Ajoy Kumar Chakraborty

Effects of Ambient Temperature and Wind Speed on Performance of Monocrystalline Solar Photovoltaic Module in Tripura, India

The effects of ambient temperature and wind speed on the performance analysis of a monocrystalline silicon solar photovoltaic module have been analyzed in a particular location called Tripura, India, for the period of 2012-2013. The research work has been carried out by monitoring the variation of module efficiency with ambient temperature and wind speed. A statistical analysis has also been done and the result indicates that the values of correlation coefficient are 96% and 68% for ambient temperature and wind speed, respectively, considering confidence level of 95%.The result shows that there is a strong positive linear relationship between module efficiency and ambient temperature and a moderate positive linear relationship between module efficiency and wind speed. The deviation from the standard test condition (STC) affects the generation of output power while designing green buildings in Tripura.

Interferometric switch based all optical scheme for conversion of binary number to its quaternary-signed digit form

Multi-valued logic (with radix>2) can be viewed as an alternative approach to solve many problems in transmission, storage and processing of large amount of information in digital signal processing. In arithmetical operation signed digit number is very essential for carry free computation. To achieve the parallelism in computation, a suitable number system and an efficient encoding/decoding scheme for handling the data are very much essential. In radix-4 system negative number is represented by quaternary-signed digit (QSD). In this study a conversion from 3-bit binary number (2s complement representation) to its equivalent single-digit QSD is reported. The technique for conversion of QSD to its binary equivalent form is also presented. All-optical circuits are designed with non-linear material-based interferometric switches such as terahertz optical asymmetric demultiplexer in optical tree architecture, where the numbers are represented by different discrete polarised state of light. Device-based simulation of the proposed optical circuit is used to verify the operation of the optical converter.

Active Line Flow Control of Power System Network with FACTS Devices of choice using Soft Computing Technique

technology opens up new opportunity for operation and control of power system. Out of the various FACTS devices (viz-TCSC, TCPST, UPFC etc.), the right choices for the maximization of power flow in power system network demands attention which helps to achieve the active power flow up to their line limits without any constraint violation and with optimal investment on FACTS devices. In this paper, an algorithm has been developed for right choices of various combination of FACTS in the power network to enhance the power transfer capability of existing lines under normal condition very close to their line limits and has been applied for modified IEEE 14- bus system. This helps the optimal investment in FACTS devices and easy control. The proposed method is based on load flow and line flow equation In this paper Newton Raphson and modified simulated annealing technique are proposed

NSGAII-based Congestion Management in a Pool-based Electricity Market Incorporating Voltage and Transient Stability

Abstract Congestion of transmission lines is a key challenge for the system operator in the open access regime and is usually managed by rescheduling generators and demands. The changes in schedule due to congestion management may cause stability margins to shrink to unacceptable levels. Stability issues must, therefore, be considered during congestion management. This article presents a multi-objective formulation of the congestion management problem in a pool-based electricity market with the competing objective functions of minimizing congestion management cost and maximizing voltage and transient stability margins. The non-dominated sorting genetic algorithm II is employed to achieve the best trade off among the three objectives. A fuzzy decision maker is used to extract the best-compromise non-dominated solution. The proposed method has been tested on the New England 39-bus system, and results are compared with those of other reported multi-objective mathematical programming based approaches. The proposed non-dominated sorting genetic algorithm II based congestion management algorithm outperforms the previously reported method. The quality of the results establishes the efficacy of the proposed approach in solving the multi-objective congestion management problem.

Placement of UPFC for minimizing active power loss and total cost function by PSO algorithm

In this paper Particle Swarm Optimization (PSO) technique has been used to minimize the active power loss and the total cost function, which includes the generation costs and the UPFC investment cost, through optimally placing the Unified Power Flow Controller (UPFC) in the power system network. Three objective functions are taken as the indexes of the system performance; identification of most suitable buses using line loss sensitivity index, minimization of active power loss and total generation cost by employing PSO. For the validation and comparison purposes of the proposed techniques, simulations are carried out on modified IEEE 14-bus power system. Results validate that the static performances of the power system can be successfully improved due to the optimal allocation of single UPFC controller.

