Sergio Asenjo Head of Solar Center of Competence

Sergio Asenjo, Head of Solar Center of Competence, June 10 th 2010 Advanced solutions for solar plants © ABB PP&PS FES Italia 19 March 2018 | Slide 1

Photovoltaic plant automation Architecture The system will manage, among traditional automation functions/features: § § Performance calculation of the different stages § ABB patented Switching System for optimizing inverter efficiency § Troubleshooting management of strings § Integration of plant security and surveillance system § © ABB Solar COC Spain 19 March 2018 | Slide 2 Solar tracking system, when available, for production maximization Production automatic reporting system

Solar standard solution Technology highlights § § Extensible and scalable solution for any plant size § Switching system for optimizing inverter efficiency § © ABB Solar COC Spain 19 March 2018 | Slide 3 High precision shadowing control algorithm for solar tracking Performance/efficiency oriented supervision system

Solar standard solution Technology highlights High precision shadowing control algorithm for solar tracking § § © ABB Solar COC Spain 19 March 2018 | Slide 4 Shadowing prevention according to tracker dimensions and plant layout Other systems use “backtracking correction”, thus preventing unnecessary movements and efficiency losses

Solar standard solution Technology highlights § High precision shadowing control algorithm for solar tracking § © ABB Solar COC Spain 19 March 2018 | Slide 5 ABB algorithm calculates the optimal position modeling panels and tracker structure geometry

Photovoltaic plant automation Architecture LAN 2 Local Automation LAN 1 Solar Tracker OPERATOR WORKPLACE DCS Inverters MV an LV Swicthgears Internet e. Mail Remote Access Transformers Remote Office © ABB Solar COC Spain 19 March 2018 | Slide 6

Photovoltaic plant automation Function allocation § At the DCS level is controlled § § Optimization - switching § Neural networks - intelligent forecast and approximation § § Solar plant power electronics device controls Alarms and events handling At local automation is performed § Trackers § § § Accurate solar tracking algorithm One and two axis movement control implementation Power connection box § § © ABB Solar COC Spain 19 March 2018 | Slide 7 Power connection box management Current per line current control to detect strings failures

Photovoltaic plant automation Local automation architecture Supervision & control systems 6 PLC 5 8 PLC 3 9 PLC 5 9 PLC 1 8 PLC 2 7 PLC 4 7 PLC 3 6 PLC 2 4 PLC 4 6 PLC 1 4 PLC 3 6 PLC 3 5 PLC 4 7 PLC 1 5 PLC 3 5 PLC 2 4 PLC 2 3 PLC 3 2 PLC 5 4 PLC 1 3 PLC 2 2 PLC 4 3 PLC 1 1 PLC 4 2 PLC 3 2 PLC 2 1 PLC 3 Cable Cat 5+ 9 PLC 4 9 PLC 2 9 PLC 4 8 PLC 1 7 PLC 2 5 PLC 1 2 PLC 1 1 PLC 2 1 PLC 1 Cable interior armario RS 20 -0400 Fibra óptica Multimodo Master 2 ADSL © ABB Solar COC Spain 19 March 2018 | Slide 8 RS 20 -0800 SAI ON-LINE Master 1 Spider 5 Tx

Photovoltaic plant automation Operator mimics © ABB Solar COC Spain 19 March 2018 | Slide 9

Photovoltaic plant automation Operator mimics © ABB Solar COC Spain 19 March 2018 | Slide 10

Solar standard solution Technology highlights Switching System for optimizing inverter efficiency § Input power distribution for optimizing inverter efficiency § Switching principles: § § Inverter high performance at medium-high loads § One inverter working at medium load, better than two inverters working at low load § © ABB Solar COC Spain 19 March 2018 | Slide 11 Inverter low performance at low loads Load balancing among inverters

Solar standard solution Technology highlights Switching System for optimizing inverter efficiency § © ABB Solar COC Spain 19 March 2018 | Slide 12 Low performance § High performance

Photovoltaic plant automation Advanced optimization § DCS advanced control functions § § Optimization based theoretical calculations § © ABB Solar COC Spain 19 March 2018 | Slide 13 Operation of the switch over cabinet Neural networks analysis

Photovoltaic plant automation Advanced optimization Over the Maximum Power Point Tracking algorithm (MPPT) to increase performance in operational points like low sun conditions it has been developed a set of algorithms based on Artificial Neural Networks (ANN) and designed to adapt themselves to the particular conditions of every PV plant © ABB Solar COC Spain 19 March 2018 | Slide 14

Solar standard solution Technology highlights Switching system for optimizing inverter efficiency § Neuronal Network is an adaptive approximation method to achieve a more accurate calculation of output power in case of switching § Working Principle: § § Switching all strings to Inverter 1 § One inverter; PI=PI 1+PI 2 (Ideal) § © ABB Solar COC Spain 19 March 2018 | Slide 15 Two inverters: PI 1=I 1*V 1 ; PI 2=I 2*V 2 One inverter; PI’=PI 1’+PI 2’ (real)

Solar standard solution Technology highlights Switching System for optimizing inverter efficiency § § © ABB Solar COC Spain 19 March 2018 | Slide 16 The difference is in the PV turbine equivalent I-V curve (affected by panel degradation, dirtiness, etc. . ) Neuronal network learns from real values to get progressively a better PI’

