scholarly journals Approach to Stochastic Modeling of Power Systems

2010 ◽  
Vol 26 (1) ◽  
pp. 37-40 ◽  
Author(s):  
Alexander Rubtsov
Keyword(s):  
Power Systems ◽  
Power System ◽  
Stochastic Modeling ◽  
Transfer Functions ◽  
Dynamic Properties ◽  
Stochastic Disturbance ◽  
Modeling Power ◽  
Linearized Model ◽  
System Power ◽  
Made In

Approach to Stochastic Modeling of Power SystemsThis paper presents an approach to modeling power system that contains sources of stochastic disturbance. It is based on frequency analysis of linearized model of power system. Power system dynamic properties are accounted by equivalent transfer functions of machines and their control equipment. This will allow more accurate calculations for different analysis tasks. Methodology of system linearization is proposed and results of linearized model test are delivered.The research was made in frame of a project with funding participation of the European Commission.

Study on the Optimum Location of PSS in Power Systems

2014 ◽  
Vol 1070-1072 ◽  
pp. 892-896
Author(s):  
Fu Xia Wu ◽  
Jian Rong Gong ◽  
Jun Xie ◽  
Ying Jun Wu
Keyword(s):  
Power Systems ◽  
Power System ◽  
Closed Loop ◽  
Power System Stabilizer ◽  
Control Effect ◽  
Factor Method ◽  
System Stabilizer ◽  
And Control ◽  
System Power ◽  
Participation Factor

Power system stabilizer in a power system is a closed-loop controller. The conventional participation factor method just considers the effect of PSS input signal. When the system stress is heavier, it may give misleading results. Based on the participation factor of modal analysis, an integrative participation factor is proposed to determine the optimum PSS location. The integrative participation factor takes into account both the input and control effect of PSS controllers. The case studied in 2-area 4-generator power system power system confirms that the integrative participation factor is more reasonable and effective than the participation factor method.

scholarly journals Transfer Function with Nonlinear Characteristics Definition Based on Multidimensional Laplace Transform and its Application to Forced Response Power Systems

Energies ◽  
2019 ◽  
Vol 12 (21) ◽  
pp. 4061
Author(s):  
Villalón ◽  
Medina-Rios
Keyword(s):  
Transfer Function ◽  
Power Systems ◽  
Power System ◽  
Laplace Transform ◽  
Frequency Response ◽  
Transfer Functions ◽  
Volterra Series ◽  
Forced Response ◽  
Nonlinear Characteristics ◽  
Test Power

In this research, the concept of nonlinear transfer function with nonlinear characteristics is introduced through the multidimensional Laplace transform and modal series (MS) method. The method of modal series is applied to the power systems dynamics analysis in order to consider nonlinear oscillations and modal interactions, which contribute to the response of the system's dynamic following disturbances. The method of MS allows the inclusion of input excitation functions obtained as Laplace domain kernels superposed to obtain a transfer function. Applying the Volterra series expansion through kernels decomposition, a transfer function with nonlinear characteristics is obtained which incorporates some of the main modal characteristics of the nonlinear system. Following the same schematic procedure, it is possible to determine second and higher order transfer functions. Once the transfer functions both linear and with nonlinear characteristics are determined, a time domain and frequency response analyses can be performed. The methodology is exemplified by denoting the numerical and analytical properties with the application to a synchronous machine-infinite busbar test power system and to a three synchronous machines–nine buses test power system. Bode and Nyquist analysis are utilized to demonstrate the transfer functions accuracy and frequency response.

scholarly journals Stable bounded value analysis of disturbance in stochastic linear power systems

2020 ◽  
pp. 002029402095910
Author(s):  
Jie Xu ◽  
Zhanbei Tong ◽  
Wengen Gao
Keyword(s):  
Stability Analysis ◽  
Power Systems ◽  
Power System ◽  
Numerical Solution ◽  
Stochastic Disturbances ◽  
Value Analysis ◽  
Stochastic Disturbance ◽  
Infinite Systems ◽  
Analysis Process ◽  
The Stability

