!Figure 1: 229 kwp photovoltaic plant at Rivière Salée!The orientation of the roof ridge is roughly North-

Similar documents
Modelling Photovoltaic Systems using PSpice

6KW Grid Interactive Photovoltaic System

USE OF PV PLANTS MONITORING TO CHARACTERIZE PV ARRAYS POWER

The Challenges of Accurately Predicting PV System Performance

Reference: Photovoltaic Systems, p. 229

ENERGY YIELD MODELLING OF PV SYSTEMS OPERATING IN NAMIBIAN CONDITIONS

FY2017 SREC Registration Program (SRP) Final As-Built Technical Worksheet Instructions Page 1

Quality Control Applied to the Photovoltaic Systems of the Galapagos Islands: The Case of Baltra and Santa Cruz. Andrea Alejandra Eras Almeida

Technical University of Cartagena (UPCT) - Spain

VDE PHOTOVOLTAICS. electrosuisse^> Verlag SYSTEM DESIGN AND PRACTICE VERLAG. Heinrich Häberlin. Translated by Herbert Eppel

Reference: Photovoltaic Systems, p References: Photovoltaic Systems, Chap. 14 Battery Service Manual, 12 th Ed., Battery Council International

Design and Performance Analysis of a Grid Connected Solar Photovoltaic System

ALL PARTIES MUST SIGN SECTION F.

GRID-CONNECTED PV SYSTEMS SYSTEM DESIGN GUIDELINES

Presented at the 29th European PV Solar Energy Conference and Exhibition, September 2014, Amsterdam, The Netherlands

Design Installation and Testing of 1.6 kwp GPV System

Main Header. PV Module Characterization Methods at CFV Solar Test Lab Sub header. Sandia 2014 PV Systems Symposium Santa Clara, CA

Grid-connected photovoltaic power systems: Power value and capacity value of PV systems

Australian Technical Guidelines for Monitoring and Analysing Photovoltaic Systems

LA SILLA PV PLANT INNOVATIVE BIFACIAL PV PLANT AT LA SILLA OBSERVATORY IN CHILE

Rooftop Solar PV System Designers and Installers. Training Curriculum. APEC Secretariat

Solar Project Yield Assessment. Workshop on Solar Power Project Development, Sept 20-21, 2012

Green Star Photovoltaic Modelling Guidelines

PERFORMANCE OF BP SOLAR TANDEM JUNCTION AMORPHOUS SILICON MODULES

EUROPEAN COMMISSION SEVENTH FRAMEWORK PROGRAMME THEME ENERGY-NMP (Joint Call) ENERGY NMP

100% Renewable New Zealand Solar Photovoltaic (PV) Contribution? Allan Miller Director, EPECentre and GREEN Grid

ASSESSMENT AND DESIGN OF ROOFTOP SOLAR PV SYSTEM. Click to begin

PV DOMESTIC HOT WATER SYSTEM

Performance loss rates of grid-connected photovoltaic technologies in warm climates

SOLAR ENERGY ASSESSMENT REPORT. For 80.5 kwp. Meteorological Data Source NASA-SSE. Date 18 October, Name of Place Uttar Pradesh.

George Gross Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign

LECTURE 15 PHOTOVOLTAIC MATERIALS. ECE 371 Sustainable Energy Systems

A study for an optimization of a hybrid renewable energy system as a part of decentralized power supply

SOLAR PV-DRIVEN AIR CONDITIONER

Investigation on Temperature Coefficients of Three Types Photovoltaic Module Technologies under Thailand Operating Condition

Dust effects on PV array performance: in-field observations with non-uniform patterns

Development of Movable Testing Equipment for Artificial Light Source Photovoltaic Module

GRID CODE COMPLIANCE TESTING OF RENEWABLES NEW REQUIREMENTS AND TESTING EXPERIENCES

Measuring Soiling Losses at Utility-scale PV Power Plants

ENERGY EFFICIENCY OF PHOTOVOLTAIC SOLAR PLANT IN REAL CLIMATE CONDITIONS IN BANJA LUKA

Basic principles for designing PV plant monitoring systems

PERFORMANCE MONITORING AND EVALUATION OF A 1.72 KW P GRID-CONNECTED PV SYSTEM

GRID-CONNECTED PV SYSTEMS (No Battery Storage) SYSTEM DESIGN GUIDELINES

Design and Simulink of Intelligent Solar Energy Improvement with PV Module

AORC Technical meeting 2014

INACCURACIES OF INPUT DATA RELEVANT FOR PV YIELD PREDICTION

Solar PV Nominated Technical Persons Criteria

Design of a Multiparameter Acquisition System for Photovoltaic Panels

GRID-CONNECTED PV SYSTEMS (No Battery Storage) SYSTEM DESIGN GUIDELINES FOR THE PACIFIC ISLANDS

International Standard Corresponding Indian Standard Degree of Equivalence

Performance Characterization of Cadmium Telluride Modules Validated by Utility-Scale and Test Systems

