Clean Energy WA Study

 

CONTENTS:

 

(For brevity called "The Full Report" 20 May 2016)

Clean Electricity Western Australia

Modelling Renewable Energy Scenarios for the SW Electricity Grid

Published 20 May 2016.

This study describes modelling of renewable energy (RE) scenarios for Western Australia’s SW electricity grid (SWIS)
It describes how SEN’s new SIREN Toolbox software was used to model power generation sufficient to meet demand in 2030.
Five scenarios with 85 – 100% renewable energy are modelled and costed. Scenarios include business as usual coal and gas and nuclear.


The full report can be downloaded here. While Attachments including the modelling and costing spreadsheets can be downloaded from the list below.

The executive summary from the latest version of the Full Report now follows:

 

EXECUTIVE SUMMARY

Western Australia’s South-West Interconnected System (SWIS) can move to 85% renewable energy (RE) for the same cost as new coal and gas. In reality, it is expected to be even cheaper as the modelling in this report has used conservative cost data for RE that is higher than current forecast costs. The SWIS can move to 100% RE for only an extra 3 to 4c/kWh, a premium of only 15% on current domestic electricity prices.

This study provides comparative assessments of a number of RE scenarios which could be realistically implemented in the SWIS by 2030 using existing proven, utility scale, commercial technologies. Using SEN’s new Integrated Renewable Energy Networks (SIREN) Toolkit software, the assessments provide technical, economic and environmental (CO2e emissions) analyses to assist policy makers, regulators and community leaders to demonstrate how an orderly transformation of the SWIS to a RE dominant system can be achieved economically by 2030.

For each modelled scenario, SEN has analysed the requirements to build a new reliable RE power generation system and the corresponding carbon emission intensity in order to identify the most practical, efficient and cost-effective low carbon energy generation options for implementation by 2030.

Western Australia is in an excellent position to move to RE over the next 15 years, but the opportunity could be wasted unless commitment, planning and the transition begin immediately.

 

KEY FINDINGS

 

1. 85% RE electricity prices equal to new coal/gas grid scenarios

The wholesale cost of electricity from a modernised electricity grid, whether coal or 85% renewable, would be about 1c/kWh more than the current (2016) wholesale cost. The retail cost of electricity1 to SWIS residential customers would increase by about 2c/kWh, regardless of whether Scenario 1 (85% RE) is implemented or the existing or renewed fossil fuelled grid is replaced.

2. RE costs trending lower

RE costs are falling as advances in technology improve efficiency and reduce installation costs (BREE 2013). It is confidently anticipated that even lower prices for electricity can be realised than those predicted with the current modelling assumptions (which have purposely been set at conservative levels). SEN considers that LCOEs of some RE technologies, for example wind and CST with MS storage, are already lower than those used in the modelling.

3. Phasing out of current coal fired electricity generation

Coal fired generation can be phased out over 14 years in an orderly and structured program. Section 6 of this study illustrates a possible transition plan to reach the lower-cost Scenario 1 (85% RE), starting with the immediate retirement of the aged Muja plants.

4. Transition to Renewable Energy (RE)

To transition to Scenario 1 (85% RE) by 2030, approximately 8,000 MW of new RE generation would need to be installed at an estimated cost of $20.1 billion, based on 2015 costs. This equates to an installation rate of approximately 570 MW per year.

5. Demand side management (DSM) would reduce LCoE

Universal installation of smart meters could be implemented at low cost to enable some customers to voluntarily opt to have some of their appliances turned down or off by the grid operator for short periods during times of peak energy cost. Use of 500 MW of this type of DSM with the RE scenarios could reduce the electricity cost by up to $2/MWh (0.2c/kWh) without DSM reserve capacity payments, while reducing carbon emissions by several thousand tonnes per year.