Stochastic disturbances play a profound problem in the power system, which have an important impact on the stability of the power system. The paper proposes the stability analysis of stochastic disturbance bounded value of linear power system, and presents that the stability of power system has bounded value under stochastic disturbance and additional disturbance, and gives the analysis process in combination with stochastic differentiation. The equation theory proposes a numerical solution based on mean stability to calculate the boundedness of infinite systems under the influence of stochastic disturbance and additional disturbance. The results show that the system has bounded value stability under the disturbance.

scholarly journals A Toolbox for Analyzing and Testing Mode Identification Techniques and Network Equivalent Models

Energies ◽  
2019 ◽  
Vol 12 (13) ◽  
pp. 2606 ◽  
Author(s):  
Kontis ◽  
Barzegkar-Ntovom ◽  
Staios ◽  
Papadopoulos ◽  
Papagiannis
Keyword(s):  
Power Systems ◽  
Power System ◽  
Large Scale ◽  
Dynamic Properties ◽  
Mathematical Formulation ◽  
Dynamic Responses ◽  
Optimal Order ◽  
Mode Identification ◽  
Equivalent Models ◽  
Identification Techniques

During the last decade the dynamic properties of power systems have been altered drastically, due to the emerge of new non-conventional types of loads as well as to the increasing penetration of distributed generation. To analyze the power system dynamics and develop accurate models, measurement-based techniques are usually employed by academia and power system operators. In this regard, in this paper an identification toolbox is developed for the derivation of measurement-based equivalent models and the analysis of dynamic responses. The toolbox incorporates eight of the most widely used mode identification techniques as well as several static and dynamic network equivalencing models. First, the theoretical background of the mode identification techniques as well as the mathematical formulation of the examined equivalent models is presented and analyzed. Additionally, multi-signal analysis methods are incorporated in the toolbox to facilitate the development of robust equivalent models. Additionally, an iterative procedure is adopted to automatically determine the optimal order of the derived models. The capabilities of the toolbox are demonstrated using simulation responses, acquired from large-scale benchmark power systems, as well as using measurements recorded at a laboratory-scale active distribution network.

The comparison and analysis of Type 3 wind turbine models used for researching the stability of electric power systems

2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Igor Razzhivin ◽  
Aleksey Suvorov ◽  
Mikhail Andreev ◽  
Alisher Askarov
Keyword(s):  
Power Systems ◽  
Power System ◽  
Large Scale ◽  
Dynamic Properties ◽  
Renewable Energy Sources ◽  
Software Tools ◽  
Generic Models ◽  
Generator Type ◽  
The Stability ◽  
Type 3

Abstract The dominant trend of the modern energy is the use of generating plants based on renewable energy sources, among which the most common is a wind power plant based on doubly fed induction generator (Type 3 WT). The large-scale introduction of Type 3 WT into the modern power systems significantly changes their dynamic properties. There are problems with ensuring the basic condition of the reliability and the survivability of power systems – the stability. The study and solution of the indicated problems is possible only with the help of the mathematical modeling of a large-scale power systems which is currently being carried out with the help of widespread purely numerical software tools of calculations of modes and processes, which are characterized by various simplifications and limitations. For the properties and capabilities of software tools for studying stability issues, mathematical models of Type 3 WT, the so-called generic models, which also have simplifications and limitations, are adapted. In this article, the reliability of stability calculations of a real power system with Type 3 WT using software tools was evaluated, which allows to identify the influence of the applied simplifications and restrictions with a purely numerical approach on the quality of solving problems of assessing the stability of power systems with Type 3 WT. Also, the studies made it possible to identify the areas of the application of generic models of Type 3 WT as a part of the model of the real dimension power system, at which the greatest and least errors arise, as well as their causes. Such a comprehensive assessment becomes feasible due to the alternative approach proposed in the article, based on the use of a detail benchmark tool model instead of the full-scale data to compare the results of modeling.

