What does the loss of Hazelwood mean for reliability

Fairfax reported that “Victoria is facing an unprecedented 72 days of possible power supply shortfalls over the next two years following the shutdown of the Hazelwood plant next week.” This was picked up by other media but a little more sense was injected by Giles Parkinson, Dylan McConnell and Tony Wood, including RenewEconomy and Radio National Breakfast. Since AEMO uses a probabilistic approach to reliability, I thought it would be helpful to graphically illustrate the meaning of reliability with probability distribution functions.


The figure is a stylised representation of the annual demand distribution (left plot) and generator availability distribution, with and without Hazelwood (right plots). I have added dashed lines when the VIC-NSW interconnector is included. Note that this is a stylised diagram and that the generator availability changes throughout the year. It also doesn’t include semi-dispatchable and non-dispatchable power (i.e. wind and solar) since these haven’t different contributions to reliability. Wind can normally be assumed to contribute 5 to 10% of rated capacity in Victoria. The plots are probability density functions (PDF’s) and can be converted to a cumulative density function (CDF), more commonly known as a load duration curve. In this case, I used the CDF algorithm designed by Preston and converted to a PDF.

The loss-of-load-probability (LOLP) can be calculated for each hour based on the generator availability. It can be thought of as the area bound by the intersection of the demand and supply curves. The LOLP for the peak hour of each day can be added to give the loss-of-load-expectation (LOLE) for a year. Most jurisdictions use LOLE as the standard reserve margin planning metric. The United States standard is a LOLE of 0.1 (‘one day in ten year’), meaning that an outage (of any duration) should only occur on one day in 10 years on average. A LOLE of 2.9 hours per year is used within the reliability standards used by France, Ireland and Belgium. Australia applies an Expected-Unserved-Energy (EUE) standard of 0.002% of annual consumption.

I have assumed a forced outage rate (FOR) of 5% to calculate the probability distribution functions (PDF) assuming that none have scheduled service. I have included all the generators in the table below. AEMO has precise data on forced outage but this information is not generally available as far as I know. The area bound by the curves should be seen as stylised and not precise.

The probability of unserved energy is determined by the intersection of the right tail of the demand distribution, with the left tail of the availability distribution. I have used a kernel density estimation (KDE) to draw the demand graph. The KDE is a non-parametric way to produce a smooth curve which can be extrapolated with a given confidence. Essentially AEMO extrapolates the right tail of the demand function and compares this to the availability function. AEMO refers to the extrapolation of “probability of exceedance (POE). If demand is greater than the reserve capacity, a “reserve shortfall” is flagged. This simply means that  there is a non-zero probability of a demand shortfall. AEMO’s actual method is described here.

From the graph, it is clear that Hazelwood has extinguished Victoria’s surplus capacity and raised the possibility of unserved energy. The headline “72 days” is highly misleading but nonetheless, reserve margins have significantly tightened.

Appendix – Generators included (units and capacity in MW)

Hazelwood 8 200
Loy Yang A 3 560
1 500
Loy Yang B 2 500
Mortlake 2 283
Newport 1 510
Somerton 4 40
Valley Power 6 50
Yallourn 2 380
2 360
Bogong 2 80
6 25
Dartmouth 1 185
Eildon 2 60
2 7.5
Hume 1 29
Laverton North 2 156
Murray 1 10 95
Murray 2 4 138
Jeeralang A 4 53
Jeeralang B 3 76
Bairnsdale 2 47
West Kiewa 4 15

EROI of the Australian electricity supply industry

I recently did a presentation on the EROI of the Australian electricity supply industry. The key aims were –

  • Calculate how much energy it takes to build, run and maintain the Australian electricity supply industry
  • Disaggregate the feedstock fuels (coal, gas, etc) from the operational energy of the system
  • Disaggregate generation, transmission, distribution & on-selling
  • Establish a net-energy baseline for Australia for future work

The analysis required calculating the direct and indirect energy of the system using various energy accounts (ABS, BREE, Energy Efficiency Opportunities (EEO) program, NGER greenhouse reporting data, AEMO). The presentation is here for 2013-14.

The main conclusions are –

  • The EROI is around 40:1 using primary energy equivalent scaling, therefore the system is not EROI constrained.
  • This is mostly due to the availability and proximity of coal in relation to the major demand centres
  • The high EROI would permit an ambitious abatement strategy based on lower EROI generation, however there is a limit to how far this could proceed
  • Unlike oil supply, electricity systems are mostly cost constrained rather then EROI constrained, although a large scale shift to renewables would most likely change this. Most of the recent cost increase are low-energy intensity costs associated with transmission and distribution

black box


Pumped hydro storage – an Australian overview

A pumped hydro primer

Nearly all electrical storage to date has been pumped hydro storage (PHS), which makes up 97% or 142 GW of global power capacity for electrical storage. The three leading PHS countries are Japan with 26 GW, China at 24 GW and the US at 22 GW. The Eurelectric region comprising the 34 European countries that are part of the Eurelectric synchronous regions, has a total installed capacity of 35 GW.

At a global scale, other utility scale storage includes thermal storage (e.g. concentrated solar thermal) at 1.7 GW, which assuming 6 hours storage equates to around 10 GWh. Other storage includes electro-mechanical (e.g. flywheel) at 1.4 GW, battery at 0.75 GW, and hydrogen at 0.003 GW (United States Department of Energy (DOE) 2016).

