scholarly journals Adaptive Hybrid Fuzzy PI-LQR Optimal Control using Artificial Immune System via Clonal Selection for Two-Area Load Frequency Control

2020 ◽  
Vol 12 (3) ◽  
pp. 667-685
Author(s):  
Muhammad Abdillah ◽  
Keyword(s):  
Optimal Control ◽  
Power System ◽  
Clonal Selection ◽  
Frequency Control ◽  
Dynamic Performance ◽  
Test System ◽  
Pi Controller ◽  
Operating Conditions ◽  
Load Frequency Control ◽  
Load Frequency

Load frequency control (LFC) problem has been a foremost issue in electrical power system operation and is becoming more important recently with growing size, changing structure, and complexity in interconnected power systems. In general, LFC system utilizes simple proportional integral (PI) controller. However, due to the PI control parameters are commonly adjusted based on classical or trial-error method (TEM), it is incapable of obtaining good dynamic performance for a wide range of operating conditions and various load change scenarios in a multi-area power system. This paper introduces a novel control scheme for load frequency control (LFC) using hybrid fuzzy proportional integral (fuzzy PI) and linear quadratic regulator (LQR) optimal control, where fuzzy logic control (FLC) is used to adjust the gains KP and KI of PI controller which called fuzzy PI in this paper, while the LQR optimal control method is employed to obtain the feedback gain KOP through Algebraic Riccati Equation (ARE). The merit of both control strategies is to tune their control feedback gains, which are KP, KI and KOP, regarding various system operating conditions. Artificial immune system (AIS) via clonal selection is utilized to optimize the membership function (MF) of fuzzy PI and weighting matrices Q and R of LQR optimal control in order to obtain their optimal feedback gains. To examine the efficacy of the proposed method, LFC of two-area power system model is utilized as a test system. The amalgamation of fuzzy PI-LQR is applied to improve the dynamic performance of two-area LFC. Other control schemes such as PI controller, hybrid PI controllerLQR, and hybrid fuzzy PI-LQR are also investigated to the studied a test system. The obtained simulation results show that the proposed method could compress the settling time and decrease the overshoot of LFC which is better than other approaches that are also employed to the tested system in this study.

scholarly journals LQR Tuning Using AIS for Frequency Oscillation Damping

2020 ◽  
Vol 3 (4) ◽  
pp. 112
Author(s):  
Muhammad Abdillah ◽  
Teguh Aryo Nugroho ◽  
Herlambang Setiadi
Keyword(s):  
Optimal Control ◽  
Power System ◽  
Clonal Selection ◽  
Dynamic Performance ◽  
Operating Conditions ◽  
Load Frequency Control ◽  
Primary Control ◽  
Frequency Oscillation ◽  
Lqr Control ◽  
Wide Range

Commonly, primary control, i.e. governor, in the generation unit had been employed to stabilize the change of frequency due to the change of electrical load during system operation. But, the drawback of the primary control was it could not return the frequency to its nominal value when the disturbance was occurred. Thus, the aim of the primary control was only stabilizing the frequency to reach its new value after there were load changes. Therefore, the LQR control is employed as a supplementary control called Load Frequency Control (LFC) to restore and keep the frequency on its nominal value after load changes occurred on the power system grid. However, since the LQR control parameters were commonly adjusted based on classical or Trial-Error Method (TEM), it was incapable of obtaining good dynamic performance for a wide range of operating conditions and various load change scenarios. To overcome this problem, this paper proposed an Artificial Immune System (AIS) via clonal selection to automatically adjust the weighting matrices, Q and R, of LQR related to various system operating conditions changes. The efficacy of the proposed control scheme was tested on a two-area power system network. The obtained simulation results have shown that the proposed method could reduce the settling time and the overshoot of frequency oscillation, which is better than conventional LQR optimal control and without LQR optimal control.

scholarly journals 5G Poor and Rich Novel Control Scheme Based Load Frequency Regulation of a Two-Area System with 100% Renewables in Africa