Markov Jump Linear System Analysis of a Microgrid Operating in Islanded and Grid Tied Modes

2020 ◽  
Author(s):  
Gilles Mpembele ◽  
Jonathan Kimball
Keyword(s):  
Monte Carlo ◽  
Power Systems ◽  
Power System ◽  
System Analysis ◽  
Differential Algebraic Equations ◽  
Algebraic Equations ◽  
Markov Jump ◽  
Numerical Application ◽  
Conditional Moments ◽  
Markov Jump Linear Systems

<div>The analysis of power system dynamics is usually conducted using traditional models based on the standard nonlinear differential algebraic equations (DAEs). In general, solutions to these equations can be obtained using numerical methods such as the Monte Carlo simulations. The use of methods based on the Stochastic Hybrid System (SHS) framework for power systems subject to stochastic behavior is relatively new. These methods have been successfully applied to power systems subjected to</div><div>stochastic inputs. This study discusses a class of SHSs referred to as Markov Jump Linear Systems (MJLSs), in which the entire dynamic system is jumping between distinct operating points, with different local small-signal dynamics. The numerical application is based on the analysis of the IEEE 37-bus power system switching between grid-tied and standalone operating modes. The Ordinary Differential Equations (ODEs) representing the evolution of the conditional moments are derived and a matrix representation of the system is developed. Results are compared to the averaged Monte Carlo simulation. The MJLS approach was found to have a key advantage of being far less computational expensive.</div>

Grasshopper Algorithm Optimized Fractional Order Fuzzy PID Frequency Controller for Hybrid Power Systems

2019 ◽  
Vol 12 (6) ◽  
pp. 519-531
Author(s):  
Deepak Kumar Lal ◽  
Ajit Kumar Barisal
Keyword(s):  
Power Systems ◽  
Power System ◽  
Fractional Order ◽  
Pid Controller ◽  
Load Frequency Control ◽  
Pid Controllers ◽  
Fuzzy Pid ◽  
Fuzzy Pid Controller ◽  
Hybrid Power ◽  
Increasing Demand

Background: Due to the increasing demand for the electrical power and limitations of conventional energy to produce electricity. Methods: Now the Microgrid (MG) system based on alternative energy sources are used to provide electrical energy to fulfill the increasing demand. The power system frequency deviates from its nominal value when the generation differs the load demand. The paper presents, Load Frequency Control (LFC) of a hybrid power structure consisting of a reheat turbine thermal unit, hydropower generation unit and Distributed Generation (DG) resources. Results: The execution of the proposed fractional order Fuzzy proportional-integral-derivative (FO Fuzzy PID) controller is explored by comparing the results with different types of controllers such as PID, fractional order PID (FOPID) and Fuzzy PID controllers. The controller parameters are optimized with a novel application of Grasshopper Optimization Algorithm (GOA). The robustness of the proposed FO Fuzzy PID controller towards different loading, Step Load Perturbations (SLP) and random step change of wind power is tested. Further, the study is extended to an AC microgrid integrated three region thermal power systems. Conclusion: The performed time domain simulations results demonstrate the effectiveness of the proposed FO Fuzzy PID controller and show that it has better performance than that of PID, FOPID and Fuzzy PID controllers. The suggested approach is reached out to the more practical multi-region power system. Thus, the worthiness and adequacy of the proposed technique are verified effectively.

