The penetration of electric vehicles (EVs) and photovoltaic (PV) systems has increased globally in the last decade. For planning purposes, the spatiotemporal variability of distributed PV power generation and EV charging needs to be quantified for urban and rural areas. This study introduces a state-of-the-art, open, and generally applicable model framework for assessing the spatiotemporal mismatch between EV load and PV generation for urban and rural areas. The model is applied to a rural and an urban area, both 16 km × 16 km and located in Sweden, and is evaluated for the extreme months of January and July. The results show that an energy deficit of, at most, 86% and an up to ten times surplus took place in January and July, respectively. A high self-consumption (SC) of 77% was observed for January and a high self-sufficiency (SS) of 69% for July. This is to say that during July, PV can fulfill 69% of the EV charging load. Moreover, there were no observed correlations between the PV-EV temporal matching scores (the SS and the SC) and the dominant type of charging, e.g., workplace charging in each grid cell (1 km × 1 km) of the areas. This can be partially attributed to the wide distribution of the rooftop orientations in both areas. This challenges the assumption of low PV-EV temporal matching in residential parts of the city. Applying the proposed methodology to other regions is incentivized.
References
1.
Z.
Navas-Anguita
, D.
García-Gusano
, and D.
Iribarren
, “A review of techno-economic data for road transportation fuels
,” Renewable Sustainable Energy Rev.
112
, 11
–26
(2019
).2.
P.
Plötz
, T.
Gnann
, P.
Jochem
, H. Ü.
Yilmaz
, and T.
Kaschub
, “Impact of electric trucks powered by overhead lines on the European electricity system and CO2 emissions
,” Energy Policy
130
, 32
–40
(2019
).3.
Q.
Hoarau
and Y.
Perez
, “Interactions between electric mobility and photovoltaic generation: A review
,” Renewable Sustainable Energy Rev.
94
, 510
–522
(2018
).4.
A.
Gautier
, B.
Hoet
, J.
Jacqmin
, and S.
Van Driessche
, “Self-consumption choice of residential PV owners under net-metering
,” Energy Policy
128
, 648
–653
(2019
).5.
G.
Masson
and I.
Kaizuka
, “Trends in PV applications 2019
,” Technical Report No. IEA PVPS T1-36:2019 (IEAPVPS, 2019
).6.
J. G.
Ingersoll
and C. A.
Perkins
, “The 2.1 kW photovoltaic electric vehicle charging station in the city of Santa Monica, California
,” in Conference Record of the Twenty Fifth IEEE Photovoltaic Specialists Conference-1996
(IEEE
, 1996
), pp. 1509
–1512
.7.
A.
Buonomano
, F.
Calise
, F. L.
Cappiello
, A.
Palombo
, and M.
Vicidomini
, “Dynamic analysis of the integration of electric vehicles in efficient buildings fed by renewables
,” Appl. Energy
245
, 31
–50
(2019
).8.
S.
Cao
, “The impact of electric vehicles and mobile boundary expansions on the realization of zero-emission office buildings
,” Appl. Energy
251
, 113347
(2019
).9.
R.
Miceli
and F.
Viola
, “Designing a sustainable university recharge area for electric vehicles: Technical and economic analysis
,” Energies
10
, 1604
(2017
).10.
P. J.
Tulpule
, V.
Marano
, S.
Yurkovich
, and G.
Rizzoni
, “Economic and environmental impacts of a PV powered workplace parking garage charging station
,” Appl. Energy
108
, 323
–332
(2013
).11.
D.
Mazzeo
, “Nocturnal electric vehicle charging interacting with a residential photovoltaic-battery system: A 3E (energy, economic and environmental) analysis
,” Energy
168
, 310
–331
(2019
).12.
M.
Van Der Kam
and W.
van Sark
, “Smart charging of electric vehicles with photovoltaic power and vehicle-to-grid technology in a microgrid; A case study
,” Appl. Energy
152
, 20
–30
(2015
).13.
