Critical Aspects of AGC Emerging from Optimal Control to Machine Learning Techniques

With the emphasis towards renewable energy lot more advancement has been done in the field of electric energy system and it is expected that future energy system may have wind power dominating control areas or hydro power be it bulk hydro or micro hydro based power generations in order to cater the rising energy demands of the modern society. Hence, automatic generation control (AGC) plays a crucial role in the modern electrical energy system in order to maintain the frequency standards to nominal value besides maintaining the power interchange between the interconnected controls areas in order to distribute value and cost effective power. This paper presents the literature survey related to some of the critical aspects of AGC such as diverse sources power generations, hydro dominating control areas, wind power based power generations and applications of flexible alternating current transmission system (FACTS) in AGC. This paper also discusses the novel control designs based on the concept of optimal control, output vector feedback, model predictive control, robust control and finally the machine learning based AGC designs are explored and the critical gaps among the available research work are well presented and discussed

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)

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

A Three Area Interconnected Power System Network Load Frequency Controller Simulator

This paper presents a MATLAB simulator of a three area interconnected power system of Thermal-Gas-Hydro. Nonlinearities intrinsic in the interconnected power system of communication delay, Generation Rate Constraint and Generation Dead Band were measured. Bat Inspired Algorithm was exploited to select the favourable parameters of the Model Predictive Controller and the Super Conducting Magnetic Energy Storage. Model Predictive Controller was the subordinate controller employed to minimalize the Area Control Error, Super Conducting Magnetic Energy Storage was the energy buffer to balance the load demand and the power generated. Integral Time Absolute Error was the performance metrics employed to minimize the Area Control Error. Parametric dissimilarity was tested on the inter-connected power system to observe the efficacy of the controller. Step load perturbation of  was concurrently applied to the three-area inter-connected network,  was introduced to the thermal generating unit,  was introduced to the gas and hydro generating unit.  Value of the tie-line was introduced to examine its effect on the frequency deviation. The results performed better when compared with Model Predictive Controller joined with Super Conducting Magnetic Energy Storage against the Model Predictive Controller without Super Conducting Magnetic Energy Storage in relations to settling time, overshoot and undershoot

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

Review on load frequency control for power system stability

Power system stability is the capability of power systems to maintain load magnitude within specified limits under steady state conditions in electrical power transmission. In modern days, the electrical power systems have grown in terms of complexity due to increasing interconnected power line exchange. For that, an inherent of controllers were essential to correct the deviation in the presence of external disturbances. This paper hence aims to review the basic concepts of power system stability in load frequency control. Various control techniques were analyzed and presented. Power system stability can be classified in terms of method to improve power system stability, which are rotor angle stability, frequency stability and voltage stability. It is found that each method has different purpose and focus on solving different types of problem occurred. It is hoped that this study can contribute to clarify the different types of power system stability in terms of where it occurs, and which is the best method based on different situation

Automatic Generation Control by Hybrid Invasive Weed Optimization and Pattern Search Tuned 2-DOF PID Controller

A hybrid invasive weed optimization and pattern search (hIWO-PS) technique is proposed in this paper to design 2 degree of freedom proportionalintegral- derivative (2-DOF-PID) controllers for automatic generation control (AGC) of interconnected power systems. Firstly, the proposed approach is tested in an interconnected two-area thermal power system and the advantage of the proposed approach has been established by comparing the results with recently published methods like conventional Ziegler Nichols (ZN), differential evolution (DE), bacteria foraging optimization algorithm (BFOA), genetic algorithm (GA), particle swarm optimization (PSO), hybrid BFOA-PSO, hybrid PSO-PS and non-dominated shorting GA-II (NSGA-II) based controllers for the identical interconnected power system. Further, sensitivity investigation is executed to demonstrate the robustness of the proposed approach by changing the parameters of the system, operating loading conditions, locations as well as size of the disturbance. Additionally, the methodology is applied to a three area hydro thermal interconnected system with appropriate generation rate constraints (GRC). The superiority of the presented methodology is demonstrated by presenting comparative results of adaptive neuro fuzzy inference system (ANFIS), hybrid hBFOA-PSO as well as hybrid hPSO-PS based controllers for the identical system

Performance Enhancement of Automatic Generation Control by Developing a Detailed Load Frequency Control Model and an Adaptive Performance Index Criterion

The imbalance between electrical loads and power supplied by the system generators causes the frequency deviations in a power system. Maintaining the frequency close to its nominal value as well as in its allowed deviation range is the first objective of the automatic generation control (AGC). Nowadays, in interconnected power systems, several control areas are connected to each other by tie-lines and power is transferred between control areas based on a specific schedule. The second objective of automatic generation control is to keep the tie-lines power flow close to their secluded values.;An accurate and realistic load frequency control (LFC) model is very essential to have an effective and adaptive AGC strategy. The first objective of this thesis is to present the importance of considering communication delay in LFC model missing in most of the studies investigating AGC and its performance using different methods and optimization techniques. The second objective of this thesis is to present a comprehensive LFC model, which contains all of the physical constraints such as governor dead-band, generation rate and delay of communication links. The third objective is to evaluate different controllers and performance index criteria used in conventional AGC. Finally, the last objective is to introduce an adaptive performance index criterion cable of defining settling time and overshoot which cannot be applied by other performance index criteria.;Different optimization methods have been used to optimize the performance of AGC such as genetic algorithm, fuzzy logic and neural networks. Genetic algorithm has been used widely in LFC studies so it is chosen to be employed in this study to optimize the performance of controllers in the utilized AGC scheme. Integrator controller is the most common controller employed in LFC studies because of its design simplicity, however, in this thesis proportional-integral-derivative (PID) controller is employed to obtain the best performance.;This study shows that without a precise and detailed LFC model, results of different techniques or strategies used in AGC will not be accurate and practical even when they are derived by optimization methods. Moreover, it is shown that PID controller has the best performance in comparison with other controllers used in LFC studies when physical constraints are not considered in the LFC model. Furthermore, a robust GA based control system is designed considering all of physical constraints for a three-area power system and the simulation results show that it can track the load change and restore the frequency of all control areas to the nominal value effectively. Different performance index criteria are evaluated and results show that in specific cases they cannot be completely accurate or reliable to assess the performance of AGC schemes. Finally, an effective and adaptive performance index is introduced and simulation results validate its effectiveness and reliability

Review On Load Frequency Control For Power System Stability

Power system stability is the capability of power systems to maintain load magnitude within specified limits under steady state conditions in electrical power transmission. In modern days, the electrical power systems have grown in terms of complexity due to increasing interconnected power line exchange. For that, an inherent of controllers were essential to correct the deviation in the presence of external disturbances. This paper hence aims to review the basic concepts of power system stability in load frequency control. Various control techniques were analyzed and presented. Power system stability can be classified in terms of method to improve power system stability, which are rotor angle stability, frequency stability and voltage stability. It is found that each method has different purpose and focus on solving different types of problem occurred. It is hoped that this study can contribute to clarify the different types of power system stability in terms of where it occurs, and which is the best method based on different situation

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