Hybrid journal (It can contain Open Access articles) ISSN (Print) 1757-6342 - ISSN (Online) 1757-6350 Published by Inderscience Publishers[449 journals]

Authors:A. Ahamed Jeelani Basha, M. Anitha, E.B. Elanchezhian Pages: 4 - 29 Abstract: In today's competitive electricity market, managing transmission congestion is a major challenging issue due to operational constraints. Flexible AC transmission system (FACTS) device can be a choice to control the power flow in the congested transmission lines. This paper explores the use of thyristor controlled series compensator (TCSC) for power flow control in congested network using firefly algorithm (FA). The optimal location of TCSC is identified based on real power performance index and reduction of total system reactive power loss methods. Further in the congestion management (CM) problem, single line outage analysis is also performed. FA is used to determine the minimum total cost which includes production cost and TCSC cost. Results of five bus, IEEE 14 and IEEE 30 bus test systems indicate that FA provides minimum cost compared to the previous literature. The efficiency of the proposed FA for obtaining the high quality solution is also established. Keywords: congestion management; CM; firefly algorithm; FA; flexible AC transmission system; FACTS; thyristor controlled series compensator; TCSC Citation: International Journal of Process Systems Engineering, Vol. 5, No. 1 (2019) pp. 4 - 29 PubDate: 2018-12-07T23:20:50-05:00 DOI: 10.1504/IJPSE.2019.096675 Issue No:Vol. 5, No. 1 (2018)

Authors:Manoj Kumar Merugumalla, Prema Kumar Navuri Pages: 30 - 52 Abstract: The population algorithms have a number of advantages over classical methods for solving complex optimisation problems such as tuning of controller parameters of motor drives These algorithms for solving various problems of global optimisation is often called as methods inspired by nature, methods in this class are based on the modelling of intelligent behaviour of organised members of the population. Particle swarm optimisation (PSO) algorithm is population-based algorithm which has ability to fine tune the controller parameters. In this paper, chaotic inertia weight and constriction factor-based PSO algorithms are proposed for tuning of proportional-integral-derivative (PID) controller parameters to control brushless direct current (BLDC) motor drive. The BLDC is modelled in MATLAB/Simulink and trapezoidal back emf waveforms are modelled as a function of rotor position using MATLAB code. The simulation results of PSO algorithms are compared and results shown the effectiveness of C-inertia weight and C-factor in tuning PID controller parameters. Keywords: brushless direct current motor; particle swarm optimisation; PSO; PID controller; constriction factor; chaotic inertia weight Citation: International Journal of Process Systems Engineering, Vol. 5, No. 1 (2019) pp. 30 - 52 PubDate: 2018-12-07T23:20:50-05:00 DOI: 10.1504/IJPSE.2019.096673 Issue No:Vol. 5, No. 1 (2018)

Authors:Asma Meddeb, Hajer Jmii, Souad Chebbi Pages: 53 - 66 Abstract: The occurrence of contingencies in the power system may cause deviation from its ideal operating condition, which initiates the security assessment for efficient operation of the power system. This paper has two objectives. First, to identify and classify the power system states that provides a consistent security analysis. Second, to evaluate each curative action based on the degree of the violation of security constraint for an effective and secure power system. Therefore, a new methodology for operation state classification using the fuzzy logic technique is proposed to achieve these objectives. Moreover, two fuzzy logic controllers are developed. The first one (FLC 1) classifies the operating states of the power system in one of four categories: normal (N), alert (A), emergency (E1) and extreme (E2). The second (FLC 2) specifies the appropriate action to avoid the transition to an extreme state. The simulation program, under MATLAB environment, was applied to evaluate the classification algorithm performances developed using the fuzzy logic technique. Keywords: contingencies; classification of operation state; fuzzy logic; Newton Raphson; power flow Citation: International Journal of Process Systems Engineering, Vol. 5, No. 1 (2019) pp. 53 - 66 PubDate: 2018-12-07T23:20:50-05:00 DOI: 10.1504/IJPSE.2019.096677 Issue No:Vol. 5, No. 1 (2018)

Authors:Ritu Raj, B.M. Mohan Pages: 67 - 92 Abstract: This paper deals with the simplest Takagi-Sugeno fuzzy two-term controllers. The analytical structures of the simplest fuzzy controllers were developed using a modified rule base. The number of tuning parameters of the controllers is reduced by introducing a novel rule base consisting of two rules. These controllers are termed as 'the simplest' since minimal (two) number of fuzzy sets is used for fuzzification. Algebraic product (AP)/minimum (min) triangular norm, bounded sum (BS)/maximum (max) triangular co-norm, different universes of discourses (UoDs) of inputs, and centre of gravity (CoG) defuzzification method are chosen to derive the mathematical models of the fuzzy controllers. The simplest fuzzy controller with modified rule base is equivalent to a (nonlinear) variable gain/structure PI/PD controller. The BIBO stability of the closed loop control system is investigated using the small gain theorem. The gain of the controller either varies or remains constant in different regions of the input plane. The gain variations and the computational burden of the fuzzy controllers are also studied. Two examples of nonlinear dynamical systems are considered to validate the developed models of the fuzzy controllers. Keywords: mathematical model; fuzzy control; BIBO stability; PI/PD controller; Takagi-Sugeno controller; variable gain controller; nonlinear controller Citation: International Journal of Process Systems Engineering, Vol. 5, No. 1 (2019) pp. 67 - 92 PubDate: 2018-12-07T23:20:50-05:00 DOI: 10.1504/IJPSE.2019.096674 Issue No:Vol. 5, No. 1 (2018)