Climate Action Partnership Project - Monitoring of Solar Home Systems in Sri Lanka

Climate Action Partnership Project - Monitoring of Solar Home Systems in Sri Lanka L. N. and G. Stapleton Centre for Photovoltaic Engineering University of New South Wales Electrical Engineering Building, UNSW, Sydney 5 AUSTRALIA Email: lauren.tan@student.unsw.edu.au gses@bigpond.com Abstract Through the support of the Australian Greenhouse Office, monitoring equipment has been installed on 1 solar home systems in Sri Lanka. These solar home systems are typically 1 module (3W-W), 1 battery and a number of DC lights. For a period of years the data obtained from these systems will be collected and studied by undergraduate students at the University of NSW. This paper describes the project and analysis of the first months data. 1. INTRODUCTION Throughout the world thousands of small solar home systems are being installed each year. These small solar home systems typically consist of: one solar module (W to 1W), one 1 V battery (Ah to 1Ah), three to six DC lights (W to 1W) and possibly a DC radio and/or TV. Figure 1 shows the components of a typical solar home system in Sri Lanka. Figure (a) Solar Module Figure (b) Solar Controller including battery Figure 1: Typical Solar Home System in Sri Lanka In order to gain more comprehensive knowledge about installed solar home systems, the Department of Environment and Heritage through the Australian Greenhouse Office (AGO) approved funding in support of the Australia-US Climate Action Partnership for the project, Monitoring of Solar Home Systems in Sri Lanka. This is a two-year project that commenced in February 5 with an objective to gain knowledge on the performance and operation of one module solar home systems and to share this knowledge with the USA and countries being monitored. Please note that at the time of writing, the project is still in progress, monitoring and analysis of the data will continue until February 7. Though some monitoring of solar home systems had been undertaken in the past in Indonesia and China, these typically were only of a few systems. Literature searches and contact with institutes around the world has failed to locate any other projects where a large number of small solar home

systems have been monitored. Though not part of the original objective, this project will also provide a learning experience of the issues that arise in managing a monitoring project where the data is continuously collected in one country and sent to another country for analysis. The project is being managed by Global Sustainable Energy Solutions Pty Ltd (GSES), a renewable energy consulting firm based in Australia. The partner in Sri Lanka is Suryavahini (PVT) Ltd, a solar company that supplies, installs and maintains solar systems in Sri Lanka. The manager of the company, Mr Pradip Jayewardene, is also president of the Sri Lanka Solar Industries Association. The data is being analysed by undergraduate thesis students at the Centre for Photovoltaic Engineering, University of New South Wales (UNSW), Australia and the results are shared with the Sri Lanka Solar Industry and the National Renewable Energy Laboratories, USA.. INSTALLATION OF MONITORING EQUIPMENT Plasmatronics Pty Ltd in Australia manufactures the PL Range of solar controllers 1 which are fully programmable. These controllers store for 3 days the following data: Daily minimum battery voltage (V max ) Daily maximum battery voltage (V min ) Daily amphrs in (from PV) (Ah in ) Daily amphrs out (load) (Ah out ) If the batteries reach float in a day, the time is recorded (T float ) Estimate of battery state of charge at midnight based on amphrs in/out (SOC) This data can be collected by either manually scrolling the screen or by using a computer and adaptor to download. For this project Plasmatronics developed the facility to download the data via wireless technology using Palm handheld computers. This has made the downloads easier and quicker for the Sri Lankan technicians. These controllers have been used successfully in the Australian market for many years and though more expensive than the typical controller installed on the small solar home systems, GSES saw the potential for using them to gain knowledge on the in-field operation of solar home systems. In February, 5 GSES staff provided training to Sri Lankan solar technicians on the installation and programming of the Plasmatronics PL solar controllers, as shown in Figure. The PL controllers were programmed with the same settings as the Sundaya controllers currently being used in the installations in Sri Lanka. The technicians were also trained in downloading the data from the controller onto a Zire31 handheld computer, which would then be forwarded for analysis. Figure : Mr Stephen Garrett (GSES) conducting training in Colombo, Sri Lanka Figure 3: Technicians Installing a PL to an existing system 1 The terms solar controllers and regulators can be interchanged. There are the same. Renewable Energy for a Sustainable Future SOLAR 5