F.
Marra
, G. Y.
Yang
, C.
Træholt
, E.
Larsen
, J.
Østergaard
, B.
Blažič
, and W.
Deprez
, “EV charging facilities and their application in LV feeders with photovoltaics
,” IEEE Trans. Smart Grid
4
, 1533
–1540
(2013
).14.
L.
Novoa
and J.
Brouwer
, “Dynamics of an integrated solar photovoltaic and battery storage nanogrid for electric vehicle charging
,” J. Power Sources
399
, 166
–178
(2018
).15.
J.
Munkhammar
, J. D.
Bishop
, J. J.
Sarralde
, W.
Tian
, and R.
Choudhary
, “Household electricity use, electric vehicle home-charging and distributed photovoltaic power production in the city of Westminster
,” Energy Build.
86
, 439
–448
(2015
).16.
C.
Good
, M.
Shepero
, J.
Munkhammar
, and T.
Boström
, “Scenario-based modelling of the potential for solar energy charging of electric vehicles in two Scandinavian cities
,” Energy
168
, 111
–125
(2019
).17.
G. B.
Litjens
, B. B.
Kausika
, E.
Worrell
, and W. G.
van Sark
, “A spatio-temporal city-scale assessment of residential photovoltaic power integration scenarios
,” Sol. Energy
174
, 1185
–1197
(2018
).18.
Y.
Ko
, K.
Jang
, and J. D.
Radke
, “Toward a solar city: Trade-offs between on-site solar energy potential and vehicle energy consumption in San Francisco, California
,” Int. J. Sustainable Transp.
11
, 460
–470
(2017
).19.
M. J.
Van der Kam
, A.
Meelen
, W. G.
van Sark
, and F.
Alkemade
, “Diffusion of solar photovoltaic systems and electric vehicles among Dutch consumers: Implications for the energy transition
,” Energy Res. Soc. Sci.
46
, 68
–85
(2018
).20.
P.
Denholm
, M.
Kuss
, and R. M.
Margolis
, “Co-benefits of large scale plug-in hybrid electric vehicle and solar PV deployment
,” J. Power Sources
236
, 350
–356
(2013
).21.
R.
Luthander
, A. M.
Nilsson
, J.
Widén
, and M.
Åberg
, “Graphical analysis of photovoltaic generation and load matching in buildings: A novel way of studying self-consumption and self-sufficiency
,” Appl. Energy
250
, 748
–759
(2019
).22.
A.
Chaouachi
, E.
Bompard
, G.
Fulli
, M.
Masera
, M. D.
Gennaro
, and E.
Paffumi
, “Assessment framework for EV and PV synergies in emerging distribution systems
,” Renewable Sustainable Energy Rev.
55
, 719
–728
(2016
).23.
P.
Lazzeroni
, S.
Olivero
, M.
Repetto
, F.
Stirano
, and M.
Vallet
, “Optimal battery management for vehicle-to-home and vehicle-to-grid operations in a residential case study
,” Energy
175
, 704
(2019
).24.
S.
Freitas
, C.
Reinhart
, and M. C.
Brito
, “Minimizing storage needs for large scale photovoltaics in the urban environment
,” Sol. Energy
159
, 375
–389
(2018
).25.
M.
Muratori
, “Impact of uncoordinated plug-in electric vehicle charging on residential power demand
,” Nat. Energy
3
, 193
–201
(2018
).26.
C.
Will
and A.
Schuller
, “Understanding user acceptance factors of electric vehicle smart charging
,” Transp. Res. Part C
71
, 198
–214
(2016
).27.
Statistiska centralbyrån
, “Folkmängd i riket, län och kommuner 31 December 2018 och befolkningsförändringar 2018
” (2019
).28.
Uppsala kommun,
“Statistik om uppsala kommun 2018
” (2018
).29.
M.
Li
, M.
Lenzen
, F.
Keck
, B.
McBain
, O.
Rey-Lescure
, B.
