A novel hybrid PSO-PS optimized fuzzy PI controller for AGC in multi area interconnected power systems

In this paper, a novel hybrid Particle Swarm Optimization (PSO) and Pattern Search (PS) optimized fuzzy PI controller is proposed for Automatic Generation Control (AGC) of multi area power systems. Initially a two area non-reheat thermal system is used and the gains of the fuzzy PI controller are optimized employing a hybrid PSO and PS (hPSO-PS) optimization technique. The superiority of the proposed fuzzy PI controller has been shown by comparing the results with Bacteria Foraging Optimization Algorithm (BFOA), Genetic Algorithm (GA), conventional Ziegler Nichols (ZN), Differential Evolution (DE) and hybrid BFOA and PSO based PI controllers for the same interconnected power system. Additionally, the proposed approach is further extended to multi source multi area hydro thermal power system with/without HVDC link. The superiority of the proposed approach is shown by comparing the results with some recently published approaches such as ZN tuned PI, Variable Structure System (VSS) based ZN tuned PI, GA tuned PI, VSS based GA tuned PI, Fuzzy Gain Scheduling (FGS) and VSS based FGS for the identical power systems. Further, sensitivity analysis is carried out which demonstrates the ability of the proposed approach to wide changes in system parameters, size and position of step load perturbation The proposed approach is also extended to a non-linear power system model by considering the effect of governor dead band non-linearity and the superiority of the proposed approach is shown by comparing the results of hybrid BFO-PSO and craziness based PSO approach for the identical interconnected power system. Finally, the study is extended to a three area system considering both thermal and hydro units with different controllers in each area and the results are compared with hybrid BFO-PSO and ANFIS approaches.     

Load frequency control using Bat inspired algorithm based dual mode gain scheduling of PI controllers for interconnected power system

This paper highlights the load frequency control using dual mode Bat algorithm based scheduling of PI controllers for interconnected power systems. The bat inspired algorithm based on the echolocation of bats has been developed in 2010. In this study, the bat inspired algorithm based dual mode PI controller is applied to the multi-area interconnected thermal power system in order to tune the parameter PI controllers. The proposed controller is simple in structure and easy for implementation. The proposed controller was compared with those from conventional the PI controllers and Fuzzy gain scheduling of PI controllers. The simulation results show the point that the proposed bat inspired algorithm, based dual mode gain scheduling of PI controllers (BIDPI), provides better transient as well as steady state of response. It is also found that the proposed controller is less sensitive to the changes in system parameters.     

A new PID load frequency controller design method in frequency domain through direct synthesis approach

In this paper a new PID controller design method based on the direct synthesis (DS) approach of controller design in frequency domain is presented. The parameters of the PID controller are obtained through frequency response matching with the DS controller. The method yields linear algebraic equations, solution of which gives the controller parameters. The design method has been developed for single-area as well as multi-area power systems. Non-linearity like the generation rate constraint (GRC) has been considered. Several examples are taken from the literature to demonstrate the effectiveness of the proposed method in comparison with some prevalent design methods.     

Properties and rapid consolidation of ultra-hard tungsten carbide

Extremely dense WC with a relative density of up to 99% was obtained within 3 min under a pressure of 80 MPa using the high frequency induction heating sintering method (HFIHS) method. The average grain size of the WC was about 87 nm. The advantage of this process is not only rapid densification to obtain a near theoretical density but also the prohibition of grain growth in nanostructured materials. The hardness and fracture toughness of the dense WC produced by the HFIHS were investigated.     

Power system transient stability regions : transient stability limits involving saliency and the optimized Szego's Liapunov function

The optimized Szego's Liapunov function has been formulated for a single-machine system connected to a large power system taking into account saliency and the effect of non-linear damping, A computer-oriented approach using Szego's Liapunov function has been outlined for the determination of transient stability limits. The specific advantages of the present method over those of Zubov and Popov (Yu and Vongsuriya 1967, Chang and Davies 1972) have been clearly brought out.     

Application of bacteria foraging algorithm for the design optimization of multi‐objective Yagi‐Uda array

The design of antenna array with desirable multiple performance parameters such as directivity, input impedance, beam width, and side‐lobe level using any optimization algorithm is a highly challenging task. Bacteria Foraging Algorithm (BFA), as reported by electrical engineers, is the most robust and efficient algorithm in comparison with other presently available algorithms for global optimization of multi‐objective, multi‐parameter design problems. The objective of this article is to apply this new optimization technique, BFA, in the design of Yagi‐Uda array for multi‐objective design parameters. We optimize length and spacing for 6 and 15 elements array to achieve higher directivity, pertinent input impedance, minimum 3‐dB beam width, and maximum front to back ratio both in the E and H planes of the array. At first, we develop a Method of Moments code in MATLAB environment for the Yagi‐Uda array structure for obtaining the above design parameters and then coupled with the BFA for the evaluation of the optimized design parameters. Detail simulation results are included to confirm the design criteria. © 2010 Wiley Periodicals, Inc. Int J RF and Microwave CAE , 2010.     

Power quality time series data mining using S-transform and fuzzy expert system

This paper presents a new approach for power quality time series data mining using S-transform based fuzzy expert system (FES). Initially the power signal time series disturbance data are pre-processed through an advanced signal processing tool such as S-transform and various statistical features are extracted, which are used as inputs to the fuzzy expert system for power quality event detection. The proposed expert system uses a data mining approach for assigning a certainty factor for each classification rule, thereby providing robustness to the rule in the presence of noise. Further to provide a very high degree of accuracy in pattern classification, both the Gaussian and trapezoidal membership functions of the concerned fuzzy sets are optimized using a fuzzy logic based adaptive particle swarm optimization (PSO) technique. The proposed hybrid PSO-fuzzy expert system (PSOFES) provides accurate classification rates even under noisy conditions compared to the existing techniques, which show the efficacy and robustness of the proposed algorithm for power quality time series data mining.     

Performance Evaluation of Recently Developed New Process HAJM during Machining Hardstone Quartz Using Hot Silicon Carbide Abrasives: an Experimental Investigation and Sustainability Assessment

Silicon - The better machining capabilities of abrasive jet machining characterized by the absence of thermal distortion make it highly competitive with other cutting processes employing plasma and...