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Sustainable Energy Management Options for Totara Bank

Sustainable Energy Management Options for Totara Bank. Project for Master of Technology: MUCER Mandy Armstrong. Project Intent. Provide a decision-support framework for investment in sustainable distributed generation energy systems for a multi-lot development

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Sustainable Energy Management Options for Totara Bank

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  1. Sustainable Energy Management Options for Totara Bank Project for Master of Technology: MUCER Mandy Armstrong

  2. Project Intent • Provide a decision-support framework for investment in sustainable distributed generation energy systems for a multi-lot development • Establish the significant criteria influencing the economic, environmental & social viability of a net-billed system (look beyond ‘payback’) • Identify the best mix of energy-use options, including the impact of energy-efficient house design on system performance

  3. Totara Bank Energy Concept • All lots are designed to make maximum use of solar energy • Coppicing firewood is provided for heating energy. • Building Performance Indexes are specified by floor area to maximise energy efficient design • Each lot is limited to maximum current of 30A & 1 switchboard. • The site is designed with each lot connected to an internal grid, with 1 ICP connecting Totara Bank to the network. • Reconciliation of energy use will be done through Residents Association rules.

  4. Decision Support Framework - Structure

  5. Energy Balance Inputs • Demand data (10min) supplied from Beacon/BRANZ monitoring of an Auckland house (energy efficient) • Climate translation analysis using ALF 3.1 to assess likely heating requirements for the Wairarapa • Assumed morning & evening heating, to a minimum of 15oC; with kWh/day based on calculated AHE’s for May-September • NIWA Cliflo data (hrly) used for radiation & wind supply • Hourly Energy Balances done for February & July only, for one lot. • More fine tuning needed!

  6. Energy Balance - Summer 2.5kW Proven turbine

  7. Energy Balance - Winter Peak Demand: 2.8 kW, 9.30 am! 2.5kW Proven turbine

  8. Data Analysis Considerations • Although a detailed data set has been used, it is only for one house. • Other data sources include HEEP & another Wairarapa house • Considering electricity-based load only; (direct use of gas can reduce electricity demand yet still contribute to total energy demand) • Behaviour assumptions have to be made – as important as appliances & heating. • Peak is lower than expected, but daily use is higher. Why? • Energy Balances then rolled up for 8 lots

  9. Connection Scenarios 1.Radial connection/embedded network • Each lot as individual generators with own grid connection & I-E meters • Baseline scenario (current standard practise) Network Individual Network connections at boundary Flow in both directions I-E I-E I-E I-E Generation area

  10. Connection Scenarios 2.Internal Loop connection • Individual lot generator, single grid connection • Customer network Network connection at boundary I-E Flow in both directions I-E Lot surplus ‘sold’/distributed to other lots as first priority; then exported to network I-E Generation area I-E I-E

  11. Connection Scenarios 3.Internal Loop connection • Whole site as generator, single grid connection • Customer network Network connection at boundary I-E Flow in both directions I-E Lot surplus ‘sold’ to other lots as first priority; then exported to network I-El Generation area - supply connected to each lot I-E I-E

  12. Connection Scenarios 4.Internal Loop connection • Individual lot generator plus whole site generation, single grid connection • Customer network Network connection at boundary I-E Flow in both directions I-E Lot surplus ‘sold’ to other lots as first priority; then exported to network I_E Generation area Supply connected to each lot I-E I-E

  13. Connection Issues • There won’t be much economic benefit from net-billing in the short term if not enough excess energy (unless can somehow supply back at peak times) ref to Anita’s data! • Meter technology is changing rapidly, although NZ is still lagging in use of smart meters: • Lease rather than own • TOU is possible, but not common or encouraged • A customer network also requires data logger system • Interface with the retailer an issue for customer to access data • Data access from TOU meters is the best way to manage load, but will be interesting to achieve... • Current smart meter initiatives focussed on benefits to the retail supply chain

  14. Energy Model Next Steps • Confirm proportion of load to be met by available resources, as well as considering: • How much to invest in PV &/or future generation options? • Is storage desirable for the long-term? • What about genset? What about charging electric cars? • Explore further opportunities to manage demand profile & reduce overall demand • Work on an “ideal” demand profile for future dwellings • Start talking about costs, issues, opportunities etc for the connection scenarios with lines company, meter suppliers, test houses & retailers

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