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A comprehensive review on the development of data-driven methods for wind power prediction and AGC performance evaluation in wind–thermal bundled power systems

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Energy and AI 2024年第2期16卷 450-463页

作者： Shuai Wang Bin Li Guanzheng Li Botong Li Hongbo Li Kui Jiao Chengshan Wang National Industry-Education Platform for Energy Storage Tianjin UniversityTianjin300350China Key Laboratory of Smart grid of Ministry of Education Tianjin UniversityTianjin300072China power Dispatching and control Center Inner Mongolia Power(Group)Co.LtdHohhot010020China

The wind–thermal bundled power system achieves energy complementarity and optimized scheduling, which is an important way to build a new type of energy system. For the safe and stable operation of the wind–thermal bundled power system, accurate data-driven analysis is necessary to maintain real-time balance between electricity supply and demand. By summarizing the development and characteristics of wind–thermal bundled power system in China and different countries, current research in this field can be clearly defined in two aspects: short-term wind power prediction for wind farms and performance evaluation of automatic generation control (AGC) for thermal power generation units. For short-term wind power prediction, it is recommended to focus on historical data preprocessing and artificial intelligence methods. The technical characteristics of different data-driven wind power prediction methods have been compared in detail. For performance evaluation of AGC units, a comprehensive analysis was conducted on current evaluation methods, including the “permitted-band” and “regulation mileage” methods, as well as the issue of evaluation failure in traditional evaluation methods in practical engineering. Finally, the relative optimal dynamic performance of AGC units was discussed and the future trend of data-driven research in wind–thermal bundled power system was summarized.

关键词： Wind power prediction Automatic generation control Performance evaluation Data-driven Feature analysis

A Scenario-classification Hybrid-based Banding Method for power Transfer Limits of Critical Inter-corridors

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Journal of Modern power Systems and Clean Energy 2024年第2期12卷 547-560页

作者： Lidong Yi Maosheng Ding Jili Wang Gao Qiu Fei Xue Ji'ang Liu Yuxiong Huang Gengfeng Li Junyong Liu state grid Ningxia Electric power co. Ltd.YinchuanChinaand M.Ding is also with State Grid Ningxia Electric Power Research InstituteYinchuanChina Northwest Branch State Grid Corporation of ChinaXi’anChina School of Electrical Engineering Sichuan UniversityChengduChina state grid Ningxia Electric power Research Institute Yinchuan YinchuanChina School of Electrical Engineering Xi’an Jiaotong UniversityXi’anChina IEEE

To secure power system operations,practical dispatches in industries place a steady power transfer limit on critical inter-corridors,rather than high-dimensional and strong nonlinear stability ***,computational complexities lead to over-conservative pre-settings of transfer limit,which further induce undesirable and non-technical congestion of power *** conquer this barrier,a scenario-classification hybrid-based banding method is proposed.A cluster technique is adopted to separate similarities from historical and generated operating condition *** a practical rule,transfer limits are approximated for each operating ***,toward an interpretable online transfer limit decision,costsensitive learning is applied to identify cluster affiliation to assign a transfer limit for a given *** this stage,critical variables that affect the transfer limit are also picked out via mean impact *** enables us to construct low-complexity and dispatcher-friendly rules for fast determination of transfer *** numerical case studies on the IEEE 39-bus system and a real-world regional power system in China illustrate the effectiveness and conservativeness of the proposed method.

关键词： Transfer limit transfer capability power transfer inter-corridor cluster cost-sensitive learning banding power system operation

Detection of Nonlinear Behavior Induced by Hard Limiting in Voltage Source converters in Wind Farms Based on Higher-order Spectral Analysis

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Journal of Modern power Systems and Clean Energy 2024年第2期12卷 630-645页

作者： Zetian Zheng Shaowei Huang Qiangsheng Bu Chen Shen Jun Yan state Key Laboratory of power Systems Department of Electrical EngineeringTsinghua UniversityBeijing 100084China state grid Jiangsu Electric power co. Ltd.Research InstituteNanjingChina

In recent years, sub-synchronous oscillation accidents caused by wind power integration have received extensive attention. The recorded constant-amplitude waveforms can be induced by either linear or nonlinear oscillation mechanisms. Hence, the nonlinear behavior needs to be distinguished prior to choosing the analysis method. Since the 1960s, the higher-order statistics(HOS) theory has become a powerful tool for the detection of nonlinear behavior(DNB) in production quality control wherein it has mainly been applied to mechanical condition monitoring and fault diagnosis. This study focuses on the hard limiters of the voltage source converter(VSC) control systems in the wind farms and attempts to detect the nonlinear behavior caused by bi-or uni-lateral saturation hard limiting using the HOS analysis. First, the conventional describing function is extended to obtain the detailed frequency domain information on the bi-and uni-lateral saturation hard limiting. Furthermore, the bi-and tri-spectra are introduced as the HOS, which are extended into bi-and tri-coherence spectra to eliminate the effects of the linear parts on the harmonic characteristics of hard limiting in the VSC control system, respectively. The effectiveness of the HOS in the DNB and the classification of the hard-limiting types is proven, and its detailed derivation and estimation procedure is presented. Finally, the quadratic and cubic phase coupling in the signals is illustrated, and the performance of the proposed method is evaluated and discussed.

