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Aggregate modeling and analysis of air conditioning load using coupled Fokker–Planck equations

Journal of Modern power systems and Clean Energy 2018年第6期6卷 1277-1290页

作者： Dingyi CHENG Wen ZHANG Yutian LIU Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University

Demand response has gained significant attention recently with the increasing penetration of renewable energy sources in power systems. Air conditioning loads are typical thermostatically controlled loads which can play an active role in ancillary services by regulating their aggregated power consumption. The aggregation of air conditioners is essential to the control of air conditioning loads. In this paper, linear state equations are proposed to aggregate air conditioning loads by solving coupled Fokker–Planck equations(CFPEs) using the finite difference method. By analyzing the numerical stability and convergence of the difference scheme, the grid spacings, including temperature step and time step, are properly determined according to the maximal principle. Stationary solutions of the CFPEs are obtained by analytical and numerical methods. Furthermore, a classification method using dimension reduction is proposed to deal with the problem of heterogeneous parameters and interval estimation is applied to describe the stochastic behavior of air conditioning loads. The simulation results verify the effectiveness of the proposed methods.

关键词： Aggregate model Air conditioner Coupled Fokker–Planck equation Grid spacing selection Heterogeneous Interval estimation Linear state equation Stationary solution

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A Carrier Synchronization Method for Global Synchronous Pulsewidth Modulation Application Using Phase-Locked Loop

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IEEE TRANSACTIONS ON power ELECTRONICS 2019年第11期34卷 10720-10732页

作者： Xu, Tao Gao, Feng Wang, Xiongfei Blaabjerg, Frede Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Shandong Peoples R China Aalborg Univ Dept Energy Technol DK-9100 Aalborg Denmark

When many distributed parallel inverters are integrated into grid without switching sequence coordinated control capability, the high-frequency harmonics will accumulate randomly at the point of common coupling. Global synchronous pulsewidth modulation (GSPWM) method can significantly attenuate the accumulated switching ripples by intentionally assuming an intelligent optimization algorithm and a communication system. To avoid the dependence on low-latency communication system, this paper proposes a novel phase-locked loop based PWM carrier synchronization (PLL-CS) method for GSPWM system, where the switching sequences can he effectively synchronized as expected without using low-latency synchronization signals. By doing so, the operational reliability of the whole GSPWM system can be significantly improved, while the additional hardware cost of GSPWM can be dramatically reduced, which can enhance the implementation adaptability of GSPWM method. Experimental results have verified the performance of the proposed PLL-CS GSPWM method.

关键词： Carrier synchronization (CS) method distributed inverters global synchronous pulsewidth modulation (GSPWM) phase-locked loop (PLL)

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Parameter estimation method of distribution network based on PMU measurement data

Parameter estimation method of distribution network based on...

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power and Electrical Engineering (ACPEE), 5th Asia Conference on

作者： Yanruo Hou Tianyu Fang Fang Shi Hengxu Zhang The Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education Shandong University Jinan P. R. China

ISBN: (数字)9781728152813

ISBN: (纸本)9781728152820

Accurate line parameters are the basis of improving real-time monitoring level and active control capability of smart distribution network. The synchronous data provided by distribution network PMU technology is an important method to distribution network line parameters estimation. This paper proposes a parameter estimation model of distribution network based on PMU measurement data and concentrated parameter characteristics. With the least square method, the estimation model is established by using the phasor data measured by PMU. And the nonlinear equations are solved by Newton iteration method to obtain the resistance, reactance and susceptance parameters of distribution network. Furthermore, the estimation model and method are extended to three-terminal lines for T-connection lines parameter estimation. PSCAD software is used to obtain the dynamic simulation data, which is used to verify the practicability and accuracy of this proposed method.

