Solar PV and battery optimisation (15%)
Download the household scale solar PV-battery spreadsheet model from Moodle.
Describe how the model works, and how it could be improved.
· Optimise the PV a
ay size for the 'stay at home' load and no battery.
· Add a 14kWh Tesla Powerwall (enter "14" in the battery size cell).
· Re-optimise the PV a
ay, then find what the battery needs to cost for this to be a sensible investment.
Repeat this process for different demand profiles, battery sizes, feed in tariffs, costs of capital and any other input assumptions you'd like to test. What do you learn about the range of costs that batteries need to get to?
Use graphs, tables. Shouldn't be much need for references, but as usual, cite any reference material you use.
Word limit: 1500. Submit as a PDF file (not excel or word)
Page limit: 15 pages
Marking ru
ic:
· Clear understanding of how the model works and its shortcomings (30%)
· Design of experiments (i.e. different input assumptions) (20%)
· Clear descriptions of the results (20%)
· Concise understanding of the implications (20%).
· Structure and references (10%)
FileNewTemplate
RSE3141 Solar Energy
Energy Markets, Storage and Integration
Roger Dargaville ( XXXXXXXXXX)
Resources Engineering
1
Building integrated energy systems
Energy markets
Generation mix
Transmission
Demand-side management
Storage
Storage
Basic concepts
Batteries
Pumped hydro
Other forms
Integration
Optimal mix of generation, storage and transmission assets for a low ca
on future
What’s coming up rest of semeste
Week 9: Active and passive solar design
Building better buildings
Week 10: Connecting to the grid
Guest lecture from Reza Razzaghi (Elec Eng)
Week 11: Siting solar PV projects
Guest lecture from Steve Phillips
Week 12: Wrap up and research lecture
Overview
2
https:
www.pv-magazine-australia.com/2021/03/18/south-australian-rooftop-solar-switched-off-in-search-for-stability
Australian Energy Market Commission (AEMC) cu
ently finalising a rule change that will see PV prevented from feeding into the grid when residual demand is very low
Will allow more PV onto the grid
May incentive more batteries
https:
www.aemc.gov.au/news-centre/media-releases/new-plan-make-room-grid-more-home-solar-and-batteries
Role of PV and batteries is very topical at the moment
Supply and demand must be perfectly matched all the time
The market operator predicts what the demand for the next time period will be
Based on time of day and year, weather, included rooftop PV (behind the meter)
Generators ‘bid in’ their capacity
Related to their operational expenditure
The market operator directs which generators should dispatch and how much
Takes into account the costs
Flexibility
Transmission constraints
E
or in the forecast and possible system faults – extra ‘spinning reserve’
How does the electrical energy market work?
GW demand in Victoria for
Heatwave in Jan 2014
‘Normal’ week
Base-load
Intermediate
Peak
Coal
Gas
Hydro
Wind
Jan 2014
Extreme and mild examples
https:
opennem.org.au/energy/nem/?range=7d&interval=30m
Demand has evolved to match the supply characteristics – cheap off peak power, deals for large continuous users, large industrial use.
Potential for efficiency, load shifting to change the shape to match a different mix is there.
System cannot operate with baseload alone – requirement for peaking capacity to follow large swings in demand
5
Technology Ca
on Intensity Dispatchability Ramp rates Cost
Hydro LOW_MEDIUM YES* FAST MEDIUM
Nuclear SLOW YES SLOW HIGH
Coal HIGH YES SLOW MEDIUM
Gas - CCGT MEDIUM YES MEDIUM LOW-MEDIUM
Gas - OCGT MEDIUM-HIGH YES FAST LOW
Wind tu
ines LOW NO - LOW
Solar PV LOW NO - LOW
Solar thermal LOW YES MEDIUM HIGH
Electricity options and characteristics
* Subject to drought
Generator type Start from cold Start from hot Spinning from low to high
Coal - Brown 24-48 hours ~6 hours 1-2 hours
Coal - Black 12-24 hours ~4-6 hours 1-2 hours
Gas - CCGT 4-6 hours 1-2 hours ~ 10 minutes
Gas - OCGT 1-2 hours 1-2 minutes <1 minute
Hydro 1-2 minutes 5-30 seconds 1-10 seconds
Start up and ramp rates
Specific to each generator – some may be quicker or slower depending on configuration
Electricity generation capacity mix in the NEM
NSW1
Black Coal Brown Coal OCGT Gas - steam CCGT Diesel Reciprocating Hydro Bioenergy Wind PV 10240 0 1388 0 620 178.7 XXXXXXXXXX 2650.55 108.211 650.98 XXXXXXXXXX QLD1
Black Coal Brown Coal OCGT Gas - steam CCGT Diesel Reciprocating Hydro Bioenergy Wind PV 8149 0 1642 0 1210 454 173.76 618 327.96 12 XXXXXXXXXX SA1 Black Coal Brown Coal OCGT Gas - steam CCGT Diesel Reciprocating Hydro Bioenergy Wind PV 0 0 730 1280 658 266 9.9 2.5 13 1473.45 XXXXXXXXXX TAS1 Black Coal Brown Coal OCGT Gas - steam CCGT Diesel Reciprocating Hydro Bioenergy Wind PV 0 0 163 0 208 224 0 2261 2 308 XXXXXXXXXX VIC1 Black Coal Brown Coal OCGT Gas - steam CCGT Diesel Reciprocating Hydro Bioenergy Wind PV 0 6290 1864 500 0 0 13 2237.65 XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX https:
www.aemc.gov.au/energy-system/electricity/electricity-market/spot-and-contract-markets
https:
www.aemc.gov.au/sites/default/files/content
Five-Minute-Settlement-directions-paper-fact-sheet-FINAL.PDF
What is the spot market?
