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| 1 | State-of-the-art review on frequency response of wind power plants in power systems显示文摘With an increasing penetration of wind power in the modern electrical grid, the increasing replacement of large conventional synchronous generators by wind power plants will potentially result in deteriorated frequency regulation performance due to the reduced system inertia and primary frequency response. A series of challenging issues arise from the aspects of power system planning,operation, control and protection. Therefore, it is valuable to develop variable speed wind turbines(VSWTs) equipped with frequency regulation capabilities that allow them to effectively participate in addressing severe frequency contingencies. This paper provides a comprehensive surveyon frequency regulation methods for VSWTs. It fully describes the concepts, principles and control strategies of prevailing frequency controls of VSWTs, including future development trends. It concludes with a performance comparison of frequency regulation by the four main types of wind power plants. | Ziping WU Wenzhong GAO Tianqi GAO Weihang YAN Huaguang ZHANG Shijie YAN Xiao WANG | 2018 | Journal of Modern Power Systems and Clean Energy2018，6，1： | 26 |
| 2 | Measures against the adverse impact of natural wind on air-cooled condensers in power plant显示文摘The natural wind plays disadvantageous roles in the operation of air-cooled steam condensers in power plant.It is of use to take various measures against the adverse effect of wind for the performance improvement of air-cooled condensers.Based on representative 2×600 MW direct air-cooled power plant,three ways that can arrange and optimize the flow field of cooling air thus enhance the heat transfer of air-cooled condensers were proposed.The physical and mathematical models of air-cooled condensers with various flow leading measures were presented and the flow and temperature fields of cooling air were obtained by CFD simulation.The back pressures of turbine were calculated for different measures on the basis of the heat transfer model of air-cooled condensers.The results show that the performance of air-cooled condensers is improved thus the back pressure of turbine is lowered to some extent by taking measures against the adverse impact of natural wind. | YANG LiJun,DU XiaoZe & YANG YongPing Key Laboratory of Condition Monitoring and Control for Power Plant Equipment of Ministry of Education of China,North China Electric Power University,Beijing 102206,China | 2010 | Science China(Technological Sciences)2010，53，5： | 21 |
| 3 | Heat and power load dispatching considering energy storage of district heating system and electric boilers显示文摘As one of promising clean and low-emission energy, wind power is being rapidly developed in China.However, it faces serious problem of wind curtailment,particularly in northeast China, where combined heat and power(CHP) units cover a large proportion of the district heat supply. Due to the inherent strong coupling between the power and the heat load, the operational flexibility of CHP units is severely restricted in winter to meet the heat supply demand, which imparts considerable stress on the wind power connection to the grid. To promote the integration of wind power and enhance the flexibility of CHP units, this paper presented a method of heat and power load dispatching by exploring the energy storage ability of electric heating boilers and district heating systems. The optimization results indicate that the proposed method can integrate additional wind power into the grid and reduce the coal consumption of CHP units over the optimized period. Furthermore, the thermal inertia of a district heating system is found to contribute more to the reduction of coal consumption, whereas the electric heating boilers contribute to lower wind curtailment. | Xianzheng HUANG Zhaofeng XU Yong SUN Yali XUE Zhe WANG Zhijun LIU Zhenyuan LI Weidou NI | 2018 | Journal of Modern Power Systems and Clean Energy2018，6，5： | 20 |
| 4 | 近海风电基础桩土作用3D有限元模拟显示文摘针对近海风电桩基础型式,采用接触单元法、表面效应单元法分别构建了桩和土的3D全实体、桩体3D实体有限元模型,以典型海上风电基础桩土作用分析算例,实现了两种模型的有限元计算。计算结果表明,表面效应单元法比接触单元法计算速率高但精度略差,比常规的m法计算精度高,为实际海上风电基础桩土作用的有限元计算分析提供了参考。 | 李炜 郑永明 周永 | 2010 | 水电能源科学2010，28，8： | 19 |
