Output Power Variation Research Articles

Smoothing the Power Output of a Wind Turbine Group with a Compensation Strategy of Power Variation

This paper proposes a new scheme to reduce the output power variation range of a wind turbine group without an energy storage system. This proposal is based on the active power compensation principle for each wind turbine. In this research, the wind turbine operates in the active power control mode. The reference active power is calculated in such a way that it compensates for the difference between the average output power and the actual output power. To verify and evaluate the proposed method, we simulated a group of two 1.5MW-wind turbines in the Simulink environment of MATLAB. Simulation results were compared to the ones of a wind turbine group without any smoothing scheme and the ones of the same group with the Exponential Moving Average method. From this comparison, we can conclude that with the proposed method, the actual output power of the wind turbine group becomes smoother than that of the wind turbine group without any smoothing scheme. Moreover, the performance of the wind turbine group with the proposed method is better than that of the wind turbine group with the Exponential Moving Average method.

Performance investigation of a thermoelectric generator system applied in automobile exhaust waste heat recovery

In this paper, a novel fluid-thermal-electric multiphysics numerical model is presented to predict the performance of a thermoelectric generator system applied in automobile waste heat recovery. The model considers the complete geometry, temperature-dependent material properties, topological connection among thermoelectric modules, and impedance matching, which can simulate the actual working conditions. Numerical simulations are carried out on the COMSOL platform combined with the exhaust temperature and exhaust mass flow rate under different vehicle speeds. In addition, the detailed physical field distribution characteristics of the automobile thermoelectric generator system, as well as the variations of output power, conversion efficiency, power losses, and net power with vehicle speed, are obtained. The position of thermoelectric modules on the hot side heat exchanger plays an important role in output uniformity, and the higher the vehicle speed is, the more uniform the output will be. At the vehicle speed of 120 km h−1, the output power and conversion efficiency of the automobile thermoelectric generator system are 38.07 W and 1.53% respectively. Considering the weight power loss and coolant pumping power loss, the net power is 23.66 W. This work fills the gap in evaluating the performance of automobile thermoelectric generator systems at different vehicle speeds comprehensively.

Low Spatial Peak-to-Average Power Ratio Transmission for Improved Energy Efficiency in Massive MIMO Systems.

A significant portion of the operating power of a base station is consumed by power amplifiers (PAs). Much of this power is dissipated in the form of heat, as the overall efficiency of currently deployed PAs is typically very low. This is because the structure of conventional precoding techniques typically results in a relatively high variation in output power at different antennas in the array, and many PAs are operated well below saturation to avoid distortion of the transmitted signals. In this work, we use a realistic model for power consumption in PAs and study the impact of power variation across antennas in the array on the energy efficiency of a massive MIMO downlink system. We introduce a family of linear precoding matrices that allow us to control the spatial peak-to-average power ratio by projecting a fraction of the transmitted power onto the null space of the channel. These precoding matrices preserve the structure of conventional precoders; e.g., they suppress multiuser interference when used together with zeroforcing precoding and bring advantages over these precoders by operating PAs in a more power-efficient region and reducing the total radiated distortion. Our numerical results show that by controlling the power variations between antennas in the array and incorporating the nonlinearity properties of PA into the precoder optimization, significant gains in energy efficiency can be achieved over conventional precoding techniques.

Wavelength-tunable L-band mode-locked fiber laser using a long-period fiber grating

We demonstrate an L-band wavelength-tunable passively mode-locked fiber laser using a single long-period fiber grating (LPFG) as a narrow-band optical attenuator (NBOA). Through bending the LPFG, the central wavelength can be continuously tuned from 1582.02 to 1597.29 nm, while the output power only varies from 1.465 to 1.057 mW, approximately a rate of 22 µW/nm variation. This is the first time that LPFG is functioned as a NBOA in mode-locked fiber lasers, showing the great advantage of less impact on output power variation reduction. Besides, the total cavity length is 5.08 m, which is the shortest length yet reported in wavelength-tunable mode-locked fiber lasers. The wavelength tuning could also be realized at harmonic mode locking with tuning range of 14.69 nm under 5th harmonic.

