Self-adaptive fuzzy-PID controller for AGC study in deregulated Power System

The aim of this paper elucidates the AGC issues in a large scale interconnected power system incorporating HVDC link under the deregulated environment. The performance of the system is degraded under the influence of abrupt load change, and parameter variation. To perceive a reliable and quality power supply, secondary robust controllers are essential. A novel self-adaptive Fuzzy-PID controller is proposed to ameliorate the dynamic performance of both the conventional PID and Fuzzy-PID controller, employed in the restructured power system. In self-adaptive Fuzzy-PID controller unlike the Fuzzy-PID controller, the output scaling factors are tuned dynamically while the controller is functioning. These three controllers are designed by enumerating different gains and scaling factors, applying a budding nature-inspired algorithm known as Wild Goat Algorithm (WGA). The superior dynamic performance of frequency and tie-line power deviation under self-adaptive Fuzzy-PID controller in comparison to its' counterparts is investigated by dispatching the scheduled and unscheduled power under different contracts such as poolco based transaction, bilateral transaction and contract violation based transaction through different tie-lines. The dynamic response under parameter variation and random load perturbation confers the robustness of the proposed controller

Chaotic multi-objective optimization based design of fractional order PI{\lambda}D{\mu} controller in AVR system

In this paper, a fractional order (FO) PI{\lambda}D\mu controller is designed to take care of various contradictory objective functions for an Automatic Voltage Regulator (AVR) system. An improved evolutionary Non-dominated Sorting Genetic Algorithm II (NSGA II), which is augmented with a chaotic map for greater effectiveness, is used for the multi-objective optimization problem. The Pareto fronts showing the trade-off between different design criteria are obtained for the PI{\lambda}D\mu and PID controller. A comparative analysis is done with respect to the standard PID controller to demonstrate the merits and demerits of the fractional order PI{\lambda}D\mu controller.Comment: 30 pages, 14 figure

Control of Thermal Power System Using Adaptive Fuzzy Logic Control

Controlling thermal power systems increases the overall system efficiency and satisfies the desired requirements. In such a large system, fuel reduction of even a small percentage leads to large energy saving. Hence, power systems are gaining significant attention from engineers and scientists. In this thesis, the uncontrolled power system for single area, two area, and three area is modelled using state space representation. Frequency deviation is simulated using MATLAB and SIMULINK. PID control is added to the system to analyze the effect of conventional control on system output response. Adaptive fuzzy logic control is added to the uncontrolled system using MATLAB Fuzzy Inference System and its effect on the system output response is measured in terms of overshoot/undershoot percentage, settling time, and steady state frequency error. Effect of adaptive fuzzy logic control is analyzed on single area, two area, and three area power system. Tie-line power exchange among areas is investigated before and after implementation of PID and adaptive fuzzy logic control. For the purpose of comparison in this thesis, a conventional PID control and an adaptive fuzzy logic control is applied to two different thermal power systems. The simulations demonstrate that adaptive fuzzy logic control is proved to be more efficient and reliable than conventional PID control in power system control problem

Optimal fuzzy-PID controller with derivative filter for load frequency control including UPFC and SMES

A newly adopted optimization technique known as sine-cosine algorithm (SCA) is suggested in this research article to tune the gains of Fuzzy-PID controller along with a derivative filter (Fuzzy-PIDF) of a hybrid interconnected system for the Load Frequency Control (LFC). The scrutinized multi-generation system considers hydro, gas and thermal sources in all areas of the dual area power system integrated with UPFC (unified power flow controller) and SMES (Super-conducting magnetic energy storage) units. The preeminence of the offered Fuzzy-PIDF controller is recognized over Fuzzy-PID controller by comparing their dynamic performance indices concerning minimum undershoot, settling time and also peak overshoot. Finally, the sensitiveness and sturdiness of the recommended control method are proved by altering the parameters of the system from their nominal values and by the implementation of random loading in the system

Selfish Herd Optimisation based fractional order cascaded controllers for AGC study