| 5 | Model predictive control and improved low-pass filtering strategies based on wind power fluctuation mitigation显示文摘The rapid development of renewable energy sources such as wind power has brought great challenges to the power grid. Wind power penetration can be improved by using hybrid energy storage(ES) to mitigate wind power fluctuation. We studied the strategy of smoothing wind power fluctuation and the strategy of hybrid ES power distribution. Firstly, an effective control strategy can be extracted by comparing constant-time low-pass filtering(CLF), variable-time low-pass filtering(VLF), wavelet packet decomposition(WPD), empirical mode decomposition(EMD) and model predictive control algorithms with fluctuation rate constraints of the identical grid-connected wind power. Moreover, the mean frequency of ES as the cutoff frequency can be acquired by the Hilbert Huang transform(HHT), and the time constant of filtering algorithm can be obtained. Then, an improved low-pass filtering algorithm(ILFA) is proposed to achieve the power allocation between lithium battery(LB) and supercapacitor(SC), which can overcome the over-charge and over-discharge of ES in the traditional low-pass filtering algorithm(TLFA). In addition, the optimized LB and SC power are further obtained based on the SC priority control strategy combined with the fuzzy control(FC) method. Finally, simulation results show that wind power fluctuation can be effectively suppressed by LB and SC based on the proposed control strategies, which is beneficial to the development of wind and storage system. | Yushu SUN Xisheng TANG Xiaozhe SUN Dongqiang JIA Zhihuang CAO Jing PAN Bin XU | 2019 | Journal of Modern Power Systems and Clean Energy2019，7，3： | 13 |
| 6 | Control scheme of hexagonal modular multilevel direct converter for offshore wind power integration via fractional frequency transmission system显示文摘A fractional frequency transmission system(FFTS)is a promising solution to offshore wind power integration,for which the hexagonal modular multilevel converter(Hexverter)is an attractive choice for power conversion.The Hexverter has recently been proposed to directly connect two three-phase systems of different frequencies and voltage amplitudes,with only six branches in the FFTS in that case.This paper examines for the first time the control scheme of the Hexverter when applied to offshore wind power integration via a FFTS.Firstly,the frequency-decoupled mathematical model of the Hexverter is deduced by introducing the double dq transformation.Then the branch energy of the Hexverter is analyzed in detail and the reactive power constraint equation is obtained.The corresponding control scheme is thoroughly discussed,including the inner loop current control,the outer loop voltage control in both grid-connected mode and passive mode,and a novel optimization method to minimize the circulating current in the Hexverter.Finally,a simulation model of offshore wind power integration via a 4-terminal FFTS based on the Hexverter is built in MATALB/Simulink to verify the feasibility of Hexverter and the effectiveness of the control scheme proposed in this paper. | Yongqing MENG Bo LIU Huiyong LUO Shuonan SHANG Haitao ZHANG Xifan WANG | 2018 | Journal of Modern Power Systems and Clean Energy2018，6，1： | 12 |
| 7 | Transition towards higher penetration of renewables: an overview of interlinked technical, environmental and socio-economic challenges显示文摘Investment for renewables has been growing rapidly since the beginning of the new century, and the momentum is expected to sustain in order to mitigate the impact of anthropogenic climate change.Transition towards higher renewable penetration in the power industry will not only confront technical challenges, but also face socio-economic obstacles.The connected between environment and energy systems are also tightened under elevated penetration of renewables.This paper will provide an overview of some important challenges related to technical, environmental and socio-economic aspects at elevated renewable penetration.An integrated analytical framework for interlinked technical, environmental and socio-economic systems will be presented at the end. | Xinyu CHEN Michael B.MCELROY Qiuwei WU Yinbiao SHU Yusheng XUE | 2019 | Journal of Modern Power Systems and Clean Energy2019，7，1： | 11 |