Wave energy harvesting impulse turbine having ring type blade: Experiments with unsteady flow

Oscillating water column (OWC) wave energy converters employ air turbines coupled with an electrical generator to convert the wave energy into electrical energy. In the present study, a ring-type axial flow impulse turbine of diameter 196 mm was manufactured to carry out the experiments in an unsteady flow test rig. The tests were done for the stroke lengths (SL) of 0.2m, 0.3m, and 0.4m, and the periods (TP) varied from 6 to 12 s. A rheostat was connected to the generator, and the turbine pressure drop and power output variations were recorded for different generator loading conditions. The flow rates for the exhalation phase were measured and time-series analysis of the pressure drop and rotor speed was done. A suitable resistive load was found out for obtaining the highest power output. A relationship between average power and average pressure drop was established. Furthermore, a relationship was established between the turbine pressure coefficient and the turbine power coefficient. Lastly, a study on damping characteristics of the turbine was also done to study the effect of damping on the turbine's overall performance.

Predicting the Performance of Solar Power Generation Using Deep Learning Methods

In recent years, many countries have provided promotion policies related to renewable energy in order to take advantage of the environmental factors of sufficient sunlight. However, the application of solar energy in the power grid also has disadvantages. The most obvious is the variability of power output, which will put pressure on the system. As more grid reserves are needed to compensate for fluctuations in power output, the variable nature of solar power may hinder further deployment. Besides, one of the main issues surrounding solar energy is the variability and unpredictability of sunlight. If it is cloudy or covered by clouds during the day, the photovoltaic cell cannot produce satisfactory electricity. How to collect relevant factors (variables) and data to make predictions so that the solar system can increase the power generation of solar power plants is an important topic that every solar supplier is constantly thinking about. The view is taken, therefore, in this work, we utilized the historical monitoring data collected by the ground-connected solar power plants to predict the power generation, using daily characteristics (24 h) to replace the usual seasonal characteristics (365 days) as the experimental basis. Further, we implemented daily numerical prediction of the whole-point power generation. The preliminary experimental evaluations demonstrate that our developed method is sensible, allowing for exploring the performance of solar power prediction.

Local topography‐induced pressure gradient effects on the wake and power output of a model wind turbine

Wind-tunnel experiments were performed to study the effect of favorable and adverse constant pressure gradients (PG) from local changes in the topography right downwind of a model wind turbine. Particle image velocimetry was used to characterize the near and intermediate wake regions. We explored five scenarios, two favorable, two adverse PG, and a case with negligible PG. Results show that the PGs induce a wake deflection and modulate the wake. They imposed a relatively small impact on the turbulence kinetic energy and kinematic shear stress but a comparatively dominant effect on the bulk flow on the flow recovery. Based on this, a simple formulation is used to describe the impact of PG on the wake. We modeled the base flow through a linearized perturbation method; the wake is obtained by solving a simplified, integrated streamwise momentum equation. This approach reasonably estimated the flow profile and PG-induced power output variations.

간헐성과 변동성을 가진 풍력출력 변동 완화를 위한 제어기 알고리즘 성능과 배터리 용량 분석

With the significant renewable energy penetration, the power output fluctuation could result in the power quality problems. Especially, to improve the power grid’s stability, it is considerable concern that the intermittent and variable power output of renewable energy plants needs the large-scale Energy Storage System(ESS). In this study, the Moving Average(MA) filter and the First-order Low Pass Filter(LPF) are investigated for less output power fluctuation and smaller battery energy capacity, based on the smoothness of each mitigated wind power output and the corresponding energy profile during charge/discharge operations. Moreover, the effect of the Ramp Rate(RR) on the battery energy capacity is analyzed varying with the smoothing filter, to reduce the rate of change of the smoothed wind power fluctuation. MA filter has the similar power smoothing performance as that of LPF with much less battery energy capacity. Moreover, the consecutive MA filter and RR control require less battery energy capacity than consecutive LPF and RR control. Also, the battery capacity for mitigation of the intermittent wind power output fluctuation depends on the constraint rate and the filter type. However, the filter type has little influence on the battery capacity to mitigate the variable wind power output fluctuation at a constraint rate more than 20%.

