scholarly journals Chaos Algorithm versus Traditional and Optimal Approaches for Regulating Line Frequency of Steam Power System

2018 ◽  
Vol 14 (2) ◽  
pp. 120-126
Author(s):  
Ahmed Elhafez ◽  
Ali Yosuf
Keyword(s):  
Optimal Control ◽  
Steady State ◽  
Power System ◽  
Settling Time ◽  
Load Frequency Control ◽  
Pid Controllers ◽  
Frequency Error ◽  
Proportional Integral ◽  
State Frequency ◽  
State Error

Load Frequency Control (LFC) is a basic control strategy for proper operation of the power system. It ensures the ability of each generator in regulating its output power in such way to maintain system frequency and tie-line power of the interconnected system at prescribed levels. This article introduces comprehensive comparative study between Chaos Optimization Algorithm (COA) and optimal control approaches, such as Linear Quadratic Regulator (LQR), and Optimal Pole Shifting (OPS) regarding the tuning of LFC controller. The comparison is extended to the control approaches that result in zero steady-state frequency error such as Proportional Integral (PI) and Proportional Integral Derivative (PID) controllers. Ziegler-Nicholas method is widely adopted for tuning such controllers. The article then compares between PI and PID controllers tuned via Ziegler-Nicholas and COA. The optimal control approaches as LQR and OPS have the characteristic of steady-state error. Moreover, they require the access for full state variables. This limits their applicability. Whereas, Ziegler-Nicholas PI and PID controllers have relatively long settling time and high overshoot. The controllers tuned via COA remedy the defects of optimal and zero steady-state controllers. The performance adequacy of the proposed controllers is assessed for different operating scenarios. Matlab and its dynamic platform, Simulink, are used for stimulating the system under concern and the investigated control techniques. The simulation results revealed that COA results in the smallest settling time and overshoot compared with traditional controllers and zero steady-state error controllers. In the overshoot, COA produces around 80% less than LQR and 98.5% less than OPS, while in the settling time, COA produces around 81% less than LQR and 95% less than OPS. Moreover, COA produces the lowest steady-state frequency error. For Ziegler-Nicholas controllers, COA produces around 53% less in the overshoot and 42% less in the settling time.

scholarly journals Performance Evaluation of Balancing Bicopter using P, PI, and PID Controller

2019 ◽  
Vol 11 (2) ◽  
pp. 44-49
Author(s):  
Esa Apriaskar ◽  
Fahmizal Fahmizal ◽  
Nur Azis Salim ◽  
Dhidik Prastiyanto
Keyword(s):  
Performance Evaluation ◽  
Steady State ◽  
Pid Controller ◽  
Performance Test ◽  
Pulse Width Modulation ◽  
Pi Controller ◽  
Settling Time ◽  
Proportional Integral ◽  
Rising Time ◽  
State Error

Due to potential features of unmanned aerial vehicles for society, the development of bicopter has started to increase. This paper contributes to the development by presenting a performance evaluation of balancing bicopter control in roll attitude. It aims to determine the best controller structure for the balancing bicopter. The controller types evaluated are based on Ziegler-Nichols tuning method; they are proportional (P), proportional-integral (PI), and proportional-integral-derivative (PID) controllers. Root locus plot of the closed-loop balancing bicopter system is used to decide the tuning approach. This work considers a difference in pulse-width-modulation (PWM) signal between the left and right rotors as the signal control and bicopter angle in roll movement as the output. Parameters tuned by the method are Kp, Ti, and Td which is based on the ideal PID structure. The performance test utilizes rising time, settling time, maximum overshoot, and steady-state error to determine the most preferred controller. The result shows that PI-controller has the best performance among the other candidates, especially in maximum overshoot and settling time. It reaches 8.34 seconds in settling time and 3.71% in maximum overshoot. Despite not being the best in rising time and resembling PID-controller performances in steady-state error criteria, PI-controller remains the most preferred structure considering the closeness of the response to the desired value.

