Wind Power Base Research Articles

Research on entropy weight variation evaluation method for wind power clusters based on dynamic layered sorting

This paper presents an evaluation method for the entropy-weighting of wind power clusters that comprehensively evaluates the allocation problems of wind power clusters by considering the correlation between indicators and the dynamic performance of weight changes. A dynamic layered sorting allocation method is also proposed. The proposed evaluation method considers the power-limiting degree of the last cycle, the adjustment margin, and volatility. It uses the theory of weight variation to update the entropy weight coefficients of each indicator in real time, and then performs a fuzzy evaluation based on the membership function to obtain intuitive comprehensive evaluation results. A case study of a large-scale wind power base in Northwest China was conducted. The proposed evaluation method is compared with fixed-weight entropy and principal component analysis methods. The results show that the three scoring trends are the same, and that the proposed evaluation method is closer to the average level of the latter two, demonstrating higher accuracy. The proposed allocation method can reduce the number of adjustments made to wind farms, which is significant for the allocation and evaluation of wind power clusters.

A numerical simulation framework for wakes downstream of large wind farms based on equivalent roughness model

Accurate assessment of the wake effect of wind farm clusters is of great significance for the development of wind power bases, yet there is currently a deficiency in numerical simulation methods with high accuracy and simple modeling. To address this issue, a numerical simulation framework for large wind-farm wakes based on a wind farm parameterization model is proposed, and is then implemented based on the open-source CFD software OpenFOAM. In this framework, a newly proposed wind farm equivalent roughness model is adopted to parameterize wind farms and incorporated into the simulation via the wall stress model. To validate the method, the large-eddy simulation based on the actuator disk model resolving all the turbines in the wind farm is taken as a benchmark. Thirty two cases including spanwise infinite wind farms and finite wind farms with different streamwise turbine spacings, spanwise turbine spacings, wind turbine thrust coefficients, and roughness lengths of ground surface are set to analyze the sensitivity of the framework to different wind farm parameters. Results show that the proposed method predicts the velocity deficit and turbulence intensity downstream of the wind farm accurately. Compared to the classical wake superposition model, the prediction accuracy of the velocity deficit is improved by more than 30 %. Furthermore, without resolving the turbines using fine mesh, the framework shows a high potential to reduce computational costs compared with the turbine-resolved simulation.

Inter-farm cluster interaction of the operational and planned offshore wind power base

The inter-farm cluster interaction is one of the most difficult aspects of building and planning ten million-kilowatt offshore wind power bases. This study is an attempt to assess the wake and production interactions in the substantial offshore wind farms in Jiangsu Province of China under operational (2020) and planned (2025) scenarios using the updated Weather Research and Forecasting model coupled with the 3D Price-Weller-Pinkel ocean model and the wind farm parameterization model. The results indicate a larger wind deficit of −0.73 ∼ −1.30 m/s in the planned levels of 2025 than that of −0.52 m/s in 2020, with the wake meandering enlarged from 30 km to 90–100 km. Moreover, the newly added power capacity path in the future wind farm development has an impact on power production. The capacity factor of the wind power base will decrease if the average number of turbines in a wind farm is increased or the turbine capacity is increased. It is interesting to note that the planned development mode of positive turbine capacity with conservative farm capacity has relatively low inter-farm cluster wake interference and can be recommended as a priority path for the offshore wind power industry to achieve carbon neutrality and cleaner production.

Allocating the capacity of shared energy storage for wind farm groups based on the over-limit power export risk

Energy storage in wind farms can stabilize the fluctuation of wind power output. Shared energy storage can reduce the construction cost of energy storage devices and stimulate the enthusiasm of wind farms to invest in energy storage. The wind power base is composed of multiple wind farm groups. Existing research methods did not consider how to allocate shared energy storage among wind farm groups in the wind power base. This paper proposes an energy storage capacity allocation method for wind farm groups. Firstly, a bilevel model for the shared energy storage allocation is established. The upper-level model optimizes the shared energy storage allocation of each wind farm group with the goal of minimizing the over-limit power export risk in the wind power base; The lower-level model calculates the over-limit power export of each wind farm group according to the energy storage capacity allocation and transfers the value of over-limit power export to the upper-level model. The bilevel model can be converted to a two-stage model that can be solved sequentially; The wind power base in Belgium is used for numerical simulation to verify the effectiveness of the proposed model. Finally, the sensitivity of confidence level, total energy storage capacity, and risk preference factor are analyzed.