Once competency was established, one hundred Plasmatronics PL controllers were installed on both old and brand new systems in five different regions in Sri Lanka. Figure 3 shows technicians installing a PL on an existing system. Details were taken on the system specifications as well as information about the end user and site. Since the owners of the system had become familiar with the LED indicators on the Sundaya controller these were left installed and the PL was used to control the battery charging and power to the loads. The data is downloaded on a monthly basis and forwarded to GSES and UNSW for analysis. Analysis of the data (for the first months) took the form of a thesis project undertaken by a UNSW student, Ms Lauren with supervision by Mr Geoff Stapleton, a part-time lecturer and managing director of GSES. Another student shall continue the project in. 3. METHODOLOGY 3.1. Information available One hundred Plasmatronics PL charge controllers were installed on old and brand new systems in Sri Lanka. The original intention was to have the controllers installed equally divided among five regions and amongst brand new and old systems, in practice this was not achieved in the time frame that the 1 controllers were installed.to date, system specifications have only been received for 97 systems in total, 1of these systems being new 3. Table 1: Breakdown by region of system s installed Region Number of systems installed to date Balangoda 15 Dehiatthakandiya 17 Hingurakgoda Kumbukgete 5 Monaragala The system specifications provided were: Location (1 of 5 regions) Customer number Customer name Customer address Date the PL was installed Date the system was installed Number of family members Size, serial number and brand of solar module Size and brand of battery Number, power and brand of lights Estimate the time the module is in full sun Location according to GPS For each of the 97 systems installed, most of the above listed specifications were supplied. Where data is missing, it is expected by the end of the project. The specification which was most absent was the location according to GPS. This is due to the fact that there is only one GPS unit being shared amongst the five installers. This information was not used in the analysis and thus did not affect the project. The majority of systems had modules of W or higher. Table shows breakdown by module size of systems installed while Table 3 shows the breakdown of systems by both module size and region. Please note that the systems on which the PL was installed will now simply be referred to as the systems. 3 Please note that a new system is one where the PL was installed at most one month after the system was installed. Renewable Energy for a Sustainable Future SOLAR 5 3

Table : Breakdown by module size of systems installed Module size Number of systems installed to date 3W 5 3.W 15 35W 5 W 5 W 1 Table 3: Breakdown of systems by module power and region Module size Region Number of systems installed to date <W Balangoda 7 Dehiatthakandiya Hingurakgoda Kumbukgete 1 Monaragala 15 W Balangoda Dehiatthakandiya 13 Hingurakgoda 15 Kumbukgete 1 Monaragala W Balangoda Dehiatthakandiya Hingurakgoda 3 Kumbukgete Monaragala 1 The data recorded was downloaded from each PL by each installer onto a Palm Zire31 handheld computer about once a month. This data was then downloaded to a computer and forwarded to the thesis student for analysis. Data was received by the student on the following dates: 17 th April 5 7 th May 5 13 th May 5 17 th June 5 7 th June 5 3 rd August 5 19 th September 5 Table is an example of how the data was received. Day refers to the number of days from the date the data was downloaded onto the palm, i.e. in Table, day 1 is 9 th March 5, day is th March 5 and so on. If the float time is :, the battery did not reach float on that day. Battery state of charge is found by difference between Ah in and Ah out and therefore is only an estimate of battery state of charge and will be inaccurate at times due to variation in charge efficiencies. It does reset to 1% under certain conditions when the controller changes from absorb to float. As such, it was not used in the analysis. Table : First set of data for system number 173 in Kumbukgete Data/Time Location Day VMax VMin FloatTime SOC ChargeAH 5 LoadAH 3/3/5 17:15 173 1 1.3 1.1 1:1 91 9 1 3/3/5 17:15 173 1.3 1.1 1:11 95 11 9 3/3/5 17:15 173 3 1.3 1.1 1:1 95 5 3/3/5 17:15 173 1.3 1.3 1:1 9 3 Please note that although data was received seven times, this did not account for every system, i.e. seven sets of data were not received for every system. 5 ChargeAH is the same as the Ahin. LoadAH is the same as the Ahout. Renewable Energy for a Sustainable Future SOLAR 5