Available online at ScienceDirect. Energy Procedia 48 (2014 )

Photovoltaic Systems II. EE 446/646 Fall 2013

AN EFFECTIVE STUDY ON PERFORMANCE ANALYSIS OF GRID CONNECTED PV SYSTEM

An inverter is the heart of a solar PV installation and it plays a critical role in maximizing energy harvest.

PHOTOVOLTAICS HISTORY OF PHOTOVOLTAICS

A Distributed Maximum Power Point Control For Efficiency Enhancement Of Photovoltaic System

Solar cell junction temperature measurement of PV module

Design and Simulation of Photovoltaic System in Matlab using Simulink

Effect of Temperature on Solar Panel Performance

Performance evaluation of hybrid solar parabolic trough concentrator systems in Hong Kong

The Efficiency of Solar PV System

Course Title: Advanced PV Design (PV201) (NRG 220) 5 credits (55 hours)

Bifacial PV modules: measurement challenges

Website:

Quality Assessment of PV systems by Analysis of System Performance

ABSTRACT. Introduction

REQUEST FOR BID (TURNKEY SOLUTION) 1MW GRID TIE SOLAR PV POWER PLANT. Location:

Solar Electric Power Generation - Photovoltaic Energy Systems

The role of Power Electronics in Photovoltaic Power Generation Systems

Fact sheet. Photovoltaic systems. Why consider photovoltaics?

Performance, Reliability and Analysis of Photovoltaic Systems. Results & Deliverables of IEA PVPS Task 2. Ulrike Jahn Christoph Hünnekes

Extreme Engineering for Extreme Conditions

Lei Chu San Office for the Development of the Energy Sector, Macau SAR, China

Technical Talk on HK s Largest Solar Power System at Lamma Power Station

Solar Energy Modeling for Residential Applications

Solar Photovoltaic Electricity Generation for Dairy Farms

Performance Analysis of PV Solar Power System

Moving Forward to Module- Level Power Optimization

PV Module Right-Sizing for Microinverters

Monitoring of 20 kwp photovoltaic system

The Performance Analysis of a Three-Phase Grid- Tied Photovoltaic System in a Tropical Area

Appendix 22. Copyright 2011 Surmount Energy Solutions Pvt. Ltd. Copyright 2011 Surmount Energy Solutions Pvt. Ltd

A technique for accurate energy yields prediction of photovoltaic system

DISTRIBUTED GENERATION AND POWER QUALITY

PID Analysis MEUBELEN VERHAEGEN BETEKOM, BELGIUM

SEAC. Roland Valckenborg 13 september Partner in solar energy solutions

Modeling a PV-FC-Hydrogen Hybrid Power Generation System

Home PV System Design

Hawai i Energy and Environmental Technologies (HEET) Initiative

Investigating the Shading Impact of Rail on the Energy Output of a PV System in Hong Kong

DuraMAT Capability 5 Field Testing: Overview and Capability Development Activities. Birk Jones and Bruce King DuraMat Workshop May 22-23, 2017

Location of Energy Storage Units

INVESTMENT PROPOSAL ON THE FORMER LANDFILL IN SCHISTO AREA - MUNICIPALITY OF PERAMA

Solar Integration Study

Validation of Methods Used in the APVI Solar Potential Tool

Energy Efficient Solar Milk Chiller

Switch Solar. Praveen Raj. [20 KWp Solar Power Plant Technical Proposal] Noble Hospital Chennai, Tamil Nadu.

