Nonlinear adaptive excitation controller design for multimachine power systems

This paper presents a nonlinear adaptive excitation control scheme to enhance the dynamic stability of multimachine power systems. The proposed controller is designed based on the adaptive backstepping technique where the mechanical power input to the generators and the damping coefficient of each generator are considered as unknown. These unknown quantities are estimated through the adaption laws. The adaption laws are obtained from the formulation of Lyapunov functions which guarantee the convergence of different physical quantities of generators such as the relative speed, terminal voltage, and electrical power output. The proposed scheme is evaluated by applying a three-phase short-circuit fault at one of the key transmission lines in an 11-bus test power system and compared with an existing backstepping controller and conventional power system stabilizer (CPSS). Simulation results show that the proposed scheme is much more effective than existing controllers.

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.

Predicting migratory flight altitudes by physiological migration models

Using the altitudinal profiles of wind, temperature, pressure, and humidity in three flight models, we tried to explain the altitudinal distributions of nocturnal migrants recorded by radar above a desert in southern Israel. In the simplest model, only the tailwind component was used as a predictor of the most preferred flight altitude (T model). The energy model (E model) predicted flight ranges according to mechanical power consumption in flapping flight depending on air density and wind conditions, assuming optimal adjustment of airspeed and compensation of crosswinds, and including the influence of mass loss during flight. The energy-water model (EW model) used the same assumptions and parameters as the E model but also included restrictions caused by dehydration. Because wind was by far the most important factor governing altitudinal distribution of nocturnal migrants, differences in predictions of the three models were small. In a first approach, the EW model performed slightly better than the E model, and both performed slightly better than the T model. Differences were most pronounced in spring, when migrants should fly high according to wind conditions, but when climbing and descending they must cross lower altitudes where conditions are better with respect to dehydration. A simplified energy model (Es model) that omits the effect of air density on flight costs explained the same amount of variance in flight altitude as the more complicated E and EW models. By omitting the effect of air density, the Es model predicted lower flight altitudes and thus compensated for factors that generally bias height distributions downward but are not considered in the models (i.e. climb and descent through lower air layers, cost of ascent, and decrease of oxygen partial pressure with altitude). Our results confirm that wind profiles, and thus energy rather than water limitations, govern the altitudinal distribution of nocturnal migrants, even under the extreme humidity and temperature conditions in the trade wind zone.

Power analysis and simulation of a vehicle under combined loads

This paper presents an analytical model of fuel consumption (AMFC) to coordinate the driving power and manage the overall fuel consumption for an internal combustion engine vehicle. The model calculates the different loads applied on the vehicle including road-slope, road-friction, wind-drag, accessories, and mechanical losses. Also, it solves the combustion equation of the engine under different working conditions including various fuel compositions, excess airs and air inlet temperatures. Then it determines the contribution of each load to signify the energy distribution and power flows of the vehicle. Unlike the conventional models in which the vehicle speed needs to be given as an input, the developed model can predict the vehicle speed and acceleration under different working conditions by allowing the speed to vary within a predefined range only. Furthermore, the model indicates the ways to minimises the vehicles' fuel consumption under various driving conditions. The results show that the model has the potential to assist in the vehicle energy management.

Power generation from randomly oriented electrospun nanofiber membranes

Randomly orientated electrospun poly(vinylidene fluoride) nanofiber membranes were directly used as active layers to make mechanical-to-electrical energy conversion devices. Without any extra poling treatment, the device can generate high electrical outputs upon receiving a mechanical impact. The device also showed long-term working stability and ability to drive electronic devices. Such a nanofiber membrane device may serve as a simple but efficient energy source for self-powered electronics.