Optimal Configuration Method for the Installed Capacity of the Solar-Thermal Power Stations

Because of the randomness of wind power and photovoltaic (PV) output of new energy bases, the problem of peak regulation capability and voltage stability of ultra-high voltage direct current (UHVDC) transmission lines, we proposed an optimum allocation method of installed capacity of the solar-thermal power station based on chance constrained programming in this work. Firstly, we established the uncertainty model of wind power and PV based on the chance constrained planning theory. Then we used the K-medoids clustering method to cluster the scenarios considering the actual operation scenarios throughout the year. Secondly, we established the optimal configuration model based on the objective function of the strongest transient voltage stability and the lowest overall cost of operation. Finally, by quantitative analysis of actual wind power and photovoltaic new energy base, this work verified the feasibility of the proposed method. As a result of the simulations, we found that using the optimal configuration method of solar-thermal power stations could ensure an accurate allocation of installed capacity. When the installed capacity of the solar-thermal power station is 1 × 106 kW, the transient voltage recovery index (TVRI) is 0.359, which has a strong voltage support capacity for the system. Based on the results of this work, the optimal configuration of the installed capacity of the solar-thermal power plant can improve peak shaving performance, transient voltage support capability, and new energy consumption while satisfying the Direct Current (DC) outgoing transmission premise.

An adaptive spatiotemporal fusion graph neural network for short-term power forecasting of multiple wind farms

Reliable short-term wind-power forecasting is crucial for the safe operation of power systems that accommodate large amount of wind power. With the development of large-scale wind power bases, wind power spatiotemporal correlations of multiple wind farms (WFs) can be used to improve short-term wind power prediction accuracy and efficiency. However, the time-varying and coupling characteristics of wind power spatiotemporal correlations present significant challenges for the accurate prediction of multi-WF power. In this paper, we propose an adaptive spatiotemporal fusion graph neural network for short-term power forecasting of multiple wind farms. Based on regional weather forecasts and historical wind power data, an adaptive directed graph is generated to model the dynamic spatial correlations between the WFs and the impact of regional weather factors on the wind power of different WFs. Graph convolution modules and temporal recursive modules are then alternately arranged to fuse the spatial and temporal features of wind power and to output the wind power prediction results for multiple WFs and time points. The case study results show that the proposed model outperforms the investigated baseline models in terms of prediction accuracy and that each model component has a unique contribution.

An Improved Quantitative Analysis Method of Oscillation Mode for DFIG-Based Wind Power Base With LCC-HVDC Transmission Considering Frequency Coupling Characteristic

The line-commutated converter-based high-voltage direct-current (LCC-HVDC) transmission has become one of the main forms to deliver wind power in China. However, due to the connections of a large number of power electronic devices (PEDs), there emerges a risk of sub/super-synchronous oscillations in the DFIG-based wind power base with LCC-HVDC transmission. The existing multi-node system analysis methods have ignored the frequency coupling characteristic (FCC) of PEDs, unable to obtain accurate oscillation characteristics. Besides, the relationship between the oscillation and multi-level factors has not been revealed yet. Therefore, this paper proposes an improved quantitative analysis method of oscillation mode which considers the FCC on the basis of the system admittance network model. Firstly, the impedance model of the system considering the FCC is established. Then, the improved quantitative analysis method of the oscillation mode considering the FCC is proposed and its steps are as follows. 1) To establish the system transfer function matrix considering the FCC, and determine the system stability accurately by the dominant oscillation mode; 2) To define the node oscillation participation factor, considering the effect of the coupling frequency, and quantify the participation degree of each node and identify the origin and weak point of oscillation; 3) To carry out multi-level oscillation mode sensitivity analysis. Finally, the oscillation characteristics and laws of the DFIG-based wind power base with LCC-HVDC transmission are studied, and the time-domain simulations in MATLAB/Simulink validate the analytical results.

Active power control strategy for wind farms based on power prediction errors distribution considering regional data.

