scholarly journals An Extreme Learning Machine Based Adaptive VISMA for Stability Enhancement of Renewable Rich Power Systems

Electronics ◽  
2022 ◽  
Vol 11 (2) ◽  
pp. 247
Author(s):  
Herlambang Setiadi ◽  
Rakibuzzaman Shah ◽  
Md Rabiul Islam ◽  
Dimas Anton Asfani ◽  
Tigor Hamonangan Nasution ◽  
...  
Keyword(s):  
Power Systems ◽  
Power System ◽  
Extreme Learning Machine ◽  
Power Plants ◽  
Test System ◽  
Operating Conditions ◽  
System Stability ◽  
Synchronous Machines ◽  
Machine Method ◽  
Learning Machine

Maintaining power system stability in renewable-rich power systems can be a challenging task. Generally, the renewable-rich power systems suffer from low and no inertia due to the integration of power electronics devices in renewable-based power plants. Power system oscillatory stability can also be affected due to the low and no inertia. To overcome this problem, additional devices that can emulate inertia without adding synchronous machines can be used. These devices are referred to as virtual synchronous machines (VISMA). In this paper, the enhancement of oscillatory stability of a realistic representative power system using VISMA is proposed. A battery energy storage system (BESS) is used as the VISMA by adding an additional controller to emulate the inertia. The VISMA is designed by using Fruit Fly Optimization. Moreover, to handle the uncertainty of renewable-based power plants, the VISMA parameters are designed to be adaptive using the extreme learning machine method. Java Indonesian Power Grid has been used as the test system to investigate the efficacy of the proposed method against the conventional POD method and VISMA tuning using other methods. The simulation results show that the proposed method can enhance the oscillatory stability of the power system under various operating conditions.

scholarly journals Designing a GA-Based Robust Controller For Load Frequency Control (LFC)

2018 ◽  
Vol 8 (2) ◽  
pp. 2633-2639 ◽  
Author(s):  
K. Soleimani ◽  
J. Mazloum
Keyword(s):  
Power Systems ◽  
Power System ◽  
Power Plants ◽  
Frequency Control ◽  
Load Frequency Control ◽  
System Stability ◽  
Robust Controller ◽  
Power Flux ◽  
Pi Controllers ◽  
Multiple Units

Power systems include multiple units linked together to produce constantly moving electric power flux. Stability is very important in power systems, so controller systems should be implemented in power plants to ensure power system stability either in normal conditions or after the events of unwanted inputs and disorder. Frequency and active power control are more important regarding stability. Our effort focused on designing and implementing robust PID and PI controllers based on genetic algorithm by changing the reference of generating units for faster damping of frequency oscillations. Implementation results are examined on two-area power system in the ideally state and in the case of parameter deviation. According to the results, the proposed controllers are resistant to deviation of power system parameters and governor uncertainties.

On-line Adaptive and Intelligent Distance Relaying Scheme for Power Network

2015 ◽  
Vol 16 (5) ◽  
pp. 473-489
Author(s):  
Rahul Dubey ◽  
S. R. Samantaray ◽  
B. K. Panigrahi ◽  
G. V. Venkoparao
Keyword(s):  
Power Systems ◽  
Transmission Lines ◽  
Model Updating ◽  
Test System ◽  
Operating Conditions ◽  
Power Network ◽  
Parallel Transmission ◽  
On Line ◽  
Distance Relaying ◽  
Learning Machine

Abstract The paper presents an on-line sequential extreme learning machine (OS-ELM) based fast and accurate adaptive distance relaying scheme (ADRS) for transmission line protection. The proposed method develops an adaptive relay characteristics suitable to the changes in the physical conditions of the power systems. This can efficiently update the trained model on-line by partial training on the new data to reduce the model updating time whenever a new special case occurs. The effectiveness of the proposed method is validated on simulation platform for test system with two terminal parallel transmission lines with complex mutual coupling. The test results, considering wide variations in operating conditions of the faulted power network, indicate that the proposed adaptive relay setting provides significant improvement in the relay performance.

