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Fare clic per inserire il titolo Per una corretta compilazione
Assessing the maximum penetration of
non-programmable RES generation in
power systems with predominant
thermal generation
Bruno Cova
Source: AUE
Head of Power Systems, Markets and Regulatory
Division Consulting, Solutions & Services
Renewable Energy Seminar, Amman, 27th-28th March 2012
Agenda
 Trends towards a progressive decarbonisation of power systems
 Increasing penetration of power generation from non-programmable RES
 Problems to overcome to enhance generation from non-programmable
RES
 Possible solutions:
 Enhancing flexibility of the power system (generation / grid / demand)
 The role of transmission infrastructure (supergrids/electricity highways)
 The CESI experience
2
Power generation in the world
 Power Generation from main energy sources
16%
2%
COAL
40%
GAS
OIL
NUCLEAR
HYDRO
15%
RENEWABLE
- Biomass
- Solar
- Wind
- Geothermal
7%
20%
World power production: ~21.240 TWh
Source: Enerdata Yearbook 2011 / CESI elaborations
3
Power generation in the Arab Countries
 Power Generation from main energy sources
Typical specific CO2
emissions (kg/MWh)
95.9%
1200
1000
750÷1000
750÷850
800
500÷700
600
350÷450
3.8%
FOSSIL FUEL
HYDRO
0.2%
200
RENEWABLE
0
Arab Countries power production: ~815 TWh
Source: AUE statistical bulletin 2010 / CESI elaborations
4
400
Coal
Oil
Gas OCGT Gas CCGT
Trends towards a progressive decarbonisation of power
systems: Europe
The EU 20-20-20 objectives to meet the goal of limiting the global surface
warming to +𝟐°𝑪 above pre-industrial level:

20% reduction of greenhouse gases (GHG) emissions in 2020 compared to 1990;

20% savings in energy consumption compared to baseline projections for 2020;

20% of overall energy mix from RES by the year 2020.
Long-term target (not binding yet) by
2050: decarbonisation up to 80-95%
compared to 1990 level
Present trend of «carbon-free»
generation in the EU power sector:
• 2010: 48%
• 2020: 54% (2000 TWh)
5
Trends towards a progressive decarbonisation of power
systems: other regions
China: announced in 2009 a target of CO2
emission reduction per unit of GDP between 40%
and 45% compared to 2005 levels by 2020
US: Northeast’s Regional Greenhouse Gas Initiative (RGGI), the first
cap-and-trade program in the United States (year 2009) to set
mandatory CO2 limits for the power sector. RGGI caps power sector
CO2 emissions at the 2009 levels and requires a 10% reduction by 2018
6
Trends towards a progressive decarbonisation of power
systems: the Arab Countries
In the Arab Countries the share of RES power generation is limited to 4%
out of which 3.8% from hydro (Egypt, Sudan, Iraq, Syria, Morocco)
…but Arab Countries
are endowed with a
huge potential of
power generation
from the sun and the
wind
Source: the Schott memorandum
From 1 sq km of desert one can obtain
with CSP up to:
 250 GWh/year of Electricity
 60 Million m³/year of Desalted
Seawater
7
Source: TREC development group
Increasing penetration of power generation from
non-programmable RES
RES generating capacity in Europe [GW]
194
250
118
200
150
114
38
78
100
50
26
0
Hydro
Wind
32
12
2010
Solar
Others
+149%
+46%
Wind
8
2020
Solar
Which problems
already
experienced in
Europe ?
Agenda
 Trends towards a progressive decarbonisation of power systems
 Increasing penetration of power generation from non-programmable RES
 Problems to overcome to enhance generation from non-programmable
RES
 Possible solutions:
 Enhancing flexibility of the power system (generation / grid / demand)
 The role of transmission infrastructure (supergrids/electricity highways)
 The CESI experience
9
Problems to overcome to enhance generation from nonprogrammable RES
Additional reserve and
balancing capability
Difficult transitions
in the ramp up/down
hours
Voltage profile and reactive
power management
10
Risk of overgeneration in
low loading conditions
Network congestion
Curtailed RES
generation !!!
Critical behaviour of the
system in dynamic conditions
Possible solutions
 Maximisation of RES generation penetration while minimising the
risk of curtailment: a FOUR-LAYER TOP-DOWN APPROACH
1. Reserve Criterion
2. Network connection / Static analysis
3. Reliability analysis
4. Dynamic Analysis
11
1. Reserve criterion – Part 1