Li
, and C.
Jiang
, “GIS-based probabilistic modeling of BEV charging load for Australia
,” IEEE Trans. Smart Grid
10
, 3525
(2019
).30.
D.
Hirooka
, N.
Murata
, Y.
Fujimoto
, and Y.
Hayashi
, “Temporal interpolation of gridded solar radiation data for evaluation of PV fluctuations
,” Energy Procedia
155
, 259
–268
(2018
).31.
E. P.
James
, S. G.
Benjamin
, and M.
Marquis
, “A unified high-resolution wind and solar dataset from a rapidly updating numerical weather prediction model
,” Renewable Energy
102
, 390
–405
(2017
).32.
D. J.
Gagne
, I. I. A.
McGovern
, S. E.
Haupt
, and J. K.
Williams
, “Evaluation of statistical learning configurations for gridded solar irradiance forecasting
,” Sol. Energy
150
, 383
–393
(2017
).33.
J. M.
Bright
, O.
Babacan
, J.
Kleissl
, P. G.
Taylor
, and R.
Crook
, “A synthetic, spatially decorrelating solar irradiance generator and application to a LV grid model with high PV penetration
,” Sol. Energy
147
, 83
–98
(2017
).34.
J. M.
Bright
, C. J.
Smith
, P. G.
Taylor
, and R.
Crook
, “Stochastic generation of synthetic minutely irradiance time series derived from mean hourly weather observation data
,” Sol. Energy
115
, 229
–242
(2015
).35.
An okta represents the cloud amount from clear-sky to total overcast.
36.
D.
Lingfors
, J.
Bright
, N.
Engerer
, J.
Ahlberg
, S.
Killinger
, and J.
Widén
, “Comparing the capability of low- and high-resolution LiDAR data with application to solar resource assessment, roof type classification and shading analysis
,” Appl. Energy
205
, 1216
–1230
(2017
).37.
D.
Lingfors
, S.
Killinger
, N. A.
Engerer
, J.
Widén
, and J. M.
Bright
, “Identification of PV system shading using a LiDAR-based solar resource assessment model: An evaluation and cross-validation
,” Sol. Energy
159
, 157
–172
(2018
).38.
Swedish Land Survey
, “Product description LiDAR data ver. 2.1
,” Technical Report (Swedish Land Survey, Gävle, 2016
).39.
Swedish Land Survey
, “Product description: GSD-property map, vector
,” Technical Report (Swedish Land Survey, Gävle, 2018
).40.
M.
Shepero
and J.
Munkhammar
, “Spatial Markov chain model for electric vehicle charging in cities using geographical information system (GIS) data
,” Appl. Energy
231
, 1089
–1099
(2018
).41.
42.
Y.
Xu
, S.
Çolak
, E. C.
Kara
, S. J.
Moura
, and M. C.
González
, “Planning for electric vehicle needs by coupling charging profiles with urban mobility
,” Nat. Energy
3
, 484
–493
(2018
).43.
SIKA
, “RES 2005–2006 The National Travel Survey
,” Technical Report No. 2007:19 (Swedish Institute for Transport and Communications Analysis, SIKA, 2007
).44.
P.
Grahn
, K.
Alvehag
, and L.
Soder
, “PHEV utilization model considering type-of-trip and recharging flexibility
,” IEEE Trans. Smart Grid
5
, 139
–148
(2014
).45.
A.
Myhr
and T.
Svahn
, “Fordon i län och kommuner 2017
,” Technical Report No, Statistik 2018:3 (Trafik analys, 2018
).46.
L. R.
Camargo
, R.
Zink
, W.
Dorner
, and G.
Stoeglehner
, “Spatio-temporal modeling of roof-top photovoltaic panels for improved technical potential assessment and electricity peak load offsetting at the municipal scale
,” Comput., Environ. Urban Syst.
52
, 58
–69
(2015
).© 2020 Author(s).
2020
Author(s)
You do not currently have access to this content.