Desain dan Komparasi Kontrol Kecepatan Motor DC

2020 ◽  
Vol 7 (2) ◽  
pp. 127-134
Author(s):  
Safah Tasya Aprilyani ◽  
Irianto Irianto ◽  
Epyk Sunarno
Keyword(s):  
Steady State ◽  
Rise Time ◽  
Settling Time ◽  
Proportional Integral

Penggunaan kontrol sangat diperlukan dalam pengaturan kecepatan motor DC. Dalam pengaturan kecepatan motor DC, salah satu jenis kontrol yang digunakan adalah kontrol Proportional Integral (PI). Untuk 4 jenis metode pada kontrol PI yang digunakan adalah metode Ziegler Nichole, Chien Servo 1, Chien Regulator 1 dan perhitungan secara analitik yang telah diperoleh dari data yang sudah ada.  Namun kontrol dengan PI 4 metode yang digunakan  sebagai pembanding memiliki waktu respon kecepatan saat stabil cenderung lambat baik dari nilai settling time, rise time dan steady state. Maka dari itu dilakukan komparasi antara 4 metode kontrol PI dengan penggunaan kontrol fuzzy. Dalam membandingkan antara 4 metode kontrol PI dan kontrol fuzzy terdapat beberapa parameter sebagai perbandingan yaitu maximum overshoot, steady state, rise time dan settling time. Hasil dari perbandingan tersebut adalah kontrol fuzzy dapat menghasilkan performa lebih baik jika dibandingkan dengan 4 metode pada kontrol PI. Kontrol fuzzy memiliki nilai rise time sebesar 0,015 detik, nilai settling time sebesar 0,025 detik dengan kecepatan sebesar 2900 rpm serta error steady state sebesar 3,33% tanpa adanya overshoot dan osilasi.

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.

scholarly journals On the Contribution of Wind Farms in Automatic Generation Control: Review and New Control Approach

2018 ◽  
Vol 8 (10) ◽  
pp. 1848 ◽  
Author(s):  
Arman Oshnoei ◽  
Rahmat Khezri ◽  
SM Muyeen ◽  
Frede Blaabjerg
Keyword(s):  
Power System ◽  
Wind Turbine ◽  
Frequency Control ◽  
Wind Farms ◽  
Automatic Generation ◽  
Load Frequency Control ◽  
Automatic Generation Control ◽  
Frequency Regulation ◽  
Proportional Integral ◽  
Generation Control

Wind farms can contribute to ancillary services to the power system, by advancing and adopting new control techniques in existing, and also in new, wind turbine generator systems. One of the most important aspects of ancillary service related to wind farms is frequency regulation, which is partitioned into inertial response, primary control, and supplementary control or automatic generation control (AGC). The contribution of wind farms for the first two is well addressed in literature; however, the AGC and its associated controls require more attention. In this paper, in the first step, the contribution of wind farms in supplementary/load frequency control of AGC is overviewed. As second step, a fractional order proportional-integral-differential (FOPID) controller is proposed to control the governor speed of wind turbine to contribute to the AGC. The performance of FOPID controller is compared with classic proportional-integral-differential (PID) controller, to demonstrate the efficacy of the proposed control method in the frequency regulation of a two-area power system. Furthermore, the effect of penetration level of wind farms on the load frequency control is analyzed.

scholarly journals Load Frequency Control in a Multi-Area Deregulated Power System with BBBC-based Discrete Fractional Order Control Scheme

2020 ◽  
Vol 15 ◽  
Keyword(s):  
Power System ◽  
Frequency Control ◽  
Big Bang ◽  
Load Frequency Control ◽  
Frequency Error ◽  
Area Control Error ◽  
Load Frequency ◽  
Deregulated Power System ◽  
Control Scheme ◽  
Big Crunch

Load frequency control (LFC) for multi-area restructured power system using discrete controlscheme has been suggested in this paper. The proposed LFC scheme utilizes synchronously measured dataof frequency and tie-line power to calculate area control error (ACE). A discrete non-integer proportionalintegral derivative controller (D-FOPID) has been used to derive frequency error to zero. Two-area thermaland four-area hydro thermal deregulated power system has been used to investigate various LFC issues. Theoptimal factors of D-FOPID have been obtained using big bang big crunch (BBBC) algorithm. The systemresults under MATLAB/Simulink validate that D-FOPID effectively work under different types of contractscenarios. D-FOPID performance has also been compared to discrete proportional integral derivativecontroller (D-PID). Further the compliance with control standards of North American electric reliabilitycouncil (NERC) has also been ensured for both the controller.

