On the determination of coherent solar microclimates for utility planning and operations

Zagouras, Athanassios; Inman, Rich H.; Coimbra, Carlos F.M.

doi:10.1016/j.solener.2014.01.021

Cited by 35 publications

(20 citation statements)

References 37 publications

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“…In this respect, a dimensionality reduction method would be essential (and unavoidable) in order to remove redundancy and bring the number of assets to a manageable size. Diabaté et al [6] and Zagouras et al [35,36] demonstrate how cluster analysis techniques can be used in detecting zones of geographical regions with similar solar resources. From a portfolio management point of view, these zones can be treated as indivi dual assets with homogeneous properties, thus allowing for a hierarchical construction of the optimal power harvesting plan 12 .…”

Section: Discussionmentioning

confidence: 99%

Optimal management of wind and solar energy resources

Τhomaidis

Santos-Alamillos

Pozo-Vázquez

et al. 2016

Computers & Operations Research

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a b s t r a c tThis paper presents a portfolio based approach to the harvesting of renewable energy (RE) resources. Our examined problem setting considers the possibility of distributing the total available capacity across an array of heterogeneous RE generation technologies (wind and solar power production units) being dispersed over a large geographical area. We formulate the capacity allocation process as a bi objective optimization problem, in which the decision maker seeks to increase the mean productivity of the entire array while having control on the variability of the aggregate energy supply. Using large scale optimization techniques, we are able to calculate to an arbitrary degree of accuracy the complete set of Pareto optimal configurations of power plants, which attain the maximum possible energy delivery for a given level of power supply risk. Experimental results from a reference geographical region show that wind and solar resources are largely complementary. We demonstrate how this feature could help energy policy makers to improve the overall reliability of future RE generation in a properly designed risk management framework.

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Section: Discussionmentioning

confidence: 99%

Optimal management of wind and solar energy resources

Τhomaidis

Santos-Alamillos

Pozo-Vázquez

et al. 2016

Computers & Operations Research

View full text Add to dashboard Cite

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“…The minimization of the DB index indicates a preferable clustering partition, while the opposite applies for the latter two indices. For more details regarding the used validity indices the reader is referred to Arbelaitz et al (2013), Zagouras et al (2013), Zagouras et al (2014). The choice of the above validity indices out of a large number of indices available in literature, was based on aspects such as the monotonicity of their emerged values and their overall good fit and performance to the structure of the dataset and the clustering methods as well (Arbelaitz et al, 2013).…”

Section: Methodsmentioning

confidence: 99%

“…where T c is the total daylight time (s) of c 30-min samples per day (Zagouras et al, 2014). For conceptual and computational simplicity in these experiments, we confined the total daylight time T c to a constant number of frames around the solar noon for each day (frames in the range solar noon ±3 h).…”

Section: Preprocessing and Feature Extractionmentioning

confidence: 99%

Clustering the solar resource for grid management in island mode

2014

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“…In this study we employed the CSM proposed by Ineichen and Perez (2002) [18] which requires as the only atmospheric input the Linke turbidity factor at an airmass of 2. In contrast to other multi-parameter CSM in the literature, the selection of this model lies in the availability of broadband input parameters and the demonstrated good performance in the state of California [19]. Current research on the accuracy of diverse CSM has shown that the particular model is among the four best-performing models out of 54 CSM in total [20].…”

Section: Clear-sky Model and Clear-sky Indexmentioning

confidence: 99%

On the role of lagged exogenous variables and spatio–temporal correlations in improving the accuracy of solar forecasting methods

2015

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a b s t r a c tWe propose and analyze a spatioetemporal correlation method to improve forecast performance of solar irradiance using gridded satellite-derived global horizontal irradiance (GHI) data. Forecast models are developed for seven locations in California to predict 1-h averaged GHI 1, 2 and 3 h ahead of time. The seven locations were chosen to represent a diverse set of maritime, mediterranean, arid and semi-arid micro-climates. Ground stations from the California Irrigation Management Information System were used to obtain solar irradiance time-series from the points of interest. In this method, firstly, we define areas with the highest correlated time-series between the satellite-derived data and the ground data. Secondly, we select satellite-derived data from these regions as exogenous variables to several forecast models (linear models, Artificial Neural Networks, Support Vector Regression) to predict GHI at the seven locations. The results show that using linear forecasting models and a genetic algorithm to optimize the selection of multiple time-lagged exogenous variables results in significant forecasting improvements over other benchmark models.

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On the determination of coherent solar microclimates for utility planning and operations

Cited by 35 publications

References 37 publications

Optimal management of wind and solar energy resources

Optimal management of wind and solar energy resources

Clustering the solar resource for grid management in island mode

On the role of lagged exogenous variables and spatio–temporal correlations in improving the accuracy of solar forecasting methods

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