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PMU-based model-free method for transient instability prediction and emergency generator-shedding control

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INTERNATIONAL JOURNAL OF ELECTRICAL power & ENERGY systemS 2019年 105卷 381-393页

作者： Yang, Hao Zhang, Wen Shi, Fang Xie, Jiping Ju, Wenjie Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Shandong Peoples R China State Grid Shandong Elect Power Co Jinan 250001 Shandong Peoples R China

Using PMU measurements, this paper proposes a model-free method to predict post-fault transient instability and develop emergency generator-shedding control. First, the multi-machine system is converted to an equivalent one-machine-infinite-bus (OMIB) system based on online generator clustering, and then the stability criteria are derived to judge the transient stability using the OMIB rotor speed (OMIB-omega) trajectory. Next, a new trajectory prediction algorithm based on ensemble online sequential learning machine (E-OS-ELM)is proposed to predict the OMIB-omega trajectory with an adaptive prediction window. The post-fault transient instability status can be detected in advance on basis of the predicted omega trajectory and the derived stability criteria. Lastly, when the system is foreseen to lose stability, an analytical generator-shedding control algorithm is presented, and the relationship between the generator-shedding amount and the time delay is illustrated. Case studies on the New England 39-bus system, the NPCC 140-bus system and a realistic province power system in China are presented to show the proposed methodology can detect the instability status early, and help the system maintain synchronism.

关键词： Transient instability prediction PMU measurements Trajectory prediction Stability control Time delay

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Robust Distributed Coordination of Parallel Restored Subsystems in Wind power Penetrated Transmission system

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IEEE TRANSACTIONS ON power systemS 2020年第4期35卷 3213-3223页

作者： Zhao, Jin Wang, Hongtao Hou, Yunhe Wu, Qiuwei Hatziargyriou, Nikos D. Zhang, Wen Liu, Yutian Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250000 Peoples R China Univ Hong Kong Dept Elect & Elect Hong Kong Peoples R China Univ Hong Kong Shenzhen Inst Res & Innovat Shenzhen Peoples R China Tech Univ Denmark Ctr Elect Power & Energy Dept Elect Engn DK-2800 Lyngby Denmark Natl Tech Univ Athens Athens 15773 Greece

Several parallel restored subsystems exist in the last stage of the build-up restoration process of bulk power systems. The whole system restoration is completed when these subsystems are reconnected and their internal loads are recovered. This paper proposes a robust distributed coordination scheme to achieve reconnection and load recovery of parallel restored subsystems in wind power penetrated transmission systems. First, robust distributed restoration models are constructed considering individual subsystems under uncertain conditions. Then, an inner-outer nested upper-lower (IOUL) iterative algorithm is developed to solve the constructed models. The robust distributed coordination can be realized according to convergence. The proposed algorithm solves the complex non-convex model with uncertain variables by iteratively solving the small-scale mixed-integer linear programming (MILP) problem. The robust distributed restoration scheme allows independent decision-making within subsystems and ensures the feasibility of the distributed restoration strategy under uncertain conditions. The effectiveness of the proposed method is validated using three interconnected 6-bus systems and the IEEE 118-bus system, showing improved computational efficiency and restoration acceleration.

关键词： Load modeling Wind power generation Uncertainty Optimization Generators power system restoration Bulk power system distributed optimization power system restoration sectionalized restoration wind power penetration

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A Statistical Upscaling Approach of Region Wind power Forecasting Based on Combination Model

A Statistical Upscaling Approach of Region Wind Power Foreca...

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3rd IEEE Student Conference on Electrical Machines and systems (SCEMS)

作者： Ding, Tingting Li, Peng Huang, Guilin Yu, Yixiao Si, Zhiyuan Yan, Fangqing Liu, Xiaoyi Li, Menglin Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan Peoples R China Imperial Coll London Elect & Elect Engn London England State Grid Shandong Elect Power Co Laiwu Elect Power Supply Co Laiwu Peoples R China State Grid China Technol Coll Jinan Peoples R China

