A novel hybrid many optimizing liaisons gravitational search algorithm approach for AGC of power systems

A hybrid Many Optimizing Liaisons Gravitational Search Algorithm (hMOL-GSA)-based fuzzy PID controller is proposed in this work for Automatic Generation Control problem. MOL is a simplified version of particle swarm optimization which ignores the particle best position consequently simplifying the algorithm. The proposed method is employed to tune the fuzzy PID parameters. The outcomes are equated with some newly proposed methods like Artificial Bee Colony (ABC)-based PID for the identical test systems to validate the supremacy of GSA and proposed hMOL-GSA techniques. Further, the design task has been carried out in a three-area test system and the outcomes are equated with newly proposed Firefly Algorithm (FA) optimized PID and Teaching Learning-Based Optimization (TLBO) tuned PIDD controller for the identical system. Better system response has been observed with proposed hMOL-GSA method. Finally, sensitivity study is being carried out and robustness of the proposed method is established

Automatic Generation Control of Multi-Area Power System Using Multi-Objective Non-Dominated Sorting Genetic Algorithm-II.

a b s t r a c t Controllers design problems are multi objective optimization problems as the controller must satisfy several performance measures that are often conflicting and competing with each other. In multi-objective approach a set of solutions can be generated from which the designer can select a final solution according to his requirement and need. This paper presents the design and analysis Proportional Integral (PI) and Proportional Integral Derivative (PID) controller employing multi-objective Non-Dominated Shorting Genetic Algorithm-II (NSGA-II) technique for Automatic Generation Control (AGC) of an interconnected system. To minimize the effect of noise in the input signal, a filter is employed with the derivative term. Integral Time multiply Absolute Error (ITAE), minimum damping ratio of dominant eigenvalues and settling times in frequency and tie-line power deviations are considered as multiple objectives and NSGA-II is employed to generate Pareto optimal set. Further, a fuzzy-based membership value assignment method is employed to choose the best compromise solution from the obtained Pareto solution set. The proposed approach is first applied to a linear two-area power system model and then extended to a non-linear power system model by considering the effect of governor dead band non-linearity. The superiority of the proposed NSGA-II optimized PI/PID controllers has been shown by comparing the results with some recently published modern heuristic optimization approaches such as Bacteria Foraging Optimization Algorithm (BFOA), Genetic Algorithm (GA) and Craziness based Particle Swarm Optimization (CPSO) based controllers for the similar interconnected power systems

Application of Search Group Algorithm for Automatic Generation Control of Multi-area Multi-source Power Systems

This paper proposes a new Search Group Algorithm based PID controller, to deal with Automatic Generation Control of two-area with six unit power system. The supremacy of SGA tuned PID controller is being shown using the comparative study with Firefly Algorithm (FA) optimization method for the same test system using ITAE as an objective function. It has been demonstrated that SGA tuned PID controller improves the performance in a large compared with FA tuned PID controller. Furthermore variation in nominal values of operating load condition and system parameters with the position of step load perturbation is being carried out to achieve sensitivity analysis. From the result of sensitivity analysis it clearly depicts the robustness of the suggested method (SGA with PID controller) for two-area with six unit power system in AGC. Finally for better investigation, the proposed method is also examined by applying randomization in step load

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

Mast Cell Tumour in a Dog and Its Surgical Management

Abstract An 8-year-old male Labrador dog was presented with a history of inappetence, occasional bloody diarrhoea and two ulcerated pea-nut sized swelling in the groin region. On the basis of complete blood cell count and cytological examination of the tumour aspirate it was diagnosed as a case of mast cell tumour. Under general anaesthesia the tumour nodules were excised and three doses of vincrystine sulphate were given at recommended dose with dextrose normal saline. Post-operatively antibiotics, analgesics and supportive therapy were followed and the dog recovered well without any recurrence

Procjena prijelazne stabilnosti dvopodručnog energetskog sustava s CSC-STATCOM-om zasnovanom na LQR-u

