The accurate prediction of the direct and diffuse solar radiation is of foremost importance for deployment of photovoltaic (PV) systems. A number of solar radiation forecasting techniques have been developed for longer and shorter forecasting times. Numerical weather prediction (NWP) models provide the best results for the longer forecasting times (4–6 h), required by utility companies. However, NWP methods are usually developed for clear-sky and open areas. These methods cannot be directly applied to urban areas with shading, trees, multisurface reflection, and other sources of solar radiation losses. To overcome these issues, improvement to the existing prediction tools are required. In this study, we develop an automated radiation forecasting tool for urban areas. This tool combines a NWP model (Weather Research and Forecasting (WRF) model) and a solar calculator (developed in the numerical toolbox OpenFOAM) to compute shading, reflection, and other losses in the urban canopy. An algorithm for extraction of building outlines and heights (if they are publicly available) is also developed as a part of the tool. Finally, the coupled solar power estimator can be applied to past, present, or future solar power predictions. Initial results obtained using the developed tool are demonstrated for an urban neighborhood in Singapore.

References

1.
Farmer
,
J. D.
, and
Lafond
,
F.
,
2016
, “
How Predictable Is Technological Progress?
,”
Res. Policy
,
45
(
3
), pp.
647
665
.
2.
Fu
,
R.
,
Feldman
,
D. J.
,
Margolis
,
R. M.
,
Woodhouse
,
M. A.
, and
Ardani
,
K. B.
,
2017
, “
U.S. Solar Photovoltaic System Cost Benchmark: Q1
,” National Renewable Energy Laboratory, Golden, CO.
3.
Reikard
,
G.
,
2009
, “
Predicting Solar Radiation at High Resolutions: A Comparison of Time Series Forecasts
,”
Sol. Energy
,
83
(
3
), pp.
342
349
.
4.
Kemmoku
,
Y.
,
Orita
,
S.
,
Nakagawa
,
S.
, and
Sakakibara
,
T.
,
1999
, “
Daily Insolation Forecasting Using a Multi-Stage Neural Network
,”
Sol. Energy
,
66
(
3
), pp.
193
199
.
5.
Sfetsos
,
A.
, and
Coonick
,
A.
,
2000
, “
Univariate and Multivariate Forecasting of Hourly Solar Radiation With Artificial Intelligence Techniques
,”
Sol. Energy
,
68
(
2
), pp.
169
178
.
6.
Mellit
,
A.
,
Benghanem
,
M.
, and
Kalogirou
,
S. A.
,
2006
, “
An Adaptive Wavelet-Network Model for Forecasting Daily Total Solar-Radiation
,”
Appl. Energy
,
83
(
7
), pp.
705
722
.
7.
Pierro
,
M.
,
Bucci
,
F.
,
De Felice
,
M.
,
Maggioni
,
E.
,
Perotto
,
A.
,
Spada
,
F.
,
Moser
,
D.
, and
Cornaro
,
C.
,
2017
, “
Deterministic and Stochastic Approaches for Day-Ahead Solar Power Forecasting
,”
ASME J. Sol. Energy Eng.
,
139
(
2
), p.
021010
.
8.
Perez
,
R.
,
Kivalov
,
S.
,
Schlemmer
,
J.
,
Hemker
,
K.
,
Renné
,
D.
, and
Hoff
,
T. E.
,
2010
, “
Validation of Short and Medium Term Operational Solar Radiation Forecasts in the Us
,”
Sol. Energy
,
84
(
12
), pp.
2161
2172
.
9.
Hammer
,
A.
,
Heinemann
,
D.
,
Lorenz
,
E.
, and
Lückehe
,
B.
,
1999
, “
Short-Term Forecasting of Solar Radiation: A Statistical Approach Using Satellite Data
,”
Sol. Energy
,
67
(
1–3
), pp.
139
150
.
10.
Chow
,
C. W.
,
Urquhart
,
B.
,
Lave
,
M.
,
Dominguez
,
A.
,
Kleissl
,
J.
,
Shields
,
J.
, and
Washom
,
B.
,
2011
, “
Intra-Hour Forecasting With a Total Sky Imager at the UC San Diego Solar Energy Testbed
,”
Sol. Energy
,
85
(
11
), pp.
2881
2893
.
11.
Lorenz
,
E.
,
Hurka
,
J.
,
Heinemann
,
D.
, and
Beyer
,
H. G.
,
2009
, “
Irradiance Forecasting for the Power Prediction of Grid-Connected Photovoltaic Systems
,”
IEEE J. Sel. Top. Appl. Earth Obs. Remote Sens.
,
2
(
1
), pp.
2
10
.
12.
Lara-Fanego
,
V.
,
Ruiz-Arias
,
J.
,
Pozo-Vázquez
,
D.
,
Santos-Alamillos
,
F.
, and
Tovar-Pescador
,
J.
