Power Profile of Effective Managers: An Exploration among the Branch Managers of a Commercial Bank in Kerala

Managers are central to any fuction in a complex and developed society. Their talents are reckoned to be cardinal in developed economies and a basic yearning of all developing economies.In order to survive and produce results in a turbulent and transient environment, the task is to understand the nature of factors contributing to managerial effectiveness. This study is an attempt towards this core issue of the present from a different perspective. This study tries to focus attention on a group of managers functioning in the field of banking, a core sector in the country's economy. The gamut of economic activities in Kerala being predominantly service-oriented, importance of commercial banking is almost indisputable. Though economists would argue that the disproportionate development of service sector is anomalous when viewed against the hazy scenarios in the primary and secondary sectors of the state’s economy, the extent and pace of growth in the banking sector has had its dole meted out by ambitious and productive managers fiinctioning in the field. Researcher’s attempt here is to thresh the grain and chaff among bank managers in terms of their effectiveness and to account for the variations in the light of their ability to affect the thoughts and actions of their subordinates. To put it succinctly, the attempt herein is to explain the effectiveness of bank managers in the light of their ‘Power Profile’ taken to be comprising Power Differentials, Power Bases, their Visibility and Credibility in the organisation and, the Power Styles typically used by them for influencing subordinates.

Main maximum power point tracking strategies intended for photovoltaics

This paper presents evaluations among the most usual MPPT techniques, doing meaningful comparisons with respect to the amount of energy extracted from the photovoltaic panel (PV) (Tracking Factor - TF) in relation to the available power, PV voltage ripple, dynamic response and use of sensors. Using MatLab/Simulink® and DSpace platforms, a digitally controlled boost DC-DC converter was implemented and connected to an Agilent Solar Array E4350B simulator in order to verify the analytical procedures. The main experimental results are presented and a contribution in the implementation of the IC algorithm is performed and called IC based on PI. Moreover, the dynamic response and the tracking factor are also evaluated using a Friendly User Interface, which is capable of online program power curves and compute the TF. Finally, a typical daily insulation is used in order to verify the experimental results for the main PV MPPT methods. © 2011 IEEE.

Smoothing of PV power fluctuations by geographical dispersion

The quality and the reliability of the power generated by large grid-connected photovoltaic (PV) plants are negatively affected by the source characteristic variability. This paper deals with the smoothing of power fluctuations because of geographical dispersion of PV systems. The fluctuation frequency and the maximum fluctuation registered at a PV plant ensemble are analyzed to study these effects. We propose an empirical expression to compare the fluctuation attenuation because of both the size and the number of PV plants grouped. The convolution of single PV plants frequency distribution functions has turned out to be a successful tool to statistically describe the behavior of an ensemble of PV plants and determine their maximum output fluctuation. Our work is based on experimental 1-s data collected throughout 2009 from seven PV plants, 20 MWp in total, separated between 6 and 360 km.

PV power forecast using a nonparametric PV model

Forecasting the AC power output of a PV plant accurately is important both for plant owners and electric system operators. Two main categories of PV modeling are available: the parametric and the nonparametric. In this paper, a methodology using a nonparametric PV model is proposed, using as inputs several forecasts of meteorological variables from a Numerical Weather Forecast model, and actual AC power measurements of PV plants. The methodology was built upon the R environment and uses Quantile Regression Forests as machine learning tool to forecast AC power with a confidence interval. Real data from five PV plants was used to validate the methodology, and results show that daily production is predicted with an absolute cvMBE lower than 1.3%.

Storage requirements for PV power ramp-rate control

Short-term variability in the power generated by large grid-connected photovoltaic (PV) plants can negatively affect power quality and the network reliability. New grid-codes require combining the PV generator with some form of energy storage technology in order to reduce short-term PV power fluctuation. This paper proposes an effective method in order to calculate, for any PV plant size and maximum allowable ramp-rate, the maximum power and the minimum energy storage requirements alike. The general validity of this method is corroborated with extensive simulation exercises performed with real 5-s one year data of 500 kW inverters at the 38.5 MW Amaraleja (Portugal) PV plant and two other PV plants located in Navarra (Spain), at a distance of more than 660 km from Amaraleja.