Enhanced mechanical energy harvesting using needleless electrospun poly(vinylidene fluoride) nanofibre web

Randomly oriented poly(vinylidene fluoride) (PVDF) nanofibre webs prepared by a needleless electrospinning technique were used as an active layer for making mechanical-to-electrical energy harvest devices. With increasing the applied voltage in the electrospinning process, a higher b crystal phase was formed in the resulting PVDF nanofibres, leading to enhanced mechanical-to-electrical energy conversion of the devices. The power generated by the nanofibre devices was able to drive a miniature Peltier cooler, which may be useful for the development of mechanically driven cooling textile. In addition, the needleless electrospinning also showed great potential in the production of nanofibres on a large scale.

Analyzing track sprint cyclists' performances using position-specific maximal-torque and power-cadence relationships

Previous studies have demonstrated the importance of maximal Torque-Cadence (T-C) and Power-Cadence (P-C) relationships, for the performances of world class track sprint cyclists. If these relationships are affected by the function of the lower limb muscles, the ability of cyclists to generate torque and power at a given cadence may vary depending on their riding position. During sprint events (individual and team sprints and Keirin), cyclists alternate between standing and seated positions. The T-C and P-C relationships may change with the position adopted by the cyclists. PURPOSE: The aim of this study was to evaluate the necessity to define position specific maximal T-C and P-C relationships. METHODS: Eight junior elite track cyclists from the National Talent Identification squad undertook two inertial-load tests that consisted of four all-out sprints each. One test was undertaken at the velodrome in a standing position on a carbon fibre track bike, and the other test was completed in a seated position on an air-braked stationary ergometer. A calibrated SRM power meter interfaced to a custom instrumentation package was used for all mechanical measurements. Maximal T-C and P-C relationships were analysed to calculate maximal Torque (T0), maximal Power (Pmax) and optimal pedalling cadence (PCopt). RESULTS: All individual T-C and P-C relationships obtained for both body positions were fitted by linear regressions (r2=0.95 ± 0.02) and second order polynomials (r2=0.96 ± 0.01), respectively. T0 was higher (209 ± 2.2N.m vs. 177.0 ± 3.9N.m, p<0.05), PCopt was lower (112.5 ± 11.4rpm vs. 120.1 ± 6.7rpm, p<0.05), and Pmax was higher (1261 ± 235W vs. 1076 ± 183W, p<0.05) in standing position compared to seated position. CONCLUSION: Analysis of track sprint cyclists’ performances can be improved by the determination of position-specific maximal T-C and P-C relationships .

Power quality impacts in a typical microgrid

Microgrid (MG) power system plays an important role to fulfill reliable and secure energy supply to critical loads of communities as well as for communities in remote area. Distributed Generation (DG) sources integrated in a MG provides numerous benefits, at the same time leads to power quality issues in the MG power distribution network. Power Quality (PQ) issue arises due to the integration of an intermittent nature of Renewable Energy (RE) sources with advanced Power Electronics (PE) converter technology. Also, presence of non-linear and unbalancing loads in MG seems to affect PQ of the energy supply in power distribution network. In this paper, PQ impacts like; power variation, voltage variation, Total Harmonic Distortion (THD), and Unbalance voltage level have been analysed in Low Voltage (LV) distribution network of typical MG power system model. In this study, development of MG model and PQ impact analysis through simulation has been done in PSS-Sincal software environment. Analysis results from the study can be used as a guideline for developing a real and independent MG power system with improved PQ conditions.

Impacts of integration of wind and solar PV in a typical power network

Integration of solar PV and wind in to the distribution network is one of the most promising challenges of the modern power system networks to meet the growing demand of energy. Analysis of the effects of solar and wind intermittencies in the network are vital to maintain the power quality. Keeping this in view, this research paper focuses on impact analysis study of a typical power network with hybrid generation: solar PV and wind integration to quantify the level of impacts like power variation and voltage variation in the network through load flow analysis. Initially, a typical network model is developed using PSS-SINCAL and load profile analysis has been carried out based on the typical daily load profile and wind/solar profile to verify the power and voltage variations extensively in the network considering different scenarios. Results of this research analysis can be used as guidelines for utility grid to provide regulated and improved quality of energy supply by implementing appropriate planning of generation reserve and other control measures in the network