Impact of PV Energy Resources on the Quality of power of the Electrical Power System

TEMPERATURE TESTING AND ANALYSIS OF PV MODULES PER ANSI/UL 1703 AND IEC STANDARDS

Transcription:

MARTINIQUE ISLAND- FIRST FULL APPLICATION OF THE MOTHERPV METHOD Antoine Guérin de Montgareuil 1, Patrice Rosamont 2, Sarah Darivon 2, Laurent Bellemare 2 1 CEATech DPACA - Cadarache, bât. 356 - F-13108 St-Paul-lez-Durance, France gdm@cea.fr 2 Agence Martiniquaise de l Energie, Immeuble les Bosquets 2-26 ZI Petite Cocotte Champigny F-97224 Ducos bellemare.l@energie.mq ABSTRACT: The Martinique energy agency (AME) and CEA lead a common research program on the performance of PV under the specific (tropical) climate of Martinique Island. AME has set up more than 25 roof integrated PV systems in the different climatic regions of the Island, from 7.5 kwp to 229 kwp. This 229 kwp system has been carefully monitored in order to apply the CEA s MotherPV method which allows 1- an estimation of the installed PV peak power and 2- a very accurate modelling of the behaviour of the system, which is able to detect even very slight problems in the energy production. This article describes the specific monitoring of the system and the result of the first full application of the MotherPV with its 2 approaches: previous indoor/outdoor measurements versus in situ measurements (new method). The two approaches give very similar results (difference of 0.4 %) and can be used for the assessment of the power of photovoltaic systems and for the monitoring of the production. Keywords: photovoltaic system peak power, MotherPV method, energy yield modelling 1. INTRODUCTION The Martinique energy agency (AME) and CEA lead a common research program on the performance of photovoltaics under the specific (tropical) climate of Martinique Island. AME has set up more than 25 roof integrated PV systems in the different climatic regions of the island, from 7.5 kwp to 229 kwp. This 229 kwp system has been monitored very carefully in order to apply and to assess the validity of the CEA s MotherPV method. This method is used to (see [1-3]): 1. Assess the real peak power of a photovoltaic system with a great accuracy 2. Monitor very accurately the behaviour of a system and detect even very slight problems in the energy production. Historically, to characterize the behaviour of the generator of a photovoltaic system, the MotherPV method used the flash-tests of the modules, indoor measurements of the module peak power of a carefully selected set of modules at a reference laboratory and outdoor measurements of a few modules at every irradiance and temperature levels (see [4]). Since 2014, instead of these preliminary measurements, MotherPV proposes to use as an alternative the monitored characteristics of the system, provided that the irradiance sensors of the monitoring perfectly match the response of the modules and are very well calibrated. This article presents the application of the two approaches of the MotherPV method applied to the 229 kwp photovoltaic plant at Rivière Salée. 2. THE RIVIERE SALEE PHOTOVOLTAIC SYSTEM Figure 1: 229 kwp photovoltaic plant at Rivière Salée The orientation of the roof ridge is roughly North- West South-East (azimuth 143.4-0 is North). 3. ACCURATE MONITORING OF THE SYSTEM The monitoring system is a combination of a standard Fronius system and a specific system (see Figure 2). The photovoltaic system in the roof of the Sport Centre of Rivière Salée has been set up in 2009. It is made of 1296 mono-crystalline silicon modules, for a total power of 229 kwp (see Figure 1). The system hosts 18 IG+150 Fronius inverters, 9 for each slope of the roof. Each inverter is linked to 6 parallel strings of 12 modules connected in series. Figure 2: Monitoring of the system The Fronius system uses an electronic card in the inverter (current and voltage on the module side of the inverter, grid injected power, grid frequency), a sensor box linked to various sensors (irradiance, wind speed

