained. Finally, the WFAPD algorithm, which is based on the regulating capacity of each wind turbine, is compared with the wind speed weighting power dispatching(WSWPD) algorithm in MATLAB. The simulation results show that the active power fluctuation of the wind farm is smaller, the rotating speed of wind turbines is smoother, and the fatigue load of highspeed turbines is effectively reduced.

Wake Effects on A Hybrid Semi-Submersible Floating Wind Farm with Multiple Hub Heights

Wind farms generally consist of a single turbine installed with the same hub height. As the scale of turbines increases,wake interference between turbines becomes increasingly significant, especially for floating wind turbines(FWT).Some researchers find that wind farms with multiple hub heights could increase the annual energy production(AEP),while previous studies also indicate that wake meandering could increase fatigue loading. This study investigates the wake interaction within a hybrid floating wind farm with multiple hub heights. In this study, FAST.Farm is employed to simulate a hybrid wind farm which consists of four semi-submersible FWTs(5MW and 15MW) with two different hub heights. Three typical wind speeds(below-rated, rated, and over-rated) are considered in this paper to investigate the wake meandering effects on the dynamics of two FWTs. Damage equivalent loads(DEL) of the turbine critical components are computed and analyzed for several arrangements determined by the different spacing of the four turbines. The result shows that the dynamic wake meandering significantly affects downstream turbines’ global loadings and load effects. Differences in DEL show that blade-root flapwise bending moments and mooring fairlead tensions are sensitive to the spacing of the turbines.

Characteristics of sub-synchronous oscillation in grid-connected wind farm system

With the rapid development of wind power, wind turbines are accompanied by a large quantity of power electronic converters connected to the grid, causing changes in the characteristics of the power system and leading to increasingly serious sub-synchronous oscillation (SSO) problems, which urgently require the generalized classification and characterization of the emerging oscillation problems. This paper classifies and characterizes the emerging types of SSO caused by grid-connected wind turbines to address these issues. Finally, the impact of the typical system parameters changes on the oscillation pattern is analyzed in depth to provide effective support for the subsequent suppression and prevention of SSO.

Performance of the CMA-GD Model in Predicting Wind Speed at Wind Farms in Hubei, China

This study assesses the predictive capabilities of the CMA-GD model for wind speed prediction in two wind farms located in Hubei Province,China.The observed wind speeds at the height of 70m in wind turbines of two wind farms in Suizhou serve as the actual observation data for comparison and testing.At the same time,the wind speed predicted by the EC model is also included for comparative analysis.The results indicate that the CMA-GD model performs better than the EC model in Wind Farm A.The CMA-GD model exhibits a monthly average correlation coefficient of 0.56,root mean square error of 2.72 m s^(-1),and average absolute error of 2.11 m s^(-1).In contrast,the EC model shows a monthly average correlation coefficient of 0.51,root mean square error of 2.83 m s^(-1),and average absolute error of 2.21 m s^(-1).Conversely,in Wind Farm B,the EC model outperforms the CMA-GD model.The CMA-GD model achieves a monthly average correlation coefficient of 0.55,root mean square error of 2.61 m s^(-1),and average absolute error of 2.13 m s^(-1).By contrast,the EC model displays a monthly average correlation coefficient of 0.63,root mean square error of 2.04 m s^(-1),and average absolute error of 1.67 m s^(-1).

Research on Asymmetric Fault Location of Wind Farm Collection System Based on Compressed Sensing

