Participation of DFIG based wind turbine generator in Load Frequency Control with linear quadratic regulator

2014 ◽  
Author(s):  
Gaurav Pandey ◽  
Sandeep Bhongade
Keyword(s):  
Wind Turbine ◽  
Frequency Control ◽  
Linear Quadratic Regulator ◽  
Load Frequency Control ◽  
Linear Quadratic ◽  
Turbine Generator ◽  
Wind Turbine Generator ◽  
Load Frequency

scholarly journals Load frequency control of a hydro dominating interconnected power system

2020 ◽  
Author(s):  
◽  
Milan Joshi
Keyword(s):  
Power System ◽  
Closed Loop ◽  
Frequency Control ◽  
Linear Quadratic Regulator ◽  
Load Frequency Control ◽  
Accurate Estimation ◽  
Renewable Energy Resources ◽  
Linear Quadratic ◽  
Random Load ◽  
Load Frequency

Energy is one of the vital figures that impact the development of civilization in the 21st century. It has been projected that by the year 2050, global energy needs will be satisfied by renewable sources. Among these renewable energy resources hydropower is available worldwide with relatively cheaper accessibility for most of the communities. Nevertheless, hydropower's control architecture raises concern for the system operators in terms of preserving the Load Frequency Control (LFC) services due to the elongated response time of hydro turbines in catering for the varying load demands. The varying load demands are inevitable in the power system due to different clients’ energy consumption patterns at different times. This, therefore, places changing control framework requests as per the requirement of diverse clients. Hence, the research proposes and demonstrates the connection of the hydro-hydro framework through the AC tie- line for LFC. The Linear Quadratic Regulator (LQR) is a plan for hydro overseeing framework in discrete mode. The application derived is displayed through closed- loop feedback gains and closed-loop eigenvalues. In the expansion model, the positive effect of a Unified Power Flow Controller (UPFC) and Redox Flow Battery (RFB) in LFC studies is investigated. This proposition moreover shows the joint endeavors of Fuzzy Logic (FL) as well as Proportional Integral Derivative (PID), with control gains well-calculated, through Particle Swarm Optimization (PSO) result into a robust FL-PSO-PID for LFC of the connected hydro framework. The different errors are defined to assess the yield as well as the execution of the FL-PSO-PID. The yield appears through a decline in blunder values as well as minimization in framework responses from accurate estimation for the LFC under various working conditions such as non- linearity, random load alteration, and parametric move as a result of a precise estimate. In the expansion, the effect of energy storage devices is also investigated to understand the enhancement provided frequency control of the hydro system, and the result obtained shows their effectiveness. Finally, the outcomes and future extent of this investigation work have been presented.

scholarly journals Optimal Decentralized LQR Control to Enhance Multi-Area LFC System Stability

2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Ashraf M. Abdelhamid ◽  
Ahmed A. M. El-Gaafary
Keyword(s):  
Power System ◽  
Frequency Control ◽  
Linear Quadratic Regulator ◽  
Load Frequency Control ◽  
System Stability ◽  
Linear Quadratic ◽  
Single Input Single Output ◽  
Load Frequency ◽  
Single Output ◽  
Optimal Linear

Many studies have been made in the field of load frequency control (LFC) through the last few decades because of its importance to healthy power system. It is important to maintain frequency deviation at zero level after a load perturbation. In decentralized control, the multi-area power system is decomposed into many single input single output (SISO) subsystems and a local controller is designed for each subsystem. The controlled subsystems may have slow poles; these undesired poles may drive the aggregated overall system into the instability region. Thus, it is required to relocate these poles to much more stable places to avoid their effect upon the overall system stability. This study aims to design a new load frequency controller based on the powerful optimal linear quadratic regulator (LQR) technique. This technique can be applied over subsystem level to shift each subsystem undesired poles one by one into a prespecified stable location which in turn shift the overall system slow poles and reduce the effect of the interaction between the interconnected subsystems among each other. This procedure must be applied many times as the number of undesired poles (pairs) until all the desired poles are achieved. The main objective is considered to get a robust design when the system is affected by a physical disturbance and ±40% model uncertainties. LQR can be applied again over the aggregated system to enhance the stability degree. Simulation results are used to evaluate the effectiveness of the proposed method and compared to other research results.

scholarly journals Distributed LQR Design for a Class of Large-Scale Multi-Area Power Systems

Energies ◽  
2019 ◽  
Vol 12 (14) ◽  
pp. 2664 ◽  
Author(s):  
Eleftherios Vlahakis ◽  
Leonidas Dritsas ◽  
George Halikias
Keyword(s):  
Power Systems ◽  
Power System ◽  
Large Scale ◽  
Convex Combination ◽  
Frequency Control ◽  
Linear Quadratic Regulator ◽  
Load Frequency Control ◽  
Linear Quadratic ◽  
Load Frequency ◽  
Power Load

Load frequency control (LFC) is one of the most challenging problems in multi-area power systems. In this paper, we consider power system formed of distinct control areas with identical dynamics which are interconnected via weak tie-lines. We then formulate a disturbance rejection problem of power-load step variations for the interconnected network system. We follow a top-down method to approximate a centralized linear quadratic regulator (LQR) optimal controller by a distributed scheme. Overall network stability is guaranteed via a stability test applied to a convex combination of Hurwitz matrices, the validity of which leads to stable network operation for a class of network topologies. The efficiency of the proposed distributed load frequency controller is illustrated via simulation studies involving a six-area power system and three interconnection schemes. In the study, apart from the nominal parameters, significant parametric variations have been considered in each area. The obtained results suggest that the proposed approach can be extended to the non-identical case.

scholarly journals LQR-Based Adaptive Virtual Inertia for Grid Integration of Wind Energy Conversion System Based on Synchronverter Model

Electronics ◽  
2021 ◽  
Vol 10 (9) ◽  
pp. 1022
Author(s):  
Walter Gil-González ◽  
Oscar Danilo Montoya ◽  
Andrés Escobar-Mejía ◽  
Jesús C. Hernández
Keyword(s):  
Wind Turbine ◽  
Linear Quadratic Regulator ◽  
State Variables ◽  
Linear Quadratic ◽  
Turbine Generator ◽  
Generator System ◽  
Worst Case ◽  
Wind Turbine Generator ◽  
Virtual Inertia ◽  
Wind Turbine Generator System

This paper proposes adaptive virtual inertia for the synchronverter model implemented in a wind turbine generator system integrated into the grid through a back-to-back converter. A linear dynamic system is developed for the proposed adaptive virtual inertia, which employs the frequency deviation and the rotor angle deviation of the synchronverter model as the state variables and the virtual inertia and frequency droop gain as the control variables. In addition, the proposed adaptive virtual inertia uses a linear quadratic regulator to ensure the optimal balance between fast frequency response and wind turbine generator system stress during disturbances. Hence, it minimizes frequency deviations with minimum effort. Several case simulations are proposed and carried out in MATLAB/Simulink software, and the results demonstrate the effectiveness and feasibility of the proposed adaptive virtual inertia synchronverter based on a linear quadratic regulator. The maximum and minimum frequency, the rate change of the frequency, and the integral of time-weighted absolute error are computed to quantify the performance of the proposed adaptive virtual inertia. These indexes are reduced by 46.61%, 52.67%, 79.41%, and 34.66%, in the worst case, when the proposed adaptive model is compared to the conventional synchronverter model.

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