and direction, ambient temperature, module temperature) and a communication device. instantaneous power of the generator 8. Model inverter s behaviour (see [2]) and calculate the theoretical energy injected on the grid 9. Detect production problems by comparing the calculated and the measured energy injection A specific system has been developed by CEA, using LEM sensors for the measurement of the current and voltage on the module side of the inverter, Moxa acquisition units for the measurements of irradiance and module temperature. Specifically calibrated shortcircuited modules are used as irradiance sensors and Jumo surface Pt100 resistors as temperature sensors. Diris acquisition units monitor the AC part of the inverters, recording voltage and current (including their harmonics), frequency, active and reactive power and energy. 4.2 Results According to [4], the coefficient of the flash test of the manufacturer is -3.1% and the power measured by the manufacturer has to be multiplied by a factor of 0.969 to get the power rated by the reference laboratory. The total flash-tested power of the 1460 modules was 258.1 kwp. Among the 1460 rated modules, 1296 modules have been anonymously used for the Rivière Salée photovoltaic system. The modules were provided by groups of 20 modules. The installer of the system used all the modules of 64 groups and 16 modules of the last group. The total flash-tested power of each group of modules has been calculated. In the worst case, the installer took the modules of the groups with the lowest power and in the best case, the modules of the groups with the highest power. The maximum difference of power between the worst and the best case is small (around 0.4 %). The average power of the 1296 selected modules was then 229.1 kwp. With the correction coefficient of 0.969, the estimated total power of the modules before their initial ageing was 222.0 kwp. The first loss coefficient has been measured at 0.976 and the estimated total power of the modules after their first ageing was 216.6 kwp. Specific software monitors data every second and stores the measurements every minute (instantaneous value and one-minute statistical values: average, minimum, maximum and standard deviation). Data are stored in a SQLServer relational database. 4. MOTHERPV MODELLING BY USING INDOOR/ OUTDOOR MEASUREMENTS 4.1 Procedure This procedure allows the calculation of the power of the power plant at any temperature and irradiance conditions. Particularly, it provides the estimation of the electric power of the system at the module side of the inverter at Standard Test Conditions (delivered peak power). The procedure is the following: 1. Determine the correction coefficient of the flash test of the manufacturer by characterizing the peak power of a limited set of carefully selected modules at a reference test laboratory (see [4]) 2. Expose a few modules outdoors during some time in order to receive a sufficient amount of radiation and characterize again their peak power to calculate the initial loss of power 3. Calculate the total power of the modules installed in the photovoltaic system by adding their flash-tested power and correcting it by the correction coefficient calculated in 1 and by the initial loss coefficient calculated in 2 4. Characterize the average behaviour of the modules at every short circuit and module temperature condition by a short outdoor measurement campaign (alternatively, this characterization may be performed indoors by a quicker procedure - see the description of this recently developed procedure in [5]) and determine the MotherPV formula allowing the calculation of the module power at every short circuit and module temperature condition 5. Take into account the effect of module mismatch, of interconnection losses (Joule effect) and of the nonideality of the maximum power point tracker of the inverter 6. Calculate the peak power of the generator (calculate the theoretical power at Standard Test Conditions using 4 and derate it by using the derate factors calculated in 5) 7. Monitor the system with the measurements of the module temperatures and of the short circuit current of reference modules (or of the signal of a perfectly matched reference cell) and calculate the total The effects (losses) of module mismatch, interconnection losses (Joule effect) and non-ideal behaviour of the inverter s maximum power point tracker have been estimated respectively to 1.5%, 1.5% and 1%, leading to a coefficient of 0.96. The total power of the generator was then 208.0 kwp and the global correction coefficient was 0.908. The derating coefficient regarding the flash-tests was 9.2%. The power of the generator of each inverter was estimated to 11.6 kwp. The behaviour of the modules has been determined by an outdoor campaign of measurements on 6 modules during a few weeks at Cadarache (See Figure 3). Figure 3: Preliminary module characterization at CEA s outdoor facility The behaviour of the 6 modules was very uniform and can be seen in Figure 4.

Figure 4: MotherPV coefficient of the tested modules The interpretation of this graph is that, for a module temperature of 25 C, as long as the short circuit current of the modules is higher than 0.5 times their short circuit current at Standard Test Conditions, their power is proportional to their power at Standard Test Conditions (module coefficient is 1). For lower irradiance conditions, the module coefficient is lower than 1, and their power is less than proportional to their power at Standard Test Conditions (see [3]). Then, using the flash-tested power, the total correction factor, the MotherPV coefficient of the module, the temperature coefficient of the module, the module temperature and the short circuit current of the reference modules, the model of the inverter s behaviour, it is possible to calculate at every time the power of the generator and the power injected on the grid. 5. Express VDC as a linear function of module temperature at each IDC level, calculate the voltage temperature coefficients and express this coefficient as a function of IDC if necessary (if it is not constant) 6. Determine the coefficients of the MotherPV formula by calculating the voltage VDC translated at 25 C as a function of IDC 7. Calculate VDCSTC by applying the MotherPV formula coefficients calculated in 6 to the value of IDCSTC calculated in 4 Then, the rest of the procedure is the same as in paragraph 4.1, items 7-9, except that the power of the generator is directly calculated from module temperatures and from IDC instead of the measurement of the short circuit current of the reference modules. 5.2 Results Data filtering has been a specific part of the work and filtering methods developed by CEA during the PV Performance European project of the 6 th framework program have been used and improved. Particularly, checking the validity of module temperature was not straightforward and required intensive comparisons of the values of several temperature sensors to discard bad values. The same work was performed for IDC data versus irradiance signal (see Figure 5). 5. NEW PROCEDURE: MOTHERPV MODELLING BY USING IN SITU MEASUREMENTS 5.1 Procedure The procedure described in paragraph 4 requires the selection and the test of modules at Standard Test Conditions at an indoor reference laboratory and their characterization at every short circuit and temperature conditions at an indoor or at an outdoor reference laboratory, which is long and costly. It took very long to send the modules from Martinique Island to the Callab of the Fraunhofer Institute at Friburg, then to Cadarache, then to Friburg again to test the ageing of the modules after their first outdoor exposure. In 2014, CEA developed a new procedure using in situ measurements to determine the total installed peak power of the system and the behaviour of the system at every irradiance and temperature conditions, allowing a very accurate modelling of the behaviour of the system, detecting every change in the system production. The procedure is the following: 1. Install perfectly matched reference devices (calibrated short circuited modules or calibrated reference cell with the same spectral response as the modules) and monitor the solar resource available to the module 2. Monitor the temperature of the modules and the current IDC and the voltage VDC of the generator, at the DC side of the inverter 3. Filter wrong data 4. Determine the value of the current of the generator IDCSTC at Standard Test Conditions by using filtered monitored data Figure 5: IDC versus irradiance non-filtered (top) and filtered (bottom) IDCSTC has been calculated by taking into account the difference of temperature of the generator and of the reference module. Then, the temperature coefficient of the voltage has been calculated at each current level and expressed as a function of the current. As this coefficient was not constant, it has been expressed as the combination of three linear functions (see Figure 6), which is new for the MotherPV method. The behaviour of this temperature