| 8 | Superconducting magnetic energy storage for stabilizing grid integrated with wind power generation systems显示文摘Due to the interconnection of various renewable energies and adaptive technologies, voltage quality and frequency stability of modern power systems are becoming erratic. Superconducting magnetic energy storage(SMES),for its dynamic characteristic, is very efficient for rapid exchange of electrical power with grid during small and large disturbances to address those instabilities.In addition,SMES plays an important role in integrating renewable sources such as wind generators to power grid by controlling output power of wind plant and improving the stability of power system.Efficient application of SMES in various power system operations depends on the proper location in the power system, exact energy and power ratings and appropriate controllers. In this paper, an effort is given to explain SMES device and its controllability to mitigate the stability of power grid integrated with wind power generation systems. | Poulomi MUKHERJEE V. V. RAO | 2019 | Journal of Modern Power Systems and Clean Energy2019，7，2： | 11 |
| 9 | Wind power prediction based on variational mode decomposition multi-frequency combinations显示文摘Because of the uncertainty and randomness of wind speed, wind power has characteristics such as nonlinearity and multiple frequencies. Accurate prediction of wind power is one effective means of improving wind power integration. Because the traditional single model cannot fully characterize the fluctuating characteristics of wind power, scholars have attempted to build other prediction models based on empirical mode decomposition(EMD) or ensemble empirical mode decomposition(EEMD) to tackle this problem. However, the prediction accuracy of these models is affected by modal aliasing and illusive components. Aimed at these defects, this paper proposes a multi-frequency combination prediction model based on variational mode decomposition(VMD). We use a back propagation neural network(BPNN),autoregressive moving average(ARMA)model, and least square support vector machine(LS-SVM) to predict high, intermediate,and low frequency components,respectively. Based on the predicted values of each component, the BPNN is applied to combine them into a final wind power prediction value.Finally,the prediction performance of the single prediction models(ARMA,BPNN and LS-SVM)and the decomposition prediction models(EMD and EEMD) are used to compare with the proposed VMD model according to the evaluation indices such as average absolute error, mean square error,and root mean square error to validate its feasibility and accuracy. The results show that the prediction accuracy of the proposed VMD model is higher. | Gang ZHANG Hongchi LIU Jiangbin ZHANG Ye YAN Lei ZHANG Chen WU Xia HUA Yongqing WANG | 2019 | Journal of Modern Power Systems and Clean Energy2019，7，2： | 10 |
| 10 | Short-term local prediction of wind speed and wind power based on singular spectrum analysis and locality-sensitive hashing显示文摘With the growing penetration of wind power in power systems, more accurate prediction of wind speed and wind power is required for real-time scheduling and operation. In this paper, a novel forecast model for shortterm prediction of wind speed and wind power is proposed,which is based on singular spectrum analysis(SSA) and locality-sensitive hashing(LSH). To deal with the impact of high volatility of the original time series, SSA is applied to decompose it into two components: the mean trend,which represents the mean tendency of the original time series, and the fluctuation component, which reveals the stochastic characteristics. Both components are reconstructed in a phase space to obtain mean trend segments and fluctuation component segments. After that, LSH is utilized to select similar segments of the mean trend segments, which are then employed in local forecasting, so that the accuracy and efficiency of prediction can be enhanced. Finally, support vector regression is adopted forprediction, where the training input is the synthesis of the similar mean trend segments and the corresponding fluctuation component segments. Simulation studies are conducted on wind speed and wind power time series from four databases, and the final results demonstrate that the proposed model is more accurate and stable in comparison with other models. | Ling LIU Tianyao JI Mengshi LI Ziming CHEN Qinghua WU | 2018 | Journal of Modern Power Systems and Clean Energy2018，6，2： | 10 |