,
2012
, “
Evaluation of the Wrf Model Solar Irradiance Forecasts in Andalusia (Southern spain)
,”
Sol. Energy
,
86
(
8
), pp.
2200
2217
.
13.
Mathiesen
,
P.
, and
Kleissl
,
J.
,
2011
, “
Evaluation of Numerical Weather Prediction for Intra-Day Solar Forecasting in the Continental United States
,”
Sol. Energy
,
85
(
5
), pp.
967
977
.
14.
Diagne
,
M.
,
David
,
M.
,
Lauret
,
P.
,
Boland
,
J.
, and
Schmutz
,
N.
,
2013
, “
Review of Solar Irradiance Forecasting Methods and a Proposition for Small-Scale Insular Grids
,”
Renewable Sustainable Energy Rev.
,
27
, pp.
65
76
.
15.
Cao
,
J. C.
, and
Cao
,
S.
,
2006
, “
Study of Forecasting Solar Irradiance Using Neural Networks With Preprocessing Sample Data by Wavelet Analysis
,”
Energy
,
31
(
15
), pp.
3435
3445
.
16.
Ji
,
W.
, and
Chee
,
K. C.
,
2011
, “
Prediction of Hourly Solar Radiation Using a Novel Hybrid Model of ARMA and TDNN
,”
Sol. Energy
,
85
(
5
), pp.
808
817
.
17.
Cao
,
S.
, and
Cao
,
J.
,
2005
, “
Forecast of Solar Irradiance Using Recurrent Neural Networks Combined With Wavelet Analysis
,”
Appl. Therm. Eng.
,
25
(
2–3
), pp.
161
172
.
18.
Aryaputera
,
A. W.
,
Yang
,
D.
, and
Walsh
,
W. M.
,
2015
, “
Day-Ahead Solar Irradiance Forecasting in a Tropical Environment
,”
ASME J. Sol. Energy Eng.
,
137
(
5
), p.
051009
.
19.
Skamarock
,
W. C.
,
Klemp
,
J. B.
,
Dudhia
,
J.
,
Gill
,
D. O.
,
Barker
,
D. M.
,
Duda
,
M. G.
,
Huang
,
X.-Y.
,
Wang
,
W.
, and
Powers
,
J. G.
,
2008
, “
A Description of the Advanced Research WRF Version 3
,” National Center for Atmospheric Research, Boulder, CO, Technical Report No.
NCAR/TN-475+STR
.
20.
Weller
,
H. G.
,
Tabor
,
G.
,
Jasak
,
H.
, and
Fureby
,
C.
,
1998
, “
A Tensorial Approach to Computational Continuum Mechanics Using Object-Oriented Techniques
,”
Comput. Physics
,
12
(
6
), pp.
620
631
.
21.
MacQueen
,
J.
,
1967
, “
Some Methods for Classification and Analysis of Multivariate Observations
,”
Fifth Berkeley Symposium on Mathematical Statistics and Probability
, Oakland, CA, pp.
281
297
.https://pdfs.semanticscholar.org/a718/b85520bea702533ca9a5954c33576fd162b0.pdf
22.
Pedregosa
,
F.
,
Varoquaux
,
G.
,
Gramfort
,
A.
,
Michel
,
V.
,
Thirion
,
B.
,
Grisel
,
O.
,
Blondel
,
M.
,
Prettenhofer
,
P.
,
Weiss
,
R.
,
Dubourg
,
V.
,
Vanderplas
,
J.
,
Passos
,
A.
,
Cournapeau
,
D.
,
Brucher
,
M.
,
Perrot
,
M.
, and
Duchesnay
,
E.
,
2011
, “
Scikit-Learn: Machine Learning in Python
,”
J. Mach. Learn. Res.
,
12
(2011), pp.
2825
2830
.http://www.jmlr.org/papers/volume12/pedregosa11a/pedregosa11a.pdf
23.
Rousseeuw
,
P. J.
,
1987
, “
Silhouettes: A Graphical Aid to the Interpretation and Validation of Cluster Analysis
,”
J. Comput. Appl. Math.
,
20
, pp.
53
65
.
24.
Andrew
,
A. M.
,
1979
, “
Another Efficient Algorithm for Convex Hulls in Two Dimensions
,”
Inf. Process. Lett.
,
9
(
5
), pp.
216
219
.
25.
Edelsbrunner
,
H.
,
Kirkpatrick
,
D.
, and
Seidel
,
R.
,
1983
, “
On the Shape of a Set of Points in the Plane
,”
IEEE Trans. Inf. Theory
,
29
(
4
), pp.
551
559
.
26.
NCEP, 2000
, “NCEP FNL Operational Model Global Tropospheric Analyses, Continuing From July 1999,” National Centers for Environmental Prediction, National Weather Service, NOAA, U.S. Department of Commerce, Silver Spring, MD.
27.
Thompson
,
G.
, and
Eidhammer
,
T.
