ATPase and Lactate Dehydrogenase Activities in Frozen Stored Fish Muscle as Indices of Cold Storage Deterioration

The effect of prolonged cold storage on muscle adenosine triphosphatase (ATPase) and lactate dehydrogenase (LDH) activities was studied in a variety of fresh water and brackish water fish. Decrease in enzyme activity was observed in all samples stored frozen (- 20°C) over a period of 180 days. Highly significant negative correlation was observed between enzyme activity and frozen storage period with mullet, pearlspot, milk fish and tilapia. Significant linear correlations were observed between decrease in enzyme activities and other biochemical indices and sensory scores. The results indicated that loss of activities of ATPase and LDH in fish muscle was significantly related to early changes in quality of frozen stored fish.     

Stability Control of Smart Power Grids with Artificial Intelligence and Wide-area Synchrophasor Measurements

Abstract—Environmental concerns due to emissions from nuclear and fossil fuel based power plants have triggered widespread utilization of renewable energy-based small- and large-scale distributed generation technologies. These technologies have been transforming the energy market towards a deregulated and dispersed entity. To cope with these transformations, and ensure appropriate grid monitoring and control, the conventional power grids across the globe have been enduring a paradigm shift towards a smart grid that is empowered with cutting edge technologies. The operational stability of these emerging smart power grids necessitates sophisticated real-time monitoring and control technologies. This article analyzes various stability concerns in smart power grids pertaining to distributed generations and proposes novel methodologies for ensuring operational stability. The proposed methodologies entail real-time stability monitoring and stability control with the use of wide-area synchrophasor measurements and artificial intelligence methods. The efficacy of the proposed methodologies has been verified through simulation studies conducted on an IEEE 14-bus system. Results of this research validate the necessity of coordinated control for maintaining stability of smart grids incorporating distributed generation technologies.     

Pragmatic multi-stage simulated annealing for optimal placement of synchrophasor measurement units in smart power grids

Conventional power grids across the globe are reforming to smart power grids with cutting edge technologies in real time monitoring and control methods. Advanced real time monitoring is facilitated by incorporating synchrophasor measurement units such as phasor measurement units (PMUs) to the power grid monitoring system. Several physical and economic constraints limit the deployment of PMUs in smart power grids. This paper proposes a pragmatic multi-stage simulated annealing (PMSSA) methodology for finding the optimal locations in the smart power grid for installing PMUs in conjunction with existing conventional measurement units (CMUs) to achieve a complete observability of the grid. The proposed PMSSA is much faster than the conventional simulated annealing (SA) approach as it utilizes controlled uphill and downhill movements during various stages of optimization. Moreover, the method of integrating practical phasor measurement unit (PMU) placement conditions like PMU channel limits and redundant placement can be easily handled. The efficacy of the proposed methodology has been validated through simulation studies in IEEE standard bus systems and practical regional Indian power grids.     

Letter to the Editor: Stability Concerns in Smart Grid with Emerging Renewable Energy Technologies

Abstract

The environmental concerns due to conventional power plants have given impetus for widespread utilization of renewable energy based distributed generation technologies. As a consequence, the concepts pertaining to a smart grid with advanced functional architecture are evolving to incorporate these technologies. Many such smart grid strategies are focused on maximum utilization of renewable energy sources compared to conventional fossil or nuclear fuels for meeting real-time load demand. The diverse characteristics of renewable energy based distributed generation technologies compared to conventional power plants have led to many operational stability concerns for the smart grid. This article discusses these stability concerns in smart grid with distributed generation technologies.     

A Novel Topological Genetic Algorithm-Based Phasor Measurement Unit Placement and Scheduling Methodology for Enhanced State Estimation

Phasor measurement units are emerging as a potential tool for on-line power system state estimation. Incorporation of phasor measurement units to the existing power system's monitoring system is impeded by various physical and economic constraints. This article proposes a novel topological genetic algorithm for optimal placement of phasor measurement units along with existing conventional measurement units such that state estimation can be achieved with enhanced accuracy and immunity against power grid contingencies. The proposed algorithm optimally places phasor measurement units so that complete observability of the power system is achieved through them and enhanced redundancy in measurement can be accomplished through conventional measurement units. Since practical phasor measurement unit placements are accomplished in multiple horizons, intelligent sorting and phase optimization methodologies have been presented to attain maximum observability during phasing periods. Placement of phasor measurement units with multiple channel limits has also been studied in this article. The efficacy of the proposed topological genetic algorithm for optimizing the number of phasor measurement units and enhancing state estimation under various operating conditions has been validated through extensive simulation studies conducted in IEEE standard bus systems. Practical case studies have been performed in the western and southern region Indian power grids.     