Density evolution and power profile optimization for iterative multiuser decoders based on individually optimum multiuser detectors

Iterative multiuser joint decoding based on exact Belief Propagation (BP) is analyzed in the large system limit by means of the replica method. It is shown that performance can be improved by appropriate power assignment to the users. The optimum power assignment can be found by linear programming in most technically relevant cases. The performance of BP iterative multiuser joint decoding is compared to suboptimum approximations based on Interference Cancellation (IC). While IC receivers show a significant loss for equal-power users, they yield performance close to BP under optimum power assignment.

Influence of rest interval duration on muscular power production in the lower-body power profile

There is a paucity of evidence-based support for the allocation of rest interval duration between incremental loads in the assessment of the load-power profile. We examined the effect of rest interval duration on muscular power production in the load-power profile and sought to determine if greater rest is required with increasing load (i.e., variable rest interval). Ten physically trained men completed 4 experimental conditions in a crossover balanced design. Participants performed jump squats across incremental loads (0-60 kg) on 4 occasions, with an allocated recovery interval of 1, 2, 3, or 4 minutes. The mean log-transformed power output at each load was used for comparison between conditions (rest intervals). Unloaded jump squats (0 kg) maximized power output at each condition. The maximal mechanical power output was 66.6 ± 6.5 W·kg (1 minute), 66.2 ± 5.2 W·kg (2 minutes), 67.1 ± 5.9 W·kg (3 minutes), and 66.2 ± 6.5 W·kg (4 minutes). Trivial or unclear differences in power output were observed between rest intervals at each incremental load. As expected, power declined per 10 kg increment in load, the magnitude of decrease was 13.9-14.5% (confidence limits [CL]: ±1.3-2.0%) and 13.4-14.6% (CL: ±2.4-3.9%) for relative peak and mean power, respectively, yet differences in power output between conditions were likely insubstantial. The prescription of rest intervals between loads that are longer than 1 minute have a likely negligible effect on muscular power production in the jump squat incremental load-power profile. Practitioners should select either a 1- to 4-minute rest interval to best accommodate the logistical constraints of their monitoring sessions.

A rationale for assessing the lower-body power profile in team sport athletes

Training at the load that maximizes peak mechanical power (Pmax) is considered superior for the development of power. We aimed to identify the Pmax load ('optimal load') in the jump squat and to quantify small, moderate, large, and very large substantial differences in power output across a spectrum of loads to identify loads that are substantially different to the optimal, and lastly, to investigate the nature of power production (load-force-velocity profiles). Professional Australian Rules Football (ARF; n = 16) and highly trained Rugby Union (RU; n = 20) players (subdivided into stronger [SP] vs. weaker [WP] players) performed jump squats across incremental loads (0-60 kg). Substantial differences in peak power (W·kg(-1)) were quantified as 0.2-2.0 of the log transformed between-athlete SD at each load, backtransformed and expressed as a percent with 90% confidence limits (CL). A 0-kg jump squat maximized peak power (ARF: 57.7 ± 10.8 W·kg(-1); RU: 61.4 ± 8.5 W·kg(-1); SP: 64.4 ± 7.5 W·kg(-1); WP: 54.8 ± 9.5 W·kg(-1)). The range for small to very large substantial differences in power output was 4.5-55.9% (CL: ×/÷1.36) and 2.8-32.4% (CL: ×/÷1.31) in ARF and RU players, whereas in SP and WP, it was 3.7-43.1% (CL: ×/÷1.32) and 4.3-51.7% (CL: ×/÷1.36). Power declined per 10-kg increment in load, 14.1% (CL: ±1.6) and 10.5% (CL: ±1.5) in ARF and RU players and 12.8% (CL: ±1.9) and 11.3% (CL: ±1.7) in SP and WP. The use of a 0-kg load is superior for the development of jump squat maximal power, with moderate to very large declines in power output observed at 10- to 60-kg loads. Yet, performance of heavier load jump squats that are substantially different to the optimal load are important in the development of sport-specific force-velocity qualities and should not be excluded.

Short-Term Trading for a Wind-PV Power Producer in an Electricity Market

This paper deals with the problem of coordinated trading of wind and photovoltaic systems in order to find the optimal bid to submit in a pool-based electricity market. The coordination of wind and photovoltaic systems presents uncertainties not only due to electricity market prices, but also with wind and photovoltaic power forecast. Electricity markets are characterized by financial penalties in case of deficit or excess of generation. So, the aim o this work is to reduce these financial penalties and maximize the expected profit of the power producer. The problem is formulated as a stochastic linear programming problem. The proposed approach is validated with real data of pool-based electricity market of Iberian Peninsula.