3/3/5 17:15 173 5 1.3 1.3 9:5 15 1 3/3/5 17:15 173 1. 1.3 1:5 13 11 3/3/5 17:15 173 7 1. 1. 1:3 9 9 9 3/3/5 17:15 173 1. 1.1 15:3 9 17 11 3/3/5 17:15 173 9 13.7 1.1 : 9 1 1 3/3/5 17:15 173 1 13. 1 : 13 11 3/3/5 17:15 173 11 1.3 1 1:1 1 15 3/3/5 17:15 173 1 1. 1. 1:5 9 1 1 3/3/5 17:15 173 13 1. 1.1 1:1 91 1 1 3/3/5 17:15 173 1 1. 1.1 17: 9 13 9 3/3/5 17:15 173 15 1.3 1.1 1:53 91 1 9 3/3/5 17:15 173 1 1. 1.1 1:1 95 1 3/3/5 17:15 173 17 1. 1.1 1:5 91 11 1 3/3/5 17:15 173 1 1. 1.1 1:5 9 11 3/3/5 17:15 173 19 1.3 1.1 15: 93 13 9 3/3/5 17:15 173 1. 1.1 1:5 9 1 1 3/3/5 17:15 173 1 1.3 1.1 13:35 9 1 3/3/5 17:15 173 1.3 1.1 1:3 93 1 3/3/5 17:15 173 3 1. 1.1 13:3 9 15 9 3/3/5 17:15 173 1. 1.1 13:1 91 1 11 3/3/5 17:15 173 5 1. 1.1 11:5 91 1 1 3/3/5 17:15 173 1.3 1.1 1: 93 1 9 3/3/5 17:15 173 7 1 1.1 : 9 15 1 3/3/5 17:15 173 1. 1.1 13: 9 1 11 3/3/5 17:15 173 9 1. 1 13:3 1 1 3/3/5 17:15 173 3 1. 1.1 1:3 9 1 13 Unfortunately, data was not received for all potential dates. As the wireless capabilities of the PL were specifically installed for this project and had not been previously field tested, there were initial problems with the data quality. On some days, the controller default values rather than the daily values were recorded. The exact cause for this is still unknown but in consultation with Plasmatronics, the manufacturer, it was thought that the problem could be one of the following: The chip used for the wireless transfer did store the factory settings and stored them for 3 days. Therefore while this chip still contained this information it might have caused corruption of the data. That when the upload to the chip occurred at midnight each day there was interference if there were DC loads on. That the time had not been set correctly so the uploads were happening in the middle of the day (thinking it was midnight) and some corruption might occur. Plasmatronics were unable to simulate the fault on the test bench. In general, after 3 to days the corrupted data disappeared and there was still sufficient data to be analysed. The default values were not included in any analysis. Default or blank values accounted for only % of the total available data. 3.. Analysis performed on each system 3..1. Controller performance Perhaps the most important feature of a charge controller is to ensure that the battery is neither overcharged nor over discharged. In order to ensure that this feature was programmed correctly, the maximum value of V max and the minimum value of V min for each system were monitored to ensure they were not outside the threshold. However, if the values were below the minimum voltages, this did not necessarily mean that the controller was incorrectly programmed. To minimise unnecessary switching, the controller only disconnects the load if the voltage has reached the minimum voltage for more than 1 minutes. Thus, the disconnection of the load may occur after the threshold voltage has been exceeded. If the thresholds were exceeded than Suryavahini (PVT) Ltd would be notified. Renewable Energy for a Sustainable Future SOLAR 5 5

3... Battery efficiency For each system, the battery efficiency was found using the total load and charge between two days where float was reached, not necessarily consecutive. This eliminated situations where the battery had been discharged for a time and had not yet recovered to full state of charge and reached float voltage. Please note that this was done with data that did not contain any default or blank values and was generally taken between the first and last float days for a set of data for that system. 3..3. Analysis of system usage The first analysis was to find the average number of days between each battery reaching float voltage. It was hypothesised that the owner of the system would flatten the battery in the first few weeks of owning the system. This means that the battery state of charge and therefore voltage would decrease in the first few weeks until the load disconnect point was reached and then stabilise at a lower state of charge. It was expected that the batteries would rarely reach float. This information was collated and averaged in the following categories: a. All systems b. By region c. By module size Next, the load amongst different systems was analysed. The average and maximum loads were found for all systems and averaged by module size. It was then collated in the following categories: a. All systems b. By region The technicians inform the customers that the system is designed to operate all lamps for 3 hours each day. If they need more hours of light, they need to reduce the number of lights. A black and white television can be used and it is equivalent to lamps and should be used accordingly. The average number of lights per system size was used to determine the recommended daily load and this was compared with the average loads. Following this, the charge into the batteries was analysed. This gives an indication of the amount of solar insolation on the module. On the other hand, once a battery nears full state of charge, the controller reduces the amount of solar input to minimise the chance of overcharging. It was originally intended for another project to provide solar insolation for the five regions however the project has not been funded at this point in time. This data could have indicated the level of module efficiency. The average and maximum daily charge for every system was found and averaged according to module size. Finally, the information was grouped by region. 3.3. Analysis performed on new systems Analysis was undertaken of the number of days between float and the average and maximum load for each of the new systems. Performance during the initial six months was closely monitored to investigate whether there were any variations in system usage as the owner became accustomed to the system.. RESULTS.1. All systems.1.1. Controller performance As discussed in Section 3..1, Controller performance, in order to ensure that the battery is not overcharged, the controller disconnects the solar module from the battery once a preset voltage is reached. This was set as 1.3V. So that the battery is not over discharged, the controller disconnects the load from the battery once a preset voltage is reached. This voltage was set at 11.3V. Out of the 9 charge controllers for which data was received, twenty systems had a maximum voltage of over 1.3V. These systems were mostly in Dehiatthakandiya and Hingurakgoda. It appears that initially the installer for these controllers had not preset the maximum voltage correctly because the high values were in early data and not seen in later data. (At the time of writing this has not yet been confirmed.) The remaining systems had a maximum voltage of less than 1.3V, as expected. Renewable Energy for a Sustainable Future SOLAR 5

