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CSEE Journal of power and Energy Systems 2022年第3期8卷 710-720页

作者： Lin Yu Huadong Sun Shiyun Xu Bing Zhao Jian Zhang state Key Laboratory of power grid Safety and Energy Conservation China Electric Power Research InstituteBeijing100192China

The power system is experiencing a higher penetration of renewable energy generations(REGs).The short circuit ratio(SCR)and the grid impedance ratio(GIR)are two indices to quantify the system strength of the power system with REGs.In this paper,the critical short circuit ratio(CSCR)is defined as the corresponding SCR when the system voltage is in the critical stable state.Through static voltage stability analysis,the mathematical expression of the CSCR considering the impact of GIR is derived.The maximum value of CSCR is adopted as the critical value to distinguish the weak power system.Based on the static equivalent circuit analysis,it is proved that the CSCR is still effective to evaluate critical system strength considering the interactive impact among REGs.Finally,we find that the GIR can be neglected and the SCR can be used individually to evaluate the system strength when SCR>2 or GIR>5.The correctness and rationality of the CSCR and its critical value are validated on ADPSS.

关键词： Critical short circuit ratio critical value grid impedance ratio maximum power transfer theorem static equivalent circuit analysis

Non-intrusive Load Monitoring Based on Graph Total Variation for Residential Appliances

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Journal of Modern power Systems and Clean Energy 2024年第3期12卷 947-957页

作者： Xiaoyang Ma Diwen Zheng Xiaoyong Deng Ying Wang Dawei Deng Wei Li the College of electrical Engineering Sichuan University state grid Chongqing electric power Company state grid Sichuan electric power Company state grid Hubei electric power Company Limited research institute

Non-intrusive load monitoring is a technique for monitoring the operating conditions of electrical appliances by collecting the aggregated electrical information at the household power inlet. Despite several studies on the mining of unique load characteristics, few studies have extensively considered the high computational burden and sample training. Based on lowfrequency sampling data, a non-intrusive load monitoring algorithm utilizing the graph total variation(GTV) is proposed in this study. The algorithm can effectively depict the load state without the need for prior training. First, the combined Kmeans clustering algorithm and graph signals are used to build concise and accurate graph structures as load models. The GTV representing the internal structure of the graph signal is introduced as the optimization model and solved using the augmented Lagrangian iterative algorithm. The introduction of the difference operator reduces the computing cost and addresses the inaccurate reconstruction of the graph signal. With low-frequency sampling data, the algorithm only requires a little prior data and no training, thereby reducing the computing cost. Experiments conducted using the reference energy disaggregation dataset and almanac of minutely power dataset demonstrated the stable superiority of the algorithm and its low computational burden.

关键词： Load monitoring Costs Home appliances Hidden Markov models Training Kernel Clustering algorithms

Optimized Auxiliary Frequency Control of Wind Farm Based on Piecewise Reduced-order Frequency Response Model

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Journal of Modern power Systems and Clean Energy 2024年第3期12卷 791-802页

作者： Xu Zhang Chen Zhao Junchao Ma Long Zhang Dan Sun Chenxu Wang Yan Peng Heng Nian the School of electrical Engineering Zhejiang University electric power research institute of state grid Zhejiang electric power Corporation

With the increasing wind power penetration in the power system, the auxiliary frequency control(AFC) of wind farm(WF) has been widely used. The traditional system frequency response(SFR) model is not suitable for the wind power generation system due to its poor accuracy and applicability. In this paper, a piecewise reduced-order frequency response(PROFR) model is proposed, and an optimized auxiliary frequency control(O-AFC) scheme of WF based on the P-ROFR model is proposed. Firstly, a full-order frequency response model considering the change in operating point of wind turbine is established to improve the applicability. In order to simplify the fullorder model, a P-ROFR model with second-order structure and high accuracy at each frequency response stage is proposed. Based on the proposed P-ROFR model, the relationship between the frequency response indexes and the auxiliary frequency controller coefficients is expressed explicitly. Then, an OAFC scheme with the derived explicit expression as the optimization objective is proposed in order to improve the frequency support capability on the premise of ensuring the full release of the rotor kinetic energy and the full use of the effect of time delay on frequency regulation. Finally, the effectiveness of the proposed P-ROFR model and the performance of the proposed OAFC scheme are verified by simulation studies.