Experimental implementation of a novel scheduling algorithm for adaptive and modified P&O MPPT controller using fuzzy logic for WECS

SummaryThis article proposes an adaptive and modified Perturb and Observe (P&O) maximum power point tracking (MPPT) algorithm, using fuzzy logic step size controller, for a wind energy conversion system (WECS) based on wound rotor synchronous generator. The modified P&O controller uses additional current information of the dc‐link, to decrease power oscillation around MPP, and choose the correct direction of the perturbation, while wind speed increase condition, depending on the sign of dc‐link current change. So, in this contribution, a modified drift‐free P&O algorithm was chosen because it gives better results, but the duty cycle step size in the proposed MPPT controller has been varied adaptively, using a fuzzy logic inference system based on the variation of the rectifier output power and the previous change of the duty cycle to get fast convergence until the MPP is reached in increasing and decreasing wind speed conditions. Performances and robustness of the proposed speed sensorless MPPT controller are evaluated in an experiment implementation, using a WECS emulator and dSpace DS1104 controller board, where experimental results show that the proposed method guarantees fast convergence with better energy quality and high robustness against speed or load change conditions.

Studying the Impact of the Temperature and Sorbed Water during Microwave-Induced In Situ Amorphization: A Case Study of Celecoxib and Polyvinylpyrrolidone.

Microwave-induced in situ amorphization of a drug into a polymeric amorphous solid dispersion (ASD) has been suggested to follow a dissolution process of the drug into the polymeric network, at temperatures above the glass transition temperature (Tg) of the polymer. Thus, increasing the compact temperature, above the Tg of the polymer, is expected to increase the rate of drug dissolution in the mobile polymer, i.e., the rate of amorphization, in a direct proportional fashion. To test this hypothesis, the present study aimed at establishing a linear correlation between the compact temperature and the rate of drug amorphization using celecoxib (CCX) and the polymers polyvinylpyrrolidone (PVP) 12 and PVP17 as the model systems. Water sorbed into the drug–polymer compacts during 2 weeks of storage at 75% relative humidity was used as the dielectric heating source for the present drug amorphization process, and therefore directly affected the compact temperature during exposure to microwave radiation; the loss of water during heating was also studied. For this, compacts prepared with 30 wt% CCX, 69.5 wt% PVP12 or PVP17 and 0.5 wt% magnesium stearate (lubricant) were conditioned to have a final water content of approx. 20 wt%. The conditioned compacts were exposed to microwave radiation for 10 min at variable power outputs to achieve different compact temperatures. For compacts containing CCX in both PVP12 and PVP17, a linear correlation was established between the measured compact end temperature and the rate of drug amorphization during 10 min of exposure to microwave radiation. For compacts containing CCX in PVP12, a fully amorphous ASD was obtained after 10 min of exposure to microwave radiation with a measured compact end temperature of 71 °C. For compacts containing CCX in PVP17, it was not possible to obtain a fully amorphous ASD. The reason for this is most likely that a fast evaporation of the sorbed water increased the Tg of the conditioned drug–polymer compacts to temperatures above the highest reachable compact temperature during exposure to microwave radiation in the utilized experimental setup. Supporting this conclusion, evaporation of the sorbed water was observed to be faster for compacts containing PVP17 compared to compacts containing PVP12.

Study of Neutronic Performance of Sodium-Cooled Fast Reactor Design for Various Output Power Using Radial Fuel Shuffling Strategy