Evaluation of the main MPPT techniques for photovoltaic applications

This paper presents evaluations among the most usual maximum power point tracking (MPPT) techniques, doing meaningful comparisons with respect to the amount of energy extracted from the photovoltaic (PV) panel [tracking factor (TF)] in relation to the available power, PV voltage ripple, dynamic response, and use of sensors. Using MatLab/Simulink and dSPACE platforms, a digitally controlled boost dc-dc converter was implemented and connected to an Agilent Solar Array E4350B simulator in order to verify the analytical procedures. The main experimental results are presented for conventional MPPT algorithms and improved MPPT algorithms named IC based on proportional-integral (PI) and perturb and observe based on PI. Moreover, the dynamic response and the TF are also evaluated using a user-friendly interface, which is capable of online program power profiles and computes the TF. Finally, a typical daily insulation is used in order to verify the experimental results for the main PV MPPT methods. © 2012 IEEE.

Modelling and power quality analysis of a grid-connected solar PV system

Increased concern about global warming coupled with the escalating demand of energy has driven the conventional power system to be more reliable one by integrating Renewable Energies (RE) in to grid. Over the recent years, integration of solar PV forming a gridconnected PV is considered as one of the most promisingtechnologies to the developed countries like Australia to meet the growing demand of energy. This rapid increase in grid connected photovoltaic (PV) systems has made the supply utilities concerned about the drastic effects that have to be considered on the distribution network in particular voltage fluctuations, harmonic distortions and the Power factor for sustainable power generation. However, irrespective of thefact that the utility grid can accommodate the variability of load or irregular solar irradiance, it is essential to study the impact of grid connected PV systems during higher penetration levels as the intermittent nature of solar PV adversely effects the grid characteristics in meeting the load demand. Hence, keeping this in track, this paper examines the grid-connected PV system considering a residential network of Geelong region (38◦.09' S and 144◦.21’ E) and explores the level of impacts considering summer load profile with a change in the level of integrations. Initially, a PV power system network model is developed in Matlab-Simulink environment and the simulations are carried out to explore the impacts of solar PV penetration at low voltage distribution network considering power quality (PQ) issues such as voltage fluctuations, harmonics distortion at different load conditions.

Optimum design and analysis study of stand-alone residential solar PV microgrid

Today’s power system network has become more complex and it has more responsibilities and challenges to provide secure, reliable and quality energysupply to the communities. A small entity of electrical network known as Microgrid (MG) is more popular nowadays to enhance reliablity and secure level of energy supply, in case of any energy crisis in the utility network. The MG can also provide clean energy supply by integrating renewable energy sources effectively. TheMG with small scale solar photovoltaic (PV) power system is more suitable to provide reliable and clean energy supply for remote or urban communities in residential level. This paper presents the basic analysis study of stand-alone solar photovoltaic (PV) MG power system which has been developed with the aid of Matlab - Simulink software, on the basis of residential load profile and solar exposure level in a particular area of Geelong, Victoria State. The simulation result depicts the control behavior of MG power system with optimum sizing of PV (4.385 kW)and battery storage (480Ah/48V) facility, fulfills daily energy needs in residential load level. This study provides a good platform to develop an effective and reliable stand-alone MG power system for the remote communities in the near future.

Simulation and hardware implementation of new maximum power point tracking technique for partially shaded PV system using hybrid DEPSO method

In photovoltaic (PV) power generation, partial shading is an unavoidable complication that significantly reduces the efficiency of the overall system. Under this condition, the PV system produces a multiple-peak function in its output power characteristic. Thus, a reliable technique is required to track the global maximum power point (GMPP) within an appropriate time. This study aims to employ a hybrid evolutionary algorithm called the DEPSO technique, a combination of the differential evolutionary (DE) algorithm and particle swarm optimization (PSO), to detect the maximum power point under partial shading conditions. The paper starts with a brief description about the behavior of PV systems under partial shading conditions. Then, the DEPSO technique along with its implementation in maximum power point tracking (MPPT) is explained in detail. Finally, Simulation and experimental results are presented to verify the performance of the proposed technique under different partial shading conditions. Results prove the advantages of the proposed method, such as its reliability, system-independence, and accuracy in tracking the GMPP under partial shading conditions.