| 11 | Probabilistic small signal stability analysis of power system with wind power and photovoltaic power based on probability collocation method显示文摘Recently, with increasing improvements in the penetration of wind power and photovoltaic power in the world, probabilistic small signal stability analysis(PSSSA) of a power system consisting of multiple types of renewable energy has become a key problem. To address this problem, this study proposes a probabilistic collocation method(PCM)-based PSSSA for a power system consisting of wind farms and photovoltaic farms. Compared with the conventional Monte Carlo method, the proposed method meets the accuracy and precision requirements and greatly reduces the computation; therefore, it is suitable for the PSSSA of this power system. Case studies are conducted based on a 4-machine 2-area and New England systems, respectively. The simulation results show that, by reducing synchronous generator output to improve the penetration of renewable energy, the probabilistic small signal stability(PSSS) of the system is enhanced. Conversely, by removing part of the synchronous generators to improve the penetration of renewable energy, the PSSS of the system may be either enhanced or deteriorated. | Cai Yan Linli Zhou Wei Yao Jinyu Wen Shijie Cheng | 2019 | Global Energy Interconnection2019，2，1： | 9 |
| 12 | Wind power forecasting based on outlier smooth transition autoregressive GARCH model显示文摘The impacts of outlying shocks on wind power time series are explored by considering the outlier effect in the volatility of wind power time series. A novel short term wind power forecasting method based on outlier smooth transition autoregressive(OSTAR) structure is advanced, then, combined with the generalized autoregressive conditional heteroskedasticity(GARCH) model, the OSTAR-GARCH model is proposed for wind power forecasting. The proposed model is further generalized to be with fat-tail distribution.Consequently, the mechanisms of regimes against different magnitude of shocks are investigated owing to the outlier effect parameters in the proposed models. Furthermore, the outlier effect is depicted by news impact curve(NIC) and a novel proposed regime switching index(RSI). Case studies based on practical data validate the feasibility of the proposed wind power forecasting method. From the forecast performance comparison of the OSTAR-GARCH models, the OSTAR-GARCH model with fat-tail distribution proves to be promising for wind power forecasting. | Hao CHEN Fangxing LI Yurong WANG | 2018 | Journal of Modern Power Systems and Clean Energy2018，6，3： | 8 |
| 13 | Maximum entropy based probabilistic load flow calculation for power system integrated with wind power generation显示文摘Distributed generation including wind turbine(WT) and photovoltaic panel increases very fast in recent years around the world, challenging the conventional way of probabilistic load flow(PLF) calculation. Reliable and efficient PLF method is required to take this chage into account.This paper studies the maximum entropy probabilistic density function reconstruction method based on cumulant arithmetic of linearized load flow formulation,and then develops a maximum entropy based PLF(MEPLF) calculation algorithm for power system integrated with wind power generation(WPG). Compared with traditional Gram–Charlier expansion based PLF(GC-PLF)calculation method, the proposed ME-PLF calculation algorithm can obtain more reliable and accurate probabilistic density functions(PDFs) of bus voltages and branch flows in various WT parameter scenarios. It can solve thelimitation of GC-PLF calculation method that mistakenly gains negative values in tail regions of PDFs. Linear dependence between active and reactive power injections of WPG can also be effectively considered by the modified cumulant calculation framework. Accuracy and efficiency of the proposed approach are validated with some test systems. Uncertainties yielded by the wind speed variations, WT locations, power factor fluctuations are considered. | Bingyan SUI Kai HOU Hongjie JIA Yunfei MU Xiaodan YU | 2018 | Journal of Modern Power Systems and Clean Energy2018，6，5： | 8 |
| 14 | Regional wind power forecasting model with NWP grid dataoptimized显示文摘Unlike the traditional fossil energy, wind, asthe clean renewable energy, can reduce the emission of thegreenhouse gas. To take full advantage of the environ-mental benefits of wind energy, wind power forecastinghas to be studied to overcome the troubles brought by thevariable nature of wind. Power forecasting for regionalwind farm groups is the problem that many power systemoperators care about. The high-dimensional feature setswith redundant information are frequently encounteredwhen dealing with this problem. In this paper, two kinds offeature set construction methods are proposed which canachieve the proper feature set either by selecting thesubsets or by transforming the original variables withspecific combinations. The former method selects thesubset according to the criterion of minimal-redundancy-maximal-relevance (mRMR), while the latter does sobased on the method of principal component analysis(PCA). A locally weighted learning method is alsoproposed to utilize the processed feature set to producethe power forecast results. The proposed model is simpleand easy to use with parameters optimized automatically.Finally, a case study of 28 wind farms in East China isprovided to verify the effectiveness of the proposedmethod. | Zhao WANG Weisheng WANG Bo WANG | 2017 | Frontiers in Energy2017，11，2： | 6 |