Aiming at the problem that most of the cables in the power collection systemof offshore wind farms are buried deep in the seabed,whichmakes it difficult to detect faults,this paper proposes a two-step fault location method based on compressed sensing and ranging equation.The first step is to determine the fault zone through compressed sensing,and improve the datameasurement,dictionary design and algorithmreconstruction:Firstly,the phase-locked loop trigonometric functionmethod is used to suppress the spike phenomenon when extracting the fault voltage,so that the extracted voltage valuewillnot have a large error due to the voltage fluctuation.Secondly,theλ-NIM dictionary is designed by using the node impedancematrix and the fault location coefficient to further reduce the influence of pseudo-fault points.Finally,the CoSaMP algorithmis improved with the generalized Jaccard coefficient to improve the reconstruction accuracy.The second step is to use the ranging equation to accurately locate the asymmetric fault of the wind farm collection system on the basis of determining the fault interval.The simulation results show that the proposedmethod ismore accurate than the compressedsensingmethod andimpedancemethod in fault section location and fault location accuracy,the relative error is reduced from 0.75%to 0.4%,and has a certain anti-noise ability.

Research on Reactive Power Optimization of Offshore Wind Farms Based on Improved Particle Swarm Optimization

The lack of reactive power in offshore wind farms will affect the voltage stability and power transmission quality of wind farms.To improve the voltage stability and reactive power economy of wind farms,the improved particle swarmoptimization is used to optimize the reactive power planning in wind farms.First,the power flow of offshore wind farms is modeled,analyzed and calculated.To improve the global search ability and local optimization ability of particle swarm optimization,the improved particle swarm optimization adopts the adaptive inertia weight and asynchronous learning factor.Taking the minimum active power loss of the offshore wind farms as the objective function,the installation location of the reactive power compensation device is compared according to the node voltage amplitude and the actual engineering needs.Finally,a reactive power optimizationmodel based on Static Var Compensator is established inMATLAB to consider the optimal compensation capacity,network loss,convergence speed and voltage amplitude enhancement effect of SVC.Comparing the compensation methods in several different locations,the compensation scheme with the best reactive power optimization effect is determined.Meanwhile,the optimization results of the standard particle swarm optimization and the improved particle swarm optimization are compared to verify the superiority of the proposed improved algorithm.

Cyber-physical Modeling Technique based Dynamic Aggregation of Wind Farm Considering LVRT Characteristic

With the increasing penetration of wind power,large-scale integrated wind turbine brings stability and security risks to the power grid.For the aggregated modeling of large wind farms,it is crucial to consider low voltage ride-through(LVRT)characteristics.However,in aggregation methods,the approximate neglect behavior is essential,which leads to inevitable errors in the aggregation process.Moreover,the lack of parameters in practice brings new challenges to the modeling of a wind farm.To address these issues,a novel cyber-physical modeling method is proposed.This method not only overcomes the aggregation problem under the black-box wind farm but also accurately realizes the aggregation error fitting according to the operation data.The simulation results reveal that the proposed method can accurately simulate the dynamic behaviors of the wind farm in various scenarios,whether in LVRT mode or normal mode.

Optimization of the Active Composition of the Wind Farm Using Genetic Algorithms

The article presents the results of research on the possibilities of using genetic algorithms for solving the multicriteria optimization problem of determining the active components of a wind farm.Optimization is carried out on two parameters:efficiency factor of wind farm use(integrated parameter calculated on the basis of 6 parameters of each of the wind farm),average power deviation level(average difference between the load power and energy generation capabilities of the active wind farm).That was done an analysis of publications on the use of genetic algorithms to solve multicriteria optimization problems.Computer simulations were performed,which allowed us to analyze the obtained statistical data and determine the main optimization indicators.That was carried out a comparative analysis of the obtained results with other methods,such as the dynamic programming method;the dynamic programming method with the general increase of the set loading;the modified dynamic programming method,neural networks.It is established that the average power deviation for the genetic algorithm and for the modified dynamic programming method is located at the same level,33.7 and 28.8 kW,respectively.The average value of the efficiency coefficient of wind turbine used for the genetic algorithm is 2.4%less than for the modified dynamic programming method.However,the time of finding the solution by the genetic algorithm is 3.6 times less than for the modified dynamic programming method.The obtained results provide an opportunity to implement an effective decision support system in energy flow management.

