Post on 17-Sep-2018
Time reconciliation Reliability criteria Space aggregation
Time-scale reconciliation to shed light on the plausibilityof long-term low carbon pathways : power system issues
Nadia Maïzi, Vincent Mazauric, Edi Assoumou et al
1MINES ParisTech, PSL Research University, CMA - Centre de mathématiques appliquées,CS 10207 rue Claude Daunesse 06904 Sophia Antipolis Cedex, France
2Chaire Modélisation prospective au service du développement durable
Short term versus long term energy planningConsidering temporal trade-offs in decarbonisation pathways
London, 2016N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 1 / 32
Time reconciliation Reliability criteria Space aggregation
Future Power System : generation mix
Figure : All-Renewable ElectricityGeneration in 2050.Source: DESERTEC.
Renewable and distributed energysources are attractive alternatives forpower generation
Z Major Technical and Economicschallenges
1 Intermittency: complexification ofoperation issues.
2 Costs: infrastructures and devices.
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 2 / 32
Time reconciliation Reliability criteria Space aggregation
Future Power System : Reliability of electricity supply
Figure : Europe from orbit during theItalian blackout (Sept. 28th, 2003). Source:French TSO.
Technical constraints binding theoperation of the future power system arerelated to:
the given level and spatialdistribution of loads and capacities;the expected level of reliability toprevent from power outages.
Z Where reliability is the capability ofthe power system to withstandsudden disturbances.
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 3 / 32
Time reconciliation Reliability criteria Space aggregation
Transient Stability and Reliability
Definition: Ability of a Power System after a Transient Period to lockback into Steady-State conditions, maintaining Synchronism.
During the Transient Period:Frequency and voltages change;The operator can’t modify the production plan;The system relies on the inertia (kinetic and magnetic) of itstransmission and production capacities;The power system must remain stable.
Transient Stability Studies assess the level of Reliability of powersystems.
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 4 / 32
Time reconciliation Reliability criteria Space aggregation
Time scale of transient stability physical phenomena
Figure : Physical phenomena associated with the electrical system (according to themain domains : protection, network control and monitoring) versus time
Reference: Bruno Meyer, Michel Jerosolimski, Marc Stubbe: Outils de simulation dynamique des réseaux
électriques. Techniques de l’ingénieur,1998.
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 5 / 32
Time reconciliation Reliability criteria Space aggregation
Assessing future power systems : dynamics issues
Stability studiesinvolve time scales ranging from afew milliseconds to a few hours
Long-term planning modelsdeal with several years or decades
Z This gap is the main reason why reliability requirements are oftenignored or not accurately implemented in long-term planning models.
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 6 / 32
Time reconciliation Reliability criteria Space aggregation
Seeking for a plausible reliable, environmentallycompliant power mix
M. Drouineau, Modélisation prospective et analyse spatio-temporelle : intégration de ladynamique du réseau électrique, Mines ParisTech PhD Thesis under N. Maïzi direction,PhD Thesis under N. Maïzi direction, Sophia-Antipolis, France, 2011.
S. Bouckaert, Assessing Smart Grids contribution to the energy transition with long-termscenarios (Contribution des Smart Grids à la transition énergétique: évaluation dans desscénarios long terme), Mines ParisTech PhD Thesis under N. Maïzi direction,Sophia-Antipolis, France, 2013.
V. Krakowski, Intégration des renouvelables et stratégie de développement du réseau(Renewable and network development strategies) ongoing Mines ParisTech PhD Thesisunder N. Maïzi direction.
