P. Srinivasa Rao Nayak

Development of an Improved P&O Algorithm Assisted Through a Colony of Foraging Ants for MPPT in PV System

The perturb and observe (P&O) algorithm is a simple and efficient technique, and is one of the most commonly employed maximum power point (MPP) tracking (MPPT) schemes for photovoltaic (PV) power-generation systems. However, under partially shaded conditions (PSCs), P&O method miserably fails to recognize global MPP (GMPP) and gets trapped in one of the local MPPs (LMPPs). This paper proposes ant-colony-based search in the initial stages of tracking followed by P&O method. In such a hybrid approach, the global search ability of ant-colony optimization (ACO) and local search capability of P&O method are integrated to yield faster and efficient convergence. A theoretical analysis of the static and dynamic convergence behavior of the proposed algorithm is presented together with computed and measured results.

Ant colony based feedback controller design for soft-starter fed induction motor drive

The objective of this work is to design and implement a closed loop system for induction motor starting at rated current. Thyristorized AC voltage regulator is used as the starting equipment and motor current regulation is carried out using an optimally tuned Proportional-Integral (PI) controller. Since, AC voltage controller fed starting of induction motor is a non-linear process, identification of optimal values of PI controller constants is performed using a novel ant colony based optimization technique. The complete drive system including AC voltage controller fed induction motor in conjunction with optimal PI controller is first simulated in MATLAB and subsequently verified experimentally. The successful implementation with a low cost microcontroller illustrates the feasibility of the new approach.

Feedback controller design for a buck-boost converter through evolutionary algorithms

This paper suggests a systematic design procedure for the feedback controller employed for the output voltage regulation of a buck-boost type dc-dc converter using evolutionary algorithms namely Genetic Algorithm (GA), Differential Evolution (DE) and Artificial immune system (AIS). The output voltage regulation is formulated as an optimization task with the controller elements as the variables and solution is achieved through each evolutionary method. Computer simulation results supported by experimental evidence clearly demonstrate that the controllers estimated through evolutionary algorithms are capable of delivering enhanced output voltage regulation under different types of load and supply disturbances.

Auxiliary Hybrid PSO-BPNN-Based Transmission System Loss Estimation in Generation Scheduling

The conventional transmission loss estimation methods used by power system utilities in scheduling problems rely on the exactness of the network model. However, the transmission network model in the system operator database is erroneous and not updated periodically. Therefore, the transmission losses calculated based on the erroneous network model is also erroneous. In this context, this paper proposes an auxiliary hybrid model using a back propagation neural network (BPNN) and a particle swarm optimization (PSO) technique to estimate transmission losses, while solving power system scheduling problems. Here, the historical information of the power system is processed by the BPNN and its control parameters are optimized using PSO. In the proposed PSO-BPNN loss estimator, power system variables such as real power generation levels, reactive power injection values, and ambient temperature are used as the input variables. The proposed loss estimator is validated using IEEE 30 bus system and Ontario power system.

A voltage constrained time sharing switching scheme for dual input buck converter

The objective of this paper is to develop and analyze an analog circuit capable of delivering regulated output voltage in a dual input buck converter. The major components of the control circuit comprise a PI controller block and a duty ratio limit block. The PI controller is designed through linear control theory and the duty ratio limit on the each power switch is based on the relative amplitude of the source voltage connected to each power source. The development of the circuit is explained first followed by computed and measured results on a prototype.

Wireless power transfer technologies for electric vehicle battery charging — A state of the art

This paper presents a state of the art on different wireless power transfer (WPT) techniques for electric vehicle (EV) battery charging. The principle of operation and advantages of WPT techniques are discussed. In addition, the limitations and challenges associated with the WPT techniques are explored. A meticulous comparison has been done to identify the better WPT for EV battery charging.

Cascaded simulated annealing/perturb and observe method for MPPT in PV systems

In this paper, we show that by suitably integrating simulated annealing (SA) with perturb and observe (P&O) algorithm, the performance of maximum power point tracking (MPPT) in a photovoltaic (PV) system under non uniform insolation conditions can be substantially improved. The appealing advantages of SA and P&O method are thus combined to yield a robust MPPT which always guarantees global convergence independent of either PV configuration or shading pattern. Simulation and experimental results are presented to validate the new scheme.

Gravitational search algorithm combined with P&O method for MPPT in PV systems

This paper proposes a novel maximum power point tracking (MPPT) algorithm for photovoltaic (PV) power generation systems under non-uniform illumination. The proposed MPPT algorithm is composed of gravitational search algorithm (GSA) and traditional perturb and observe (P&O) method. In the initial stages of tracking, the power-voltage (P-V) curve is scanned through GSA and the best solution obtained is transferred to P&O algorithm in the later stage. The combined algorithm is shown to possess the principal advantages of the two methods resulting in improved tracking performance. Simulation and experimental studies on a prototype PV system show enhanced performance of the new method.

Buck-Boost converter controller design using bacterial foraging

This paper reports the development of a bacterial foraging algorithm for output voltage control of Buck-Boost type converter. The solution to the optimization is carried out through the said algorithm and extensive results are shown to validate the new method.

Analysis on the failure of dynamic braking of capacitor-run induction motor supplied from half-controlled converter

This paper examines the viability of applying dynamic braking to AC voltage controller supplied capacitor-run induction motor. During the variable speed operation, the AC voltage regulator is gated during both half-cycles of the supply voltage. It is proposed to effect dynamic braking of the motor by inhibiting firing pulses during the negative half-cycles of the supply voltage. This will lead to half-controlled converter operation applying DC voltage across the motor terminals, and is supposed to cause dynamic braking. Contrary to expectation, motor is observed to rotate at a very low speed instead of braking. Theoretical, computed and measured results are presented in this paper to explain the failure of dynamic braking.