scholarly journals Improved Synthesis of Global Irradiance with One-Minute Resolution for PV System Simulations

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Martin Hofmann ◽  
Stefan Riechelmann ◽  
Cristian Crisosto ◽  
Riyad Mubarak ◽  
Gunther Seckmeyer
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Transition Probability ◽  
Weather Condition ◽  
Weather Conditions ◽  
Pv System ◽  
High Resolution Data ◽  
Frequency Distributions ◽  
Global Irradiance ◽  
Mean Square Errors

High resolution global irradiance time series are needed for accurate simulations of photovoltaic (PV) systems, since the typical volatile PV power output induced by fast irradiance changes cannot be simulated properly with commonly available hourly averages of global irradiance. We present a two-step algorithm that is capable of synthesizing one-minute global irradiance time series based on hourly averaged datasets. The algorithm is initialized by deriving characteristic transition probability matrices (TPM) for different weather conditions (cloudless, broken clouds and overcast) from a large number of high resolution measurements. Once initialized, the algorithm is location-independent and capable of synthesizing one-minute values based on hourly averaged global irradiance of any desired location. The one-minute time series are derived by discrete-time Markov chains based on a TPM that matches the weather condition of the input dataset. One-minute time series generated with the presented algorithm are compared with measured high resolution data and show a better agreement compared to two existing synthesizing algorithms in terms of temporal variability and characteristic frequency distributions of global irradiance and clearness index values. A comparison based on measurements performed in Lindenberg, Germany, and Carpentras, France, shows a reduction of the frequency distribution root mean square errors of more than 60% compared to the two existing synthesizing algorithms.

scholarly journals Evaluating the Experimental High-Resolution Rapid Refresh–Alaska Modeling System Using USArray Pressure Observations

2018 ◽  
Vol 33 (4) ◽  
pp. 933-953 ◽  
Author(s):  
Taylor A. McCorkle ◽  
John D. Horel ◽  
Alexander A. Jacques ◽  
Trevor Alcott
Keyword(s):  
High Resolution ◽  
Surface Pressure ◽  
Weather Conditions ◽  
Horizontal Resolution ◽  
Production Cycle ◽  
Downslope Winds ◽  
Downslope Wind ◽  
Wind Events ◽  
Environmental Prediction ◽  
Mean Square Errors

Abstract The High-Resolution Rapid Refresh–Alaska (HRRR-AK) modeling system provides 3-km horizontal resolution and 0–36-h forecast guidance for weather conditions over Alaska. This study evaluated the experimental version of the HRRR-AK system available from December 2016 to June 2017, prior to its operational deployment by the National Centers for Environmental Prediction in July 2018. Surface pressure observations from 158 National Weather Service (NWS) stations assimilated during the model’s production cycle and pressure observations from 101 USArray Transportable Array (TA) stations that were not assimilated were used to evaluate 265 complete 0–36-h forecasts of the altimeter setting (surface pressure reduced to sea level). The TA network is the largest recent expansion of Alaskan weather observations and provides an independent evaluation of the model’s performance during this period. Throughout the study period, systematic differences in altimeter setting between the HRRR-AK 0-h forecasts were larger relative to the unassimilated TA observations than relative to the assimilated NWS observations. Upon removal of these initial biases from each of the subsequent 1–36-h altimeter setting forecasts, the model’s 36-h forecast root-mean-square errors at the NWS and TA locations were comparable. The model’s treatment of rapid warming and downslope winds that developed in the lee of the Alaska Range during 12–15 February is examined. The HRRR-AK 0-h forecasts were used to diagnose the synoptic and mesoscale conditions during this period. The model forecasts underestimated the abrupt increases in the temperature and intensity of the downslope winds with smaller errors as the downslope wind events evolved.

scholarly journals Calibration of NSRP Models from Extreme Value Distributions

Hydrology ◽  
2019 ◽  
Vol 6 (4) ◽  
pp. 89 ◽  
Author(s):  
De Luca ◽  
Galasso
Keyword(s):  
High Resolution ◽  
Probability Distributions ◽  
Mathematical Expression ◽  
Extreme Value ◽  
Extreme Value Distributions ◽  
Data Set ◽  
Maximum Rainfall ◽  
High Resolution Data ◽  
Frequency Distributions ◽  
Annual Maximum Rainfall