Study of neutronic performance analysis of Sodium-Cooled Fast Reactor (SFR) design based on the variations of output power using radial fuel suffling strategy has been performed. SFR is a type of the generation IV reactor that is widely researched for application on a commercial scale. The reactor design uses natural uranium as a fuel and Sodium as a coolant. The research has been carried out by using the SRAC code and JENDL-3.2 as a library with two dimensional R- Z suffling strategy of cylinder core for variations of power output 300, 350, 400, 450 and 500 MWTh. The neutronic parameters such as a multiplication factor (k-eff and k-inf) and burn-up analysis are observed. The SFR core is separated into 10 regions having the same volume fraction in the radial direction. At beginning of burn-up process, the reactor core is only filled with natural uranium fuel called fresh fuel and prepared for the one cycle of 10 years of burn-up time. The burn-up result in the first region is shifted into the second region, the burn-up result in the second region is shifted into the third region, and so on until burn-up result into the tenth region. The burn-up result in the tenth region is removed from the reactor core, then the first region can be filled with fresh natural uranium fuel and so on up to 10 times fuel cycles of reactor operation. The neutron calculation results indicate that the multiplication factors (k-eff and k-inf) in a critical condition are occurred on the 300 MWTh of output power. Overall, the output power of 300 MWTh has requirements and a greater chance of being operated for SFR designed.

Grid Support Benefits of Solar PV Systems as STATCOM (PV-STATCOM) Through Converter Control: Grid Integration Challenges of Solar PV Power Systems

Inverter-based resources (IBRs) such as solar PV systems and wind power systems are experiencing a phenomenal growth worldwide in an effort to minimize carbon emissions. It is anticipated by the International Renewable Energy Agency that by 2050 about 35% of world?s electricity will be provided by solar PV systems. Increasingly ambitious targets are being set by various countries to achieve 100% renewable power generation in narrowing time horizons. However, IBRs present unique integration challenges that include: 1) an increase in steady-state voltages resulting in reduced hosting capacity of solar systems, 2) voltage fluctuations, 3) reverse power flows, 4) interaction with conventional voltage regulation equipment, 5) variability of power output, 6) balancing power supply and demand, 7) changes in active power flow in feeders, 8) increased line losses, 9) harmonic injections, 10) protection and control issues, 11) reduced short circuit current issues, 12) unintentional islanding; and so on. Displacement of conventional fossil-fired generating systems by IBRs and also high penetration of the latter causes frequency regulation issues and an increase in power oscillations due to a reduction in overall system inertia.

Capacity Value from Wind and Solar Sources in Systems with Variable Dispatchable Capacity—An Application in the Brazilian Hydrothermal System

The most robust methods to determine the capacity contribution from intermittent sources combine load curve, variable generation profile, and dispatchable generators’ data to calculate any new inserted variable source’s capacity value in the power system. However, these methods invariably adopt the premise that the system’s dispatchable generators’ capacity is constant. That is an unacceptable limitation when the energy mix has a large share of hydroelectric sources. Hydroelectric plants are dispatchable sources with variable maximum power output over time, varying mainly according to the reservoirs’ level. This article develops a method that makes it possible to calculate the capacity value from renewable resources when the dispatchable generation units of an electric system have variable capacity. The authors apply the method to calculate the capacity value from solar and wind sources in Brazil as an exercise. By abandoning the hypothesis of constant dispatchable capacity, the developed approach is in principle extensible for other energy-limited resources, such as batteries and concentrating solar power (CSP). This can be a strategy to incorporate energy-limited capacity sources into the planning and operation models as reliable capacity sources.

Spatiotemporal Graph Neural Network for Performance Prediction of Photovoltaic Power Systems

In recent years, a large number of photovoltaic (PV) systems have been added to the electrical grid as well as installed as off-grid systems. The trend suggests that the deployment of PV systems will continue to rise in the future. Thus, accurate forecasting of PV performance is critical for the reliability of PV systems. Due to the complex non-linear variability in power output of the PV systems, forecasting PV power is a non-trivial task. This variability affects the stability and planning of a power system network, and accurate forecasting of the performance of the PV system can reduce the uncertainty caused during PV operation. In this work, we leverage spatial and temporal coherence among the power plants for PV power forecasting. Our approach is motivated by the observation that power plants in a region undergo similar environmental exposure. Thus, one power plant’s performance can help improve the forecast of other power plants' power values in the region. We utilize the relationship between PV plants to build a spatiotemporal graph neural network (st-GNN) and train machine learning models to forecast the PV power. The computational experiments on large-scale data from a network of 316 systems show that spatiotemporal forecasting of PV power performs significantly better than a model that only applies temporal convolution to isolated systems or nodes. Furthermore, the longer the future forecast time, the difference between the spatiotemporal forecasting and the isolated system forecast when only temporal convolution is applied increases further.