The minimum voltage ranged from 1.5V to 1.3V. There were only eight systems for which the minimum voltage was less than the preset value of 11.3V. This was not a major concern as all systems reached float voltage at least once implying that the battery was not excessively discharged..1.. Battery efficiency The overall average battery efficiency for all systems is 79% and the battery efficiency is consistent amongst different module sizes, as shown in Figure. All batteries were the same brand with different capacity batteries in different size systems..9..7..5..3..1. <W W W Figure : Battery efficiency collated by module size There is much more variation in battery efficiency when collated by region. This can be seen in Figure 5 and at this stage it is unknown why? This will be further investigated. 1..9..7..5..3..1. Balangoda Dehiatthakandiya Hingurakgoda Kumbukgete Monaragala Figure 5: Battery efficiency collated by region Renewable Energy for a Sustainable Future SOLAR 5 7

.1.3. Analysis of system usage The average number of days between the batteries reaching float voltage for all systems is 3.7 days. This means that the battery is reaching float voltage every third or fourth day on average. This implies that the batteries are maintaining a relatively good state of charge. Figure shows the average number of days between float for each region. There are more days between float for systems in Monaragala than in any other region. 5 Average number of days between float 3 1 Balangoda Dehiatthakandiya Hingurakgoda Kumbukgete Monaragala Region Figure : Average number of days between the battery reaching float voltage collated by region The average number of days between float for each module size system is shown in Figure 7. The W module systems have the most number of days between float. It is interesting to observe that W module systems reach float almost every day while systems with modules less than W reach float every second day. 5 Number of days between float 3 1 < Module power (W) Figure 7: Average number of days between the battery reaching float voltage collated by module size Renewable Energy for a Sustainable Future SOLAR 5

As expected with working systems, the average daily charge is always greater than the average daily load; The average charge not including float days is shown to see the potential charge available. Figure shows the average daily load and charge collated by module size. As expected, the larger the module size, the larger the average daily load and charge. It can be seen that the average actual load was always less than the recommended load, though only slightly less in most systems and this does imply that the customers are following the recommendations. It is interesting to note that average daily load only increases by 1 Ah between module sizes, while average daily charge increases by 1 or Ah with increasing module size. This is lower than expected as module sizes increase much more. This in turn implies that the W systems are being under utilised; the system receives about 5% more energy from the sun than a W module and yet has an average load 15% higher than that of a W system. This is further confirmed by the fact that the recommended load is significantly more than the actual average load. 1 1 1 Average daily load (Ah) 1 < Module size (W) Average load Recommended load Average charge Average charge, not including float days Figure : Average daily load and charge collated by module size The average daily load and charge for systems with module size less than W is shown in Figure 9. These values are greatest in Hingurakgoda. Although the average charge is always greater than the average load, in all regions except Monaragala, the average load is significantly greater than the recommended load. The systems in Monaragala consisted of mostly 3.W modules and one 35W system. This implies that the smaller systems are over utilised, although the average charge is still greater than the average load and thus the system is still functioning. 1 1 Average battery behaviour (Ah) Balangoda Hingurakgoda Kumbukgete Monaragala Region Average load Recommended load Average charge Average charge, not including float days Figure 9: Average load and charge for systems with module size less than W in size collated by region Renewable Energy for a Sustainable Future SOLAR 5 9