Analysis between graph-based and Power Transfer Distribution Factors (PTDF)-based model reduction methods in Electric Power Systems

2020 ◽  
Vol 0 (0) ◽  
Author(s):  
Diego A. Monroy-Ortiz ◽  
Sergio A. Dorado-Rojas ◽  
Eduardo Mojica-Nava ◽  
Sergio Rivera
Keyword(s):  
Power Systems ◽  
Power System ◽  
Model Reduction ◽  
Electrical Power ◽  
Schur Complement ◽  
Power Transfer ◽  
Electrical Power System ◽  
Admittance Matrix ◽  
Test Beds ◽  
Power Transfer Distribution Factors

Abstract This article presents a comparison between two different methods to perform model reduction of an Electrical Power System (EPS). The first is the well-known Kron Reduction Method (KRM) that is used to remove the interior nodes (also known as internal, passive, or load nodes) of an EPS. This method computes the Schur complement of the primitive admittance matrix of an EPS to obtain a reduced model that preserves the information of the system as seen from to the generation nodes. Since the primitive admittance matrix is equivalent to the Laplacian of a graph that represents the interconnections between the nodes of an EPS, this procedure is also significant from the perspective of graph theory. On the other hand, the second procedure based on Power Transfer Distribution Factors (PTDF) uses approximations of DC power flows to define regions to be reduced within the system. In this study, both techniques were applied to obtain reduced-order models of two test beds: a 14-node IEEE system and the Colombian power system (1116 buses), in order to test scalability. In analyzing the reduction of the test beds, the characteristics of each method were classified and compiled in order to know its advantages depending on the type of application. Finally, it was found that the PTDF technique is more robust in terms of the definition of power transfer in congestion zones, while the KRM method may be more accurate.

scholarly journals Series Compensation of Transmission Systems: A Literature Survey

Energies ◽  
2021 ◽  
Vol 14 (6) ◽  
pp. 1717
Author(s):  
Camilo Andrés Ordóñez ◽  
Antonio Gómez-Expósito ◽  
José María Maza-Ortega
Keyword(s):  
Steady State ◽  
Power Systems ◽  
Power System ◽  
Case Studies ◽  
Electronic Devices ◽  
Literature Survey ◽  
Power Electronic ◽  
Transmission Systems ◽  
Series Compensation ◽  
Near Future

This paper reviews the basics of series compensation in transmission systems through a literature survey. The benefits that this technology brings to enhance the steady state and dynamic operation of power systems are analyzed. The review outlines the evolution of the series compensation technologies, from mechanically operated switches to line- and self-commutated power electronic devices, covering control issues, different applications, practical realizations, and case studies. Finally, the paper closes with the major challenges that this technology will face in the near future to achieve a fully decarbonized power system.

scholarly journals Power System Transient Stability Assessment Based on Snapshot Ensemble LSTM Network

2021 ◽  
Vol 13 (12) ◽  
pp. 6953
Author(s):  
Yixing Du ◽  
Zhijian Hu
Keyword(s):  
Power Systems ◽  
Power System ◽  
Transient Stability ◽  
Short Term Memory ◽  
Risk Function ◽  
Stability Margin ◽  
Risk Level ◽  
Stability Assessment ◽  
Lstm Network ◽  
Hierarchical Assessment

Data-driven methods using synchrophasor measurements have a broad application prospect in Transient Stability Assessment (TSA). Most previous studies only focused on predicting whether the power system is stable or not after disturbance, which lacked a quantitative analysis of the risk of transient stability. Therefore, this paper proposes a two-stage power system TSA method based on snapshot ensemble long short-term memory (LSTM) network. This method can efficiently build an ensemble model through a single training process, and employ the disturbed trajectory measurements as the inputs, which can realize rapid end-to-end TSA. In the first stage, dynamic hierarchical assessment is carried out through the classifier, so as to screen out credible samples step by step. In the second stage, the regressor is used to predict the transient stability margin of the credible stable samples and the undetermined samples, and combined with the built risk function to realize the risk quantification of transient angle stability. Furthermore, by modifying the loss function of the model, it effectively overcomes sample imbalance and overlapping. The simulation results show that the proposed method can not only accurately predict binary information representing transient stability status of samples, but also reasonably reflect the transient safety risk level of power systems, providing reliable reference for the subsequent control.

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