Passively Q-switched erbium-doped fiber laser with mechanical exfoliation of 8-HQCDCL2H2O as saturable absorber

In this work, we have experimentally reported passively Q-switched erbium-doped fiber laser (EDFL) by incorporating 8-Hydroxyquonolino cadmium chloride hydrate (8-HQCDCL2H2O) as saturable absorber (SA). The 8-HQCDCL2H2O SA was prepared by mechanical exfoliation using the scotch tape. The SA was then incorporated in two different EDFL’s cavity configurations having different output couplers. First, the fiber laser generated a high output power of 23.4 mW and pulse energy of 172 nJ by using a 50:50 output coupler in the EDFL setup. Then, after changing the output coupler from 50/50–95/05, the pulse width was reduced to 1.66 µs and repetition rate increased to 173 kHz. The variation in output power, pulse width and pulse repetition rate was observed with the change in output couplers. To the best of author`s knowledge, 8-HQCDCL2H2O is mechanically exfoliated for the first time to be used as SA.

Impact of optimal power generation scheduling for operating cleaner hybrid power systems with energy storage

De-carbonization of the electric power system, reduction in greenhouse gas emissions and the enhancement of environmental security have emphasized the need for the optimal utilization of renewable/cleaner energy in power system operation. However, unpredictability and intermittency are the major barriers that limit the penetration of renewable power generation (RPG). In this context, large-scale energy storage (LSES) facilities may prove to be an effective means for mitigating the long-term volatility and vulnerability of RPG and subsequently reduce the power dependence on fossil fuel-based generation systems. Thus, the possibility of increasing the penetration of cleaner power may be achieved by simultaneously implementing LSES and an intelligent scheduling strategy so that the hybrid power system may be operated with lower power loss, more cost-effective operation, and an enhanced voltage security. Previous researchers in multiple works have demonstrated the operational analysis and optimization of hybrid configurations with and without storage in stand-alone, islanded and remote operations. In contrast, attempts have been made in this work to incorporate, analyse and validate the impact of LSES facilities (ie, pumped hydroelectric storage (PHS) and compressed air energy storage (CAES)) with benchmark power grid configuration (ie, New-England-39 bus).In this work, a comparative analysis among different hybrid configurations, particularly wind-solar-thermal, wind-solar-hydro-thermal, wind-solar-hydro-thermal-PHS and wind-solar-hydro-thermal-CAES is conducted within a multi-objective optimization environment. The proposed design problem is analysed with the inclusion of real-time constrictions in the form of stochastic variation in renewable power output and random disruptions. The modified bacteria foraging algorithm is used to evaluate the optimum generation schedule for which the operational objectives will be achieved for the design problem. Further, using fuzzy membership function, the trade-off between conflicting objectives is portrayed in Pareto optimal domain. Among different hybrid configurations considered, the HPS which incorporates the CAES system exhibits the most superior performance.

Voltage stability assessment of isolated hybrid dish-stirling solar thermal-diesel microgrid with STATCOM using mine blast algorithm

This paper presents the voltage control of an isolated hybrid diesel-dish-Stirling solar thermal system (DSP) based power system. As DSP is employed with an induction generator (IG), it needs reactive power for magnetic field. Though synchronous generator (SG) is coupled with the diesel generator, SG alone unable to supply sufficient reactive power to cater the reactive power requirement of the consumers load and the IG. Under such circumstances, static synchronous compensator (STATCOM) is used to meet the reactive power demand. The parameters of the controllers employed with the STATCOM as well as automatic voltage regulator (AVR) of the SG are tuned simultaneously applying recently developed mine blast algorithm (MBA). Performance of the MBA based controllers are compared with that of the cuckoo search algorithm (CS), and particle swarm optimization (PSO) based counterpart on the proposed model. Application of STATCOM and MBA based control strategy in diesel-dish-Stirling solar thermal system-based hybrid system for reactive power regulation is a maiden attempt. Extensive simulations of the model for dynamic responses of voltage deviations and reactive deviations under several uncertain conditions, such as step disturbance in reactive power load of the consumers and IG without/ with STATCOM, realistic variations of power output of DSP and reactive load have been carried out. Results analyses indicate that MBA based control strategy is the best amongst all the control strategies attempted here in the terms of maximum overshoot and the settling time. Further, meager values of the maximum overshoot and the settling time under several uncertain conditions justify the coordinated control of AVR and STATCOM to maintain the voltage stability of the isolated hybrid system.