One of the renewable energy resources, wind energy is widely used due to its wide distribution, large reserves, green and clean energy, and it is also an important part of large-scale grid integration. However, wind power has strong randomness, volatility, anti-peaking characteristics, and the problem of low wind power prediction accuracy, which brings serious challenges to the power system. Based on the difference of power prediction error and confidence interval between different new energy power stations, an optimal control strategy for active power of wind farms was proposed. Therefore, we focus on solving the problem of wind power forecasting and improving the accuracy of wind power prediction. Due to the prediction error of wind power generation, the power control cannot meet the control target. An optimal control strategy for active power of wind farms is proposed based on the difference in power prediction error and confidence interval between different new energy power stations. The strategy used historical data to evaluate the prediction error distribution and confidence interval of wind power. We use confidence interval constraints to create a wind power active optimization model that realize active power distribution and complementary prediction errors among wind farms with asymmetric error distribution. Combined with the actual data of a domestic (Cox’s Bazar, Bangladesh) wind power base, a simulation example is designed to verify the rationality and effectiveness of the proposed strategy.

Distributed onshore wind farm siting using intelligent optimization algorithm based on spatial and temporal variability of wind energy

Distributed joint complementary wind generation is a powerful way to reduce the variability and improve the penetration of wind power. But distributed wind farm siting is a complex problem of nonlinear and global combinatorial optimization. Various correlation coefficients were used to measure the complementarity of renewable energy, which were not intuitive and accurate in former studies, and traditional siting methods are based on the abundance of wind energy, siting results cannot fully utilize the complementary potential of distributed wind energy. In this study, intelligent optimization algorithm is adopted to select the location of distributed wind farm in China mainland from the perspective of utilizing the complementarity of wind energy. The result showed that the existing wind power bases have obvious complementary superiority, combined power generation can improve availability from about 57.61% to 66.93%, reduce the long/short term variability confidence by about 40%. Siting result indicated that central and eastern Inner Mongolia, Xinjiang and Hexi Corridor are still key regions for the future wind farms construction. This study provides more direct evidence of the complementarity of existing wind power bases, and the proposed siting methodology can be applied in different regions worldwide.

Modeling and Simulation of Large-Scale Wind Power Base Output Considering the Clustering Characteristics and Correlation of Wind Farms

The rapid development of renewable energy improves the requirements of renewable energy output simulation. The clustering characteristics and correlation of renewable energy would improve the accuracy of power output simulation. To clarify the typical power output process of a large-scale wind power base, a novel method is proposed for wind power output scene simulation in this paper. Firstly, the genetic algorithm (GA) Kmeans is used to divide the wind farm clusters. The wind power output of each cluster is calculated by the wind turbine model. Then, the Copula principle is used to describe the correlation characteristic of wind farm clusters. Finally, the power output scenes are simulated by the Markov chain Monte Carlo (MCMC) method. To verify the effectiveness of proposed method, the wind power base in the downstream Yalong River basin is taken as the case study. The results show that the 65 wind farms should be divided into 6 clusters. The five typical power output scenes in winter–spring and summer–autumn seasons are simulated respectively based on the clustering characteristics and correlation of wind farms. This study provides a valuable reference for other large-scale renewable power bases all over the world.

Mesoscale simulations of a real onshore wind power base in complex terrain: Wind farm wake behavior and power production

Sustainable development of wind power is challenging due to the difficulty in detecting farm-to-farm wake. In this work, the wind farm wake and power production of Zhangbei wind power base under various wind and topography are studied using the mesoscale weather research and forecasting model coupled with a wind farm parameterization. The results show that the farm wake is closely related to wind and topography. The maximum wind deficit that occurs in the medium prevailing wind at isolated and mountainous regions are 2.5 m/s and 0.5 m/s, respectively. The farm wake recovers downstream 20–35 km or more in isolated wind farms and about 6 km or less in mountainous wind farms, which can be neglected vertically higher than twice and fourfold diameters above the hub height. Moreover, the wind farms fully utilize the terrain acceleration outperform those located in the lower areas at the windward of the hill. The uncoordinated wind farm region with the minimum average normalized power of 0.47 is detected, which is attributed to the dense layout and no reasonable buffer zone along with the prevailing wind. It is imperative to perceive these and provide potential solutions to promote the sustainable development of wind power.