Modified simulated annealing technique based Optimal Power Flow with FACTS devices

Simulated annealing is a probabilistic method for finding the global minimum of a cost function that may possess several local minima. In this paper, a Modified Simulated Annealing (MSA) technique is proposed to minimise the generation cost in Optimal Power Flow (OPF) control with Flexible AC Transmission Systems (FACTS) devices. The main goal of this paper is to verify the validity of using MSA to solve the OPF problem simultaneously composed by the load flow and the economic dispatch problem. A six bus system is used to highlight the goodness of the solution technique.

Quasi-reflected ions motion optimization algorithm for short-term hydrothermal scheduling

This paper describes quasi-reflected ions motion optimization algorithm to solve the short-term hydrothermal scheduling problem. The aim of hydrothermal scheduling is to minimize the total cost of generation by optimizing power generation of several hydro and thermal units on an hourly basis. The algorithm mainly works on the principle that opposite charges attract each other and same charges repel each other. Two phases are employed in this algorithm, namely liquid phase and crystal phase, in order to perform exploration and exploitation. Furthermore, quasi-reflected-based learning scheme is incorporated to ions motion optimization algorithm, in order to increase the convergence speed as well as the quality of the solution. To investigate the performance of the ions motion optimization algorithm, the algorithm has been tested on seven test systems. The results obtained by the ions motion optimization algorithm have been compared with those obtained by many recently developed optimization techniques such as evolutionary programming, genetic algorithm, particle swarm optimization, differential evolution, artificial immune system, teaching–learning-based optimization, real-coded chemical-reaction-based optimization, cuckoo search algorithm and modified cuckoo search algorithm. Moreover, some statistical tests have been performed to evaluate the performance of ions motion optimization algorithm.

Advanced metering infrastructure: Technology and challenges

Smart Grid has evolved as a recent topic of discussion and research in many parts of the world and thus the smart metering systems. The electrical supply industry is in the process of integration with bidirectional information and power flow infrastructure commonly called smart grid. In laymens terms Smart grid is the integration of Information Technology and Electrical Grid. Advance metering infrastructure (AMI) is an important component of the smart grid in which data and signal are transferred from consumer smart meter to smart grid and vice versa. In this work, design of smart meter scheme, its hardware and software requirements, and its technologies has been discussed. This paper also focuses on the communication protocol developments as well as information security associate with smart meters. A detailed discussion on the financial and other technological issues related to smart meter has been presented in this paper and a few remedies have also been suggested.

Non dominated sorting gravitational search algorithm based optimal power flow with emission and non smooth cost functions

This article presents application of non dominated sorting based gravitational search algorithm (NSGSA) for solving optimal power flow (OPF) problems with economic and environment objectives. Fast elitist non-dominated sorting and crowding distance have been used to locate and manage the Pareto optimal front. The proposed method is tested and implemented on standard IEEE 30-bus test power system, with different objectives, that reflect the minimization of total quadratic fuel cost, piecewise quadratic fuel cost, fuel cost with valve point loading effect of generators and emission cost. The numerical results have been compared with other recently developed algorithms to reveal the tangible superiority of the proposed method for solving the OPF problems.

Multi objective optimal power flow using NSMOGSA

Application of non dominated sorting multi objective gravitational search algorithm (NSMOGSA) for solution of different optimal power flow (OPF) problem is presented in this article. NSMOGSA is an extension of the gravitational search algorithm (GSA), where the gravitational acceleration is updated using non-dominated sorting concept. A mixture of sign and reordering mutations are also proposed in to reduce the chance of trapping in local optima. The proposed method is employed for optimal adjustments of the power system control variables which involve both continuous and discrete variables of the OPF problem. To show the effectiveness of the proposed algorithm, it has been tested on a standard IEEE 30-bus system with two different individual objectives that reflect total emission cost minimization and fuel cost minimization. The performance of NSMOGSA is compared with the results found by other meta-heuristic techniques reported in the recent literature to demonstrate the tangible superiority of the proposed method.