What is the contract market?
Swaps
Caps
https:
www.asx.com.au/products/energy-derivatives/australian-electricity.htm
How does the electricity market work (Australia)
How the market works
Spot price is determined based of the demand and the bids of the generators
Market ‘settles’ based on these prices
Market co
ects based on the contract market
The price the consumer pays is only partly driven by the spot market price for electricity
But it also includes
Network costs
Retail mark-up
Green certification (renewable energy certificates)
Ca
on costs (not at the moment)
Network cost (”poles and wires”) make up the biggest portion (not energy).
Relating the wholesale (spot market) price to the retail price
Trends in electricity prices (indexed to 2015) and projections
https:
www.aemo.com.au/-/media/files/electricity/nem/planning_and_forecasting/demand-forecasts/efi/jacobs-retail-electricity-price-history-and-projections_final-public-report-june-2017.pdf?la=en&hash=7A21136F67086A90D182A43F81BCCBBE
Since 2007, prices have increased around 60%
Most of the increase occu
ed between 2007 and 2015
Around 20-30% is generation
~15% is retailer chargers
~50% is network charges
Transmission system is a natural monopoly
Needs to be regulated
Regulated markets can be poorly managed
Overly generous – too expensive
Not generous enough – lack of capacity
What makes up your electricity bill?
http:
www.ipart.nsw.gov.au
Breakdown of bills for different states in Australia
https:
www.aemo.com.au/-/media/files/electricity/nem/planning_and_forecasting/demand-forecasts/efi/jacobs-retail-electricity-price-history-and-projections_final-public-report-june-2017.pdf?la=en&hash=7A21136F67086A90D182A43F81BCCBBE
Contribution of different factors to decrease in demand XXXXXXXXXX
https:
australiainstitute.org.au
eport/power-down-ii-australias-electricity-demand
Main reason for decrease is energy efficiency
Light bulbs
Motors
Air conditioning/ refrigeration
Other important reasons are
Price effects
Lower than expected growth
Industrial closures (e.g. car industry, aluminium)
Generation trend XXXXXXXXXXGWh/yr)
100000
80000
60000
40000
20000
XXXXXXXXXX XXXXXXXXXX XXXXXXXXXX
Why use energy storage?
What are the technologies?
Hydro
Batteries
Compressed ai
Fly wheel
Costs?
Energy Storage
Hornsdale power reserve (South Australia)
AKA Tesla Big Battery
Impact of storage on energy systems
Thanks to Rob Clinch @ ARUP
Have a look at openNEM.org.au
Transformers
Transmission
Distribution
Generation
Sub Station
Commercial and industrial customers
Residential customers
Storage
Storage
Storage
Storage
Storage
Grid Stabilisation
Renewable storage
Peak load relief
UPS and A
itrage
Domestic A
itrage
Storage applications in the grid
Pumped hydro (180GW)
Chemical and flow batteries
Flywheels
Thermal storage systems
Storage Technologies – global capacity
https:
www.sandia.gov/ess/global-energy-storage-database
20
[CATEGORY NAME]
[CATEGORY NAME]
Compressed Air Energy Storage Electro-chemical Electro-mechanical Hydrogen Storage Liquid Air Energy Storage Lithium Ion Battery Thermal Storage Pumped Hydro Storage 8410 3297178 2600688 20485 5350 754120 3275126 XXXXXXXXXX
[CATEGORY NAME]
[CATEGORY NAME]
[CATEGORY NAME]
Compressed Air Energy Storage Electro-chemical Electro-mechanical Hydrogen Storage Liquid Air Energy Storage Lithium Ion Battery Thermal Storage 8410 3297178 2600688 20485 5350 754120 3275126
Pumped hydro
Simple reversal of the hydro system. Works with Francis type tu
ines
Okinawa pumped seawater system
Australia cu
ently has 3 pumped hydro systems, Tumut XXXXXXXXXXMW), Shoalhaven (240MW) and Wivenhoe (500MW)
Used in conjunction with a gas fired tu
ine – improves efficiency by a factor of 3
Pumps compress air underground when power is cheap
Compressed air storage
2 utility scale projects running – 290 MW Huntorf plant, (Germany) and 110 MW plant in McIntosh (Alabama)
Work by storing energy in chemical bonds.