关键词： Bi-coherence spectrum detection of nonlinear behavior hard limiting higher-order statistics tri-coherence spectrum voltage source converter wind farms.

Optimal scheduling of flexible grid-side resources and auxiliary service cost allocation model considering renewable-energy penetration

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Clean Energy 2024年第4期8卷 90-102页

作者： Bin Bai Yanli Xiao Rui Zhao Xin Ju Shangke Liu state grid Ningxia Electric power co. Ltd.Economic Technology Research InstituteYinchuan 750011China

Renewable energy has penetrated power grid enterprises on a large *** to the intermittency and volatility of renewable energy generation,it is necessary to build new flexible grid-side resources to ensure the safe and stable operation of the power grid,which will cause great pressure on cost allocation for power grid *** article considers four types of flexible grid-side resources and constructs a dual-level configuration optimization model for flexible grid-side resources under the penetration of renewable en*** on the configuration results,the cost scale of flexible grid-side resources is estimated and an improved ancillary service cost allocation model based on the Shapley value method is proposed to smooth the allocation of ancillary service costs in the cost of flexible grid-side resources between the two main bodies of renewable energy and *** calculation results show that,when the penetration rate of renewable-energy power is 30%and 35%,respectively,the cost of flexible grid-side resources is 9.606 billion yuan and 21.518 billion yuan,*** proportion of ancillary service costs allocated to load is relatively high-about five times that of the ancillary service costs allocated to renewable energy-and the higher the penetration rate of renewable energy,the higher the proportion of ancillary service costs allocated to renewable energy.

关键词： renewable-energy penetration flexible grid-side resources ancillary service costs Shapley allocation model

Anomaly Detection Algorithm of power System Based on Graph Structure and Anomaly Attention

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computers, Materials & continua 2024年第4期79卷 493-507页

作者： Yifan Gao Jieming Zhang Zhanchen Chen Xianchao Chen Zhaoqing power Supply Bureau of Guangdong power grid co. Ltd.Zhaoqing526060China

In this paper, we propose a novel anomaly detection method for data centers based on a combination of graphstructure and abnormal attention mechanism. The method leverages the sensor monitoring data from targetpower substations to construct multidimensional time series. These time series are subsequently transformed intograph structures, and corresponding adjacency matrices are obtained. By incorporating the adjacency matricesand additional weights associated with the graph structure, an aggregation matrix is derived. The aggregationmatrix is then fed into a pre-trained graph convolutional neural network (GCN) to extract graph structure ***, both themultidimensional time series segments and the graph structure features are inputted into a pretrainedanomaly detectionmodel, resulting in corresponding anomaly detection results that help identify abnormaldata. The anomaly detection model consists of a multi-level encoder-decoder module, wherein each level includesa transformer encoder and decoder based on correlation differences. The attention module in the encoding layeradopts an abnormal attention module with a dual-branch structure. Experimental results demonstrate that ourproposed method significantly improves the accuracy and stability of anomaly detection.

关键词： Anomaly detection transformer graph structure

Locating Sources of Oscillations Induced by control of Voltage Source converters Based on Energy Structure and Nonlinearity Detection

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Journal of Modern power Systems and Clean Energy 2024年第4期12卷 1285-1294页

作者： Zetian Zheng Shaowei Huang Jun Yan Qiangsheng Bu Chen Shen Mingzhong Zheng Ye Liu state Key Laboratory of power Systems Department of Electrical EngineeringTsinghua UniversityBeijing 100084China state grid Jiangsu Electric power co. Ltd.Research InstituteNanjing 211103China

The oscillation phenomena associated with the con-trol of voltage source converters(VSCs)are concerning,mak-ing it crucial to locate the sources of such oscillations and sup-press the ***,this paper presents a location scheme based on the energy structure and nonlinearity *** energy structure,which conforms to the principle of the energy-based method and dissipativity theory,is developed to describe the transient energy flow for VSCs,based on which a defined characteristic quantity is implemented to narrow the scope for locating the sources of ***,based on the self-sustained oscillation characteristics of VsCs,an in-dex for nonlinearity detection is applied to locate the VSCs that produce the oscillation *** combination of the energy structure and nonlinearity detection distinguishes the contribu-tions of different VSCs to the *** results of a case study implemented by the PSCAD/EMTDC simulation validate theproposed scheme.