,
2014
, “
A Study of Aerosol Impacts on Clouds and Precipitation Development in a Large Winter Cyclone
,”
J. Atmos. Sci.
,
71
(
10
), pp.
3636
3658
.
28.
Grell
,
G. A.
, and
Freitas
,
S. R.
,
2014
, “
A Scale and Aerosol Aware Stochastic Convective Parameterization for Weather and Air Quality Modeling
,”
Atmos. Chem. Phys
,
14
(
10
), pp.
5233
5250
.
29.
Iacono
,
M. J.
,
Delamere
,
J. S.
,
Mlawer
,
E. J.
,
Shephard
,
M. W.
,
Clough
,
S. A.
, and
Collins
,
W. D.
,
2008
, “
Radiative Forcing by Long-Lived Greenhouse Gases: Calculations With the Aer Radiative Transfer Models
,”
J. Geophys. Res.: Atmos.
,
113
(
D13
), pp. 1–8.
30.
Hong
,
S.-Y.
,
Noh
,
Y.
, and
Dudhia
,
J.
,
2006
, “
A New Vertical Diffusion Package With an Explicit Treatment of Entrainment Processes
,”
Mon. Weather Rev.
,
134
(
9
), pp.
2318
2341
.
31.
Jiménez
,
P. A.
, and
Dudhia
,
J.
,
2012
, “
Improving the Representation of Resolved and Unresolved Topographic Effects on Surface Wind in the Wrf Model
,”
J. Appl. Meteorol. Climatol.
,
51
(
2
), pp.
300
316
.
32.
Niu
,
G.-Y.
,
Yang
,
Z.-L.
,
Mitchell
,
K. E.
,
Chen
,
F.
,
Ek
,
M. B.
,
Barlage
,
M.
,
Kumar
,
A.
,
Manning
,
K.
,
Niyogi
,
D.
,
Rosero
,
E.
, Tewari,
M.
, and Xia,
Y.
,
2011
, “
The Community Noah Land Surface Model With Multiparameterization Options (NOAH-MP)—1: Model Description and Evaluation With Local-Scale Measurements
,”
J. Geophys. Res.: Atmos.
,
116
(
D12
), pp. 1–19.
33.
Yang
,
Z.-L.
,
Niu
,
G.-Y.
,
Mitchell
,
K. E.
,
Chen
,
F.
,
Ek
,
M. B.
,
Barlage
,
M.
,
Longuevergne
,
L.
,
Manning
,
K.
,
Niyogi
,
D.
,
Tewari
,
M.
, and
Xia
,
Y.
,
2011
, “
The Community Noah Land Surface Model With Multiparameterization Options (NOAH-MP)—2: Evaluation Over Global River Basins
,”
J. Geophys. Res.: Atmos.
,
116
(
D12
), pp. 1–16.
34.
Jimenez
,
P. A.
,
Hacker
,
J. P.
,
Dudhia
,
J.
,
Haupt
,
S. E.
,
Ruiz-Arias
,
J. A.
,
Gueymard
,
C. A.
,
Thompson
,
G.
,
Eidhammer
,
T.
, and
Deng
,
A.
,
2016
, “
WRF-Solar: Description and Clear-Sky Assessment of an Augmented NWP Model for Solar Power Prediction
,”
Bull. Am. Meteorol. Soc.
,
97
(
7
), pp.
1249
1264
.
35.
The OpenFOAM Foundation
, 2017, “
Openfoam v5.0
,” OpenFOAM Foundation, UK, accessed July 26, 2017, www.openfoam.org
36.
OpenCFD,
2016, “
Openfoam v1612
,” OpenCFD (ESI Group), France, accessed Jan. 10, 2017, www.openfoam.com
37.
Klucher
,
T. M.
,
1979
, “
Evaluation of Models to Predict Insolation on Tilted Surfaces
,”
Sol. Energy
,
23
(
2
), pp.
111
114
.
38.
Maxwell
,
E. L.
,
Stoffel
,
T. L.
, and
Bird
,
R. E.
,
1986
, “
Measuring and Modeling Solar Irradiance on Vertical Surfaces
,” Solar Energy Research Institute, Golden, CO, Technical Report No.
SERI/TR-215-2525
.https://www.nrel.gov/docs/legosti/old/2525.pdf
39.
Pomeroy
,
J. W.
,
Marks
,
D.
,
Link
,
T.
,
Ellis
,
C.
,
Hardy
,
J.
,
Rowlands
,
A.
, and
Granger
,
R.
,
2009
, “
The Impact of Coniferous Forest Temperature on Incoming Longwave Radiation to Melting Snow
,”
Hydrol. Processes
,
23
(
17
), pp.
2513
2525
.
40.
Kubilay
,
A.
,
Derome
,
D.
, and
Carmeliet
,
J.
,
2017
, “
Coupling of Physical Phenomena in Urban Microclimate: A Model Integrating Air Flow, Wind-Driven Rain, Radiation and Transport in Building Materials
,”
Urban Clim.
,
24
, 398–418.
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