Irradiance Variability Quantification and Small-Scale Averaging in Space and Time: A Short Review

Lohmann, Gerald M.

doi:10.3390/atmos9070264

Cited by 44 publications

(57 citation statements)

References 154 publications

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“…These profiles were generated from a single Global Horizontal Irradiance (GHI) measurement and then shifted and scaled to account for geographical separation of the PV sites. The PV irradiance profiles were then smoothed based on the plant sizes using the Wavelet Variability Model [43][44][45][46] to account for spatial averaging with large PV systems. To understand the impact of spatial averaging on the irradiance profiles the reader is invited to review [47,48].…”

Section: Simulations With the Pnm Modelmentioning

confidence: 99%

A Comparison of DER Voltage Regulation Technologies Using Real-Time Simulations

et al. 2020

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Grid operators are now considering using distributed energy resources (DERs) to provide distribution voltage regulation rather than installing costly voltage regulation hardware. DER devices include multiple adjustable reactive power control functions, so grid operators have the difficult decision of selecting the best operating mode and settings for the DER. In this work, we develop a novel state estimation-based particle swarm optimization (PSO) for distribution voltage regulation using DER-reactive power setpoints and establish a methodology to validate and compare it against alternative DER control technologies (volt–VAR (VV), extremum seeking control (ESC)) in increasingly higher fidelity environments. Distribution system real-time simulations with virtualized and power hardware-in-the-loop (PHIL)-interfaced DER equipment were run to evaluate the implementations and select the best voltage regulation technique. Each method improved the distribution system voltage profile; VV did not reach the global optimum but the PSO and ESC methods optimized the reactive power contributions of multiple DER devices to approach the optimal solution.

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Section: Simulations With the Pnm Modelmentioning

confidence: 99%

A Comparison of DER Voltage Regulation Technologies Using Real-Time Simulations

et al. 2020

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“…Clouds present the greatest source of subhourly variability in GHI, with the fractional changes greatest at midday [2,17]. Furthermore, daily and seasonal changes in the zenith angle can introduce other errors in GHI measurements [38].…”

Section: Clearness Indexmentioning

confidence: 99%

“…Improving forecasts of power from solar panels, whether short-range forecasts out to a few hours, or longer, such as subseasonal forecasts, has been the subject of much research in recent years (as reviewed by [1][2][3][4]). The target uses of the forecasts include planning future installations, optimizing plant operations and efficiency, or balancing load demand and delivery [5].…”

Section: Introductionmentioning

confidence: 99%

Assessing Evidence for Weather Regimes Governing Solar Power Generation in Kuwait

et al. 2019

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With electricity representing around 20% of the global energy demand, and increasing support for renewable sources of electricity, there is also an escalating need to improve solar forecasts to support power management. While considerable research has been directed to statistical methods to improve solar power forecasting, few have employed finite mixture distributions. A statistically-objective classification of the overall sky condition may lead to improved forecasts. Combining information from the synoptic driving conditions for daily variability with local processes controlling subdaily fluctuations could assist with forecast validation and enhancement where few observations are available. Gaussian mixture models provide a statistical learning approach to automatically identify prevalent sky conditions (clear, semi-cloudy, and cloudy) and explore associated weather patterns. Here a first stage in the development of such a model is presented: examining whether there is sufficient information in the large-scale environment to identify days with clear, semi-cloudy, or cloudy conditions. A three-component Gaussian distribution is developed that reproduces the observed multimodal peaks in sky clearness indices, and their temporal distribution. Posterior probabilities from the fitted mixture distributions are used to identify periods of clear, partially-cloudy, and cloudy skies. Composites of low-level (850 hPa) humidity and winds for each of the mixture components reveal three patterns associated with the typical synoptic conditions governing the sky clarity, and hence, potential solar power.

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“…Photovoltaic systems (PVs) have become one of the most common and attractive electricity generation sources in the distribution networks, because of its clean power and competitive energy generation cost [1]. Other advantageous include long lifetime, silent operation, and sustainability that encouraged worldwide governments and stakeholders to develop incentive schemes to promote its deployment at residential and industrial levels.…”

Section: Introductionmentioning

confidence: 99%

Gene expression technique‐based approach to improve the accuracy of estimating the total generated power by neighbouring photovoltaic systems

Al-Hilfi

Shahnia

Abu-Siada

2020

IET Renewable Power Generation

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The penetration of photovoltaic systems (PVs) to existing power grids is increasing as they are considered attractive options for electricity generation in distribution networks. This paper focuses on estimating the total power generated by a group of neighbouring PVs, spread over a distribution network using a single pyranometer for measuring the solar irradiance. A new empirical‐based model that employs the Gene Expression Programming (GEP) technique is proposed to correlate the distribution of the PVs and the irradiance measured by the pyranometer and estimate the total power generated by the PVs. The geographic variability reduction index has been considered in developing the proposed model that also employs a Wavelet Transform technique to enhance its accuracy. The effective performance of the proposed model is validated using real data collected by the Solar Project at the University of Queensland, Brisbane, Australia. Results reveal that the proposed technique yields more accurate results when compared with other existing approaches in the literature.

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Irradiance Variability Quantification and Small-Scale Averaging in Space and Time: A Short Review

Cited by 44 publications

References 154 publications

A Comparison of DER Voltage Regulation Technologies Using Real-Time Simulations

A Comparison of DER Voltage Regulation Technologies Using Real-Time Simulations

Assessing Evidence for Weather Regimes Governing Solar Power Generation in Kuwait

Gene expression technique‐based approach to improve the accuracy of estimating the total generated power by neighbouring photovoltaic systems

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