Figure 1 shows the average daily load and charge for W systems. The systems in Balangoda had the lowest average daily load and charge. It is interesting to note that apart from the systems in Balangoda, the average load was roughly the same as the recommended load, though it was slightly greater in Hingurakgoda and Monaragala. In fact, the systems in Balangoda seem quite anomalous; there is a much lower average load and charge. This implies that the system owners may modify system use depending on the amount of insolation as inferred from the weather. The remaining regions share the trends of much higher average daily charge than load. 1 1 Average battery behaviour (Ah) Balangoda Dehiatthakandiya Hingurakgoda Kumbukgete Monaragala Region Average load Recommended load Average charge Average charge, not including float days Figure 1: Average load and charge for W module systems collated by region Figure 11 shows the average daily load and charge for W module systems. There was only one W system in Monaragala. The battery in this system reached float voltage every day and thus there is no value for the average charge when float days were not included. There is more variation amongst different regions for W module systems than for other size systems. This implies that some systems may be oversized for the needs of a particular customer; a customer may only require a W module system but purchases a W module system or they expect an increase in their load in the future. This is more pronounced in Hingurakgoda and Monaragala where the recommended load is much greater than the actual average load. 1 1 1 Average battery behaviour (Ah) 1 1 Dehiatthakandiya Hingurakgoda Kumbukgete Monaragala Region Average load Recommended load Average charge Average charge, not including float days Figure 11: Average load and charge for W module systems collated by region Renewable Energy for a Sustainable Future SOLAR 5 1

Though the average daily charge is expected to be greater than the average daily load in working systems, the maximum load may be greater than the maximum charge as long as it is not consistently so. The maximum daily load and charge collated in module size is shown in Figure 1. The average values generally increase with module size, though only by about Ah. The average maximum daily charge is very close to the average maximum daily load. The peak load is consistently greater than the peak charge. 5 5 Mean maximum battery behaviour (Ah) 35 3 5 15 1 5 <W Module size (W) Mean max load Mean max charge Absolute max load Absolute max charge Figure 1: Maximum load and charge collated by module size Figure 13 shows the maximum daily load and charge for systems with a module size less than W collated by region. The charge is usually greater than the load, except in Kumbukgete. The average and peak values are the same for Hingurakgoda and Kumbukgete as there was only data available for one system 1 1 Maximum battery behaviour (Ah) 1 1 1 Balangoda Hingurakgoda Kumbukgete Monaragala Region Mean max load Mean max charge Absolute max load Absolute max charge Figure 13: Maximum load and charge for systems with module size less than W in size collated by region Renewable Energy for a Sustainable Future SOLAR 5 11

The maximum daily load and charge for W systems grouped by region is shown in Figure 1. The maximum daily charge is roughly the same across all regions implying that there is a similarity to the insolation across all regions. However, the average maximum load varies from about 11Ah in Balangoda to about 1Ah in Dehiatthakandiya. Nevertheless, the actual maximum load and charge may occur on different days and there may be other factors influencing the maximum load, e.g., a special evening event. 3 5 Maximum battery behaviour (Ah) 15 1 5 Balangoda Dehiatthakandiya Hingurakgoda Kumbukgete Monaragala Region Mean max load Mean max charge Absolute max load Absolute max charge Figure 1: Maximum load and charge for W module systems collated by region Figure 15 shows the maximum daily load and charge of W systems arranged by region. There is much more variation here than with other smaller systems. As mentioned previously, this can be attributed to the system user not using his system to its potential. Please note that roughly the same variation can be found in the average and average maximum values for W systems. The single W system in Monaragala had a much lower maximum daily load and charge than the average in other regions. 5 5 Maximum battery behaviour (Ah) 35 3 5 15 1 5 Dehiatthakandiya Hingurakgoda Kumbukgete Monaragala Region Mean max load Mean max charge Absolute max load Absolute max charge Figure 15: Maximum load and charge for W module systems collated by region Renewable Energy for a Sustainable Future SOLAR 5 1