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 7 / 32
Time reconciliation Reliability criteria Space aggregation
Assessment of reliable future power systemsZ This study proposes an approach combining these dynamics issues to assessfuture power mixes where
Future power mix are assessed through along-term model
TIMES, a bottom up technologicalmodel realizing the minimization of theglobal discounted cost of the RES
A reliability criteria
is established to handle the dynamicmanagement (frequency and voltagecontrols)
depending on:
the level of reliabilityrequired,the dynamic propertiesof capacities,the load profilethe grid properties
avoiding time-consumingmethods relying on Kirchhofflaws.N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 8 / 32
Time reconciliation Reliability criteria Space aggregation
From the reversibility condition to network management
The best power transaction achieves :
tertiary & secondary control ∼ mn︷ ︸︸ ︷Pmechext = P∗Joule +
primary control︷ ︸︸ ︷dE∗cindt︸ ︷︷ ︸
∼ s
+dF∗
dt︸ ︷︷ ︸∼ ms
(1)
While in steady-state :
Electricity consumption = generation
Frequency and Voltage: constant
Embedded kinetic and magnetic free-energies are time-invariant
A fluctuation occurs : during the Transient Period, Frequency and voltages change;
Magnetic energy:spread the fluctuation over the gridProvide stiffness between distributed kinetic reserves
Kinetic energy: inertia for the power system
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 9 / 32
Time reconciliation Reliability criteria Space aggregation
Load fluctuation and stability
∼ mn︷ ︸︸ ︷Pmechext = PJoule +
dEcin
dt︸ ︷︷ ︸∼ s
+dF
dt︸ ︷︷ ︸∼ ms
Two events experienced by a power system: an admissible load
fluctuation is lifted by the electromagnetic coupling energy
(ΦIexc), the kinetic reserve (Ecin) and the generation
realignement during a load fluctuation (left) ; conversely, a
short circuit lowers the coupling energy and the kinetic reserve
leading to a collapse of power transmission (right).
Energy exchanges between the subsystems involved in the Thermodynamic Framework Source: V. Mazauric
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 10 / 32
Time reconciliation Reliability criteria Space aggregation
Control operations
Thus time response is related to dynamic management of a suddenimbalance involving the three control levels needed for network operations :
1 primary : automatic devices re-establishes the balance between demand and generation at a
system frequency other than the frequency set-point value (50 Hz). It causes a deviation in power exchanges
between control areas from the scheduled values. (ancillary services)
2 secondary : automatic devices restore the system frequency to its set-point and restore the
power exchanges between the control areas. (system adequacy)
3 tertiary : TSO manual action to activate reactive compensation equipment. (system
adequacy)
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 11 / 32
Time reconciliation Reliability criteria Space aggregation
Deriving reliability indicators (Patent FR 11 61087)
Z In order to ensure system reliability enough reserve levels must beprovided:
magnetic reserve : transmission maintenance ;kinetic reserve : frequency maintenance.
Z The higher the reserves, the more reliable the system is.
Reliability criteriaThe reserves are associated to two indicators Hcin Hmag
They refer to dynamic properties of the installed capacities, eachcontributing to the reserves level in a specific way
The level of reliability is characterized by H:the time you have to recover the stability of the system after a loadfluctuation (equivalent to the whole system capacity) by monitoring itsreserves.
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 12 / 32
Time reconciliation Reliability criteria Space aggregation
Steps of the approach
1 A power mix is delivered through the prospective horizon using TIMES
2 The level of reliability of the power system can be derived fromthe dynamic properties of the installed capacitiesthe associated inertia of the system (kinetic and magnetic)the load profile.