| 15 | Accommodation of curtailed wind power by electric water heaters based on a new hybrid prediction approach显示文摘Wind power curtailment is of great importance with the increase of large-scale wind power connected to the grid. A new concept of redundant wind power accommodated by dispatching electric water heaters(EWHs) is developed in the paper. Precise predictions of wind power and EWHs load power are the basis for this work. A hybrid multi-kernel prediction approach integrating an adaptive fruit fly optimization algorithm(AFOA)and multi-kernel relevance vector machine(MKRVM) is proposed to deal with the sample distribution of multisource heterogeneous features uncovered by an energy entropy method, where AFOA is used to determine the kernel parameters in MKRVM adaptively and avoid the arbitrariness. For the large computation of the prediction approach, parallel computation based on the Hadoop cluster is used to accelerate the calculation. Then, an economic dispatching model for accommodating wind power is built taking into account the penalty of curtailed wind power and the operation cost of EWHs. The proposedscheme is implemented in an intelligent residential district.The results show that the optimization performance of the hybrid prediction approach is superior to those of four usual optimization algorithms in this case. Regular or orderly scheduling of EWHs enables accommodation of superfluous wind power and reduces dispatch cost. | Yang YU Zengqiang MI Xiaoming ZHENG Da CHANG | 2019 | Journal of Modern Power Systems and Clean Energy2019，7，3： | 6 |
| 16 | Quantitative method for evaluating detailed volatility of wind power at multiple temporal-spatial scales显示文摘With the increasing proportion of wind power integration, the volatility of wind power brings huge challenges to the safe and stable operation of the electric power system. At present, the indexes commonly used to evaluate the volatility of wind power only consider its overall characteristics, such as the standard deviation of wind power, the average of power variables, etc., while ignoring the detailed volatility of wind power, that is, the features of the frequency distribution of power variables. However, how to accurately describe the detailed volatility of wind power is the key foundation to reduce its adverse influences. To address this, a quantitative method for evaluating the detailed volatility of wind power at multiple temporal-spatial scales is proposed. First, the volatility indexes which can evaluate the detailed fluctuation characteristics of wind power are presented, including the upper confidence limit, lower confidence limit and confidence interval of power variables under the certain confidence level. Then, the actual wind power data from a location in northern China is used to illustrate the application of the proposed indexes at multiple temporal(year–season–month–day) and spatial scales(wind turbine–wind turbines–wind farm–wind farms) using the calculation time windows of 10 min, 30 min, 1 h, and 4 h. Finally, the relationships between wind power forecasting accuracy and its corresponding detailed volatility are analyzed to further verify the effectiveness of the proposed indexes. The results show that the proposed volatility indexes can effectively characterize the detailed fluctuations of wind power at multiple temporal-spatial scales. It is anticipated that the results of this study will serve as an important reference for the reserve capacity planning and optimization dispatch in the electric power system which with a high proportion of renewable energy. | Yongqian Liu Han Wang Shuang Han Jie Yan Li Li Zixin Chen | 2019 | Global Energy Interconnection2019，2，4： | 5 |