Dynamic Tuning of the Controller Parameters in a Two-Area Multi-Source Power System for Optimal Load Frequency Control Performance

2020 ◽  
Vol 51 ◽  
pp. 111-129
Author(s):  
Peter Anuoluwapo Gbadega ◽  
Akshay Kumar Saha
Keyword(s):  
Fuzzy Logic ◽  
Power System ◽  
Frequency Control ◽  
Load Frequency Control ◽  
Pid Controllers ◽  
Control Performance ◽  
Source Power ◽  
Dynamic Tuning ◽  
Load Frequency ◽  
Tie Line

Frequency control is becoming increasingly critical today due to the growing size and changing structure of complex interconnected power networks. Scaling up economic pressures for efficiency and reliability of the power system has necessitated a requirement for maintaining system frequency, and tie-line power flows as close as possible to scheduled values. High-frequency deviations may degrade load performance, damage equipment, resulting in overloading of transmission lines, which may interfere with system protection schemes, and, finally, may also result in an unstable condition of the power system. More so, Load Frequency Control ( LFC) plays a vital role in the modern power system as an auxiliary service to support power exchanges and, at the same time, to provide better conditions for the trading of electricity. Therefore, the tuning of the dynamic controller (i.e., net frequency and net power interchange errors) is a significant factor in achieving optimum LFC performance. Appropriate tuning of the controller parameters is required in order to achieve excellent control action. In view of this, this paper introduces the dynamic tuning of controller parameters in a two-area multi-source power system with an AC-DC parallel tie line for optimum load-frequency control performance. Matlab/Simulink software is used to realize the system simulation. System dynamic performance is observed for conventional PID tuning by the Ziegler Nichols method and the Kitamori method, fuzzy logic controllers, fuzzy-logic PID controllers, fuzzy PID controllers, and polar-Fuzzy controllers. Furthermore, the frequency and tie-line power response of the interconnected areas were compared based on the setting-time, peak-overshoot, and peak-undershoot. The simulation results show that the responses of the fuzzy-based controllers are faster than those of the classical controllers, resulting in minimized frequency and tie-line power deviations.

scholarly journals Genetic algorithm tuned IP controller for Load Frequency Control of interconnected power systems with HVDC links

2014 ◽  
Vol 63 (2) ◽  
pp. 161-175 ◽  
Author(s):  
S. Selvakumaran ◽  
V. Rajasekaran ◽  
R. Karthigaivel
Keyword(s):  
Genetic Algorithm ◽  
Power Systems ◽  
Power System ◽  
Frequency Control ◽  
Settling Time ◽  
Load Frequency Control ◽  
Line System ◽  
Load Frequency ◽  
Interconnected Power Systems ◽  
Tie Line

Abstract A new design of decentralized Load Frequency Controller for interconnected thermal non-reheat power systems with AC-DC parallel tie-lines based on Genetic Algorithm (GA) tuned Integral and Proportional (IP) controller is proposed in this paper. A HVDC link is connected in parallel with an existing AC tie-line to stabilize the frequency oscillations of the AC tie-line system. Any optimum controller selected for load frequency control of interconnected power systems should not only stabilize the power system but also reduce the system frequency and tie line power oscillations and settling time of the output responses. In practice Load Frequency Control (LFC) systems use simple Proportional Integral (PI) or Integral (I) controller. The controller parameters are usually tuned based on classical or trial-and-error approaches. But they are incapable of obtaining good dynamic performance for various load change scenarios in multi-area power system. For this reason, in this paper GA tuned IP controller is used. A two area interconnected thermal non-reheat power system is considered to demonstrate the validity of the proposed controller. The simulation results show that the proposed controller provides better dynamic responses with minimal frequency and tie-line power deviations, quick settling time and guarantees closed-loop stability margin.