关键词： Frequency control Frequency response Rotors Analytical models Indexes Optimization Delay effects

DG Hosting Capacity Assessment Considering Dependence Among Wind Speed,Solar Radiation,and Load Demands

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CSEE Journal of power and Energy Systems 2024年第3期10卷 1011-1025页

作者： Junyi Yang Jiangmin Bao Yuhan Hou Han Wu Qiang Li Yue Yuan Hohai University Nanjing 211100China state grid jiangsu electric power Co. Ltd.Suzhou Power Supply BranchSuzhou 215004China Nanjing institute of Technology Nanjing 211167China electric power research institute of state grid jiangsu electric power Co.Ltd. Nanjing 211103China IEEE CSEE

Dependence of distributed generation(DG)outputs and load plays an essential role in renewable energy accommodation.This paper presents a novel DG hosting capacity(DGHC)evaluation method for distribution networks considering highdimensional dependence relations among solar radiation,wind speed,and various load types(i.e.,commercial,residential,and industrial).First,an advanced dependence modeling method called regular vine(R-vine)is applied to capture the complex dependence structure of solar radiation,wind speed,commercial loads,industrial loads,and residential loads.Then,a chanceconstrained DGHC evaluation model is employed to figure out maximum hosting capacity of each DG and its optimal allocation plan with different operational risks.Finally,a Benders decomposition algorithm is also employed to reduce computational burden.The proposed approaches are validated using a set of historical data from China.Results show dependence among different DGs and loads has significant impact on hosting capacity.Results also suggest using the R-vine model to capture dependence among distributed energy resources(DERs)and load.This finding provides useful advice for distribution networks in installing renewable energy generations.

关键词： Benders decomposition correlation DG hosting capacity regular vine

Traveling Wave Characteristics Based Pilot Protection Scheme for Hybrid Cascaded HVDC Transmission Line

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Journal of Modern power Systems and Clean Energy 2024年第3期12卷 971-980页

作者： Dalin Mu Sheng Lin Xiaopeng Li the School of electrical Engineering Southwest Jiaotong University the state grid Sichuan electric power research institute

The hybrid cascaded high-voltage direct current(HVDC) transmission system has various operation modes, and some operation modes have sharply increasing requirements for protection rapidity, while the traditional pilot differential protection(PDP) has poor rapidity, and even refuses to operate when faults occur on the DC line. Therefore, a novel pilot protection scheme based on traveling wave characteristics is proposed. First, the adaptability of the traditional PDP applied in engineering is analyzed for different operation modes. Then, the expressions of the forward traveling wave(FTW) and backward traveling wave(BTW) on the rectifier side and the inverter side are derived for different fault locations. From the theoretical derivation, the difference between the BTW and FTW on the rectifier side is less than zero, and the same is true on the inverter side. However, in the event of an external fault of DC line, the difference between the BTW and FTW at nearfault terminal protection installation point is greater than zero. Therefore, by summing over the product of the difference between BTW and FTW of the rectifier side and that of the inverter side, the fault identification criterion is constructed. The simulation results show that the proposed pilot protection scheme can quickly and reliably identify the short-circuit faults of DC line in different operation modes.

关键词： HVDC transmission Inverters Rectifiers Delays Partial discharges Fault diagnosis Valves

Multi-Time Scale Operation and Simulation Strategy of the Park Based on Model Predictive Control

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Energy Engineering 2024年第3期121卷 747-767页

作者： Jun Zhao Chaoying Yang Ran Li Jinge Song grid Center State Grid Shanxi Electric Power Company Electric Power Science Research InstituteTaiyuan030000China

Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected economy.This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min.In order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the park.Finally,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples.

关键词： Demand response model predictive control multiple time scales operating simulation

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.

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Analysis and Modeling of Time Output Characteristics for Distributed Photovoltaic and Energy Storage

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Energy Engineering 2024年第4期121卷 933-949页

作者： Kaicheng Liu Chen Liang Xiaoyang Dong Liping Liu China electric power research institute Beijing100192China electric power research institute State Grid Gansu Electric Power CompanyLanzhou730000China state Key Laboratory of power grid Safety Beijing100084China