Application of Extreme Learning Machine in Transient Stability Assessment of Power Systems

2013 ◽  
Vol 392 ◽  
pp. 544-547 ◽  
Author(s):  
Yang Li ◽  
Xue Ping Gu
Keyword(s):  
Power Systems ◽  
Extreme Learning Machine ◽  
Rough Sets ◽  
Transient Stability ◽  
Test System ◽  
System Level ◽  
Stability Assessment ◽  
Fuzzy Rough Sets ◽  
Operation Condition ◽  
Learning Machine

This paper presents a new method for transient stability assessment (TSA) of power systems using kernel fuzzy rough sets and extreme learning machine (ELM). Considering the possible real-time information provided by phasor measurement units, a group of system-level classification features were firstly extracted from the power system operation condition to construct the original feature set. Then kernelized fuzzy rough sets were used to reduce the dimension of input space, and ELM was employed to build a TSA model. The effectiveness of the proposed method is validated by the simulation results on the New England 39-bus test system.

scholarly journals Intelligent Fault Classification and Location Identification Method for Microgrids Using Discrete Orthonormal Stockwell Transform-Based Optimized Multi-Kernel Extreme Learning Machine

Energies ◽  
2019 ◽  
Vol 12 (23) ◽  
pp. 4504 ◽  
Author(s):  
Teke Gush ◽  
Syed Basit Ali Bukhari ◽  
Khawaja Khalid Mehmood ◽  
Samuel Admasie ◽  
Ji-Soo Kim ◽  
...  
Keyword(s):  
Extreme Learning Machine ◽  
High Performance ◽  
Test System ◽  
Operating Conditions ◽  
Fault Classification ◽  
Identification Method ◽  
Kernel Extreme Learning Machine ◽  
Location Identification ◽  
Learning Machine ◽  
Stockwell Transform

This paper proposes an intelligent fault classification and location identification method for microgrids using discrete orthonormal Stockwell transform (DOST)-based optimized multi-kernel extreme learning machine (MKELM). The proposed method first extracts useful statistical features from one cycle of post-fault current signals retrieved from sending-end relays of microgrids using DOST. Then, the extracted features are normalized and fed to the MKELM as an input. The MKELM, which consists of multiple kernels in the hidden nodes of an extreme learning machine, is used for the classification and location of faults in microgrids. A genetic algorithm is employed to determine the optimum parameters of the MKELM. The performance of the proposed method is tested on the standard IEC microgrid test system for various operating conditions and fault cases, including different fault locations, fault resistance, and fault inception angles using the MATLAB/Simulink software. The test results confirm the efficacy of the proposed method for classifying and locating any type of fault in a microgrid with high performance. Furthermore, the proposed method has higher performance and is more robust to measurement noise than existing intelligent methods.

scholarly journals Assessing the Impact of Cybersecurity Attacks on Power Systems

Energies ◽  
2019 ◽  
Vol 12 (4) ◽  
pp. 725 ◽  
Author(s):  
Athanasios Dagoumas
Keyword(s):  
Power Systems ◽  
Power System ◽  
Linear Trend ◽  
Operating Cost ◽  
Energy System ◽  
Operating Conditions ◽  
System Stability ◽  
System Cost ◽  
System Operator ◽  
The Impact

Cybersecurity is an emerging challenge for power systems, as it strongly affects their reliability and the whole energy system cost. The paper uses several Unit Commitments (UC) models, applying different methods to tackle renewables’ uncertainty. The selected power system is IEEE RTS 96. The UC models are used to assess the impact of different cybersecurity threats. The focus is to assess their impact on the total operating cost and the power grid adequacy to handle them. The comparison between the UC models shows that more robust UC models lead to higher total operating costs. The cost, unit dispatching, and energy mix evolution have a non-linear trend, depending on the power system characteristics and the cyberattacks types. However, the paper provides evidence of considerable price signals in the case of the examined cyberattacks. Each Transmission System Operator (TSO) should examine combinations of cyberattacks and operating conditions to identify crucial cases for system stability and power system cost operation. The applied methodology would also require substantial developments or supplementary approaches to assess cyberthreats at the distribution level.

scholarly journals Application of Neuro-Fuzzy Controller to Replace SMIB and Interconnected Multi-Machine Power System Stabilizers