scholarly journals PERBANDINGAN PENGENDALI PI, PD DAN PID PADA PENGENDALIAN KECEPATAN MOTOR INDUKSI TIGA FASA DENGAN MEMANFAATKAN SUPERVISORY CONTROL AND DATA ACQUISITION (SCADA)

2019 ◽  
Vol 3 (2) ◽  
pp. 276
Author(s):  
Sariman Sariman ◽  
Manlahima Padarid ◽  
Dindi Hamamie Mahfie ◽  
Bhakti Yudho Suprapto
Keyword(s):  
Steady State ◽  
Data Acquisition ◽  
Supervisory Control ◽  
Settling Time ◽  
Proportional Integral Derivative ◽  
Proportional Integral

Motor Induksi tiga fasa merupakan salah satu jenis motor yang paling banyak digunakan pada industri. Motor ini biasanya yang menjadi perhatian khusus adalah pengendalian kecepatan. Pengendali yang digunakan biasanya hanya pengendali Proportional Integral Derivative (PID). Namun terkadang pada proses kontrol, pengendali lain seperti Proportional Integral (PI) dan Proportional Derivative (PD) juga sering digunakan. Penelitian ini akan membandingkan pengendali-pengendali tersebut dalam proses pengendalian kecepatan pada motor induksi tiga fasa saat berbeban dan tanpa beban. Untuk memudahkan proses pengendaliannya, digunakan Supervisory Control and Data Acquisition (SCADA) yang memiliki kemampuan dalam mengakuisisi data dan monitoring. Dalam pengujiannya didapatkan bahwa pada pengendali terbaik yakni PID dimana error steady state kecil, settling time cepat dan tetap stabil meskipun terdapat perubahan beban.  Pengendali PID ini memiliki parameter KP  = 2,  Ti = 1, Td =3. Sedangkan data yang ditampilkan oleh sistem SCADA dapat dikatakan baik dan valid, dimana persentase penyimpangan untuk data kecepatan sebesar 0,1%.

scholarly journals Meningkatkan kinerja motor induksi menggunakan teknologi fuzzy logic controller berbasis artificial intelligence

2021 ◽  
Vol 2 (2) ◽  
pp. 40-47
Author(s):  
I Putu Sutawinaya ◽  
◽  
Anak Agung Ngurah Made Narottama ◽  
Keyword(s):  
Artificial Intelligence ◽  
Fuzzy Logic ◽  
Steady State ◽  
Fuzzy Logic Controller ◽  
Settling Time ◽  
Peak Time ◽  
State Error

Motor induksi adalah merupakan motor listrik arus bolak balik (AC) yang umum digunakan pada industri-industri karena memiliki beberapa keuntungan, diantaranya relatif murah, kokoh serta handal. Namun kelemahan motor induksi saat terjadi perubahan torsi beban secara mendadak, maka akan terjadi penurunan kinerja (performansi) motor. Hal tersebut akan berpengaruh terhadap kestabilan putaran motor, di mana overshoot maupun undershoot relatif tinggi serta risetime relatif lambat. Untuk mengantispasi hal tersebut dibutuhkan sistem kontrol kecepatan motor induksi yang tentunya dapat meningkatkan kinerja motor induksi tersebut. Dalam penelitian ini dilakukan pengujian terhadap sistem kontrol kecepatan motor induksi menggunakan teknologi Fuzzy Logic Controller (FLC) melalui simulasi perangkat lunak Matlab. Dilakukan pengujian terhadap perubahan kinerja motor induksi melalui pemberian torsi beban serta setpoint yang berubah-ubah. Adapun hasil simulasi menunjukan bahwa performansi motor induksi, seperti undershoot, overshoot dan steady state error relatif kecil serta peak time, risetime dan settling time relatif cepat. Sistem yang dirancang mampu menurunkan arus start rata-rata sekitar 72,7% dan torsi awal rata-rata sekitar 81,8% terhadap kondisi idealnya.

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