Due to the unpredictable output characteristics of distributed photovoltaics,their integration into the grid can lead to voltage fluctuations within the regional power grid.Therefore,the development of spatial-temporal coordination and optimization control methods for distributed photovoltaics and energy storage systems is of utmost importance in various scenarios.This paper approaches the issue from the perspective of spatiotemporal forecasting of distributed photovoltaic(PV)generation and proposes a Temporal Convolutional-Long Short-Term Memory prediction model that combines Temporal Convolutional Networks(TCN)and Long Short-Term Memory(LSTM).To begin with,an analysis of the spatiotemporal distribution patterns of PV generation is conducted,and outlier data is handled using the 3σ rule.Subsequently,a novel approach that combines temporal convolution and LSTM networks is introduced,with TCN extracting spatial features and LSTM capturing temporal features.Finally,a real spatiotemporal dataset from Gansu,China,is established to compare the performance of the proposed network against other models.The results demonstrate that the model presented in this paper exhibits the highest predictive accuracy,with a single-step Mean Absolute Error(MAE)of 1.782 and an average Root Mean Square Error(RMSE)of 3.72 for multi-step predictions.

关键词： Photovoltaic power generation spatio-temporal prediction temporal convolutional network long short-term memory network

Multi-area Frequency-constrained Unit Commitment for power Systems with High Penetration of Renewable Energy Sources and Induction Machine Load

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Journal of Modern power Systems and Clean Energy 2024年第3期12卷 754-766页

作者： Leibao Wang Hui Fan Jifeng Liang Longxun Xu Tiecheng Li Peng Luo Bo Hu Kaigui Xie the state grid Hebei electric power research institute state Key Laboratory of power Transmission Equipment & System Security and New Technology Chongqing University

The increasing penetration of renewable energy sources(RESs) brings great challenges to the frequency security of power systems. The traditional frequency-constrained unit commitment(FCUC) analyzes frequency by simplifying the average system frequency and ignoring numerous induction machines(IMs) in load, which may underestimate the risk and increase the operational cost. In this paper, we consider a multiarea frequency response(MAFR) model to capture the frequency dynamics in the unit scheduling problem, in which regional frequency security and the inertia of IM load are modeled with high-dimension differential algebraic equations. A multi-area FCUC(MFCUC) is formulated as mixed-integer nonlinear programming(MINLP) on the basis of the MAFR model. Then, we develop a multi-direction decomposition algorithm to solve the MFCUC efficiently. The original MINLP is decomposed into a master problem and subproblems. The subproblems check the nonlinear frequency dynamics and generate linear optimization cuts for the master problem to improve the frequency security in its optimal solution. Case studies on the modified IEEE 39-bus system and IEEE 118-bus system show a great reduction in operational costs. Moreover, simulation results verify the ability of the proposed MAFR model to reflect regional frequency security and the available inertia of IMs in unit scheduling.

关键词： Security Frequency response Load modeling Indexes Costs Sensitivity power system dynamics

Bi-level Multi-leader Multi-follower Stackelberg Game Model for Multi-energy Retail Package Optimization

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Journal of Modern power Systems and Clean Energy 2024年第1期12卷 225-237页

作者： Hongjun Gao Hongjin Pan Rui An Hao Xiao Yanhong Yang Shuaijia He Junyong Liu the College of electrical Engineering Sichuan UniversityChengdu 610065China the electric power research institute State Grid Jiangsu Electric Power CompanyNanjing 211100China the institute of electrical Engineering Chinese Academy of SciencesBeijing 100190China

In the competitive energy market,energy retailers are facing the uncertainties of both energy price and demand,which requires them to formulate reasonable energy purchasing and selling strategies for improving their competitiveness in this market.Particularly,the attractive multi-energy retail packages are the key for retailers to increase their benefit.Therefore,combined with incentive means and price signals,five types of multi-energy retail packages such as peak-valley time-of-use(TOU)price package and day-night bundled price package are designed in this paper for retailers.The iterative interactions between retailers and end-users are modeled using a bi-level model of stochastic optimization based on multi-leader multi-follower(MLMF)Stackelberg game,in which retailers are leaders and end-users are followers.Retailers make decisions to maximize the profit considering the conditional value at risk(CVaR)while end-users optimize the satisfaction of both energy comfort and economy.Besides,a distributed algorithm is proposed to obtain the Nash equilibrium of above MLMF Stackelberg game model while the particle swarm optimization(PSO)algorithm and CPLEX solver are applied to solve the optimization model for each participant(retailer or end-user).Numeral results show that the designed retail packages can increase the overall profit of retailers,and the overall satisfaction of industrial users is the highest while that of residential users is the lowest after game interaction.

关键词： Conditional value at risk(CVaR) energy retailer multi-energy retail package design multi-leader multi-follower(MLMF)Stackelberg game satisfaction

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