Lead Acid invented in 1859 (Planté), refined by Fauré (1881)
Typically designed for small appliances (i.e. Li-ion in laptops) or short sharp usage (i.e. car battery)
More recently for transport (EVs) and energy storage
Lots of different types
Lead acid
Lithium ion
Sodium/Sulfu
Vanadium-Redox flow
Electro-chemical batteries
Pb + PbO2 + 2H2SO XXXXXXXXXX2PbSO4 + 2H2O
Flywheels store energy as angular momentum
Best suited to storage periods of 1 second to 10 minutes
The flywheel case is designed with a shield to contain a failed rotor and its pieces if it shatters and blows up
Batteries are much cheaper than flywheel systems (moving parts) but flywheels can charge/discharge many more times
Flywheels
070403
Images courtesy of Beacon Powe
Source: www.ecolectic.org
24
Compressed H2 and NG Storage
Hydrogen storage – well proven
Produce H2 by electrolysis of wate
(or from fossil fuel, but that’s not sustainable!)
H2 pressures range from 2000 to 10,000 psi
CNG (compressed natural gas) is stored at 3000 psi
NH4 (ammonia) another possible medium
Key issue is efficiency of producing hydrogen and gas compression and then efficiency of electricity production
25
Thermal storage
Can be stored for days
Potential for additional storage from off the grid
Expensive infrastructure
Molten Salt integrated into CSP
3 main stages: liquefaction, storage, and power recovery
Liquid Air Energy Storage
Pilot plant: Highview Power Storage (Slough, UK)
300kW – planning 10MW system now
Round-trip efficiency (RTE) of the system: 8-12% (with 60C waste heat) but claim they can get an efficiency of 60% in the 10MW plant
Capital cost
Storage capacity and discharge times
Cost per discharge
i.e. how much do I need to store for how long, how many times will it cycle?
Which storage system to choose?
29
Lots of different technologies with different characteristics
Capacity, power, response time, cost
Pumped hydro most favourable for medium response speed storage, but needs appropriate hydrology and geography. CAES also has geological constraints
Battery technologies evolving as incentives improve (i.e. higher penetration of RE leading to more variability in energy systems)
Storage summary
Demand-side management
Can alter demand patterns
Shape load
New users for off-peak
Shift load
Off-peak hot wate
Reduce load
efficiencies
Increase load
Electric Vehicles
http:
siteresources.worldbank.org/INTENERGY/Resources/PrimeronDemand-SideManagement.pdf
What will the electrical energy system of the future look like? Depends on:
The target we aim to hit (50, 80 or 100% emission abatement?)
Cost of technologies
Resource availability
Role of storage and demand side management
Where, when and how much of what technologies should be built?
Assumes a centrally run, well coordinated energy system…
Least cost system modelling
Demand has evolved to match the supply characteristics – cheap off peak power, deals for large continuous users, large industrial use.
Potential for efficiency, load shifting to change the shape to match a different mix is there.
System cannot operate with baseload alone – requirement for peaking capacity to follow large swings in demand
35
Broad range of technologies available
Conventional technologies
Coal, gas, nuclear – reliable, but come with emissions + risk
Established renewables
Wind, solar PV, hydro – low ca
on but intermittent/constrained
Emerging renewables
Concentrating solar thermal, wave, geothermal, biomass, biogas – expensive
Storage – PHES and distributed batteries
Plus need to wo
y about transmission, security of supply, voltage and frequency stability
Things to conside
Build a simulation tool of the NEM of medium complexity
Run an optimisation routine to find the least cost combination for a given emission reduction target.
Model considers hourly variability, discount rate (10%) and other scenarios (low discount, higher non-synchronous allowances…)
Considers the transition (not just a snap shot in 2050)
Approach
Modelling setup
Find the least cost total system cost for a combination of generation technologies for 100% emission abatement by 2050 (other targets also possible)
Broad range of technologies considered (technology agnostic)
Coal (
own and black coal), Gas (OCGT and CCGT)
Hydro, wind, sola
Concentrating solar thermal, Ca
on capture and storage (CCS), bioenergy, Pumped hydro energy storage (PHES)
At same time consider transmission constraints and costs of additional transmission capacity
Hourly economic dispatch model, inertia constraints, ramp rates, unit commitment
We run 8 hours of storage for both PHES and CSP
Discount rate: 10%
Electrification of transport
1.4 times demand increase by 2050 cf to 2013
Build cost ($/kW) real 2017 dollars XXXXXXXXXXfrom CSIRO cost projections used in the AEMO’s ISP (integrated System Plan)
Technology cost scenarios
CSP ($kW) PHES ($/kW)
YEAR 2018 2050 2018 2050
SLOW 4434 3312 1860 1860
NEUTRAL 4434 2190 1386 1077
RAPID 4434 1068 800 800
Run various combinations of slow, neutral and rapid for the two technologies.