A novel RNN based load modelling method with measurement data in active distribution system

Abstract Due to the high penetration of renewable energy and the wide application of electronic devices in the distribution systems, it becomes more complicated to formulate an accurate load model than ever before. For some cases, the formulation cannot be successfully established via the traditional modelling approaches. Therefore, how to establish an accurate load model under the new challenges is drawing a great deal of attention. In this paper, measurement based method using recurrent neural network (RNN) is proposed for constructing an accurate equivalent of active distribution systems, and an application scheme of the proposed model is presented. With the purpose of thoroughly investigating the performance of the proposed RNN based load model in an electric power system, it is applied to reproduce the dynamic behaviors of active distribution systems. In the testing scenario, the performance of the RNN model is evaluated by two types (i.e. using the same disturbance cases and different new disturbance cases).

[1]  Kit Po Wong,et al.  Measurement-based dynamic load modelling using time-domain simulation and parallel-evolutionary search , 2016 .

[2]  Pouyan Pourbeik,et al.  Implementation of the WECC Composite Load Model for utilities using the component-based modeling approach , 2016, 2016 IEEE/PES Transmission and Distribution Conference and Exposition (T&D).

[3]  D. Hill,et al.  Modelling and identification of nonlinear dynamic loads in power systems , 1994 .

[4]  Takashi Hiyama,et al.  Artificial neural network based dynamic load modeling , 1997 .

[5]  Zhe Chen,et al.  A Systematic Approach for Dynamic Security Assessment and the Corresponding Preventive Control Scheme Based on Decision Trees , 2014, IEEE Transactions on Power Systems.

[6]  Mark K. Transtrum,et al.  Measurement-Directed Reduction of Dynamic Models in Power Systems , 2017, IEEE Transactions on Power Systems.

[7]  Byoung-Kon Choi,et al.  Measurement-based dynamic load models: derivation, comparison, and validation , 2006, IEEE Transactions on Power Systems.

[8]  Alireza Rouhani,et al.  Real-Time Dynamic Parameter Estimation for an Exponential Dynamic Load Model , 2016, IEEE Transactions on Smart Grid.

[9]  Kurt Hornik,et al.  Approximation capabilities of multilayer feedforward networks , 1991, Neural Networks.

[10]  Robert J. Thomas,et al.  Power system dynamic load modeling using artificial neural networks , 1994 .

[11]  Eleftherios O. Kontis,et al.  Measurement-Based Dynamic Load Modeling Using the Vector Fitting Technique , 2018, IEEE Transactions on Power Systems.

[12]  Kai Sun,et al.  Measurement-based correlation approach for power system dynamic response estimation , 2015 .

[13]  F. Nozari,et al.  Load modeling for power flow and transient stability computer studies , 1988 .

[14]  C. W. Taylor,et al.  Model validation for the August 10, 1996 WSCC system outage , 1999 .

[15]  Geoffrey E. Hinton,et al.  Generating Text with Recurrent Neural Networks , 2011, ICML.

[16]  P. Kundur,et al.  Power system stability and control , 1994 .

[17]  Yilu Liu,et al.  A measurement-based power system model for dynamic response estimation and instability warning , 2015 .

[18]  Ronald R. Mohler,et al.  Neural-network-based load modeling and its use in voltage stability analysis , 2003, IEEE Trans. Control. Syst. Technol..

[19]  G.W. Chang,et al.  A Neural-Network-Based Method of Modeling Electric Arc Furnace Load for Power Engineering Study , 2010, IEEE Transactions on Power Systems.

[20]  Jinyu Wen,et al.  Wide-Area Damping Controller for Power System Interarea Oscillations: A Networked Predictive Control Approach , 2015, IEEE Transactions on Control Systems Technology.

[21]  M. Glavic,et al.  A component-based power system model-driven architecture , 2004, IEEE Transactions on Power Systems.

[22]  Kaizhu Huang,et al.  Robust Text Detection in Natural Scene Images , 2013, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[23]  Delberis Lima,et al.  Measurement-based load modeling using transfer functions for dynamic simulations , 2014, 2014 IEEE PES T&D Conference and Exposition.

[24]  Geoffrey E. Hinton,et al.  Deep Learning , 2015, Nature.

[25]  Jovica V. Milanovic,et al.  Effects of load dynamics on power system damping , 1995 .

[26]  D. Kosterev,et al.  Load modeling in power system studies: WECC progress update , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[27]  Theofilos A. Papadopoulos,et al.  Derivation and evaluation of generic measurement-based dynamic load models , 2016 .

[28]  Xiaodong Liang.  A New Composite Load Model Structure for Industrial Facilities , 2016, IEEE Transactions on Industry Applications.

[29]  Istvan Erlich,et al.  Artificial neural network-based dynamic equivalents for distribution systems containing active sources , 2004 .

[30]  Mohammad Taghi Ameli,et al.  Measurement-based modelling of composite load using genetic algorithm , 2018 .

[31]  Jovica V. Milanovic,et al.  Dynamic load modelling based on measurements in medium voltage distribution network , 2008 .

[32]  C. W. Taylor,et al.  Identification of power system load dynamics using artificial neural networks , 1997 .

[33]  S.M. Halpin.  Advanced Load Models in Power System Dynamic Studies: Application Issues , 2006, 2005/2006 IEEE/PES Transmission and Distribution Conference and Exhibition.