Options for addressing the balancing challenges

Options for addressing the balancing
challenges:
Integrated gas and electricity perspectives
Meysam Qadrdan and Goran Strbac
1
Balancing challenges
• Large increase in wind generation capacity in GB
• Balancing challenges due to wind variability
• A number of technically-feasible options:
•
•
•
•
Generation flexibility
Electricity storage
Power-to-Gas
Demand flexibility
• Efficacy of these options?
• What is the impacts on the operation of gas network
(linepack changes)?
• What is the role of gas network?
Type
Capacity (GW)
Gas
44
Coal
10
Nuclear
12
Wind
45
Hydro
1.1
Interconnector
7.6
Pumped storage
2.7
Generation capacity mix in 2030,
Source: National Grid ETYS, 2012
2
Combined Gas and Electricity Network model
(CGEN)
• CGEN is an optimisation model for integrated gas and electricity
network
• Rolling optimisation approach
START
Day = 1
Data from Database, inc.
·
Gas and electricity
demand data
·
Capacity and location of
the networks
components
·
Costs (generation cost,
fuel price, …)
·
Wind generation
Day = Day + 1
(Rolling
optimisation)
CGEN model
Minimisation of operational costs
(MINLP)
Day < 7
Import results to the
next iteration (day),
as previous state of
the system
YES
NO
FINISH
3
Case studies
• Options for addressing balancing challenges:
•
•
•
•
Reference
Flexible CCGTs
Electricity storage
Power-to-Gas
• Simplified electricity and gas networks were
used to represent the GB system in 2030
• A typical winter week in 2030 was modelled
(with hourly time steps)
• No constraint on power transmission capacity
was assumed
4
Data from: National Grid, Elexon and ITRC
Impacts on power system \ 1
In the Reference case:
• Wind curtailment occurs during
low demand-high wind periods.
• CCGTs ramp up/down to
compensate for variability of net
load.
• Frequent on/off cycles for CCGTs
5
Impacts on power system \ 2
• Introduction of flexibility options reduced wind curtailment.
• More flexible CCGTs provided:
• Slightly lower power output
• Higher spinning reserve
• Power-to-Gas provided reserve through flexible demand for H2
electrolysers
6
Impacts on the gas network \ 1
In all the case studies:
• Higher gas supply and compressor power
during low wind-high demand periods
Reference case
• The volume of gas within pipes (linepack)
was used to meet abrupt increase in gas
demand.
• Despite higher compressor power
consumption, roughly 40 mcm drop in the
linepack occurred during low wind – high
demand period (peak hours – Day 5)
7
Impacts on the gas network \ 2
• Using more flexible CCGTs increased (in
respect to the reference case):
• Maximum hourly depletion of linepack
• Linepack fluctuation
• Employing electricity storage resulted in less
variable power output from gas plants and
consequently less fluctuation in linepack.
• Average/Max compressor power ratio is the
lowest for the case with flexible CCGTs:
• i.e. higher maximum flow but lower level of
utilisation (lower capacity factor)
• Could lead to higher connection (to the gas
network) fee
8
Operational costs
• Up to 1.7% reduction in the total
operational cost of gas and electricity
networks over a week
• Flexible CCGTs: lower start up/shut down
costs, provision of higher spinning reserve
• Electricity storage: avoiding wind
curtailment and providing reserve
• Power-to-Gas: avoiding wind curtailment,
providing reserve (flexible demand)
• Capital costs of the flexibility options
need to be taken into account.
9
Electricity storage vs. Power-to-Gas
• Taking into account the power
transmission constraints resulted in better
performance of Power-to-Gas:
• Employing electrolysers in congested area
(mostly Scotland and North England) to
absorb wind power
• Bypassing power transmission congestion
through employing the gas network
storage/transport capacity
10
Source: National Grid, GTYS 2012
Integration of low carbon generation
technologies:
Value of gas plant flexibility and impact on gas plant
operation
11
Balancing and need for flexibility
Zero or negative energy prices for
>15% of time
Value of energy frequently lower
than value of flexibility
Unprecedented price volatility….
leading to increased base-load & peak generation investment risks...
...while providing significant opportunities for flexible generation, demand side response,
storage, interconnection, H2
12
Enhanced time-domain stochastic scheduling:
simulation of wind-integrated power systems
Wind statistics
1
0.9
60000
0.8
Demand net wind (MW)
50000
0.7
wind forecast
0.6
0.5
40000
30000
20000
10000
0.4
0
1
9
17
25
33
41
49
57
65
73
81
89
97
105
113
121
129
137
145
153
161
Aggregate wind power (p.u.)
• Technical and cost parameters
(Rated output, MSG, Ramp-rates,
Min up-/down-time, Response
slope, Efficiency curve, Fuel costs,
Start-up costs, Emissions)
Storage Capacity:
18GWh
Rating:
+/- 4GW
Round-trip efficiency: 72%
0.3
Time (hr)
0.2
wind, demand, outage
realisation
0.1
16:00
15:00
14:00
13:00
12:00
11:00
10:00
09:00
08:00
07:00
06:00
05:00
04:00
03:00
02:00
01:00
00:00
0
Time (hrs)
35000
30000
Demand risk
00:00
23:00
22:00
21:00
20:00
19:00
18:00
17:00
16:00
15:00
14:00
13:00
12:00
11:00
10:00
09:00
08:00
25000
Time (hrs)
Demand uncertainty model
Deterministic UC
40000
50th percentile
30000
Reserve
20000
10000
0
-10000 0
-20000
4
8
12
16
20
24
Time horizon (hr)
50000
Online
λ Δt
Unavailable
Available
μ Δt
Outage
model
60000
30000
20000
10000
0
-10000 0
-20000
Deterministic security
targets
Response
Reserve
50000
Wind
40000
Storage
coal
30000
CCGT
20000
Nuclear
10000
4
8
12
16
20
24
Time horizon (hr)
Outage risk
Scheduling
model
startup
70000
Stochastic UC
40000
VOLL
30,000 €/ MWh
online capacity
0
Demand
1
11
21
31
41
51
61
71
81
91
101
111
121
131
141
151
161
Wind risk
40000
50000
Generation (MW)
45000
Demand + outages net wind
(MW)
Aggregate demand (MW)
50000
Demand + outages net wind
(MW)
demand
forecast
Wind uncertainty model
Time (hr)
Dispatch,
operating costs,
CO2 emissions...
Stochastic security
target
13
Energy production by gas plant at different
wind penetration levels
Reduction in volumes of gas non-linear
14
Predicting gas consumption – alternative
models /1
Base Case
Plant maintenance
Granular time resolution needed
15
Predicting gas consumption – alternative
models /2
Base Case
Additional 5GW Storage
16
Investment in flexibility?
System value of enhanced
flexibility of CCGTs will be significant
How about the value to
investors?
17
Enhancing flexibility will lead to increase in
number of start ups
Flexible
Inflexible
18
Participation of storage in balancing market
19
How important is efficiency?
20
Summary
• Opportunities/challenges of employing different flexibility options were
investigated with respect to electricity and gas networks.
• Large capacity of gas-fired generators, compensating for wind
variability, will increase fluctuations in the gas network linepack.
• Within-day linepack management will be required to maintain withinday gas storage capability of the NTS.
• A number of options for dealing with balancing challenge identified,
including Power to Gas - decarbonising of the gas network
• Potential conflicts between national and investor objectives
21