2020 ◽  
Vol 12 (22) ◽  
pp. 9591 ◽  
Author(s):  
Aliyu Sabo ◽  
Noor Izzri Abdul Wahab ◽  
Mohammad Lutfi Othman ◽  
Mai Zurwatul Ahlam Mohd Jaffar ◽  
Hakan Acikgoz ◽  
...  
Keyword(s):  
Power Systems ◽  
Power System ◽  
Fuzzy Controller ◽  
Operating Conditions ◽  
System Stability ◽  
Test Power ◽  
Large Power ◽  
Neuro Fuzzy ◽  
And Performance ◽  
Damping Controller

In this research, an effective application and performance assessment of the Neuro-Fuzzy Controller (NFC) damping controller is designed to replace a single machine infinite bus (SMIB) power system stabilizer (PSS), and coordinated multi PSSs in large interconnected power systems are presented. The limitation of the conventional PSSs on SMIB and interconnected multi-machine test power systems are exposed and disclosed by the proposed NFC stabilizer. The NFC is a nonlinear robust controller which does not require a mathematical model of the test power system to be controlled, unlike the conventional PSSs’ damping controller. The Proposed NFC is designed to improve the stability of SMIB, an interconnected IEEE 3-machine, 9-bus power system, and an interconnected two-area 10-machine system of 39-bus New England IEEE test power system under multiple operating conditions. The proposed NFC damping controller performance is compared with the conventional PSS damping controller to confirm the capability of the proposed stabilizer and realize an improved system stability enhancement. The conventional PSSs’ design problem is transformed into an optimization problem where an eigenvalue-based objective function is developed and applied to design the SMIB-PSS and the interconnected multi-machine PSSs. The time-domain phasor simulation was done in the SIMULINK domain, and the simulation results show that the transient responses of the system rise time, settling time, peak time, and peak magnitude were all impressively improved by an acceptable amount for all the test system with the proposed NFC stabilizer. Thus, the NFC was able to effectively control the LFOs and produce an enhanced performance compared to the conventional PSS damping controller. Similarly, the result validates the effectiveness of the proposed NFC damping controller for LFO control, which demonstrates more robustness and efficiency than the classical PSS damping controller. Therefore, the application and performance of the NFC has appeared as a promising method and can be considered as a remarkable method for the optimal design damping stabilizer for small and large power systems.

scholarly journals Optimized Extreme Learning Machine for Power System Transient Stability Prediction Using Synchrophasors

2015 ◽  
Vol 2015 ◽  
pp. 1-8 ◽  
Author(s):  
Yanjun Zhang ◽  
Tie Li ◽  
Guangyu Na ◽  
Guoqing Li ◽  
Yang Li
Keyword(s):  
Power Systems ◽  
Power System ◽  
Extreme Learning Machine ◽  
Large Scale ◽  
Transient Stability ◽  
Stability Prediction ◽  
Learning Machine ◽  
Elm Classifier ◽  
Ipso Algorithm ◽  
Synchronized Measurements

A new optimized extreme learning machine- (ELM-) based method for power system transient stability prediction (TSP) using synchrophasors is presented in this paper. First, the input features symbolizing the transient stability of power systems are extracted from synchronized measurements. Then, an ELM classifier is employed to build the TSP model. And finally, the optimal parameters of the model are optimized by using the improved particle swarm optimization (IPSO) algorithm. The novelty of the proposal is in the fact that it improves the prediction performance of the ELM-based TSP model by using IPSO to optimize the parameters of the model with synchrophasors. And finally, based on the test results on both IEEE 39-bus system and a large-scale real power system, the correctness and validity of the presented approach are verified.

scholarly journals On the possibility of participation of npps with vverin emergency frequency regulation in power system

2019 ◽  
Vol 21 (3) ◽  
pp. 99-108
Author(s):  
V. A. Khrustalev ◽  
M. V. Garievskii ◽  
I. A. Rostuntsova ◽  
A. V. Portyankin
Keyword(s):  
Power Systems ◽  
Power System ◽  
Nuclear Power ◽  
Power Plants ◽  
Frequency Control ◽  
Reactor Core ◽  
Operating Conditions ◽  
Frequency Regulation ◽  
Primary Control ◽  
Main Circulation