ISBN: (纸本)9781728156224

Regional wind power forecasting is of great significance to ensure the wind power absorption and power grid safety economy. This paper proposes a regional wind power statistical upscaling forecasting method based on the combination model to improve the forecasting accuracy of the region wind power. The K-means clustering algorithm is used to divide the region, the forecasting accuracy of the wind farms, and the correlation coefficient between wind farms and sub-regions are used to select the reference wind farms in each sub-region. The BP neural network quantile regression model is used to forecast the wind power of the reference wind farm. Based on the prediction results of reference wind farms, the combined model formed by the beta distribution estimation, kernel density estimation, and sparse Bayesian learning is used to forecast the wind power of the sub-region. The region power forecasting results can be obtained by adding the forecasting results of the sub-regions. Case studies verify the effectiveness of the method proposed in this paper.

关键词： Combined forecasting model regional wind power forecasting statistical upscaling forecasting probabilistic forecasting

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Mobile Emergency Generator Planning in Resilient Distribution systems: A Three-Stage Stochastic Model With Nonanticipativity Constraints

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IEEE TRANSACTIONS ON SMART GRID 2020年第6期11卷 4847-4859页

作者： Zhang, Gang Zhang, Feng Zhang, Xin Wang, Zhaoyu Meng, Ke Dong, Zhao Yang Shandong Univ Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China Cranfield Univ Sch Water Energy & Environm Energy & Power Theme Cranfield MK43 0AL Beds England Iowa State Univ Dept Elect & Comp Engn Ames IA 50011 USA Univ New South Wales Sch Elect Engn & Telecommun Sydney NSW 2052 Australia

Mobile emergency generators (MEGs) can effectively restore critical loads as flexible backup resources after power network disturbance from extreme events, thereby boosting the distribution system resilience. Therefore, MEGs are required to be optimally allocated and utilized. For this purpose, a novel three-stage stochastic planning model is proposed for MEG allocation of resilient distribution systems in consideration of planning stage (PLS), preventive response stage (PRS) and emergency response stage (ERS). Moreover, the nonanticipativity constraints are proposed to guarantee that the MEG allocation decisions are dependent on the stage-based uncertainties. Specifically, in the PLS, the intensity uncertainty (IU) of disasters and the outage uncertainty (OU) incurred by a given disaster are considered with probability-weighted scenarios for the effective MEG allocation. Then, with the IU that can be observed in the PRS, the MEGs are pre-positioned in the consideration of OU. It is noted that the pre-position decisions should only correspond to the IU realizations, according to nonanticipativity constraints. Last, with the further realization of OU in the ERS, the MEGs are re-routed from the pre-position to the target location, so that the provisional microgrids can be formed to restore critical loads. The proposed planning model can be large-scale due to multiple scenarios. Therefore, the progressive hedging algorithm (PHA) is customized to reduce the computational burden. The simulation results in 13 and 123 node distribution systems show the effectiveness and superiority of the proposed three-stage MEG planning model over the traditional two-stage model.

关键词： Planning Erbium Uncertainty Stochastic processes Generators Load modeling Fault tolerance Mobile generator planning nonanticipativity constraints distribution system three-stage stochastic programming resilience uncertainty

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controlled power system Separation Using Generator PMU Data and system Kinetic Energy

arXiv

引用

arXiv 2022年

作者： Tyuryukanov, Ilya Popov, Marjan Bos, Jorrit A. van der Meijden, Mart A.M.M. Terzija, Vladimir Delft University of Technology Delft2628CD Netherlands Siemens Energy AG Freyeslebenstr. 1 Erlangen91058 Germany TenneT TSO B.V. Utrechtseweg 310 Arnhem6812AR Netherlands Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education School of Electrical Engineering Shandong University Jinan250061 China

With the growing number of severe system disturbances and blackouts around the world, controlled system separation is becoming an increasingly important system integrity protection scheme (SIPS) to save the electric power system from a complete or partial disintegration. A successful controlled splitting approach should at least tackle the following two well-known and interrelated problems:"when to split?" and"where to split?". Multiple previous publications consider these problems separately, and even those pursuing a combined approach propose solutions with limited applicability. In this paper, we are proposing a novel PMU-based detector of loss of synchronism that utilizes generator PMU data to promptly detect rotor angle instabilities over a wide area. Moreover, we are showing how our loss of synchronism detection principle can be coupled with the known controlled splitting techniques to form an integrated defense scheme against unintentional loss of synchronism. The performance of this wide-area SIPS is demonstrated on the IEEE 39-bus test power system for various types of unstable conditions. © 2022, CC BY-NC-ND.