In a modern, and complex power system (PS), robust controller is obligatory to regulate the frequency under uncertain load/parameter change of the system. In addition to this, presence of nonlinearities, load frequency control (LFC) of a Power System becomes more challenging which necessitates a suitable, and robust controller. Single stage controller does not perform immensely against aforesaid changed conditions. So, a novel non-integer/fractional order (FO) based two-stage controller incorporated with 2-degrees of freedom (2-DOF), derivative filter (N), named as 2-DOF-FOPIDN-FOPDN controller, is adopted to improve the dynamic performance of a 3-area power system. Each area of the power system consists of both non-renewable and renewable generating units. Again, to support the superior performance of 2-DOF-FOPIDN-FOPDN controller, it is compared with the result produced by PID, FOPID, and 2-DOF-PIDN-PDN controllers. The optimal design of these controllers is done by applying Selfish Herd Optimisation (SHO) technique. Further, the robustness of the 2-DOF-FOPIDN-FOPDN controller is authenticated by evaluating the system performance under parameter variation. The work is further extended to prove the supremacy of SHO algorithm over a recently published article based on pathfinder algorithm (PFA)

Frequency deviations stabilizations in restructured power systems using coordinative controllers

Modern restructured power system faces excessive frequency aberrations due to the intermittent renewable generations and persistently changing load demands. An efficient and robust control strategy is obligatory to minimise deviations in the system frequency and tie-line to avoid any possible blackout. Hence, in this research, to achieve this target, automatic generation control (AGC) is utilized as a secondary controller to alleviate the changes in interconnected restructured systems at uncertainties. The objective of AGC is to quickly stabilize the deviations in frequency and tie-line power following load fluctuations. This thesis addresses the performance of AGC in two-area restructured power systems with many sophisticated control strategies in the presence of renewable and traditional power plants. As per literature of research work, there are quite a few research studies on AGC of a restructured system using optimized coordinative controllers. Besides, investigations on advanced optimized-based coordinative controller approaches are also rare to find in the literature. So, various combinations of two degrees of freedom (2DOF) controllers are utilized as supplementary controllers to diminish the frequency deviations. Nevertheless, the interconnected tie-lines are typically congested in areas with huge penetration of renewable sources, which may reduce the tie -line capability. Therefore, distinct FACTS controllers and ultra-capacitor (UC) are integrated into two-area restructured systems for strengthening the tie-line power and frequency. Further, new optimization techniques such as cuckoo search (CS), bat algorithm (BA), moth-flame optimization (MFO) are utilized in this work for investigating the suggested 2DOF controllers and compared their performance in all contracts of restructured systems. As per the simulation outcomes, the amalgamation of DPFC and UC with MFObased 2DOF PID-FOPDN shows low fluctuation rate in frequency and tie-line power. Besides, the settling times (ST) of two areas are 9.5 S for ΔF1, 8.2 S for ΔF2, and 10.15 S for ΔPtie. The robustness of the suggested controller has been verified by ±25% variations in system parameters and loading conditions

A Robust Discrete FuzzyP+FuzzyI+FuzzyD Load Frequency Controller for Multi-Source Power System in Restructuring Environment

In this paper a fuzzy logic (FL) based load frequency controller (LFC) called discrete FuzzyP+FuzzyI+FuzzyD (FP+FI+FD) is proposed to ensure the stability of a multi-source power system in restructured environment. The whale optimization algorithm (WOA) is used for optimum designing the proposed control strategy to reduce fuzzy system effort and achieve the best performance of LFC task. Further, to improve the system performance, an interline power flow controller (IPFC) and superconducting magnetic energy system (SMES) is included in the system. Governor dead band, generation rate constraint, and time delay are considered as important physical constraints to get an accurate understanding of LFC task. The performance of the optimized FP+FI+FD controller is evaluated on a two area six-unit hydro-thermal power system under different operating conditions which take place in a deregulated power market and varying system parameters in comparison with the classical fuzzy PID controller. Simulation results shows that WOA based tuned FP+FI+FD based LFC controller are relatively robust and achieve good performance for a wide change in system parameters considering system physical constraints