characterized by H as a measure of the kinetic energy inertia
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 13 / 32
Time reconciliation Reliability criteria Space aggregation
Path variant towards 100% renewable in France
Power mix in the six reference scenarios (nuclear 50% by 2025, RES 27% by 2020 and 40% by 2030)
This power mix ensure only system adequacy (84 Time slices, Disaggregation of each dispatchable
power plant into six processes for a better representation of the production curve, peak load factor, flexibility
options.)N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 14 / 32
Time reconciliation Reliability criteria Space aggregation
Path towards 40% to 100% renewable in France
Overall installed capacity from 2013 to 2050 (six reference scenarios + three variants)
No week with low wind/PV production (v1) ; VREs do not participate in peak load factor (v2)
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 15 / 32
Time reconciliation Reliability criteria Space aggregation
Path towards 40% to 100% renewable in France
Power production in 2050 in the reference 100% RES scenario
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 16 / 32
Time reconciliation Reliability criteria Space aggregation
Kinetic reserves for peak periods in 2050
Deviation of kinetic reserves in 2050 compared to the minimum 2012 level, in the reference 100% RES scenario,
with import contribution (variant v8) / wind contribution (variant v9), and in three variants with high biomass
potential (variants v5-v7)
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 17 / 32
Time reconciliation Reliability criteria Space aggregation
Seeking for a reliable, environmentally compliantpower mix
Reliability Indicators as constraints
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 18 / 32
Time reconciliation Reliability criteria Space aggregation
Focusing on the Reunion Island
power production: 100%renewable in 2030
1 Blessed with high renewableenergy potentials
2 Small, weakly-meshed andremoted power system
3 Binding target in 2030:100% renewable sources inpower generation
4 Maximum : 30% EnRintermittency
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 19 / 32
Time reconciliation Reliability criteria Space aggregation
The electricity sector in 2008
Electricity production: 2 546 GWh
Installed capacitiesThermal units (76%):
476 MWFuels: coal, fuel oil,sugarcane bagasse
Hydroelectricity (20%):Dams: 109,4 MWRun-of-the-river: 11,6 MW
Others (4%):Wind: 16,8 MWSolar PV: 10 MWMunicipal Waste: 2 MW
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 20 / 32
Time reconciliation Reliability criteria Space aggregation
Existing power plants
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 21 / 32
Time reconciliation Reliability criteria Space aggregation
BAU Scenario : production (GWh)
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 22 / 32
Time reconciliation Reliability criteria Space aggregation
100% Renewable Energy in 2030, production (GWh)
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 23 / 32
Time reconciliation Reliability criteria Space aggregation
Is 30% the maximum share ?Electricity production mix in 2030
of a typical day during summer
0 5 7 9 12 17 20 22 240
5
10
15
20
25
30
35
t (h)
Hcin(s)
of a typical day during winter
0 5 7 9 12 17 20 22 240
5
10
15
20
25
30
35
t (h)
Hcin(s)
0 20 40
100 % EnR PV−OCE REF−2008
100 % EnR : limitation of 30 % of instantaneous power production issuedfrom intermittent sources
PV-OCE : no constraint on intermittency
REF-2008 : kinetic reserve level in 2008
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 24 / 32
Time reconciliation Reliability criteria Space aggregation
Storage contribution to dynamic supportDedicated storage devices must be : distributed (Supercapacities, Batteries NaS,
Li-ion, PbA, etc) in order to contribute to increase the kinetic indicator
Short time response6 15s (timecaracteristic to enableprimary reserve)
High Power Capacity
103 MW
102 MW
10 MW
1 MW
102 kW
10 kW
1 kW
1 kWh 10 kWh 102 kWh 1 MWh 10 MWh 102 MWh 103 MWh 104 MWh 105 MWh
Energie stockée
Pu
issa
nce
fo
urn
ie
10-3 heures (3.6 s)
103 heures (41 jours)
1 heure
Supercondensateurs
Batteries
CAES (petite taille)
Volant d’inertie haute vitesse
Volant d’inertie basse vitesse
Micro SMES
SMES
Batteries à circulation
CAES grande taille
STEP
P. Wang, 2014, From Ibrahim et al, 2008
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 25 / 32
Time reconciliation Reliability criteria Space aggregation