The purpose of the article is to study the possibility and feasibility of participation of nuclear power plants (NPPs) with VVER in emergency frequency control in power systems with a high proportion of nuclear power units and, at the same time, of reducing the power consumption for the own needs of the main circulation pumps during modes with power below nominal. To solve these problems, it was proposed to increase the achievable speeds of power gain (load increase) due to the installation of frequency controlled drives of the MCP. Large system frequency variations (caused by large imbalances between generation and demand) may jeopardize electrical equipment, in terms of maintaining stable and reliable operating conditions. For NPPs, the task of preventing or localizing accidents is even more important than for TPPs, since in case of major system accidents, it is possible to completely stop external power supply of the NPPs own needs. Thus, besides the requirements for the primary control of the frequency of NPPs with VVER, today we need more stringent requirements for their emergency acceleration and mobility. The operation of NPPs with long-term non-recoverable active power shortage causes a decrease in the speed of the main circulation pumps of NPPs with VVER and a decrease in the coolant flow rate. It is shown that the installation of variable frequency drives of the MCPs at NPP with VVER is appropriate not only to save energy consumption for their drive in partial modes, but also to increase the power of NPP above the nominal (without reducing the reserve before the heat exchange crisis in the reactor core) for the elimination of system accidents, and thus to improve the safety of the NPPs included in the power system.

scholarly journals Power System Stability Study on Multi Machine Systems having DFIG Based Wind Generation System

2020 ◽  
Vol 6 (3) ◽  
pp. 27-30
Author(s):  
Pramod Kumar Mehar ◽  
Mrs. Madhu Upadhyay
Keyword(s):  
Steady State ◽  
Power Systems ◽  
Power System ◽  
Power Plants ◽  
Transient Stability ◽  
Power System Stability ◽  
Stability Study ◽  
System Stability ◽  
Synchronous Generators ◽  
The Impact

Power system stability is related to principles of rotational motion and the swing equation governing the electromechanical dynamic behavior. In the special case of two finite machines the equal area criterion of stability can be used to calculate the critical clearing angle on the power system, it is necessary to maintain synchronism, otherwise a standard of service to the consumers will not be achieved. With the increasing penetration of doubly fed induction generators (DFIGs), the impact of the DFIG on transient stability attracts great attention. Transient stability is largely dominated by generator types in the power system, and the dynamic characteristics of DFIG wind turbines are different from that of the synchronous generators in the conventional power plants. The analysis of the transient stability on DFIG integrated power systems has become a very important issue. This paper is a review of three types of stability condition. The first type of stability, steady state stability explains the maximum steady state power and the power angle diagram. There are several methods to improve system stability in which some methods are explained.

Tuning of Power System Stabilizer (Unitrol D) in Benghazi North Power Plant

2013 ◽  
Vol 2 (2) ◽  
pp. 32-43 ◽  
Author(s):  
Tawfiq H. Elmenfy
Keyword(s):  
Power Systems ◽  
Power System ◽  
Power Plants ◽  
Optimization Technique ◽  
System Stability ◽  
Power System Stabilizer ◽  
Power System Stabilizers ◽  
Particle Swarm Optimization Technique ◽  
Matlab Package ◽  
System Stabilizer

The use of power system stabilizers (PSSs) to damp power system swing mode of oscillations is of practical important. The authors purpose is to retune the power system stabilizer (PSS1A) parameters in Unitrol D produced by ABB– was installed in 1995 in Benghazi North Power Plants (BNPPs) at General Electricity Company of Libya (GECOL). Power systems are steadily growing with larger capacity, so the optimal values of the power system stabilizer (PSS1A) parameters should be retuned. A particle swarm optimization technique (PSO) is used to determine the parameters of the PSS off-line. The objective is to damp the local and inter-area modes of oscillations that occur following power system disturbances. The retuned power system stabilizer (PSS1A) can cope with large disturbance at different operating points and has an enhanced power system stability, The MATLAB package with SIMULINK is used for the design and simulations.

Sign in / Sign up

Export Citation Format

Share Document