The storage capacity of most PHS facilities in the US, Japan and China range from 8 to 25 GWh per GW of installed capacity, corresponding to a typical daily arbitrage cycle with spare capacity. In Europe, the storage capacity of 2,500 GWh is dominated by Spain with 1,530 GWh. US storage capacity equates to around 545 GWh.

Australia’s PHS

Australia has 3 PHS storage plants – Wivenhoe, Shoalhaven and Tumut 3. Wivenoe usually operates with about a 0.8 GWh pump cycle, Shoalhaven about 0.7 GWh, Tumut about 1.5 GWh. Tumut 3 capacity is 1,800 MW (after being upgraded from 1,500 MW in 2011), but only 3 of the 6 generators have pumps. These plants total about 3 GWh total storage but the actual capacity may be greater. Pumping power capacity is Tumut-3  473 MW; Shoalhaven 240 MW; and Wivenhoe 550 MW. To get a sense of scale, the NEM supplies about 600 GWh of energy per day.

The role of PHS

PHS has historically operated in unison with coal and nuclear baseload. In the US, the deployment of PHS was relatively slow until the 1960s, but developed in parallel with nuclear during the 1960s and 70s, and subsequently slowed in the 1980s when nuclear deployment came to a standstill. Since the 1980s, PHS has been superseded by gas turbines (i.e. utilising stored sunlight), which have a low capital cost and quick build time, and present lower risk for investors.

Baseload-PHS usually operates with a daily arbitrage cycle between overnight off-peak and daytime peak. The daily cycling maximises energy throughput for a given storage capacity and underpins the economic return for PHS. Since the deregulation of electricity markets, the use of pumped hydro has expanded to cover a range of additional services. PHS can also be used for load following intermittent renewables, provided that continuous power is available for charging. In Australia, PHS charging is simply utilising whatever generation is available – whether it be coal, gas, wind or solar. In practice, PHS is more likely to be relying on overnight coal baseload, and surplus wind at increasing wind penetration.

Utilisation of Australia’s PHS

Interestingly, Australia’s PHS plants aren’t used that much. There was only 118 GWh and 172 GWh consumed in pumping by these plants in 2014 and 2015 respectively (I’ve uploaded my spreadsheet here). Total capacity for these is about 1,391 MW giving a capacity factor of 1.0% and 1.5% respectively. Given the sunk cost, I’m not sure why these plants aren’t used more and whether price gaming may be part of the explanation. More likely, these simply require a much higher arbitrage than often assumed. Traditionally a low off-peak and high peak price supported PHS but price volatility is also seen as being essential with greater penetration of renewables. South Australia has a more volatile market which improves the volatility economics for the potential seawater scheme on the Spencer Gulf, but may not provide the certainty for a regular arbitrage cycle. The problem with relying on volatility of course, is that additional supply cannibalises its own economics.

The proposed Tantangara-Talbingo scheme

I contacted Peter Lang, who did an estimate at BraveNewClimate for a much larger Tantangara-Blowering scheme in 2010. The current proposed scheme is for a similar but smaller scheme linking the Tantangara-Talbingo reservoirs. The topology is that Tantangara (1,230 metres above sea level) sits near the top of the hill and Talbingo (550 metres) is upstream of Blowering (379 metres). 


Peter put together some rough costings for the proposed Snowy PHS –

Tantangara-Talbingo (TT) head is 686 m versus average head 850 m for Tantangara-Blowering (TB); the generating capacity of TT is stated to be 2 GW versus 8 GW for TB.  But with only the three tunnels used for generating.  8 GW/3 x 80% = 2.1 GW.  This implies the tunnel diameters and flow rates are the same in the two projects.

Tantangara-Talbingo tunnel length is 27 km v 53 km for TB – i.e. about half the tunnel length.  This should reduce the cost of the tunnels by about 40% and reduce the project by about 24%.  That is, about $1.5B in 2010 A$.  Therefore, based on my 2010 estimate for TB, the $2 billion for 2 GW for TT seems roughly reasonable.  

But it does not fit with overseas experience – US costs for PHS are around $3 to 4 billion per GW.  UK DECC (p57) gives a figure of GBP 3.4 per GW.  That’s around A$5.5 B per GW (using GBP 1 = AUD 1.6).  Of course there are differences (no dams, no land reclamation; on the other hand, three tunnels but only one productive and highly inflexible because of the tunnel length and the mass of water in the tunnels that has to be accelerated and decelerated).

What does it all mean?

What does all this mean for the Snowy upgrade? More storage has got to be better as more intermittency is added, but is it economically viable? Why aren’t the existing PHS facilities being used more and why is the proposed expansion going to be better? Is the market structured for merchant storage? Is there too much emphasis on intermittent renewables rather than low-emission baseload or dispatchable renewables? What scale of PHS will be required at higher penetration of intermittent renewables? 

As I see it, the bigger problem is that we simply don’t have markets that are designed to work with a changing market mix and storage. Markets can work if given the right long-term signals and policy stability but require technology agnosticism. Some progress might be on the horizon with the proposed AEMC rule change to reduce the settlement period from 30 down to 5 minutes. This will provide greater value for fast ramping generation that can capture market transients over OCGTs. But how do we value storage in an energy-only market?

These are interesting questions requiring resolution.

Thanks to Peter Lang for information and insights on Australia’s pumped hydro.