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A Novel Defender-Attacker-Defender Model for Resilient Distributed Generator Planning with Network Reco.figuration and Demand Response

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Energy Engineering 2024年第5期121卷 1223-1243页

作者： Wenlu Ji Teng Tu Nan Ma Nanjing power Supply co.pany State Grid Jiangsu Electric Power Co.Ltd.Nanjing210019China

To improve the resilience of a distribution system against extreme weather,a fuel-based distributed generator(DG)allocation model is proposed in this study.In this model,the DGs are placed at the planning stage.When an extreme event occurs,the co.trollable generators form temporary microgrids(MGs)to restore the load maximally.Simultaneously,a demand response program(DRP)mitigates the imbalance between the power supply and demand during extreme events.To co.e with the fault uncertainty,a robust optimization(RO)method is applied to reduce the long-term investment and short-term operation co.ts.The optimization is formulated as a tri-level defenderattacker-defender(DAD)framework.At the first level,decision-makers work out the DG allocation scheme;at the seco.d level,the attacker finds the optimal attack strategy with maximum damage;and at the third level,restoration measures,namely distribution network reco.figuration(DNR)and demand response are performed.The problem is solved by the nested co.umn and co.straint generation(NC&CG)method and the model is validated using an IEEE 33-node system.Case studies validate the effectiveness and superiority of the proposed model acco.ding to the enhanced resilience and reduced co.t.

关键词： Distribution system resilience defender-attacker-defender distributed generator demand response microgrids formation

Intelligent power grid Load Transferring Based on Safe Action-co.rection Reinforcement Learning

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Energy Engineering 2024年第6期121卷 1697-1711页

作者： Fuju Zhou Li Li Tengfei Jia Yongchang Yin Aixiang Shi Shengrong Xu Suqian power Supply Branch State Grid Jiangsu Electric Power Co.Ltd.Suqian223800China

When a line failure occurs in a power grid, a load transfer is implemented to reco.figure the network by changingthe states of tie-switches and load demands. co.putation speed is one of the major performance indicators inpower grid load transfer, as a fast load transfer model can greatly reduce the eco.omic loss of post-fault powergrids. In this study, a reinforcement learning method is developed based on a deep deterministic policy gradient.The tedious training process of the reinforcement learning model can be co.ducted offline, so the model showssatisfactory performance in real-time operation, indicating that it is suitable for fast load transfer. co.sideringthat the reinforcement learning model performs poorly in satisfying safety co.straints, a safe action-co.rectionframework is proposed to modify the learning model. In the framework, the action of load shedding is co.rectedacco.ding to sensitivity analysis results under a small discrete increment so as to match the co.straints of line flowlimits. The results of case studies indicate that the proposed method is practical for fast and safe power grid loadtransfer.

关键词： Load transfer reinforcement learning electrical power grid safety co.straints

Distributed Robust Optimal Dispatch of Regional Integrated Energy Systems Based on ADMM Algorithm with Adaptive Step Size

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Journal of Modern power Systems and Clean Energy 2024年第3期12卷 852-862页

作者： Zhoujun Ma Yizhou Zhou Yuping Zheng Li Yang Zhinong Wei the co.lege of Energy and electrical Engineering Hohai University state grid jiangsu electric power co. Ltd. state Key Laboratory of Smart grid Protection and co.trol NARI Group Corporation

This paper proposes a distributed robust optimal dispatch model to enhance information security and interaction among the operators in the regional integrated energy system(RIES). Our model regards the distribution network and each energy hub(EH) as independent operators and employs robust optimization to improve operational security caused by wind and photovoltaic(PV) power output uncertainties, with only deterministic information exchanged across boundaries. This paper also adopts the alternating direction method of multipliers(ADMM) algorithm to facilitate secure information interaction among multiple RIES operators, maximizing the benefit for each subject. Furthermore, the traditional ADMM algorithm with fixed step size is modified to be adaptive, addressing issues of redundant interactions caused by suboptimal initial step size settings. A case study validates the effectiveness of the proposed model, demonstrating the superiority of the ADMM algorithm with adaptive step size and the eco.omic benefits of the distributed robust optimal dispatch model over the distributed stochastic optimal dispatch model.

关键词： Uncertainty co.ts power systems Stochastic processes Renewable energy sources Optimization methods Adaptation models

DG Hosting Capacity Assessment co.sidering 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 acco.modation.This paper presents a novel DG hosting capacity(DGHC)evaluation method for distribution networks co.sidering highdimensional dependence relations among solar radiation,wind speed,and various load types(i.e.,co.mercial,residential,and industrial).First,an advanced dependence modeling method called regular vine(R-vine)is applied to capture the co.plex dependence structure of solar radiation,wind speed,co.mercial loads,industrial loads,and residential loads.Then,a chanceco.strained 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 deco.position algorithm is also employed to reduce co.putational 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 deco.position co.relation DG hosting capacity regular vine

Detection of Nonlinear Behavior Induced by Hard Limiting in Voltage Source co.verters 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 reco.ded co.stant-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 beco.e a powerful tool for the detection of nonlinear behavior(DNB) in production quality co.trol wherein it has mainly been applied to mechanical co.dition monitoring and fault diagnosis. This study focuses on the hard limiters of the voltage source co.verter(VSC) co.trol 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 co.ventional 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-co.erence spectra to eliminate the effects of the linear parts on the harmonic characteristics of hard limiting in the VSC co.trol 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 co.pling in the signals is illustrated, and the performance of the proposed method is evaluated and discussed.

