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Advanced solutions for solar plantsMilan Infracon, Head of Solar Center of Competence, June 10th 2012
© MIPL SOLAR PLANTApril 21, 2023 | Slide
Sergio Asenjo, Head of Solar Center of Competence, June 10th 2010
© MIPL Solar April 21, 2023 | Slide 2
Photovoltaic plant automationArchitecture
The system will manage, among traditional automation functions/features:
Solar tracking system, when available, for production maximization
Performance calculation of the different stages
MIPL patented Switching System for optimizing inverter efficiency
Troubleshooting management of strings
Integration of plant security and surveillance system
Production automatic reporting system
© MIPL Solar April 21, 2023 | Slide 3
Solar standard solutionTechnology highlights
High precision shadowing control algorithm for solar tracking
Extensible and scalable solution for any plant size
Switching system for optimizing inverter efficiency
Performance/efficiency oriented supervision system
© MIPL Solar April 21, 2023 | Slide 4
Solar standard solutionTechnology highlights
High precision shadowing control algorithm for solar tracking
Shadowing prevention according to tracker dimensions and plant layout
Other systems use “backtracking correction”, thus preventing unnecessary movements and efficiency losses
© MIPL Solar April 21, 2023 | Slide 5
Solar standard solutionTechnology highlights
High precision shadowing control algorithm for solar tracking
MIPL algorithm calculates the optimal position modeling panels and tracker structure geometry
© MIPL Solar April 21, 2023 | Slide 6
Photovoltaic plant automationArchitecture
LAN 2
Local Automation
Solar Tracker
Inverters
MV an LV Swicthgears
DCS
Transformers
OPERATORWORKPLACE
Remote Office
Internet
Remote Access
LAN 1
© MIPL Solar April 21, 2023 | Slide 7
Photovoltaic plant automationFunction allocation
At the DCS level is controlled
Solar plant power electronics device controls
Optimization - switching
Neural networks - intelligent forecast and approximation
Alarms and events handling
At local automation is performed
Trackers
Accurate solar tracking algorithm
One and two axis movement control implementation
Power connection box
Power connection box management
Current per line current control to detect strings failures
© MIPL Solar April 21, 2023 | Slide 8
RS20-0800 RS20-0800
RS20-0400 Spider 5Tx
9PLC5
Fibra ópticaMultimodo
Cable Cat5+
Cable interior armario
9PLC4
9PLC3
9PLC2
9PLC1
9PLC4
8PLC3
8PLC2
8PLC1
7PLC4
7PLC3
7PLC2 7PLC1
6PLC5
6PLC4
6PLC3
6PLC2
6PLC1
5PLC4
5PLC3
4PLC4
4PLC3
5PLC2
5PLC1
4PLC2
4PLC1
3PLC4
3PLC3
3PLC2
3PLC1
2PLC5
2PLC4
2PLC3
1PLC4
2PLC2
2PLC1
1PLC3
1PLC2 1PLC1
Master 2 Master 1
SAION-LINE
ADSL
Supervision & control systems
Photovoltaic plant automationLocal automation architecture
© MIPL Solar April 21, 2023 | Slide 9
Photovoltaic plant automationOperator mimics
© MIPL Solar April 21, 2023 | Slide 10
Photovoltaic plant automationOperator mimics
© MIPL Solar April 21, 2023 | Slide 11
Solar standard solutionTechnology highlights
Switching System for optimizing inverter efficiency
Input power distribution for optimizing inverter efficiency
Switching principles:
Inverter low performance at low loads
Inverter high performance at medium-high loads
One inverter working at medium load, better than two inverters working at low load
Load balancing among inverters
© MIPL Solar April 21, 2023 | Slide 12
Solar standard solutionTechnology highlights
Switching System for optimizing inverter efficiency
Low performance High performance
© MIPL Solar April 21, 2023 | Slide 13
Photovoltaic plant automationAdvanced optimization
DCS advanced control functions
Operation of the switch over cabinet
Optimization based theoretical calculations
Neural networks analysis
© MIPL Solar April 21, 2023 | Slide 14
Photovoltaic plant automationAdvanced 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
© MIPL Solar April 21, 2023 | Slide 15
Solar standard solutionTechnology 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:
Two inverters: PI1=I1*V1 ; PI2=I2*V2
Switching all strings to Inverter 1
One inverter; PI=PI1+PI2 (Ideal)
One inverter; PI’=PI1’+PI2’ (real)
© MIPL Solar April 21, 2023 | Slide 16
Solar standard solutionTechnology highlights
Switching System for optimizing inverter efficiency 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’
1nvIP
2nvIP
3nvIP
1nvIP
3nvIP
1nvIP
2nvIP
3nvIP
1nvIP
3nvIP
© MIPL Solar April 21, 2023 | Slide 17