An Observational Study on the Local Climate Effect of the Shangyi Wind Farm in Hebei Province

Zhangjiakou is an important wind power base in Hebei Province,China.The impact of its wind farms on the local climate is controversial.Based on long-term meteorological data from 1981 to 2018,we investigated the effects of the Shangyi Wind Farm(SWF)in Zhangjiakou on air temperature,wind speed,relative humidity,and precipitation using the anomaly or ratio method between the impacted weather station and the non-impacted background weather station.The influence of the SWF on land surface temperature(LST)and evapotranspiration(ET)using MODIS satellite data from 2003 to 2018 was also explored.The results showed that the SWF had an atmospheric warming effect at night especially in summer and autumn(up to 0.95℃).The daytime air temperature changes were marginal,and their signs were varying depending on the season.The annual mean wind speed decreased by 6%,mainly noted in spring and winter(up to 14%).The precipitation and relative humidity were not affected by the SWF.There was no increase in LST in the SWF perhaps due to the increased vegetation coverage unrelated to the wind farms,which canceled out the wind farm-induced land surface warming and also resulted in an increase in ET.The results showed that the impact of wind farms on the local climate was significant,while their impact on the regional climate was slight.

Sub-synchronous frequency domain-equivalent modeling for wind farms based on rotor equivalent resistance characteristics

The equivalent simplification of large wind farms is essential for evaluating the safety of power systems.However,sub-synchronous oscillations can significantly affect the stability of power systems.Although detailed mathematical models of wind farms can help accurately analyze the oscillation mechanism,the solution process is complicated and may lead to problems such as the“dimensional disaster.”Therefore,this paper proposes a sub-synchronous frequency domain-equivalent modeling method for wind farms based on the nature of the equivalent resistance of the rotor,in order to analyze sub-synchronous oscillations accurately.To this end,Matlab/Simulink is used to simulate a detailed model,a single-unit model,and an equivalent model,considering a wind farm as an example.A simulation analysis is then performed under the sub-synchronous frequency to prove that the model is effective and that the wind farm equivalence model method is valid.

Two-stage ADMM-based distributed optimal reactive power control method for wind farms considering wake effects

Since the connection of small-scale wind farms to distribution networks,power grid voltage stability has been reduced with increasing wind penetration in recent years,owing to the variable reactive power consumption of wind generators.In this study,a two-stage reactive power optimization method based on the alternating direction method of multipliers(ADMM)algorithm is proposed for achieving optimal reactive power dispatch in wind farm-integrated distribution systems.Unlike existing optimal reactive power control methods,the proposed method enables distributed reactive power flow optimization with a two-stage optimization structure.Furthermore,under the partition concept,the consensus protocol is not needed to solve the optimization problems.In this method,the influence of the wake effect of each wind turbine is also considered in the control design.Simulation results for a mid-voltage distribution system based on MATLAB verified the effectiveness of the proposed method.

A novel dynamic equivalence method for grid-connected wind farm

Dynamic equivalence of the wind farm is a fundamental problem in the simulation of a power system connected with wind farms because it is unpractical to model every generator in a wind farm in detail. In this paper, an Equivalence Method based on the Output Characteristics (EMOC) is proposed, with which the wind farm composed of Squirrel-Cage Induction Generators (SCIGs) can be equivalent to one generator. By considering the diversity of wind generators and special operating characteristics of a wind farm, the equivalent generator based on EMOC responds accurately in various faults. No matter whether the wind farm is integrated in grid or just programmed, EMOC can be used to acquire an accurate equivalent generator. Simulation of the dynamic equivalence of an SCIG wind farm validated the method.