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

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Investigating Periodic Dependencies to Improve Short-Term Load Forecasting

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Energy Engineering 2024年第3期121卷 789-806页

作者： Jialin Yu Xiaodi Zhang Qi Zhong Jian Feng state grid Zhejiang Jiaxing electric power co. Ltd.Jiaxing314000China state grid Zhejiang electric power co. Ltd.Hangzhou310000China

With a further increase in energy flexibility for customers,short-term load forecasting is essential to provide benchmarks for eco.omic dispatch and real-time alerts in power grids.The electrical load series exhibit periodic patterns and share high associations with metrological data.However,current studies have merely focused on point-wise models and failed to sufficiently investigate the periodic patterns of load series,which hinders the further improvement of short-term load forecasting accuracy.Therefore,this paper improved Autoformer to extract the periodic patterns of load series and learn a representative feature from deep deco.position and reco.struction.In addition,a novel multi-factor attention mechanism was proposed to handle multi-source metrological and numerical weather prediction data and thus co.rect the forecasted electrical load.The paper also co.pared the proposed model with various co.petitive models.As the experimental results reveal,the proposed model outperforms the benchmark models and maintains stability on various types of load co.sumers.

关键词： Load forecasting transformer attention mechanism power grid

Flexible Load Participation in Peaking Shaving and Valley Filling Based on Dynamic Price Incentives

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Energy Engineering 2024年第2期121卷 523-540页

作者： Lifeng Wang Jing Yu Wenlu Ji Nanjing power Supply co.pany Nanjing210019China state grid jiangsu electric power co. Ltd.Nanjing211103China

co.sidering the widening of the peak-valley difference in the power grid and the difficulty of the existing fixed time-of-use electricity price mechanism in meeting the energy demand of heterogeneous users at various moments or motivating users,the design of a reasonable dynamic pricing mechanism to actively engage users in demand response beco.es imperative for power grid co.panies.For this purpose,a power grid-flexible load bilevel model is co.structed based on dynamic pricing,where the leader is the dispatching center and the lower-level flexible load acts as the follower.Initially,an upper-level day-ahead dispatching model for the power grid is established,co.sidering the lowest power grid dispatching co.t as the objective function and inco.porating the power grid-side co.straints.Then,the lower level co.prehensively co.siders the load characteristics of industrial load,energy storage,and data centers,and then establishes a lower-level flexible load operation model with the lowest user power-co.suming co.t as the objective function.Finally,the proposed method is validated using the IEEE-118 system,and the findings indicate that the dynamic pricing mechanism for peaking shaving and valley filling can effectively guide users to respond actively,thereby reducing the peak-valley difference and decreasing users’purchasing co.ts.

关键词： Demand response fixed time-of-use electricity price mechanism dynamic price incentives mechanism bi-level model flexible load

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 co.lege of electrical Engineering Sichuan University state grid Chongqing electric power co.pany state grid Sichuan electric power co.pany state grid Hubei electric power co.pany Limited Research Institute

Non-intrusive load monitoring is a technique for monitoring the operating co.ditions of electrical appliances by co.lecting the aggregated electrical information at the household power inlet. Despite several studies on the mining of unique load characteristics, few studies have extensively co.sidered the high co.putational 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 co.bined Kmeans clustering algorithm and graph signals are used to build co.cise 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 co.puting co.t and addresses the inaccurate reco.struction of the graph signal. With low-frequency sampling data, the algorithm only requires a little prior data and no training, thereby reducing the co.puting co.t. Experiments co.ducted using the reference energy disaggregation dataset and almanac of minutely power dataset demonstrated the stable superiority of the algorithm and its low co.putational burden.

关键词： Load monitoring co.ts Home appliances Hidden Markov models Training Kernel Clustering algorithms

Torque Limit-based Inertial co.trol Method Based on Delayed Support for Primary Frequency co.trol of Wind Turbines

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Journal of Modern power Systems and Clean Energy 2024年第2期12卷 561-570页

作者： Wei Gu Zaiyu Chen Qun Li Minghui Yin Qiang Li Yun Zou School of Automation Nanjing University of Science and TechnologyNanjing 210094China state grid jiangsu electric power co. Ltd.Research InstituteNanjing 211103China

To avoid the seco.dary frequency dip caused by the steep drop of the electrical power of wind turbines(WTs)at the end of frequency support stage,the torque limit-based iner-tial co.trol(TLIC)method sets the power reference as a linear function of rotor speed,rather than the step form for the step-wise inertial co.trol.However,the co.pensation effect on the frequency nadir(FN)caused by the load surge is weakened as the TLIC power is no longer in the step form.Specifically,the maximum point of the frequency response co.ponent(FRC)co.tributed by TLIC occurs earlier than the minimum point of FRC co.responding to the load surge,so that the FN cannot be adequately raised.Therefore,this paper first investigates the relation between the peak and nadir times of FRCs stimulated by the TLIC and load power.On this basis,with the co.pensation principle of matching the peak and nadir times of FRCs,the improved TLIC method based on delayed support is proposed.Finally,the effectiveness of the proposed method is validated via the experiments on the test bench of wind-integrated power system.

关键词： Wind turbine frequency response co.ponent torque limit inertial co.trol delayed support

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