coefficient has not been explained yet. Figure 8: Modelling of the behaviour of the generator at Figure 6: VDC temperature coefficient expressed as a function of IDC Finally, VDC was expressed as a function of IDC. Figure 7 shows the non-filtered and the filtered data, without temperature correction. One can see that the filtering process has been essential to determine the standard behaviour of the generator. Figure 7: VDC versus IDC, non-filtered (top) and filtered (bottom) Finally, the DC voltage was translated to 25 C and the MotherPV coefficients were calculated (see Figure 8, where the agreement between the model and the average behaviour of the system is obvious). 25 C Then, the voltage and the power at Standard Test Conditions were calculated. The calculated power was 11.5 kwp with a loss of 9.6% regarding the flash-tests. These 9.6 % have to be compared to the 9.2 % calculated by the former approach using preliminary measurements. The difference is quite low and may be easily explained by the uncertainty budget and/or by an underestimation of losses due to the module mismatch, the Joule effect in the interconnection cables and the nonideal behaviour of the inverter s maximum power point tracker. 5. CONCLUSION For the first time, the two approaches of the MotherPV method have been used, during a collaboration between the Martinique energy agency (AME) and CEA. The first approach, developed in 2010, requires preliminary measurements of the power of the modules at a reference laboratory in order to evaluate the real quality of the manufacturer s flash tester. The new approach, developed in 2014, uses the data provided by the monitoring of the power plant. To get accurate results, the use of a very well calibrated reference device is mandatory (reference module of the same type, or reference cell with the same behaviour). In Martinique, the two approaches gave very coherent results for the determination of the installed power. The use of preliminary module tests estimated the losses regarding the flash-tests at -9.2 % while the direct use of monitored data calculated the loss at -9.6 %. Depending on the situation, both methods may be used. The real advantage of the new approach is to provide a very accurate modelling of the behaviour of the system, allowing the detection of even slight variations in the energy production. 6. REFERENCES [1] Guérin de Montgareuil A., Description of MotherPV, the new method developed at INES / CEA for the assessment of the energy production of photovoltaic modules, 22nd European Photovoltaic Solar Energy Conference, Milano, Italy, 2007. [2] Guérin de Montgareuil A., Mezzasalma F., Merten J., Application of the MotherPV method to the

accurate monitoring of the grid-connected photovoltaic systems, 23rd European Photovoltaic Solar Energy Conference, Valencia, Spain, 2008. [3] Guérin de Montgareuil A., Sicot L., Martin J.-L., Mezzasalma F., Merten J., A new tool for the MotherPV method: modelling of the irradiance coefficient of photovoltaic modules, 24th European Photovoltaic Solar Energy Conference, Hamburg, Germany, 2009. [4] Guérin de Montgareuil A., Darivon S., Merten J., Bellemare L., Uncertainties on the real power of Photovoltaics, 25th European Photovoltaic Solar Energy Conference, Valencia, Spain, 2010. [5] Guérin de Montgareuil A., Delesse Y., Favre W., Martin J.-L., Mezzasalma F., Merten J., Razongles G., Sicot L., From watt-peak to watt-hours: MotherPV method and IEC 61853-3 standard, 28th European Photovoltaic Solar Energy Conference, Paris, France, 2013.