2020 ◽  
Vol 5 (1) ◽  
pp. 2
Author(s):  
Hady H. Fayek
Keyword(s):  
Power System ◽  
Fractional Order ◽  
Packet Loss ◽  
Pid Controller ◽  
Frequency Control ◽  
Operating Conditions ◽  
Load Frequency Control ◽  
Load Frequency ◽  
Control Scheme ◽  
Non Linear

Remote farms in Africa are cultivated lands planned for 100% sustainable energy and organic agriculture in the future. This paper presents the load frequency control of a two-area power system feeding those farms. The power system is supplied by renewable technologies and storage facilities only which are photovoltaics, biogas, biodiesel, solar thermal, battery storage and flywheel storage systems. Each of those facilities has 150-kW capacity. This paper presents a model for each renewable energy technology and energy storage facility. The frequency is controlled by using a novel non-linear fractional order proportional integral derivative control scheme (NFOPID). The novel scheme is compared to a non-linear PID controller (NPID), fractional order PID controller (FOPID), and conventional PID. The effect of the different degradation factors related to the communication infrastructure, such as the time delay and packet loss, are modeled and simulated to assess the controlled system performance. A new cost function is presented in this research. The four controllers are tuned by novel poor and rich optimization (PRO) algorithm at different operating conditions. PRO controller design is compared to other state of the art techniques in this paper. The results show that the PRO design for a novel NFOPID controller has a promising future in load frequency control considering communication delays and packet loss. The simulation and optimization are applied on MATLAB/SIMULINK 2017a environment.

scholarly journals STUDI ANALISIS GOVERNOR SEBAGAI LOAD FREQUENCY CONTROL PADA PLTG MENGGUNAKAN FUZZY LOGIC CONTROLLER

2018 ◽  
Vol 17 (1) ◽  
pp. 107
Author(s):  
Gusti Made Ngurah Christy Aryanata ◽  
I Nengah Suweden ◽  
I Made Mataram
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Fuzzy Logic Controller ◽  
Frequency Control ◽  
Pi Controller ◽  
Active Power ◽  
Load Frequency Control ◽  
Electrical Power System ◽  
Load Frequency ◽  
Frequency Changes

A good electrical power system is a system that can serve the load in a sustainable and stable voltage and frequency. Changes in frequency occur due to the demand of loads that change from time to time. The frequency setting of the PLTG power system depends on the active power charge in the system. This active power setting is done by adjusting the magnitude of the generator drive coupling. The frequency setting is done by increasing and decreasing the amount of primary energy (fuel) and carried on the governor. Simulation in governor analysis study as load frequency control at PLTG using fuzzy logic controller is done by giving four types of cultivation that is 0,1 pu, 0,2pu, 0,3 pu and 0,4 pu. The simulation is done to compare the dynamic frequency response output and the resulting stability time using fuzzy logic controller with PI controller. Based on the results of comparative analysis conducted to prove that governor as load frequency control using fuzzy logic control is better than using PI controller. This can be seen from the output response frequency and time stability.

Fuzzy Logic Based Load Frequency Control of Two Area Power System in Deregulated Environment

2014 ◽  
Vol 626 ◽  
pp. 219-226 ◽  
Author(s):  
Ajitha S. Priyadarsini ◽  
P. Melba Mary ◽  
N. Albert Singh
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Fuzzy Logic Controller ◽  
Frequency Control ◽  
Operating Conditions ◽  
Load Frequency Control ◽  
Bilateral Contracts ◽  
Load Frequency ◽  
Frequency Control System ◽  
Tie Lines

In this paper fuzzy logic based load frequency control (LFC) of two area power system in deregulated environment was studied. A two area system is considered in which all areas are interconnected by normal AC tie-lines. In the proposed system the effects of bilateral contracts between DISCOs and GENCOs are also considered. The performance of the fuzzy logic controller is tested on a deregulated two area load frequency control system for different operating conditions using MATLAB Simulink tool.