Single Busbar model

Additional reserve to face the
unpredictability of RES is
estimated
Secondary and Tertiary reserves
are sized to manage the frequency
error and the largest generator
tripping

Acceptable gradients of max power
increase/decrease are taken into
account to confirm the limit of nondispatchable generation

RES energy feed points and
network constraints are not
considered yet
Increase in reserve requirement
Source: IEA-Wind
12
1. Reserve criterion – Part 2
Results
 First evaluation of maximum RES penetration that can be
accepted by the system
Max{RES} = Demand - (∑i PMIN-i + Tertiary reserve + Additional reserve)
P
MAX i
i
Secondary
increase reserve
Tertiary
increase
reserve
Renewable
production
Traditional
generation
P
i
13
MIN i
Additional
reserve for
RES
Secondary
decrease reserve
Tertiary
decrease
reserve
2. Network connection / Static analysis




Load flow calculations in compliance with the N and N-1 security
criteria (TSO rules)
The most significant load scenarios are considered (i.e. peak and low
load conditions)
Check the congestions on transmission network
Impact of wind production on the system’s voltage profile
Results
 Distribution of RES energy

production capacity
The best connection points
of RES units on the network
14
3. Reliability analysis – Part 1
Different scenarios of RES penetration are evaluated to highlight the
effects of increased RES generation on the secure and reliable supply of
electricity
7,000
6,000
5,000
4,000
3,000
2,000
1,000
0
1
304
607
910
1213
1516
1819
2122
2425
2728
3031
3334
3637
3940
4243
4546
4849
5152
5455
5758
6061
6364
6667
6970
7273
7576
7879
8182
8485
Probabilistic analysis using Monte
Carlo method and considering:
 The probabilistic nature of
generation-transmission system
over a whole year of operation
 The unavailability of all power
system components
 Possible optimal exploitation of
hydro sources
 A simplified or complete network
model
Annual wind production [MW]
8,000
Annual photovoltaic production [MW]
25,000
20,000
15,000
10,000
5,000
1
326
651
976
1301
1626
1951
2276
2601
2926
3251
3576
3901
4226
4551
4876
5201
5526
5851
6176
6501
6826
7151
7476
7801
8126
8451
0
15
3. Reliability analysis – Part 2
LOLE [h/year]
Results
25
 Three meaningful “Risk Indices”:
• Loss Of Load Expectation
• Loss Of Load Probability
• Expected Energy Not Supplied
 Reliability of the system to fulfil power
demand
 The maximum RES penetration
compliant with reliability standards
20
15
Scenario A
Scenario B
Bound
10
5
0
EENS
[p.u.]
LOLP
[%]
 Wind /solar curtailment due to network element overloads, lack of
interconnection or minimum stable operation of conventional units in
low load condition
 Possible network reinforcements, new storage devices and reserve
margins able to preserve the static reliability and the security of the
system
16
4. Dynamic Analysis – Part 1
 Check the fluctuations due to RES production intermittency
(mainly frequency due to wind)
17
4. Dynamic Analysis – Part 2
 Analysis of network response, voltages and frequency to major
fault events
Results
 Measures to avoid any RES production restriction due to
dynamic constraints
18
Possible solutions
 Energy storage
Two levels:
 small scale to smooth high frequency
low amplitude intermittency: batteries at
s/s
 large scale for systemwide stabilisation:
hydro pumping / different policies for
unit commitment : higher rate of start
up/ shut down of unit : OC TG
 Demand responsiveness
 Demand response from users
……. including electric vehicles
19
The role of transmission infrastructure: the electricity highways
Source EC
20
The role of transmission infrastructure: electricity highways
between Europe and the MENA region
21
Agenda
 Trends towards a progressive decarbonisation of power systems