Optimal placement of PMUs for the smart grid implementation in Indian power grid—A case study

Efficient utilization of energy resources is essential for a developing country like India. The concept of smart grid (SG) can provide a highly reliable power system with optimized utilization of available resources. The present Indian power grid requires revolutionary changes to meet the growing demands and to make the grid smarter and reliable. One of the important requirements for SG is the instantaneous monitoring of the voltage, current and power flows at all buses in the grid. The traditional monitoring system cannot satisfy this requirement since they are based on nonlinear power flow equations. Synchro-phasor-measurement devices like phasor measurement units (PMUs) can measure the phasor values of voltages at installed buses. Consequently, the currents passing through all branches connected to that bus can be computed. Since the voltage phasor values at the neighboring buses of a bus containing the PMU can be estimated using Ohm’s law, it is redundant to install PMUs at all the buses in a power grid for its complete observability. This paper proposes the optimal geographical locations for the PMUs in southern region Indian power grid for the implementation of SG, using Integer Linear Programming. The proposed optimal geographical locations for PMU placement can be a stepping stone for the implementation of SG in India.     

INFRASTRUCTURE AND METROPOLITAN REORGANIZATION: AN EXPLORATION OF THE RELATIONSHIP IN AFRICA AND INDIA

Despite decades of effort, deficiencies in access and quality of infrastructure persist in cities of the developing world. One common response to the infrastructure problem is to reorganize the structure of metropolitan areas in the hopes that infrastructure provision, management, and quality will improve. What is not clear globally, however, is how the reorganization of metropolitan areas comes to be, and how infrastructure deficiencies function as a rationale for reform in conjunction with other dominant reasons or drivers of metropolitan reorganization. Building on the demand for increased cross‐regional comparison in urban studies generally, this article explores and compares the relationship between infrastructure quality and political and social pressures in four cities—two in India and two in East Africa. The comparison is intended to be exploratory; it shows how city and national government efforts to improve infrastructure quality are shaped by political and social pressures. The results provide a foundation for future cross‐regional comparison and theory building.     

Fault Detection and Localization Methodology for Self-healing in Smart Power Grids Incorporating Phasor Measurement Units

Recent developments in several fields of engineering have accelerated the evolution of smart power grids encompassing both transmission and distribution systems across the globe. Self-healing, a crucial operational function of a smart power grid, requires detection as well as localization of the transmission line faults in the power network in real time. A support vector machine based fault-localization methodology has been proposed to accurately detect and localize any type of transmission line faults for the entire smart power grid. This methodology identifies the transmission line fault in smart power grid and precisely pinpoints the bus to which the faulty branch is connected. Afterward, the faulty branch is discriminated, and the distance of fault location from the bus related to the fault is estimated. The methodology relies on frequency-domain analysis of the equivalent voltage phasor angle and equivalent current phasor angle using fast Fourier transform. The proposed methodology has been corroborated using extensive case studies conducted on 7- and 13-bus power systems. The major contribution of the proposed methodology is that it can identify and localize all types of transmission line faults using phasor measurement unit measurements. The methodology can be applied for transmission systems as well as distribution systems.     

Framework for morphometric classification of cells in imaging flow cytometry

Imaging flow cytometry is an emerging technology that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy. It allows high‐throughput imaging of cells with good spatial resolution, while they are in flow. This paper proposes a general framework for the processing/classification of cells imaged using imaging flow cytometer. Each cell is localized by finding an accurate cell contour. Then, features reflecting cell size, circularity and complexity are extracted for the classification using SVM. Unlike the conventional iterative, semi‐automatic segmentation algorithms such as active contour, we propose a noniterative, fully automatic graph‐based cell localization. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label‐free leukaemia cell‐lines MOLT, K562 and HL60 from video streams captured using custom fabricated cost‐effective microfluidics‐based imaging flow cytometer. The proposed system is a significant development in the direction of building a cost‐effective cell analysis platform that would facilitate affordable mass screening camps looking cellular morphology for disease diagnosis.