关键词： Kinetics

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A Data-Driven Slow Dynamic Characteristic Extraction and State Estimation Method for Large power Grid

A Data-Driven Slow Dynamic Characteristic Extraction and Sta...

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3rd IEEE Student Conference on Electrical Machines and systems (SCEMS)

作者： Cui Xinhui Ma Kaigang Meng Xinyuan Zhang Xiaohua Duan Fangwei Li Tie Cui Dai Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan Peoples R China State Grid Jibei Elect Power Co Ltd Beijing Peoples R China State Grid Jibei Elect Power Co Ltd Shenyang Peoples R China State Grid Liaoning Elect Power Co Ltd Shenyang Peoples R China

ISBN: (数字)9781728156224

ISBN: (纸本)9781728156224

The steady-state time-varying law of the grid state variables caused by load fluctuations is the slow dynamic characteristic of the grid, and the rapid extraction of its characteristics is the basis for the rapid estimation of the large scale grid operation state and the optimization of static stability prevention and control. To solve the computation speed problem of large power grid system state calculation by load prediction multiplied by jacobian inverse matrix, a data-driven slow dynamic characteristic extraction and state estimation method are proposed in this paper. Based on the various characteristics of the PV curve determined by bifurcation theory and continuous power flow, a series of time-varying second-order polynomials of bus voltage is used to represent the slow dynamic characteristics. The estimated operation state can be quickly calculated by short-term historical operating data according to this characteristic. The accuracy and rapidity of the proposed method are demonstrated on several test systems.

关键词： large power grid slow dynamic characteristic state estimation

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Probability-Interval-Based Optimal Planning of Integrated Energy system With Uncertain Wind power

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IEEE TRANSACTIONS ON INDUSTRY APPLICATIONS 2020年第1期56卷 4-13页

作者： Li, Zhe Wang, Chengfu Li, Bowen Wang, Jinyu Zhao, Penghui Zhu, Wenli Yang, Ming Ding, Ying Shandong Univ Sch Elect Engn Minist Educ Key Lab Power Syst Intelligent Dispatch & Control Jinan 250061 Peoples R China Nanyang Technol Univ Rolls Royce Corp Lab Singapore 639798 Singapore State Grid Jibei Elect Power Co Ltd Beijing 100054 Peoples R China State Grid China Technol Coll Jinan 250002 Peoples R China

Owing to a higher energy supply efficiency and operational flexibility, integrated energy system (IES), including the power, heating, and gas systems, will be the primary form of energy supply in the future. However, with the increase of large-scale stochastic wind power integration, the IES planning will face a significant challenge as the traditional power system. Therefore, a probability-interval-based IES planning considering wind power integration is proposed in this article. First, a conditional value-at-risk (CVaR) based probability-interval method is developed to describe the uncertain wind power. Second, beside traditional facilities, electricity storage system is introduced to improve the flexibility of IES. Then, an expansion planning model for IES is established to minimize the total cost including investment, operation, CVaR cost, and unserved energy cost. Moreover, the piecewise linearization method is used to deal with the nonlinear integral terms of the proposed model to improve the solution efficiency. Finally, IEEE14-NGS14 and IEEE118-NGS40 systems are constructed and the planning model is solved by GAMS/CPLEX. The numerical results illustrate the correctness and effectiveness of the proposed method.

关键词： Wind power generation Artificial neural networks Cogeneration Planning Pipelines power systems Numerical models Conditional value-at-risk (CVaR) electricity storage system (ESS) integrated energy system (IES) optimal planning uncertain wind power

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