In this work, the authors investigated the feasibility of calibrating a model which is suitable for the generation of continuous high-resolution rainfall series, by using only data from annual maximum rainfall (AMR) series, which are usually longer than continuous high-resolution data, or they are the unique available data set for many locations. In detail, the basic version of the Neyman–Scott Rectangular Pulses (NSRP) model was considered, and numerical experiments were carried out, in order to analyze which parameters can mostly influence the extreme value frequency distributions, and whether heavy rainfall reproduction can be improved with respect to the usual calibration with continuous data. The obtained results were highly promising, as the authors found acceptable relationships among extreme value distributions and statistical properties of intensity and duration for the pulses. Moreover, the proposed procedure is flexible, and it is clearly applicable for a generic rainfall generator, in which probability distributions and shape of the pulses, and extreme value distributions can assume any mathematical expression.

scholarly journals Tailored Algorithms for Anomaly Detection in Photovoltaic Systems

Energies ◽  
2020 ◽  
Vol 13 (1) ◽  
pp. 225 ◽  
Author(s):  
Pedro Branco ◽  
Francisco Gonçalves ◽  
Ana Cristina Costa
Keyword(s):  
Time Series ◽  
Alternative Energy ◽  
Weather Conditions ◽  
Electricity Production ◽  
Pv System ◽  
Detection Algorithms ◽  
Pv Systems ◽  
Adverse Weather ◽  
Full Capacity ◽  
And Performance

The fastest-growing renewable source of energy is solar photovoltaic (PV) energy, which is likely to become the largest electricity source in the world by 2050. In order to be a viable alternative energy source, PV systems should maximise their efficiency and operate flawlessly. However, in practice, many PV systems do not operate at their full capacity due to several types of anomalies. We propose tailored algorithms for the detection of different PV system anomalies, including suboptimal orientation, daytime and sunrise/sunset shading, brief and sustained daytime zero-production, and low maximum production. Furthermore, we establish simple metrics to assess the severity of suboptimal orientation and daytime shading. The proposed detection algorithms were applied to a set of time-series of electricity production in Portugal, which are based on two periods with distinct weather conditions. Under favourable weather conditions, the algorithms successfully detected most of the time-series labelled with either daytime or sunrise/sunset shading, and with either sustained or brief daytime zero-production. There was a relatively low percentage of false positives, such that most of the anomaly detections were correct. As expected, the algorithms tend to be more robust under favourable rather than under adverse weather conditions. The proposed algorithms may prove to be useful not only to research specialists, but also to energy utilities and owners of small- and medium-sized PV systems, who may thereby effortlessly monitor their operation and performance.

scholarly journals Mode Determination by Fourier Analysis of Line-Profile Variations: Application to τ Peg

1993 ◽  
Vol 139 ◽  
pp. 147-147
Author(s):  
E.J. Kennelly ◽  
G.A.H. Walker ◽  
W.J. Merryfield ◽  
J.M. Matthews
Keyword(s):  
Time Series ◽  
High Resolution ◽  
Line Profiles ◽  
High Resolution Data ◽  
Low Degree ◽  
Scuti Star ◽  
High Degree ◽  
Scuti Stars ◽  
Resolution Data ◽  
Good Agreement

AbstractThe identification of modes of oscillation is an important first step towards the seismology of stars. Low- and high-degree nonradial modes of oscillation may appear as variations in the line profiles of rapidly rotating δ Scuti stars. We present a technique whereby complex patterns in the line profiles are decomposed into Fourier components in both time and “Doppler space”. The technique is applied to the 7.3-hour time series of high-resolution data obtained from CFHT for the δ Scuti star τ Peg. In addition to the low-degree mode which has been identified in photometric studies (Breger 1991), we find evidence for at least three high-degree modes near 11 and 15. Correcting for the rotation of the star, most of these modes appear to oscillate with frequencies near 17 cycles day-1. Our results are found to be in good agreement with the theoretical limits imposed on the frequencies of oscillation by the models of Dziembowski (1990).

scholarly journals ASCAT Wind Superobbing Based on Feature Box

2018 ◽  
Vol 2018 ◽  
pp. 1-10
Author(s):  
Boheng Duan ◽  
Weimin Zhang ◽  
Haijin Dai
Keyword(s):  
High Resolution ◽  
Positive Impact ◽  
Weather Conditions ◽  
Error Characteristic ◽  
Data Sets ◽  
Observation Data ◽  
High Resolution Data ◽  
Correlated Error ◽  
Meteorological Features ◽  
Resolution Data