Komparativna analiza primjene optimalnog upravljanja za automatsko upravljanje sustavima za proizvodnju električne energije

In this study, an attempt is made to present the application and comparative performance analysis of optimal control approach for automatic generation control (AGC) of electric power generating systems. Optimal controller is designed utilizing performance index minimization criterion. To conduct the study, various single and multi-area models with/without system nonlinearities from the literature are simulated under sudden load perturbation. In this comparative study, to corroborate the worth of optimal controller, the performance of optimal AGC controller is compared with that of I/PI controller optimized adopting recently published the best established techniques such as teacher learning based optimization (TLBO), differential evolution (DE), genetic algorithm (GA), particle swarm optimization (PSO), hybrid bacteria foraging optimization algorithm-PSO (hBFOA-PSO), craziness based PSO (CBPSO), firefly algorithm (FA), krill herd algorithm (KHA), moth-flame optimization (MFO), glow swarm optimization (GSO), simulated annealing (SA), bat algorithm (BA), stochastic fractal search (SFS) and hybrid SFS-local unimodal sampling (hSFS-LUS) technique. The simulated results are compared in terms of settling time (ST), peak undershoot (PU)/overshoot (PO), various performance indices (PIs), minimum damping ratio and system eigenvalues. A sensitivity study is conducted to certify the robustness of optimal controller.U ovom radu se razmatra primjena i komparativna analiza sustava za automatsko planiranje proizvodnje proizvođača električne energije. Sinteza optimalnog regulatora proporcionalno-integralne strukture je provedena korištenjem integralnih kriterija. Različiti modeli s jednim područjem i više područja te s i bez nelinearnosti korišteni su u simulaciji nagle promjena opterećenja. Kako bi se pokazala važnost optimalnog regulatora, u komparativnoj analizi su performanse dizajniranog optimalnog regulatora uspoređene s peformansama postignutim korištenjem I i PI regulatora sintetiziranih primjenom postojećih uobičajeno korištenih metoda kao što su "teacher learning optimization", diferencijska evolucija, genetski algoritam, optimizacija rojem čestica, "hybrid bacteria foraging" optimizacijski algoritam, "craziness based" optimizacija rojem čestica, "firefly" algoritam, "krill herd" algoritam, "moth-flame" optimizacija, "glow swarm" optimizacija, metoda simuliranog kaljenja, "bat" algoritam, stohastično fraktalno traženje (eng. "stochastic fractal search", SFS) i metoda hibridnog SFS lokalnog unimodalnog uzorkovanja. Performanse primijenjenih algoritama upravljanja vrednovani su usporedbom ostvarenih vremena ustaljivanja, iznosa podbačaja i prebačaja te drugih pokazatelja performansi, minimalnih relativnih koeficijentima prigušenja i svojstvenih vrijednosti sustava upravljanja. Provedena analiza osjetljivosti potvrđuje robusnost parametara optimalnog regulatora za širok raspon radnih točaka i parametara sustava

On the contribution of wind farms in automatic generation control: Review and new control approach

© 2018 by the authors. 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

Multi Area Load Frequency Control Using Particle Swarm Optimization and Fuzzy Rules

AbstractThis paper present heuristics based study of multi area power network. Heuristic procedures involving Particle Swarm Intelligence and Fuzzy based inferences have been employed to effectively obtain the optimized gains of PID controller. Any change in the load demand causes generator's shaft speed lower than the pre-set value and the system frequency deviates from the standard value results in malfunctioning of frequency relays. A five area load frequency model is constructed in Matlab/simulink by implementing the PID (Proportional, Integral and Differential) controllers to control the frequency deviations. The effect of interconnection of multi area power system as ring connection has been discussed. Simulations performed show the effectiveness of the current approach over simple fuzzy inferences in terms of performance as well as execution efficiency