Web tools for performance analysis and planning support for solar energy plants starting from remotely sensed optical images Dr.

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1 Web tools for performance analysis and planning support for solar energy plants starting from remotely sensed optical images Dr. Marco Morelli University of Milano Department of Physics Flyby S.r.l. R&D Department EnviroInfo EU EnerGEO / ENDORSE Session Hamburg, 3 rd September 2013

2 Outline 1. Introduction 2. Scheme of the web services 3. CSP-Planner service 4. CSP-Controller service 5. First results obtained 6. Current coverage and users 7. Free access to the demo versions 8. Conclusion and outlooks

3 Introduction Flyby developed two innovative web services in the field of renewable energy also through the collaboration with the University of Milano and the participation to the FP7 ENDORSE project The services concern with solar energy plants planning and monitoring, exploiting satellite-based data (MACC Core Services) and being delivered on the web using also GIS technology

4 Scheme of the web services The two services, that are adaptable to any solar energy plant (e.g. PV, CSP or CPV), are the followings: Controller web service -> monitors in near real-time the performances of an existing solar energy plant, readily detecting possible malfunctioning Planner web service -> supports the identification of the best site for installing a new solar energy plant and for configuring it optimally, providing also an estimate of the potential investment s profitability

5 Scheme of the web services Controller Planner Near real-time (day before) solar irradiance (GHI or BNI) calculated from satellite every 15 minutes Plane of arrays/receivers irradiance modelling Average solar irradiance (GHI or BNI) and average temperature (2m) calculated from long time-series of satellite imagery Location and technical features of the planned solar energy plant Solar energy plant and inverters physical modelling Solar energy plant and inverters physical modelling NRT expected AC power behavior Expected monthly AC energy production Comparison with the measured production and alert in case of malfunctioning Expected break-even point and Return on Investment (RoI) analysis

6 Example: CSP energy plants Parabolic-trough CSP plants modelling (ENDORSE)

7 CSP-Planner service: inputs (I) Select Location page Average BNI map Average air temperature map Average wind intensity map

8 CSP-Planner service: inputs (II) Technical features page Solar collector modules Heat Transfer Fluid Glass Envelope Absorber Pipe Thermal Energy Storage

9 CSP-Planner service: outputs Plant producibility and economics page Monthly energy yield Global economic indicators Cumulative cash flow Break-even point

10 CSP-Controller service

11 Calculated daily AC energy (kwh) First results obtained The service has been successfully tested in August 2013 for a CSP plant located in Sicily (Italy): the discrepancies between the satellite-based AC power and the measured one were below 10%, i.e. within the typical end-users expectations y = x R² = Measured daily AC energy (kwh)

12 Current coverage and users the current coverage of the Controller service is the MSG satellite FOV (from -66 to 66 both in latitude and longitude) the Planner service has been developed only for Italy (at the moment) the CSP-Planner/Controller services have been tested and received positive feedbacks from many end-users, such as: Enel Green Power (Italy) Endesa (Spain) Sahara Forest Project (Norway) ESTELA (European Association)

13 Free access to the demo versions CSP-Planner and CSP-Controller are currently free accessible online (in their demo versions) with the following credentials: CSP-Planner Web-address: User: user Password: Ersim_2011 CSP-Controller Web-address: User: csp_user Password: Ersim_2011 Possible comments and feedbacks are welcome!!

14 Conclusion and outlooks The PV-Planner/Controller services have being satisfactorily used since several years by tens of end-users CSP-Planner and CSP-Controller have been tailored for parabolic-trough CSP plants, but are currently being developed to include also Fresnel CSPs The Planner and the Controller services are being adapted also to CPV plants The satellite-based temperature, currently used in the Planner service, could be included also in the Controller service (NRT technique in development with the collaboration of the University of Genoa) -> big-quick environmental data handling problem still to be solved!

15 Contacts Many thanks for your attention! Dr. Marco Morelli Department of Physics University of Milano, Italy Dr. Fabrizio Ruffini R&D Department Flyby S.r.l., Livorno, Italy Dr. Marco Alberto Carlo Potenza Department of Physics University of Milano, Italy Eng. Andrea Masini R&D Department Flyby S.r.l., Livorno, Italy