A modified fuzzy min-max neural network for data clustering and its application to power quality monitoring

When no prior knowledge is available, clustering is a useful technique for categorizing data into meaningful groups or clusters. In this paper, a modified fuzzy min-max (MFMM) clustering neural network is proposed. Its efficacy for tackling power quality monitoring tasks is demonstrated. A literature review on various clustering techniques is first presented. To evaluate the proposed MFMM model, a performance comparison study using benchmark data sets pertaining to clustering problems is conducted. The results obtained are comparable with those reported in the literature. Then, a real-world case study on power quality monitoring tasks is performed. The results are compared with those from the fuzzy c-means and k-means clustering methods. The experimental outcome positively indicates the potential of MFMM in undertaking data clustering tasks and its applicability to the power systems domain.

Optimal power allocation and load distribution for multiple heterogeneous multicore server processors across clouds and data centers

For multiple heterogeneous multicore server processors across clouds and data centers, the aggregated performance of the cloud of clouds can be optimized by load distribution and balancing. Energy efficiency is one of the most important issues for large-scale server systems in current and future data centers. The multicore processor technology provides new levels of performance and energy efficiency. The present paper aims to develop power and performance constrained load distribution methods for cloud computing in current and future large-scale data centers. In particular, we address the problem of optimal power allocation and load distribution for multiple heterogeneous multicore server processors across clouds and data centers. Our strategy is to formulate optimal power allocation and load distribution for multiple servers in a cloud of clouds as optimization problems, i.e., power constrained performance optimization and performance constrained power optimization. Our research problems in large-scale data centers are well-defined multivariable optimization problems, which explore the power-performance tradeoff by fixing one factor and minimizing the other, from the perspective of optimal load distribution. It is clear that such power and performance optimization is important for a cloud computing provider to efficiently utilize all the available resources. We model a multicore server processor as a queuing system with multiple servers. Our optimization problems are solved for two different models of core speed, where one model assumes that a core runs at zero speed when it is idle, and the other model assumes that a core runs at a constant speed. Our results in this paper provide new theoretical insights into power management and performance optimization in data centers.

Effects of baffles on flow distribution in an electrostatic precipitator (ESP) of a coal based power plant

Electrostatic Precipitators (ESP) are the most reliable and industrially used control devices to capture fine particles for reducing exhaust emission. Its efficiency is 99% or more. However, capturing submicron particles which are hazardous is still a problem as it involves complex flow phenomena and ESP design limitations. In this study, the effect of baffles on flow distribution inside the ESP is investigated computationally. Baffles are expected to increase the residence time of flue gas which helps to collect more particles into the collector plates, and hence increase the collection efficiency of an ESP. Besides, the placement of a baffle is likely to cause swirling of flue gas and hence sub-micron particles move towards the collector plate due to eccentric and electrostatic force. Therefore, the effects of position, shape and thickness of the baffles on collection efficiency which are also important for ESP design are reported in this study. The fluid flow distribution has been modelled using computational fluid dynamics (CFD) software Fluent and the result and outcome are presented and discussed. The result shows that baffles have significant influence on fluid flow pattern and the efficiency of ESP.

Covalent/crystallite cross-linked co-network hydrogels : an efficient and simple strategy for mechanically strong and tough hydrogels

Covalent/crystallite cross-linked co-network hydrogels have been prepared using epoxy and PVA through a cyclic freezing-thawing process. The PVA/epoxy hydrogels show enhanced mechanical strength and toughness. PVA/epoxy hydrogels with 4 wt% epoxy loading display maximum tensile strength and toughness of 1.1 MPa and 2838 kJ/m3 respectively. The fracture toughness of PVA/epoxy hydrogels ranges from 160 to 450 J/m2. Radius of gyration and fractal information of the hydrogels were obtained by fitting the SAXS data to the Guinier and power law models. The enhanced mechanical properties are attributed to the increase in covalent bonding and decrease in crystallite distribution with an increase in epoxy content. However a larger hysteresis is shown for PVA/epoxy hydrogels due to irreversible destruction of covalent bonds between epoxy and PVA.

Robust control for power sharing in microgrids with low-inertia wind and PV generators

This paper presents a robust control design scheme for a multidistributed energy resource (DER) microgrid for power sharing in both interconnected and islanded modes. The scheme is proposed for micgrogrids consisting of photovoltaic (PV) units and wind turbine driven doubly fed induction generators (DFIGs). A battery is integrated with each of the wind and solar DER units. The control scheme has two levels: 1) one centralized multi-input–multi-output robust controller for regulating the set reference active and reactive powers and 2) local real and reactive power droop con-trollers, one on each DER unit. The robust control scheme utilizes multivariable H1 control to design controllers that are robust to the changes in the network and system nonlinearities. The effectiveness of the proposed controller is demonstrated through large-distur-bance simulations, with complete nonlinear models, on a test micro-grid. It is found that the power sharing controllers provide excellent performance against large disturbances and load variations during islanding transients and interconnected operation.