scholarly journals Introducing LQR-fuzzy for a dynamic multi area LFC-DR model

2019 ◽  
Vol 9 (2) ◽  
pp. 861
Author(s):  
Palakaluri Srividya Devi ◽  
R.Vijaya Santhi
Keyword(s):  
Power System ◽  
Demand Response ◽  
Frequency Control ◽  
Dynamic Performance ◽  
Vital Role ◽  
Electric Power System ◽  
Operating Conditions ◽  
Load Frequency Control ◽  
Control Loop ◽  
Interconnected Power System

It is well known that Load Frequency Control (LFC) model plays a vital role in electric power system design and operation. In the literature, much research works has stated on the advantages and realization of DR (Demand Response), which has proved to be an important part of the future smart grid. In an interconnected power system, if a load   demand changes randomly, both frequency and tie line power varies. LFC-DR model is tuned by standard controllers like PI, PD, PID controllers, as they have constant gains. Hence, they are incapable of acquiring desirable dynamic performance for an extensive variety of operating conditions and various load changes. This paper presents the idea of introducing a DR control loop in the traditional Multi area LFC model (called LFC -DR) using LQR- Fuzzy Logic Control. The effect of DR-CDL i.e. (Demand Response Communication Delay Latency) in the design is also considered and is linearized using Padé approximation. Simulation results shows that the addition of DR control loop with proposed controller guarantees stability of the overall closed-loop LFC-DR system which effectively improves the system dynamic performance and is superior over a classical controller at different operating scenarios.

Gain Schedule PI Fuzzy Load Frequency Control for Two-Area Electric Power System

2020 ◽  
Vol 9 (3) ◽  
pp. 39-50
Author(s):  
Tawfiq H. Elmenfy
Keyword(s):  
Power System ◽  
Electric Power ◽  
Frequency Control ◽  
Electric Power System ◽  
Operating Conditions ◽  
Load Frequency Control ◽  
Rule Base ◽  
Level Control ◽  
Load Frequency ◽  
Gain Schedule

The use of proportional integral (PI) load frequency control (LFC) to ensure the stable and reliable operation of electric power system is practical important. Any imbalance between synchronous generators and consumption loads will cause frequency unstable within the complete power system. The purpose of the load frequency control (LFC) is to keep the power system frequency and the inter-area tie power as near equilibrium point. This article introduces a gain schedule PI fuzzy load frequency control (GLFC) applying to two area electric power system. The GLFC consists of two level control systems, where the PI controller in the conventional form and its parameters are tuned in real time by fuzzy system. A fuzzy rule base is constructed in the form set of IF-THEN that describe how to choose the PI parameters under different operating conditions. The simulation has been conducted in MATLAB Simulink package. The effectiveness of the GLFC is measured by comparison with conventional PI load frequency controller.

Load frequency control of a two-area multi-source power system using a tilt integral derivative controller

2016 ◽  
Vol 24 (1) ◽  
pp. 110-125 ◽  
Author(s):  
Pretty Neelam Topno ◽  
Saurabh Chanana
Keyword(s):  
Power System ◽  
Frequency Control ◽  
Parameter Tuning ◽  
Test System ◽  
Load Frequency Control ◽  
Source Power ◽  
Interconnected Power System ◽  
Load Frequency ◽  
Optimal Value ◽  
Parameter Variations

This paper introduces a tilt integral derivative controller as the supplementary controller for load frequency control of a two-area interconnected power system. The optimal value of parameters of the tilt integral derivative controller is evaluated using constrained nonlinear optimization by means of a performance index-based method. The proposed tilt integral derivative control offers superior properties such as simple parameter tuning and its performance does not compromise the occurrence of any parameter variations in the system. To verify these features of the controller, the test system is subjected to step load disturbance and parameter variations that ensure the robustness of the tilt integral derivative controller. Comparative analysis with previously published work indicates that the proposed tilt integral derivative controller gives better performance and holds the property of robustness. Simulations have been performed using Matlab®.

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