Power ramp rates and variability of individual and aggregate photovoltaic systems using measured production data at the municipal scale

Intermittency from photovoltaic systems can negatively impact electricity grid stability due to increased power ramp rates and temporal misalignment between generation and load. Distributed systems, especially rooftop residential systems, present a range of orientations and spatial separation that when aggregated introduce temporal diversity. If these features reduce negative impacts, they should be weighed against increased costs per delivered energy compared to larger commercial/industrial systems. We compare power production data from 60 distributed residential PV systems spread across a large municipality with medium and large commercial rooftop systems located centrally in the municipality. Power ramp rates and power output variability were calculated. The aggregated distributed residential system ramp rates never exceed 13% per 5 min, while the medium/large commercial systems experienced ramp rates up to 61% and 68% per 5 min. In aggregate the residential output variability is 3 times lower than the commercial sites. Consistent with previous literature the output variability decreases as the number of systems grows. There are however diminishing returns due to the limited geographic area, with a relative output variability for the municipality approaching 20% of the variability of a single system. Residential data was scaled up to represent 10% of electrical load and resulted in 10% more electricity grid ramp rates exceeding ±5 MW per 5 min compared to baseline. Finally, a comparison between pyranometer and photovoltaic system ramps rates shows the latter are less severe, likely because pyranometers are single points sources.

Analysis and Control of Current-Fed Integrated Dual-DC Boost Converter Topology

This article introduces a dual-input single-output dc–dc power electronic converter topology to interface two independent sources into a common output. The proposed converter is denoted as integrated dual-dc boost converter (IDDBC), and this topology provides step-up conversions for both inputs using three controllable switches. Due to its architecture, IDDBC can be adapted to provide uninterrupted power (realizing a dispatchable system) even if any one of the two input sources are unavailable or has significant output power variation. The steady-state analysis, modeling, and design of the converter are presented, and a pulsewidth-modulation control scheme is proposed. The closed-loop control system for the converter consists of voltage-mode control for output and current-mode control for one-source input current. The behavior of converter operation is validated through experimentation on a digital-signal-processor-based laboratory prototype.

The Physiological, Neuromuscular, and Perceptual Response to Even- and Variable-Paced 10-km Cycling Time Trials.

During self-paced (SP) time trials (TTs), cyclists show unconscious nonrandom variations in power output of up to 10% above and below average. It is unknown what the effects of variations in power output of this magnitude are on physiological, neuromuscular, and perceptual variables. To describe physiological, neuromuscular, and perceptual responses of 10-km TTs with an imposed even-paced (EP) and variable-paced (VP) workload. Healthy male, trained, task-habituated cyclists (N = 9) completed three 10-km TTs. First, an SP TT was completed, the mean workload from which was used as the mean workload of the EP and VP TTs. The EP was performed with an imposed even workload, while VP was performed with imposed variations in workload of ±10% of the mean. In EP and VP, cardiorespiratory, neuromuscular, and perceptual variables were measured. Mean rating of perceived exertion was significantly lower in VP (6.13 [1.16]) compared with EP (6.75 [1.24]), P = .014. No mean differences were found for cardiorespiratory and almost all neuromuscular variables. However, differences were found at individual kilometers corresponding to power-output differences between pacing strategies. Variations in power output during TTs of ±10%, simulating natural variations in power output that are present during SP TTs, evoke minor changes in cardiorespiratory and neuromuscular responses and mostly affect the perceptual response. Rating of perceived exertion is lower when simulating natural variations in power output, compared with EP cycling. The imposed variations in workload seem to provide a psychological rather than a physiological or neuromuscular advantage.