Retraction Note: Research on subsynchronous oscillation characteristics and suppression strategy of AC network with wind power base

Retraction Note: Research on subsynchronous oscillation characteristics and suppression strategy of AC network with wind power base

Cross-regional integrated transmission of wind power and pumped-storage hydropower considering the peak shaving demands of multiple power grids

Due to the inherent uncertainty and intermittence of wind power, and the geographical mismatch between the wind power bases and the load demand, the problem of wind curtailment is becoming increasingly serious in China. To promote the consumption of wind power, this paper studies the short-term operation of a wind farm-pumped storage hydropower plant (WF-PSHP) hybrid system which transmits power to multiple cross-regional power grids through ultra-high-voltage (UHV) transmission lines. In this study, the forecasted error distribution of wind power is fitted using kernel density estimation. An optimization model that considers the peak shaving demands of receiving-end power grids (REPGs) is then established to determine the daily operation of the WF-PSHP system. The hydraulic constraints of the PSHP and individual unit operation constraints are also taken into account to make the model more accurate. To improve the solving efficiency, the original stochastic model is transformed into a deterministic mixed-integer linear programming (MILP) problem through several deterministic conversion and linearization techniques. The real-world case studies demonstrate that the integrated transmission of the WF and PSHP can reduce the peak-valley difference of the REPGs while absorbing large-scale wind power on different typical days in summer and winter.

RETRACTED ARTICLE: Research on subsynchronous oscillation characteristics and suppression strategy of AC network with wind power base

When the wind farm is connected to the power system, certain issues, such as SSO, will be caused, rendering the protection of the power grid unstable. Researchers have found that this situation can be effectively avoided by direct-drive permanent magnet wind power generation. Generates synchronous frequency oscillation is with the help of a grid connection without series compensation. This mode of power generation is part of a new method of subsynchronous oscillation of the wind farm, and the concepts and steps are not explicit. From the point of view of theory, this paper analyzes the causes of its effect, as well as the methods and measures used, and lists the study reports and findings on the synchronous oscillation of grid-connected direct-driven wind farms at home and abroad. At the end of the article, the author also put forward the hypothesis and the imagination of this process. The theory of the wind fire bundling DC transmission system is that the equipment and AC current will communicate, and synchronous electrical oscillation will also occur, and the torsional vibration of the thermal power unit will occur. Our study starts from the investigation of the and explaining the theory behind the wind power and AC network. In combination with the power grid parameter data, the oscillation times of subsynchronous current harmonics in the wind farm are obtained in a specific environment and the conditions of the subsynchronous harmonic generation are analyzed. At the same time, the effect of line harmonic impedance and current oscillation frequency is also simulated.

Storage-Transmission Joint Planning Method to Deal with Insufficient Flexibility and Transmission Congestion

The insufficient power system flexibility and transmission congestion are two fundamental reasons for wind power curtailment. As the scale of the wind power in the power system is growing rapidly, the two factors of wind power curtailment events coexist and have a certain coupling relationship. The configuration of the energy storage system can not only increase the flexibility of the system but also alleviate transmission congestion. Therefore, the joint planning of energy storage and transmission grid that takes into account the flexibility of the system and the transmission congestion is of great significance to solve the wind curtailment. Hence, this paper first decouples the insufficient flexibility and transmission congestion wind power curtailment, and quantitatively analyzes the impact of transmission capacity on the coupling relationship between the two; second, reveals the principle of joint planning of energy storage system and transmission congestion, and constructs an optimization model, and proposes to set up the capacity of the wind power which connects the power network. The solution procedure, which deals with grid planning and the energy storage system optimization in turn, not only ensures the accuracy of the model, but also significantly reduces the calculation cost. Finally, a case study of a wind power base in Northeast China and an improved Garver-6 system are carried out to verify the effectiveness of the proposed method.

Optimal allocation of onshore wind power in China based on cluster analysis

Development of wind power in China, a key measure to mitigate China’s carbon emissions and achieve global climate goals, faces serious curtailment issues. In an interlinked electric power system, a strategic allocation of wind power capacities offers an important means to take advantage of geographical smoothing effects and enhance accommodation of wind power into the electric power system. Applying K-means clustering algorithm with assimilated meteorological data, we differentiate seven wind zones in the Chinese mainland. The zonal variation features of wind power are characterized and associated with influencing weather systems and geographical conditions. A multi-objective optimization model is developed to identify the optimal allocation of wind power capacity across the seven zones in 2030, which demonstrates further improvement of wind power quality from the current distribution case in terms of high power outputs (+0.2%), low short-term variation (−10.3%) and high firm capacity (+3.7%). Northern China, where existing large-scale wind power bases are located, and southeastern regions are identified as key areas for future deployment of wind power. These findings are expected to offer a new perspective for decision makers in the construction of power grid systems and spatial development strategy for wind power in China.

