Advanced and Innovative Optimization Techniques in Controllers: A Comprehensive Review

New commercial power electronic controllers come to the market almost every day to help improve electronic circuit and system performance and efficiency. In DC–DC switching-mode converters, a simple and elegant hysteretic controller is used to regulate the basic buck, boost and buck–boost converters under slightly different configurations. In AC–DC converters, the input current shaping for power factor correction posts a constraint. But, several brilliant commercial controllers are demonstrated for boost and fly back converters to achieve almost perfect power factor correction. In this paper a comprehensive review of the various advanced optimization techniques used in power electronic controllers is presented

Load frequency controllers considering renewable energy integration in power system

Abstract: Load frequency control or automatic generation control is one of the main operations that take place daily in a modern power system. The objectives of load frequency control are to maintain power balance between interconnected areas and to control the power flow in the tie-lines. Electric power cannot be stored in large quantity that is why its production must be equal to the consumption in each time. This equation constitutes the key for a good management of any power system and introduces the need of more controllers when taking into account the integration of renewable energy sources into the traditional power system. There are many controllers presented in the literature and this work reviews the traditional load frequency controllers and those, which combined the traditional controller and artificial intelligence algorithms for controlling the load frequency

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

Load Frequency Control (LFC) Strategies in Renewable Energy‐Based Hybrid Power Systems:A Review

The hybrid power system is a combination of renewable energy power plants and conventional energy power plants. This integration causes power quality issues including poor settling times and higher transient contents. The main issue of such interconnection is the frequency variations caused in the hybrid power system. Load Frequency Controller (LFC) design ensures the reliable and efficient operation of the power system. The main function of LFC is to maintain the system frequency within safe limits, hence keeping power at a specific range. An LFC should be supported with modern and intelligent control structures for providing the adequate power to the system. This paper presents a comprehensive review of several LFC structures in a diverse configuration of a power system. First of all, an overview of a renewable energy-based power system is provided with a need for the development of LFC. The basic operation was studied in single-area, multi-area and multi-stage power system configurations. Types of controllers developed on different techniques studied with an overview of different control techniques were utilized. The comparative analysis of various controllers and strategies was performed graphically. The future scope of work provided lists the potential areas for conducting further research. Finally, the paper concludes by emphasizing the need for better LFC design in complex power system environments

Small-signal stability analysis of hybrid power system with quasi-oppositional sine cosine algorithm optimized fractional order PID controller

This article deals with the frequency instability problem of a hybrid energy power system (HEPS) coordinated with reheat thermal power plant. A stochastic optimization method called a sine-cosine algorithm (SCA) is, initially, applied for optimum tuning of fractional-order proportional-integral-derivative (FOPI-D) controller gains to balance the power generation and load profile. To accelerate the convergence mobility and escape the solutions from the local optimal level, quasi-oppositional based learning (Q-OBL) is integrated with SCA, which results in QOSCA. In this work, the PID-controller's derivative term is placed in the feedback path to avoid the set-point kick problem. A comparative assessment of the energy-storing devices is shown for analyzing the performances of the same in HEPS. The qualitative and quantitative evaluation of the results shows the best performance with the proposed QOSCA: FOPI-D controller compared to SCA-, grey wolf optimizer (GWO), and hyper-spherical search (HSS) optimized FOPI-D controller. It is also seen from the results that the proposed QOSCA: FOPI-D controller has satisfactory disturbance rejection ability and shows robust performance against parametric uncertainties and random load perturbation. The efficacy of the designed controller is confirmed by considering generation rate constraint, governor dead-band, and boiler dynamics effects

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

Parallel distribution compensation PID based on Takagi-Sugeno fuzzy model applied on egyptian load frequency control

This paper presents a new technique for a Takagi-Sugeno (TS) fuzzy parallels distribution compensation-PID'S (TSF-PDC-PID'S) to improve the performance of Egyptian load frequency control (ELFC). In this technique, the inputs to a TS Fuzzy model are the parameters of the change of operating points. The TS Fuzzy model can definite the suitable PID control for a certain operating point. The parameters of PID'S controllers are obtained by ant colony optimization (ACO) technique in each operating point based on an effective cost function. The system controlled by the proposed TSF-PDC-PID’S is investigated under different types of disturbances, uncertainty and parameters variations. The simulation results ensure that the TSF-PDC-PID'S can update the suitable PID controller at several operating points so, it has a good dynamic response under many types of disturbances compared to fixed Optimal PID controller

Design of Multivariate PID Controller for Power Networks Using GEA and PSO

The issue of proper modeling and control for industrial systems is one of the challenging issues in the industry. In addition, in recent years, PID controller design for linear systems has been widely considered. The topic discussed in some of the articles is mostly speed control in the field of electric machines, where various algorithms have been used to optimize the considered controller, and always one of the most important challenges in this field is designing a controller with a high degree of freedom. In these researches, the focus is more on searching for an algorithm with more optimal results than others in order to estimate the parameters in a more appropriate way. There are many techniques for designing a PID controller. Among these methods, meta-innovative methods have been widely studied. In addition, the effectiveness of these methods in controlling systems has been proven. In this paper, a new method for grid control is discussed. In this method, the PID controller is used to control the power systems, which can be controlled more effectively, so that this controller has four parameters, and to determine these parameters, the optimization method and evolutionary algorithms of genetics (EGA) and PSO are used.  One of the most important advantages of these algorithms is their high speed and accuracy. In this article, these algorithms have been tested on a single-machine system, so that the single-machine system model is presented first, then the PID controller components will be examined. In the following, according to the transformation function matrix and the relative gain matrix, suitable inputs for each of the outputs are determined. At the end, an algorithm for designing PID controller for multivariable MIMO systems is presented. To show the effectiveness of the proposed controller, a simulation was performed in the MATLAB environment and the results of the simulations show the effectiveness of the proposed controller

Control Theory in Engineering

The subject matter of this book ranges from new control design methods to control theory applications in electrical and mechanical engineering and computers. The book covers certain aspects of control theory, including new methodologies, techniques, and applications. It promotes control theory in practical applications of these engineering domains and shows the way to disseminate researchers’ contributions in the field. This project presents applications that improve the properties and performance of control systems in analysis and design using a higher technical level of scientific attainment. The authors have included worked examples and case studies resulting from their research in the field. Readers will benefit from new solutions and answers to questions related to the emerging realm of control theory in engineering applications and its implementation