 Increasing penetration of power generation from non-programmable RES
 Problems to overcome to enhance generation from non-programmable
RES
 Possible solutions:
 Enhancing flexibility of the power system (generation / grid / demand)
 The role of transmission infrastructure (supergrids/electricity highways)
 The CESI experience
22
CESI experience
 Max penetration of RES in Tunisia
 Max wind generation penetration in
Jordan
HVDC to
Europe
PREVISIONNEL AN 2016
 Renewable
Integration Development
Programme – Ireland
23
 Max wind generation penetration in
Italy
End of
Presentation
24
Problems to overcome to enhance generation from nonprogrammable RES
 Need for additional reserve to cope with the intermittency
of non-programmable RES generation
Increase in reserve requirement
Solar (PV) generation is treated like wind production
with additional reserve equal to the half of wind one
P
i MAX i
Source: IEA-Wind
Tertiary increase reserve
Generated power
 Penetration: wind / solar production
[MW] / demand
 Additional reserve [%]: percentage
of wind / solar generation
Additional increase
reserve
Renewable production
Wind + solar
Traditional
generation
P
i
25
Secondary increase
reserve
MIN i
Secondary decrese
reserve
Additional decrease
reserve
Tertiary decrease
reserve
Problems to overcome to enhance generation from nonprogrammable RES
 Excessive RES generation over the instantaneous demand: risk of
overgeneration
 Possible voltage problems
Downward wind modulation
Wind generation in Spain on 4th and 5th March 2008 (source REE)
26
Problems to overcome to enhance generation from nonprogrammable RES
 Coping with sharp variations of RES generation
Ramp rate up to 10% of
installed wind capacity
per hour
Example of Spain
Situation 9th Mai 2005
27
Problems to overcome to enhance generation from nonprogrammable RES
 Difficult upward/downward transitions
No correlation between wind/sun
generation and demand !!!
demand
Difficult transitions
during load ramp
up/down
Gradient of generation
Load Request
Wind + Solar
Example of Spain
28
wind
Time (min)
Problems to overcome to enhance generation from nonprogrammable RES
 Network congestions caused by RES generation:
 Sun and wind are location dependent – often remote locations w.r.t. the demand
centres
 No correlation between demand and non-programmable RES generation location
- power flowing on longer patterns through the network with risk of creating
“scattered” congestions also relatively far away from RES generation areas
Expected congestion in the 150 kV of the Italian peninsular regions due to WF
(year 2009) – (source: CIGRE, CESI-Terna paper)
29
Problems to overcome to enhance generation from nonprogrammable RES
Solar Radiation (W/m2)
Typical solar radiation
1000.00
 Critical dynamic behavior of the system caused by
800.00
Radiation (W/m^2)
 Intermittency in RES generation causing a higher stress
on the conventional units to balance the system
900.00
700.00
600.00
Winter
500.00
Summer
400.00
300.00
200.00
100.00
0.00
1
3
5
7
9
11
13
Hours
 Faults (e.g.: short circuits on a network
component)
Frequency (Hz)
Risk of cascading
effect leading to the
system collapse
30
15
17
19
21
23
Problems to overcome to enhance generation from nonprogrammable RES
Different feasible penetration
levels of non-programmable
RES generation
31
Curtailed non-progr. RES gen.
 (In)flexibility of power plants
 (in)adequacy of the transmission /distribution infrastructures (including
cross-border lines)
40%
 Possibility of energy storage
35%
 Demand responsiveness
30%
25%
20%
15%
28%
22%
10%
5%
16%
10%
5%
0%
1,000
2,000
3,000
4,000
Installed RES capacity [MW]
5,000
RES penetration for each area
Risks of RES generation curtailment depending on:
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