1. Power to the Coast Project Presented by: Su Wei Tan Industrial Research Ltd

2. Background The goal of this programme is to improve the availability of cost effective energy services to isolated communities. The focus of the research is to create technologies and solutions that make use of available distributed energy resources and integrate with community demand patterns in order to improve the efficiency of the local energy supply infrastructure. This project is centred around the Te Puia Springs community and at other sites on the East Coast. Local health provider Ngati Porou Hauora is the local partner in this research.

3. My role in this project Analysis of the existing power consumption data that has been collected since 2003 to find out the average hourly load and one year load demand for an average house in Te Puia Springs Obtain Te Puia Springs 11 kV feeder records. Compare the profiles of the 11 kV supply energy with the average house profile, and report on similarity/variation. Simulate the data for different kinds of generation. To find out how much network energy saving and capacity support can be achieved through network connected battery storage PV / wind turbine systems.

4. What I have found A single record representing 1-year demand and average hourly load for an averaged house was produced. It was found that the averaged house peaks coincide with the system feeder peaks, so that method to reduce house peaks would also reduce the system peaks directly. The capacity factor from the collected PV data was calculated, and capacity factors for the 300 W wind turbine using both NIWA and NASA wind speed data were calculated also. The capacity factor for WTG (Wind Turbine Generator) system was found to be much higher compared to that of the PV system. The simulation results from HOMER show that the WTG / Grid system has the shortest payback time compared to the PV / Grid system. The PV systems are more expensive compared to the WTG system.

5. Average Hourly Load for all 9 houses

6. Wind Turbine System Simulation

7. Annual Network Saving (using the 300 W Wind Turbine) Annual Network Supply Saving ($) kWh Supplied by 300 W WTG per year NIWA Data (wind speed at 10 m) With battery storage $216978 kWh NASA Data (wind speed at 10 m) With battery Storage $130590 kWh

8. Recommendations Continue monitoring the load data of House with the PV system. At the moment, only load data for March and April are available. Once 12 months of continuous load data is obtained, a more accurate comparison of the load data with and without the PV system can be performed. The capacity factor of the PV system can also be measured. An on-site wind monitoring programme should be implemented at one of the selected sites where the wind turbine is to be installed. This will provide a more accurate analysis and also provide a comparison to the NASA and NIWA data.

9. Thank you!