Dragos Isvoranu Viorel Badescu University Politehnica of Bucharest Comparison between measurements and numerical assessment of global solar irradiation in Romania Dragos Isvoranu Viorel Badescu University Politehnica of Bucharest

Purpose Motivation Quality and performance of global solar irradiance forecasting. Purpose Motivation Variability of solar power production at different spatial and temporal scales: intermittent weather patterns day/night cycles humidity and aerosol load cloud structure Adapting the load schedule of grid operators optimization of energy transport in low voltage grid balancing energy; avoid outages and congestions spot market sell ; penalties for wrong load schedules maintenance planning protection from extreme events

Historical perspective contrary to wind forecasting, solar radiation forecasting is relatively new 2008, Germany 2011, Canada significant reduction in RMSE with increasing the geographic area under consideration in both cases 2011, Spain, point forecast, RMSE between 10-50% depending on cloudiness. Solar radiation forecasting Forecasting horizon for PV: from 24 h up to 72 h. In this range: numerical weather prediction based on equations of fluid dynamics and thermodynamics to estimate the state of the atmosphere at some time in the future. NWP: Initialization: sample the state of the atmosphere at a given time ( ground station, satellite, radar) Time stepping: tens of minutes for global climate models to a few seconds or minutes for regional models. extrapolation methods (mainly for nowcasting) (global models) statistical methods (up to 24 h horizon) (global models) for regional models additional physics details

WRF presentation NWP is stronly dependent on space scale Meteorology scales: global planetary (synoptic) regional (mesoscale) (5- hundreds of km) microscale (below 1 km) Synoptic models: GFS, ECMWF, GME, UKMO Mesoscale models: HRM, Hirlam, Lokal Model, WRF-(NMM, ARW), Unified Model, MM5 Selection of the numerical model: popularity cost performance accessibility to meteo and satellite data European mesoscale codes: HRM, Hirlam, Lokal Model semi-Lagrangian, semi-implicit formulation North-American codes: WRF (ARW,NMM), MM5 Eulerian formulation Many pros and cons for each type of formulation Though, a major failure for London Met Office for cloud propagation from Eyjafjallajökul eruption in April 2010

WRF presentation 2 dynamical nuclei: ARW (NCAR) and NMM (NCEP) multigrid multi-level non-hidrostatic LES turbulence model space scales from tens of meters hundreds of km and even synoptic one and bi-directional coupling with various physics modules nested and moving grids ARW : Arakawa-C type of grid NMM : Arakawa-E type of grid great flexibility and versatility by adding up new tailored modules less numerical dissipation due to high order numerical algorithms full parallelization recent simulations showed similar accuracy compared to Unified Model from UK Meteorological Office and GME from Deutsche Wetterdienst

WRF presentation

WRF presentation

Radiation model radiation schemes: atmospheric heating and ground heat budget. LW radiation: infrared radiation absorbed and emitted by gases and surfaces. Upward LW flux depends on the surface emissivity (land-use type, and ground (skin) temperature.) SW radiation includes visible and surrounding wavelengths that make up the solar spectrum. Hence, the only source is the Sun, but processes include absorption, reflection, and scattering in the atmosphere and at surfaces Upward SW flux is the reflection due to surface albedo. Within the atmosphere, radiation responds to model-predicted cloud and water vapor distributions, as well as specified carbon dioxide, ozone. All the radiation schemes in WRF currently are column (one-dimensional) schemes(each column is treated independently), Radiative fluxes are similar to those in infinite horizontally uniform planes WRF options: GFDL ; Lacis and Hansen (1974) MM5 (Dudhia); Dudhia (1989) Goddard Shortwave; Chou and Suarez (1994) CAM Shortwave; NCAR Community Atmosphere Model (CAM 3.0)

Radiation model  MM5 (Dudhia); Simple downward integration of solar flux,. Accounting for clear-air scattering, water vapor absorption (Lacis and Hansen, 1974), and cloud albedo and absorption. It uses look-up tables for clouds from Stephens (1978). In WRF V3, the scheme has an option to account for terrain slope and shadowing effects on the surface solar flux. cloud absorption and scattering absorption and scattering transmisivity Evaluation of downward component of shortwave flux: effects of solar zenith angle downward component and the path length; clouds  albedo and absorption; bilinearly interpolated from tabulated functions. The total effect above height z  percentage of Sd clear air: scattering taken uniform and proportional to the atmosphere's mass path length, again allowing for the zenith angle  water-vapour absorption as a function of water vapor path (zenith angle)

ANM Timisoara station supplied with Kipp & Zonen CM6B radiometers. Results Station name Station code Geogra-phical code Lat. (deg N) Long. (deg E) Alt. (m asl) Timisoara 15247 546115 45.77 21.26 86

WRF set-up single-moment microphysics scheme following Hong et al. (2004) the YSU planetary boundary layer scheme (Hong et al., 2006) Kain–Fritsch cumulus scheme (Kain and Fritsch, 1993) MM5 similarity based on Monin-Obukhov with Carslon-Boland viscous sub-layer for surface layer (Paulson, 1970, Dyer and Hicks, 1970 and Webb, 1970), Unified Noah land-surface model, RRTM scheme for long-wave radiation (Mlawer et al., 1997) Dudhia scheme for shortwave radiation (Dudhia, 1989) The synoptic meteorological data (GFS model) started on 06/13/2010- 00:00:00 and expanded up to 06/20/2010-12:00:00 covering 180 hours of forecast of the 0 cycle initialization. Simulation domain centered on the geographical coordinates of radiometer station and expands 1700 km in E-W direction and 850 km in N-S direction. Grid spacing is 18.5 km. No nested grids. The measured data consist of only 110 recordings covering the same forecast horizon

red dots: simulation; black line: measurements; n: point-cloudiness ranging between 0 and 1.

n=0 n=0-0.3 n=0.3-0.7 n=0.7-0.1 n=1.0 all data rMBE (%) 18.23 14.22 11.68 75.69 281.91 32.50 rRMSE 21.62 17.64 26.55 105 412.84 53.63

Thank you for your patience Conclusions GHI forecast fits well within experimental data for situations ranging from clear sky to moderate cloudiness (n<= 0.7) The statistics (MBE, RMSE) show 5%-10% larger values than results of Lara-Fanego (2011) who used a different micro-physics and grid step. Thank you for your patience