Solar standard solutionTechnology highlights
Performance/efficiency oriented supervision system
Real time plant performance ratio calculation based on:
Irradiation
Panels strings
Inverters
Transformers
© MIPL Solar April 21, 2023 | Slide 18
New advanced featuresOriented to performance
Efficiency calculation:
For individual elements (strings, trackers, inverters…)
For stages
For the whole plant
To allocate malfunctions in the shortest time
Alarms for deviation in real time (alarms)
Reports
© MIPL Solar April 21, 2023 | Slide 19
Stages for performanceCalculations
Modules Efficiency
Tracking Efficiency
Cabling efficiency
Inverters and Swicthing Efficiency
Trasnformers efficiency
Irradiation
Temperature
Strings Inverters Inverters output
Modules Characteristics
Tracking- Perfect- Optimal
distribution
Inverter characteristics
Swicthing scheme
Transformers characteristics
Real Position
String Tracker Inverters Transformer
Trafo
Counter
DC cable Design charactericits
DC fieldA
V
A
V
A
V
A
V
© MIPL Solar April 21, 2023 | Slide 20
Real performanceDevices for measuring
Measurements devices:
Weather station
Pyranometers
Reference cells
Inclinometers
Strings measurements
Inverters measurement
Input DC
Output ac
Transformers
Electrical metering
© MIPL Solar April 21, 2023 | Slide 21
Theoretical performanceCalculation methods
Equipment characteristics
Modules behavior
Tracking models
Perfect
Optimal
Cabling design
Switching, inverter curves
Transformers performance curves
Control system strategy and features
PLCs, SCADA, Databases
© MIPL Solar April 21, 2023 | Slide 22
Energy balance reports
18/12/2009 Modules
Plant Líne String RadiationOutput
MeasuredOutput
Calculated Eff. Measured Eff. Calculated Ratio
P1 P1-L1 P1-L1-S1 8 KWh 1,2 KWh 1,22 KWh 14% 14,5% 96,6%
P1-L1-S2 8 KWh 1,2 KWh 1,22 KWh 14% 14,5% 96,6 %
P1-L1-S3 8 KWh 1,2 KWh 1,22 KWh 14% 14,5% 96,6 %
P1-L1 24 KWh 3,6 KWh 3,66 Kwh 14% 14,5% 96,6 %
P1-L2 P1-L2-S1 8 KWh 1,2 KWh 1,22 KWh 14% 14,5% 96,6 %
P1-L2-S2 8 KWh 0,9 KWh 1,22 KWh 11,25% 14,5% 77,58%
P1-L2-S3 8 KWh 1,2 KWh 1,22 KWh 14% 14,5% 96,6%
P1-L2 24 KWh 3,3 KWh 3,66 Kwh 12,5% 14,5% 90,26%
P1 -- 48 KWh 6,9 KWh 7,32 Kwh 13,78% 14,5% 93,52%
P2 P2-L1 P2-L1-S1 8 KWh 1,2 KWh 1,22 KWh 14% 14,5% 96,6 %
P2-L1-S2 8 KWh 1,2 KWh 1,22 KWh 14% 14,5% 96,6 %
P2-L1-S3 8 KWh 1,1 KWh 1,22 KWh 13% 14,5% 90,11 %
P2-L1 24 KWh 3,5 KWh 3,66 Kwh 13,64% 14,5% 94,35%
P2 -- 24 KWh 3,5 KWh 3,66 Kwh 13,64% 14,5% 94,35%
Summary -- -- 72 KWh 10,4 KWh 10,98 Kwh 13,71% 14,5% 93,80%
© MIPL Solar April 21, 2023 | Slide 23
Production increase.
Nubosidad
Disminución de irradiancia debido a la posición horizontal
0,00
200,00
400,00
600,00
800,00
1000,00
1200,00
7:59 10:23 12:47 15:11Hora
Irra
dia
ncia
(W
/m2)
Wind position.
Production in normal conditions
Production during high wind
Irradiancia aprovechada en caso de viento
0
100
200
300
400
500
600
7:59 9:11 10:23 11:35 12:47 13:59 15:11 16:23
Horas con seguidor en posición horizontal
Irrad
ianc
ia (W
/m2)
Irradiancia aprovechada con conmutación
0
20
40
60
80
100
120
140
160
180
200
4:48 7:12 9:36 12:00 14:24 16:48 19:12
Hora
Con granizo
Hail Position
Production in normal conditions
Production during hail situation.
MIPL system optimizationAutomatic Switching system during hail and high wind
© MIPL Solar April 21, 2023 | Slide 24
Irradiancia día 23
0,00
100,00
200,00
300,00
400,00
500,00
600,00
700,00
800,00
0:00 2:24 4:48 7:12 9:36 12:00 14:24 16:48 19:12 21:36
Tiempo (h)
Dawn
Cloudiness
Dawn - nightfallr
Red color area production increase
MIPL system optimizationAutomatic Switching system in dawn, nightfall and clouds
© MIPL Solar April 21, 2023 | Slide 25
Solar standard solutionTechnology improvements
0 Kwh
10 Kwh
20 Kwh
30 Kwh
40 Kwh
50 Kwh
60 Kwh
70 Kwh
80 Kwh
90 Kwh
100 Kwh
6:
00
7:
00
8:
00
9:
00
10
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11
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12
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13
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14
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18
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20
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23
:00
PV Plant 1 PV Plant 3 PV Plant 2
Performance/efficiency increased by 0,8% to 2,5%
Production increased during the whole day, starting earlier and shutting off later.
© MIPL Solar April 21, 2023 | Slide 26
Photovoltaical power plant (PV) Reference plant
© MIPL Solar April 21, 2023 | Slide 27
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