Solar standard solution Technology highlights Performance/efficiency oriented supervision system § Real time plant performance ratio calculation based on: § § Panels strings § Inverters § © ABB Solar COC Spain 19 March 2018 | Slide 17 Irradiation Transformers

New advanced features Oriented to performance § Efficiency calculation: § For individual elements (strings, trackers, inverters…) § For stages § For the whole plant § § Alarms for deviation in real time (alarms) § © ABB Solar COC Spain 19 March 2018 | Slide 18 To allocate malfunctions in the shortest time Reports

Stages for performance Calculations Tracking Perfect Optimal distribution Modules Characteristics DC cable Design charactericits Strings Transformers characteristics Inverter characteristics Swicthing scheme Inverters output Inverters Irradiation Real Position Temperature String Modules Efficiency © ABB Solar COC Spain 19 March 2018 | Slide 19 V Tracker Tracking Efficiency A A DC field Cabling efficiency Inverters and Swicthing Efficiency A Counter V V V Trafo Transformer Trasnformers efficiency A

Real performance Devices for measuring § Measurements devices: § Weather station § Pyranometers § Reference cells § Inclinometers § Strings measurements § Inverters measurement § Input DC § Output ac § § © ABB Solar COC Spain 19 March 2018 | Slide 20 Transformers Electrical metering

Theoretical performance Calculation methods § Equipment characteristics § Modules behavior § Tracking models § Perfect § Optimal § § Switching, inverter curves § § Cabling design Transformers performance curves Control system strategy and features § © ABB Solar COC Spain 19 March 2018 | Slide 21 PLCs, SCADA, Databases

Energy balance reports 18/12/2009 Modules Output Calculated Plant Líne String Radiation Output Measured P 1 -L 1 -S 1 8 KWh 1, 22 KWh 14% 14, 5% 96, 6% P 1 -L 1 -S 2 8 KWh 1, 22 KWh 14% 14, 5% 96, 6 % P 1 -L 1 -S 3 8 KWh 1, 22 KWh 14% 14, 5% 96, 6 % P 1 -L 1 24 KWh 3, 66 Kwh 14% 14, 5% 96, 6 % P 1 -L 2 -S 1 8 KWh 1, 22 KWh 14% 14, 5% 96, 6 % P 1 -L 2 -S 2 8 KWh 0, 9 KWh 1, 22 KWh 11, 25% 14, 5% 77, 58% P 1 -L 2 -S 3 8 KWh 1, 22 KWh 14% 14, 5% 96, 6% P 1 -L 2 24 KWh 3, 3 KWh 3, 66 Kwh 12, 5% 14, 5% 90, 26% Eff. Measured Eff. Calculated Ratio P 1 48 KWh 6, 9 KWh 7, 32 Kwh 13, 78% 14, 5% 93, 52% P 2 -L 1 -S 1 8 KWh 1, 22 KWh 14% 14, 5% 96, 6 % P 2 -L 1 -S 2 8 KWh 1, 22 KWh 14% 14, 5% 96, 6 % P 2 -L 1 -S 3 8 KWh 1, 1 KWh 1, 22 KWh 13% 14, 5% 90, 11 % P 2 -L 1 24 KWh 3, 5 KWh 3, 66 Kwh 13, 64% 14, 5% 94, 35% P 2 - 24 KWh 3, 5 KWh 3, 66 Kwh 13, 64% 14, 5% 94, 35% Summary © ABB Solar COC Spain 19 March 2018 | Slide 22 -- -- -- 72 KWh 10, 4 KWh 10, 98 Kwh 13, 71% 14, 5% 93, 80%

ABB system optimization Automatic Switching system during hail and high wind § Production increase. Wind position. q Production in normal conditions q Production during high wind Nubosidad Hail Position q Production in normal conditions © ABB Solar COC Spain 19 March 2018 | Slide 23 q Production during hail situation.

ABB system optimization Automatic Switching system in dawn, nightfall and clouds Red color area production increase Cloudiness Dawn - nightfallr Dawn © ABB Solar COC Spain 19 March 2018 | Slide 24

Solar standard solution Technology improvements 00 10 : 0 0 11 : 0 0 12 : 0 0 13 : 0 0 14 : 0 0 15 : 0 0 16 : 0 0 17 : 0 0 18 : 0 0 19 : 0 0 20 : 0 0 21 : 0 0 22 : 0 0 23 : 0 0 00 9: 8: PV Plant 2 § § § § 7: § § § 6: 00 100 Kwh § 90 Kwh § 80 Kwh § 70 Kwh § 60 Kwh § 50 Kwh § 40 Kwh § 30 Kwh § 20 Kwh § 10 Kwh § 0 Kwh PV Plant 3 § § PV Plant 1 § 00 § Performance/efficiency increased by 0, 8% to 2, 5% Production increased during the whole day, starting earlier and shutting off later. © ABB Solar COC Spain 19 March 2018 | Slide 25

Photovoltaical power plant (PV) Reference plant © ABB Solar COC Spain 19 March 2018 | Slide 26

© ABB Solar COC Spain 19 March 2018 | Slide 27