6. Carbon emissions reduction

RE electricity generation scenarios for the SWIS presented in this study reduce annual CO2e emissions by 11.1 million tCO2e for Scenario 1 (85% RE), or to 12.3 million tCO2e for the best 100% scenario, which represent 85% and 92% reductions respectively. As Western Australia’s population is about 2.7 million (AustraliaPopulation2016 2016), this equates to emissions reductions of 4.1 – 4.6 tCO2e per person.

7. Protection from future gas and carbon price increases

RE scenarios have stabilising effects on the electricity price, because they are much less susceptible to fuel price fluctuations (only 5 – 15% of generation relies on fuelled generation).

The RE scenarios are also less sensitive to the price of carbon emissions, unlike the Business as Usual (BAU) Scenario 6, as the RE Scenarios incur only 8 – 17% of the carbon costs of BAU.

8. Benefits of BM battery storage

Behind-the-meter (BM) battery storage is likely to be a cost effective option for both consumers with rooftop PV and those without. This will tend to flatten the demand profile, reducing the amount of expensive gas turbine generation required (as shown in Figure 3, Section 3.4).

9. RE grids reduce network costs and capacity payments

A modernised dispersed wind and solar based electricity grid with battery storage would provide the following cost savings:

  • Reduced network charges.

  • Reduced tariff adjustment payments (TAP).

  • Reduced reserve capacity payments (CP).

10. Reduced externalised costs of pollution

As Scenario 1 (85% RE) has less than 17% of the carbon emissions of Scenario 6 (BAU), the externalised impacts/costs of pollution (CO2 contribution to global warming; heavy metal and particulate pollution) and negative effects on human and environmental health will be greatly reduced.

11. Fuelled scenarios have higher risks

The risk analysis in Section 7 shows that the two fuelled generation dominant scenarios modelled (coal/gas and nuclear/gas) carry much higher risks than any of the RE Scenarios. Nuclear had the highest risk profile, particularly in terms of safety and environment (radioactive waste) and also in terms of costs and project implementation. Coal and gas carry high environmental (carbon pollution) risks and are susceptible to fuel availability and price fluctuations. Moving to 100% gas fuelled generation would achieve less than a 30% reduction in CO2 emissions.

12. Base load generation not required on RE systems

The large, inflexible base load generators that operate constantly in traditional fossil fuelled grids are not needed, and indeed are a hindrance, in RE powered grids. However, open cycle gas turbines (OCGTs) are essential components of the RE powered SWIS scenarios as they provide:

  • Rapid response balancing power when storage runs out during extended periods of low wind and sun.

  • Power quality control requirements (when spinning in synchronous compensation mode).

OCGTs and/or batteries and/or flywheels can be used instead of base load generators for frequency stability.

1 The modelling assumes a $30/tCO2e carbon price.

 

Fig 1: Power Generation Capacity – Comparative Scenarios

Findings_-_Fig_1_Power_generation_capacities_and_LCoE_of_the_RE_and_BAU_scenarios_investigated..png

 

Fig 2: Summary of Scenario Costs and Carbon Emissions

Findings_-_Fig_2_Summary_of_Scenario_Costs_and_Carbon_Emissions.png

 

Fig 3: Effect of behind the meter batteries in ‘flattening’ demand profiles

Findings_-Fig_3_Conceptual_typical_daily_demand_curves_and_effect_of_batteries.png

 

 

Fig 4: Hourly shortfall in summer for Scenario 2

Findings_Fig_4_Hourly_shortfall_in_summer_for_Scenario_2.png

 

 

Fig 5: Hourly shortfall in winter for Scenario 2

Findings_-_Fig_5_Hourly_shortfall_in_winter_for_Scenario_2.png

 

 

Table 10: Summary of scenario costs and carbon emissions

Table_10_Summary_of_scenario_costs_and_carbon_emissions.jpg

   

BASIS AND KEY ASSUMPTIONS

  1. Carbon price $30/tonne of CO2e.

  2. All scenarios include:

    • New-build cost of the entire electricity generation and storage components.