关键词： Double-loop proportional-integral(PI)control energy structure Hamiltonian model nonlinearity detection oscillation source location(OSL) voltage source converter(VSC)

SO_(2)and SOF_(2)simultaneous detection by single mid-infrared laser based on tunable diode laser absorption spectroscopy

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High Voltage 2024年第4期9卷 786-793页

作者： Yin Zhang Yan Li Jin Yan Chao Bian Xuan Chen Xiaoxing Zhang Hubei Engineering Research Center for Safety Monitoring of New Energy and power grid Equipment Hubei University of TechnologyWuhanChina state grid Jiangsu Electric power co. Ltd.Ultra High Voltage BranchNanjingChina

In the detection of multi-component gas based on tunable diode laser absorption spectroscopy(TDLAS),the problem of overlapping interference between the absorption lines of each gas is often *** example,when detecting a gas mixture of sulphur dioxide(SO_(2))and thionyl fluoride(SOF_(2)),the characteristic decomposition components of SF6,there is overlapping interference in the absorption lines of the two gases,which makes it difficult to detect the concentration of gases *** view of this problem,a novel method based on support vector regression model used for TDLAS is proposed to detect two gases *** detection results show that the correlation coefficients between the concentration of SO_(2)and SOF_(2)and the average value of the second harmonic peak reached 0.992 and *** addition,through model testing,different concentrations of SO_(2)and SOF_(2)gas mixture are simultaneously detected,and the resulting maximum errors for measuring SO_(2)and SOF_(2)concentrations are less than 7.13×10^(-5)and 0.26×10^(-2).The maximum errors of the measurement results in the verification test are not more than 6.4×10^(-3)and 4.6×10^(-2).Therefore,with assistance of the novel method,the detection of multiple gases by using a single laser is achieved.

关键词： tunable diode absorption

Cloud-Edge collaborative Federated GAN Based Data Processing for IoT-Empowered Multi-Flow Integrated Energy Aggregation Dispatch

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computers, Materials & continua 2024年第7期80卷 973-994页

作者： Zhan Shi Electric power Dispatching control Center Guangdong Power Grid Co.Ltd.Guangzhou510030China

The convergence of Internet of Things(IoT),5G,and cloud collaboration offers tailored solutions to the rigorous demands of multi-flow integrated energy aggregation dispatch data *** generative adversarial networks(GANs)are instrumental in resource scheduling,their application in this domain is impeded by challenges such as convergence speed,inferior optimality searching capability,and the inability to learn from failed decision making ***,a cloud-edge collaborative federated GAN-based communication and computing resource scheduling algorithm with long-term constraint violation sensitiveness is proposed to address these *** proposed algorithm facilitates real-time,energy-efficient data processing by optimizing transmission power control,data migration,and computing resource *** employs federated learning for global parameter aggregation to enhance GAN parameter updating and dynamically adjusts GAN learning rates and global aggregation weights based on energy consumption constraint *** results indicate that the proposed algorithm effectively reduces data processing latency,energy consumption,and convergence time.

关键词： IoT federated learning generative adversarial network data processing multi-flowintegration energy aggregation dispatch

RL and AHP-Based Multi-Timescale Multi-Clock Source Time Synchronization for Distribution power Internet of Things

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computers, Materials & continua 2024年第3期78卷 4453-4469页

作者： Jiangang Lu Ruifeng Zhao Zhiwen Yu Yue Dai Kaiwen Zeng Electric power Dispatching and control Center Guangdong Power Grid Co.Ltd.Guangzhou510600China

Time synchronization(TS)is crucial for ensuring the secure and reliable functioning of the distribution power Internet of Things(IoT).Multi-clock source time synchronization(MTS)has significant advantages of high reliability and accuracy but still faces challenges such as optimization of the multi-clock source selection and the clock source weight calculation at different timescales,and the coupling of synchronization latency jitter and pulse phase *** this paper,the multi-timescale MTS model is conducted,and the reinforcement learning(RL)and analytic hierarchy process(AHP)-based multi-timescale MTS algorithm is designed to improve the weighted summation of synchronization latency jitter standard deviation and average pulse phase ***,the multi-clock source selection is optimized based on Softmax in the large timescale,and the clock source weight calculation is optimized based on lower confidence bound-assisted AHP in the small *** shows that the proposed algorithm can effectively reduce time synchronization delay standard deviation and average pulse phase difference.

关键词： Multi-clock source time synchronization(TS) power Internet of Things reinforcement learning analytic hierarchy process