.. New systems..1. Analysis of system usage As can be seen in Figure 1, four new systems had one day between float, i.e. the battery reached float voltage every day. Seventeen out of twenty of the new systems reached float on average at most every fourth day. This shows that the batteries in new systems are not being immediately flattened and left to operate around a low state of charge. The remaining three new systems still reach float voltage on a regular basis implying that the batteries are still in good condition. 7 Average number of days between float 5 3 1 13 159 1599 133 199 173 1997 13 199 1999 17179 199 1 1359 1 1397 13 13 1915 System number Figure 1: Average number of days between the battery reaching float voltage for new systems The average load for systems with module size less than W is displayed in Figure 17. The wide variation is a consequence of the individual module sizes. This category includes 3W, 3.W and 35W module systems. However, there is still significant variation from month to month, though there seems to be no trend. About half the systems have a lower average load than the average load for all systems with module size less than W. Discounting the unusually high load in April for system number 13, the load seems to stay roughly the same in the first few months of operation. Thus the speculation that as a user learns the operation of their system is disproved. 1 1 Total Mar Apr May Jun Jul Aug 133 13 13 13 173 All <W Recommended load Figure 17: Average load for new systems with module size less than W Renewable Energy for a Sustainable Future SOLAR 5 13

Figure 1 shows the average load for new W systems. There is more variation from the recommended load and average load for all W systems than with other module categories; most systems have an average load less than the average load for all W systems. Once again, most systems have a fairly consistent average load from month to month, disproving the hypothesis that there would be variation as the user became accustomed to their system. The exceptions are system numbers 1 and 1397, whose load significantly decreased, and system numbers 1359, 199 and 199, whose load slightly increased. 1 1 1 Total Mar Apr May Jun Jul Aug 13 1397 159 1599 199 1999 1359 199 1 1915 1997 199 All W Recommended load Figure 1: Average load for new W systems The average load for new W systems can be seen in Figure 19. For system number 17179 where the most data was available, it can be seen that the average load decreased then increased in the last month, but not more than the initial average load. Please note that this system was always greater than the average and recommended load for all W systems. The other systems had an average load less than the recommended load, though system number 1 had the same average load as the average load for all W systems and system number 1975 had an average load less than the average load for all W systems. 1 1 1 1 1 Total Mar Apr May Jun Jul Aug 17179 1 1975 All W Recommended load Figure 19: Average load of new W systems Renewable Energy for a Sustainable Future SOLAR 5 1

Figure shows the maximum load for new systems with module size less than W. Other than for system number 133, the maximum load varies greatly from month to month. Unusually high loads may be due to special events or the lights being left on accidentally. 1 1 1 1 Load (Ah) 1 Total Mar Apr May Jun Jul Aug All <W 133 13 13 13 173 Figure : Maximum load for new systems with module size less than W The maximum load for new W systems is provided as Figure 1. Most new W systems have a maximum load less than that of all W systems. Apart for systems number 1999, 1 and 1397, the maximum load is fairly consistent from month to month. The latter two systems only had two months of data and the load decreased after the first month. There were more months of data for system number 1999 and the maximum load increased from 5Ah in March to Ah in July. 3 5 15 1 5 Total Mar Apr May Jun Jul Aug 13 1397 159 1599 199 1999 1359 199 1 1915 1997 199 All W Figure 1: Maximum load for new W systems Renewable Energy for a Sustainable Future SOLAR 5 15

Figure shows the maximum load for new W systems. There is a significant outlier for system number 1. In August, the maximum load was 3Ah. As this system has seven W lights, this equates to the lights being on for 1 hours. Other than this, the maximum load is fairly consistent on a monthly basis for each individual new system. 5 5 35 3 5 15 1 5 Total Mar Apr May Jun Jul Aug 17179 1 1975 All W Figure : Maximum load for new W systems 5. CONCLUSION & RECOMMENDATIONS Though only months data has been analysed the main conclusion is that in the 1 systems being monitored the batteries are being maintained in a good state of charge since the batteries are reaching float on an average of every th day and with all system reaching float at some time with the data available. The data will continue to be collected until February 7. In addition to the areas covered in this paper the analysis will include: Monthly average and maximum loads for each system Monthly average and maximum charge for each system Battery Efficiency for first and last months for each system. ACKNOWLEDGEMENTS The authors would like to acknowledge the following support for this project: The Department of Environment and Heritage through the Australian Greenhouse Office for funding the project. Mr Pradip Jayewardene and his staff at Suryavahini (PVT) Ltd for installing the PL controllers and collecting the data. Mr Alan Hutchinson from Plasmatronics for investigating and installing the wireless technology in the PL to facilitate downloading with a handheld computer. Mr Stephen Garrett, GSES Pty Ltd, for continual input to the analysis. Renewable Energy for a Sustainable Future SOLAR 5 1