Characteristics and Suppression Strategies of Subsynchronous Oscillation in AC Power Grid Containing Wind Power Base

The use of renewable energy sources such as wind and solar energy to replace increasingly depleted fossil energy sources has become a key way to achieve sustainable development in human society. Wind energy is one of the fastest growing clean energy sources in the world and the third largest clean energy source behind hydropower and nuclear power. However, the wind turbine is connected to the power grid through power electronics and adopts the traditional vector control based on the locker ring. Its dynamic behavior is not as friendly as that of a synchronous generator, and its resistance to disturbances is even worse in a weak grid. As the proportion of wind power continues to increase, the strength of the power grid continues to decline, resulting in a series of safety and stability accidents. In recent years, there have been many related studies on the application of synchronous control in inverters, but very little research on the application of synchronous control in double-fed fans. In this context, this paper mainly studies the sub-synchronous oscillation of AC power grids with wind power bases. Characteristics and suppression strategies. In this paper, the time window is 6-10s, and the eigenvalue analysis method is used to identify the type of the model. It can be seen that the identification result of PRONY analysis is consistent with the eigenvalue analysis, which verifies the correctness of the model and eigenvalue analysis result.

Coordination control method for multi-wind farm systems to prevent sub/super-synchronous oscillations

In recent years, the sub/super-synchronous oscillations occur frequently in the large-scale wind power bases of China. Since the oscillation frequencies are close to the fundamental frequency, the current components can spread over a large area, and may destroy the shafting of rotating devices in the power grid. Improving the control strategy and parameters of wind turbines can prevent this problem to some extent, however, due to the complex operation conditions and continuous development of wind power, the off-line improvement measure on wind turbines cannot eliminate the potential oscillations risks. This paper is to propose an oscillation risk screening and stability assessment method, and develop a coordination control method for the large-scale wind farm systems to prevent the sub/super-synchronous oscillations. The Nyquist criterion and the modal analysis method are combined to generate quantitative factors for the stability assessment and the control strategy design. The coordination control method consists of minute-level power coordinated allocation and second-level fast power control to prevent and eliminate the oscillations. Detailed simulation model of a multiple wind farms system originated from the actual wind power base in China is presented to verify the effectiveness of the proposed method.

A Storage and Transmission Joint Planning Method for Centralized Wind Power Transmission

Centralized delivery has become the main operation mode under the scaled development of wind power. Transmission channels are usually the guarantee of out-delivered wind power for large-scale wind base. The configuration of transmission capacity, which has the features of low utilization and poor economy, is hardly matching correctly due to the volatility and low energy density of wind. The usage of energy storage can mitigate wind power fluctuations and reduce the requirement of out-delivery transmission capacity, but facing the issue of energy storage cost recovery. Therefore, it is necessary to optimize the allocation of energy storage while considering the problem of wind power transmission. This paper studies the joint optimization of large-scale wind power transmission capacity and energy storage, reveals the mechanism of energy storage in order to reduce the power fluctuation of wind power base and slow down the demand of transmission. Then, analyze the multi-functional cost-sharing mode of energy storage, improve the efficiency of energy storage cost recovery. Constructs the coordination optimization configuration model to deal with the problem of large-scale wind power transmission capacity and energy storage, and realizes the transmission capacity optimization coordination and optimization with energy storage. The proposed method is verified by a wind base located in Northeast China.

Resonance Stability Analysis of Large-Scale Wind Power Bases with Type-IV Wind Generators

To guarantee the reliable and efficient development of wind power generation, oscillation problems in large-scale wind power bases with Type-IV generators are investigated from the view of resonance stability in this paper. Firstly, the transfer characteristics of disturbances in Type-IV wind generators are analyzed to establish their impedance model, based on the balance principle of frequency components. Subsequently, considering the dynamic characteristics of the transmission network and the interaction among several wind farms, the resonance structure of a practical wind power base is analyzed based on the s-domain nodal admittance matrix method. Furthermore, the unstable mechanism of the resonance mode is further illustrated by the negative-resistance effect theory. Finally, the established impedance model of the Type-IV wind generator and the resonance structure analysis results of the wind power bases are verified through the time-domain electro-magnetic transient simulation in PSCAD/EMTDC. Case studies indicate that there is a certain resonance instability risk in large-scale wind power bases in a frequency range of 1–100 Hz, and the unstable resonance mode is strongly related to the negative-resistance effect and the capacitive effect of Type-IV wind generators.