Redundant observations impose a computational burden on an operational data assimilation system, and assimilation using high-resolution satellite observation data sets at full resolution leads to poorer analyses and forecasts than lower resolution data sets, since high-resolution data may introduce correlated error in the assimilation. Thus, it is essential to thin the observations to alleviate these problems. Superobbing like other data thinning methods lowers the effect of correlated error by reducing the data density. Besides, it has the added advantage of reducing the uncorrelated error through averaging. However, thinning method using averaging could lead to the loss of some meteorological features, especially in extreme weather conditions. In this paper, we offer a new superobbing method which takes into consideration the meteorological features. The new method shows very good error characteristic, and the numerical simulation experiment of typhoon “Lionrock” (2016) shows that it has a positive impact on the analysis and forecast compared to the traditional superobbing.

scholarly journals Integration Monitoring of On-grid Photovoltaic System: Case Study

2019 ◽  
Vol 63 (2) ◽  
pp. 99-105 ◽  
Author(s):  
Michał Jasiński ◽  
Jacek Rezmer ◽  
Tomasz Sikorski ◽  
Jarosław Szymańda
Keyword(s):  
Power Quality ◽  
Electrical Power ◽  
Weather Condition ◽  
Weather Conditions ◽  
Photovoltaic System ◽  
Monitoring Systems ◽  
Electrical Power System ◽  
Pv System ◽  
Power And Energy

The aim of the paper is to present possible using of monitoring systems associated with photovoltaic systems (PV) in point of its integration with electrical power system (EPS). Presented investigations is a case study of 15 kW Scientific Photovoltaic System. The paper contains a description of applied control and monitoring systems including monitoring of PV panels parameters, weather condition, PV DC/AC inverters as well as special monitoring systems dedicated to power quality (PQ) and shape of voltage and current. The aim of the paper is to exhibit a possibility to combine different monitoring systems of the PV in order to improve evaluation of integration of PV with EPS. Presented example contains selected elements of power quality assessment, power and energy production, weather conditions for selected period of PV system working time.

scholarly journals An Intelligent Maximum Power Point Using a Fuzzy Log Controller under Severe Weather Conditions

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Khaled Bataineh
Keyword(s):  
Fuzzy Logic Controller ◽  
Fuzzy Controller ◽  
Weather Condition ◽  
Weather Conditions ◽  
Pv System ◽  
Maximum Power Point ◽  
Partial Shading ◽  
Pv Panel ◽  
Simulation Results ◽  
Power Point

This study is aimed at providing a comparison between fuzzy systems and convectional P&O for tracking MPP of a PV system. MATLAB/Simulink is used to investigate the response of both algorithms. Several weather conditions are simulated: (i) uniform irradiation, (ii) sudden changing, and (iii) partial shading. Under partial shading on a PV panel, multipeaks appeared in P-V characteristics of the panel. Simulation results showed that a fuzzy controller effectively finds MPP for all weather condition scenarios. Furthermore, simulation results obtained from the FLC are compared with those obtained from the P&O controller. The comparison shows that the fuzzy logic controller exhibits a much better behavior.

scholarly journals Performance analysis of grid-tied photovoltaic system under varying weather condition and load

2021 ◽  
Vol 11 (1) ◽  
pp. 94
Author(s):  
Abayomi A. Adebiyi ◽  
Ian J. Lazarus ◽  
Akshay K. Saha ◽  
Evans E. Ojo
Keyword(s):  
Dynamic Performance ◽  
Weather Condition ◽  
Weather Conditions ◽  
Maximum Power ◽  
Photovoltaic System ◽  
Solar Irradiation ◽  
Variable Load ◽  
Distribution Grid ◽  
Pv System ◽  
The Impact

Model and simulation of the impact of the distribution grid-tied photovoltaic (PV) system feeding a variable load with its control system have been investigated in this study. Incremental Conductance (IncCond) algorithm based on maximum power point tracking (MPPT) was implemented for the PV system to extract maximum power under different weather conditions when solar irradiation varies between 250W/m2 and 1000W/m2. The proposed system is modelled and simulated with MATLAB/Simulink tools. Under different weather conditions, the dynamic performance of the PV system is evaluated. The results obtained show the efficacy of the proposed MPPT method in response to rapid daytime weather variations. The results also show that the surplus power generated is injected into the grid when the injected power from the PV system is higher than the load demand; otherwise, the grid supplies the load.

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