A current source converter (CSC) based static synchronous compensator (STATCOM) is a shunt flexible AC transmission system (FACTS) device, which has a vital role as a stability support for small and large transient instability in an interconnected power network. A robust linear quadratic regulator (LQR) based controller for CSC-STATCOM is proposed. In this paper, LQR based CSC-STATCOM is designed to enhance the transient stability of two-area two-machine power system. First of all, modeling & LQR based controller design for CSC-STATCOM are described. After that, the impact of the proposed scheme on the test system with different disturbances is demonstrated. The feasibility of the proposed scheme is demonstrated through simulation in MATLAB and the simulation results show an improvement in the transient stability of power system with CSC-STATCOM. Also, the robustness and effectiveness of CSC-STATCOM are better rather than other shunt FACTS devices (SVC & VSC-STATCOM) in this paper.Statički sinkroni kompenzator (STATCOM) zasnovan na pretvaraču strujnog izvora (CSC) je uređaj za izmjenični prijenos s fleksibilnim "shuntom" (FACTS), koji značajno doprinosi stabilnosti malih i srednjih prijelaznih nestabilnosti u međusobno povezanoj energetskoj mreži. Ovdje je predložen robusni sustav upravljanja zasnovan na linearnom kvadratičnom regulatoru (LQR) za CSC-STATCOM. U ovom radu, CSC-STATCOM zasnovan na LQR-u dizajniran je za povećanje stabilnosti dvopodručnog energetskog sustava s dva motora. Prvo su opisani postupak modeliranja te upravljački sustav zasnovan na LQR-u za CSC-STATCOM. Nakon toga, prikazan je utjecaj predstavljene sheme na ispitni sustav uz prisutnost različitih poremećaja. Provedivost predstavljenog pristupa je prikazana kroz MATLAB simulacije čiji rezultati prikazuju poboljšanje u prijelaznoj stabilnosti energetskog sustava s CSC-STATCOM-om. Također, u ovom radu je prikazana veća robusnost i efikasnost CSC-STATCOM "shunt" FACTS uređaja u odnosu na SVC i VSC-STATCOM

Speed control with torque ripple reduction of switched reluctance motor by many optimizing liaison technique

This paper presents a control mechanism for speed control of switched reluctance motor (SRM) along with torque ripple minimization employing many optimizing liasion (MOL) technique. The control mechanism includes speed controller in the outer loop, current controller in the inner loop, intelligent selection of turn on and turn off angle for a 60 kW, 3-phase 6/8 SRM. It is noticed that the torque ripple coefficient, ISE of speed & current are reduced by 10.43%, 36.53%, 16.01% respectively by MOL algorithm compared to gravitational search algorithm (GSA) algorithm. It is also observed that the settling times in torque, speed and current are reduced by 42%, 45.65% and 47.91% by proposed MOL algorithm compared to the GSA algorithm. Keywords: Switch reluctance motor (SRM), Proportional integral (PI) controller, Torque ripple, Many optimizing liaison (MOL), Gravitational search algorithm (GSA

Speed control with torque ripple reduction of switched reluctance motor by Hybrid Many Optimizing Liaison Gravitational Search technique

This paper presents a control scheme for simultaneous control of the speed of Switched Reluctance Motor (SRM) and minimizing the torque ripple employing Hybrid Many Optimizing Liaison Gravitational Search Algorithm (Hybrid MOLGSA) technique. The control mechanism includes two controlling loops, the outer loop is governed for speed control and a current controller for the inner loop, intelligent selection of turn on and turn off angle for a 60 KW, 3-phase 6/8 SRM. It is noticed that the torque ripple coefficient, ISE of speed & current are reduced by 12.81%, 38.60%, 16.74% respectively by Hybrid MOLGSA algorithm compared to Gravitational Search Algorithm (GSA) algorithm. It is also observed that the settling times for the controller using the parameter values for obtaining best values of torque ripple, Integral square error of speed and current are reduced by 51.25%, 58.04% and 59.375% by proposed Hybrid MOLGSA algorithm compared to the GSA algorithm

Application of many optimizing liaisons technique for speed control with torque ripple minimization of switched reluctance motor

A comparison in the performance of Many Optimizing Liaisons (MOL) and Gravitational Search Algorithm (GSA) techniques are utilised in the present work for speed control with torque ripple minimization of Switched Reluctance Motor (SRM). The control mechanism consists of  two control loop (PI controller) and  turn on/ turn off angle control of the 75 KW, 4-phase 8/6 SRM. The problem considered here is to obtain the operating parameter of speed controller, current controller and turn on/ turn off angle is regarded as multi objective problem for optimization with the goal of reducing torque ripple and integral square error of speed. The simulation and analysis  is executed in MATLAB/SIMULINK environment. The execution evaluation of MOL and GSA is done by evaluating different statistical parameter. It is noticed that the torque ripple coefficient, ISE of speed & current are significantly reduced by MOL approach