| 17 | Gain-scheduling control of a floating offshore wind turbine above rated wind speed显示文摘This paper presents an application of gain-scheduling(GS) control techniques to a floating offshore wind turbine on a barge platform for above rated wind speed cases. Special emphasis is placed on the dynamics variation of the wind turbine system caused by plant nonlinearity with respect to wind speed. The turbine system with the dynamics variation is represented by a linear parameter-varying(LPV) model, which is derived by interpolating linearized models at various operating wind speeds. To achieve control objectives of regulating power capture and minimizing platform motions, both linear quadratic regulator(LQR) GS and LPV GS controller design techniques are explored. The designed controllers are evaluated in simulations with the NREL 5 MW wind turbine model, and compared with the baseline proportional-integral(PI) GS controller and non-GS controllers. The simulation results demonstrate the performance superiority of LQR GS and LPV GS controllers, as well as the performance trade-off between power regulation and platform movement reduction. | Omid BAGHERIEH Ryozo NAGAMUNE | 2015 | Control Theory and Technology2015，13，2： | 5 |
| 18 | Onshore-offshore wind energy resource evaluation based on synergetic use of multiple satellite data and meteorological stations in Jiangsu Province,China显示文摘The demand for efficient and cost-effective renewable energy is increasing as traditional sources of energy such as oil,coal,and natural gas,can no longer satisfy growing global energy demands.Among renewable energies,wind energy is the most prominent due to its low, manageable impacts on the local environment.Based on meteorological data from 2006 to 2014 and multi-source satellite data (i.e.,Advanced Scatterometer,Quick Scatterometer,and Windsat)from 1999 to 2015,an assessment of the onshore and offshore wind energy potential in Jiangsu Province was performed by calculating the average wind speed,average wind direction,wind power density, and annual energy production (AEP).Results show that Jiangsu has abundant wind energy resources,which increase from inland to coastal areas.In-onshore areas, wind power density is predominantly less than 200 W/m^2, while in offshore areas,wind power density is concentrates in the range of 328-500 W/m^2.Onshore areas comprise more than 13,573.24 km^2,mainly located in eastern coastal regions with good wind farm potential The total wind power capacity in onshore areas could be as much as 2.06×10^5 GWh.Meanwhile,offshore wind power generation in Jiangsu Province is calculated to reach 2×10^6 GWh, which is approximately four times the electricity demand of the entire Jiangsu Province.This study validates the effective application of Advanced Scatterometer,Quick Scatterometer,and Windsat data to coastal wind energy monitoring in Jiangsu.Moreover,the methodology used in this study can be effectively applied to other similar coastal zones. | Xianglin WEI Yuewei DUAN Yongxue LIU Song JIN Chao SUN | 2019 | Frontiers of Earth Science2019，13，1： | 4 |
| 19 | Maximum Power Point Tracking in Variable Speed Wind Turbine Based on Permanent Magnet Synchronous Generator Using Maximum Torque Sliding Mode Control Strategy显示文摘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). | Esmaeil Ghaderi Hossein Tohidi Behnam Khosrozadeh | 2017 | Journal of Electronic Science and Technology2017，15，4： | 3 |
| 20 | Mode for reducing wind curtailment based on battery transportation显示文摘Renewable energy sources, such as wind and solar, face several obstacles, including curtailment, where the generated energy exceeds local demand and production must be reduced because of limited transmission capacity.Simultaneously, consumer demand for large-capacity batteries is expanding given the recent rapid development of electric vehicles(EVs) and plug-in hybrid EVs. A batterycharging mode, in which discharged batteries are transported from battery exchange stations in high-load areas to wind farms, is proposed to alleviate curtailment. In this study, batteries store otherwise curtailed energy and smooth the wind power output simultaneously. The structure of the battery-charging device is discussed, and the concept of a battery-charging container is proposed. The control principle of the battery-charging management unit is presented with a simulation model constructed in the PSCAD/EMTDC environment. A case study is simulated,and the feasibility of the mode is analyzed considering the levelized cost and energy losses. Simulation results show that this mode is a feasible solution to alleviating wind curtailment and providing fresh impetus for developing EV battery exchanges. | Zhanlong ZHANG Daojun MEI Han JIANG Guohua LIU Hongpeng HE Yue CHEN | 2018 | Journal of Modern Power Systems and Clean Energy2018，6，6： | 2 |
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