Wind Farm Support Vessel Extreme Roll Assessment While Docking in the Bohai Sea

Robust prediction of extreme motions during wind farm support vessel(WFSV)operation is an important safety concern that requires further extensive research as offshore wind energy industry sector widens.In particular,it is important to study the safety of operation in random sea conditions during WFSV docking against the wind tower,while workers are able to get on the tower.Docking is performed by thrusting vessel fender against wind tower(an alternative docking way by hinging is not studied here).In this paper,the finite element software AQWA has been used to analyze vessel response due to hydrodynamic wave loads,acting on a specific maintenance ship under actual sea conditions.Excessive roll may occur during certain sea conditions,especially in the beam sea,posing a risk to the crew transfer operation.The Bohai Sea is the area of diverse industrial activities such as offshore oil production,wave and wind power generation,etc.This paper advocates a novel method for estimating extreme roll statistics,based on Monte Carlo simulations(or measurements).The ACER(averaged conditional exceedance rate)method and its modification are presented in brief detail in Appendix.The proposed methodology provides an accurate extreme value prediction,utilizing available data efficiently.In this study the estimated return level values,obtained by ACER method,are compared with the corresponding return level values obtained by Gumbel method.Based on the overall performance of the proposed method,it is concluded that the ACER method can provide more robust and accurate prediction of the extreme vessel roll.The described approach may be well used at the vessel design stage,while defining optimal boat parameters would minimize potential roll.

Analysis on Lightning Strike Cause of Directly Buried Optical Cable in Wind Farm and Its Prevention Methods

Directly buried metal optical cable is a form of erecting optical fiber ring network communication system in wind farms. Although the directly buried optical cable is much less than the overhead optical cable affected by lightning, sometimes lightning damaging optical cable and flashover discharge accidents of optical cable port occurred. In this paper, the amplitude spectrum of lightning wave, the breakdown depth and breakdown distance of lightning wave to soil, the metal components of optical cable port and the impedance characteristics of grounding wire are systematically analyzed, and the prevention methods of directly buried optical cable in wind farm to avoid lightning damage are proposed.

Frequency Regulation of Power Systems With a Wind Farm by Sliding-Mode-Based Design

Load frequency regulation is an essential auxiliary service used in dealing with the challenge of frequency stability in power systems that utilize an increasing proportion of wind power.We investigate a load frequency control method for multiarea interconnected power systems integrated with wind farms,aimed to eliminate the frequency deviation in each area and the tie-line power deviation between different areas.The method explores the derivative and integral terminal sliding mode control technology to solve the problem of load frequency regulation.Such technology employs the concept of relative degrees.However,the subsystems of wind-integrated interconnected power systems have different relative degrees,complicating the control design.This study develops the derivative and integral terminal sliding-mode-based controllers for these subsystems,realizing the load frequency regulation.Meanwhile,closed-loop stability is guaranteed with the theory of Lyapunov stability.Moreover,both a thermal power system and a wind power system are applied to provide frequency support in this study.Considering both constant and variable external disturbances,several numerical simulations were carried out in a two-area thermal power system with a wind farm.The results demonstrate the validity and feasibility of the developed method.

Characteristics of Lightning Damage to Coastal Wind Farms and Its Protective Measures

Firstly, characteristics of coastal wind farms were analyzed, and then lightning damage to coastal wind farms was discussed, finally main lightning protection measures were put forward from aspects of turbine blades, engine rooms and overvoltage protection. Besides conventional light- ning protection technology, local lightning protection, pre-discharge and lightning motoring and early warning techniques should be used to protect coastal wind farms against lightning.

Special report on relationship between wind farms and power grids

The installed capacity of a large scale wind power plant will be up to a number of hundreds MW, and the wind power is transmitted to load centers through long distance transmission lines with 220 kV, 500 kV, or 750 kV. Therefore, it is necessary not only considering the power transmission line between a wind power plant and the first connection node of the power network, but also the power network among the group of those wind power plants in a wind power base, the integration network from the base to the existed grids, as well as the distribution and consumption of the wind power generation by loads. Meanwhile, the impact of wind power stochastic fluctuation on power systems must be studied. In recent years, wind power prediction technology has been studied by the utilities and wind power plants. As a matter of fact, some European countries have used this prediction technology as a tool in national power dispatch centers and wind power companies.