    • New-build costs only for transmission lines & substations additional to existing.

    • No difference in costs of distribution system (poles & wires).

  3. Cost of capital: 10% for all generation (based on BREE AETA3); Government low risk rate of 6% for transmission and pump hydro storage projects; 5% savings rate for ‘behind the meter’ PV and battery.

  4. There is a single load source - the Perth Metropolitan Area.

  5. Wind and solar energy costed is the energy transmitted to the major load source = (generated energy) - (transmission losses).

  6. All wind and solar energy generated is costed at the following average LCOEs (BREE AETA Model3 estimate for 2025 in 2015 net present value): Wind $85/MWh; Utility-scale fixed PV $110/MWh; Concentrated solar thermal (CST) with 6 hours storage: $165/MWh.

  7. LCOE for rooftop PV is costed at $65/MWh (Solar Choice website, 2015)

  8. Dispatchable (balancing) power and storage are costed differently: a fixed annual cost per MW capacity installed plus variable costs (including fuel) for each MWh of energy generated.

  9. Wind and solar generation surplus to load is still fully costed in the LCOE, even though in reality it may be curtailed or sold more cheaply.

  10. All wind turbines are onshore (land-based).

  11. A nuclear option has not been included as nuclear fission generation is inherently non-renewable, is not available in the required timeframe and has significant unresolved safety, environmental and cost issues. Costing and issues for nuclear at SWIS grid scale will be discussed in the full Modelling Report.

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Website: www.sen.asn.au

Email: siren@sen.asn.au 

Post:PO Box341,WestPerthWA6872

 

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Footnotes

1 The modelling assumes a $30/tCO2e carbon price.

2 Using single and double 330 kV lines from Geraldton and Merredin to the Metro area; and east of Albany connecting to the existing 33 kV network at Collie.

3 Bureau of Resources and Energy Economics: 'Australian Energy Technology Assessment Model' v.2.1; 14/01/14.

 

Commercial users are encouraged to donate to SEN which enabled this modelling. SIREN Team members volunteered many hours of their time and expertise to develop this powerful and adaptable modelling package. A contribution will help greatly, thanks.

Users wanting assistance in the use or specific application of SIREN Toolbox on a commercial basis can contact Angus King angus@ozsolarwind.com for work involving SIREN and /or Ben Rose biroses@westnet.com.au for work involving Powerbalance. 

 

 


 

ATTACHMENTS

Attachment 1 - Powerbalance Optimized Scenarios for Renewable Energy

Attachment 2 - Powerbalance Optimized Scenarios for Coal BAU, Nuclear, Gas

Attachment 3 - Dispatchable Power Costings

Attachment 4 - 2030 Renewable SWIS Risk Matrix (in Excel format)

Attachment 5 - RE Roadmap 1.6pct grwth, 3500MW gas

Attachment 6 - Ramp rates

Attachment 7 - Storage required to eliminate fuelled generation

Attachment 8 - 2030 Renewable SWIS Risk Matrix (as PDF)

 

The FULL REPORT can be downloaded here.

 

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GLOSSARY

BAU Business as Usual

BMB Behind the meter battery storage (household and commercial)

CO2e Carbon dioxide equivalent

CP Reserve capacity payments

CST Concentrated solar thermal

LC Levelised cost

LCOE Levelised cost of electricity

MW megawatt

MWh megawatt hour(s)

OCGT Open cycle gas turbine

PHS Pumped hydro storage

PV Photovoltaic

TAP Tariff adjustment payment

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Questions and Answers

Q. How much land area will these renewable stations occupy?

A. Very little land area is required. The blue and yellow squares on the map below show the actual land area taken up by 6000 MW of wind and 3000 MW of solar PV, enough to provide 85% of the state’s electricity demand in 15 years’ time at an assumed demand growth rate of 1.6% per year. 

Area_Map_-_W6PV3_565H.jpg

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