Impact on Demand Side Management and StorageDSM = postponing demand from peak to off-peak periods + EE
Electricity production mix of a typical day during summer in 2030
Without reliability constraint∀t : Hcin,t >min(Hcin,2008)
Reliability + DSM+ Storage (24MW)
0 5 7 9 12 17 20 22 240
200
400
600
800
t (h)
Puissance
(MW
)
0 5 7 9 12 17 20 22 240
200
400
600
800
t (h)
Puissance
(MW
)
0 5 7 9 12 17 20 22 240
200
400
600
800
t (h)
Puissance
(MW
)
BAGWOO COB DAM GEO OCE−ETM RUN SOL OCE−WAV WIN
share of intermittentsources > 50%
↗ total installedcapacities of 9.4 %
share of intermittentsources > 50%
↘ total installedcapacities of 6 %
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 26 / 32
Time reconciliation Reliability criteria Space aggregation
Impact on Demand Side Management and StorageDSM = postponing demand from peak to off-peak periods + EE
Electricity production mix of a typical day during summer in 2030
Without reliability constraint∀t : Hcin,t >min(Hcin,2008)
Reliability + DSM+ Storage (24MW)
0 5 7 9 12 17 20 22 240
200
400
600
800
t (h)
Puissance
(MW
)
0 5 7 9 12 17 20 22 240
200
400
600
800
t (h)
Puissance
(MW
)
0 5 7 9 12 17 20 22 240
200
400
600
800
t (h)
Puissance
(MW
)
BAGWOO COB DAM GEO OCE−ETM RUN SOL OCE−WAV WIN
share of intermittentsources > 50%
↗ total installedcapacities of 9.4 %
share of intermittentsources > 50%
↘ total installedcapacities of 6 %
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 26 / 32
Time reconciliation Reliability criteria Space aggregation
Impact on Demand Side Management and StorageDSM = postponing demand from peak to off-peak periods + EE
Electricity production mix of a typical day during summer in 2030
Without reliability constraint∀t : Hcin,t >min(Hcin,2008)
Reliability + DSM+ Storage (24MW)
0 5 7 9 12 17 20 22 240
200
400
600
800
t (h)
Puissance
(MW
)
0 5 7 9 12 17 20 22 240
200
400
600
800
t (h)
Puissance
(MW
)
0 5 7 9 12 17 20 22 240
200
400
600
800
t (h)
Puissance
(MW
)
BAGWOO COB DAM GEO OCE−ETM RUN SOL OCE−WAV WIN
share of intermittentsources > 50%
↗ total installedcapacities of 9.4 %
share of intermittentsources > 50%
↘ total installedcapacities of 6 %
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 26 / 32
Time reconciliation Reliability criteria Space aggregation
Seeking for a reliable, environmentally compliantpower mix
Do we meet synchronism conditions ?
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 27 / 32
Time reconciliation Reliability criteria Space aggregation
Synchronism issues
So far Ecin is implicitely added. This assumes that synchronism isinconditionally achieved, whatever the regime and the fluctuation!
However we have some concerns about synchronism coming from phase transition theory where 2d-DoF (DoF
physical) objects (here the rotors of the generators) coupled within a 2D lattice (the grid) is not inconditionally
ordered (synchronized) and may experience a disordering process under long-range soft modes.
Z The factors for desynchronization are: N large, weak and sparsecouplings between generators;Z The factors favouring synchronism are: strong and highly correlatedcouplings between generators (copper plate).
The universality of phase transitions and critical phenomena theory allows to study the synchronism with a
dedicated model (instead the actual and cumbersome electromagnetic behavior) [Kuramoto,1984] enabling to derive
a new indicator :λ2,G
max(i,j)∈εG |Pi − Pj|> 1
(Dörfler, 2013)N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 28 / 32
Time reconciliation Reliability criteria Space aggregation
Path towards 40% to 100% renewable in France
Figure : Synchronism indicator for Peak periods in 2050 (cweek is low wind andsun, no imports)
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 29 / 32
Time reconciliation Reliability criteria Space aggregation
Summary and perspectives
We have developed an innovative approach in order to qualify
The level of reliability of an assessed power mix system resulting forTIMES assessment. It is derived from
the dynamic properties of the installed capacitiesthe associated inertia of the system (kinetic and magnetic)the load profilethe grid properties
This approach is dedicated to assess the technical feasibility of futurepower mix throughZ criteria reflecting kinetic energy inertia HcinZ criteria reflecting magnetic energy inertia HmagZ criteria reflecting synchronism K
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 30 / 32
Time reconciliation Reliability criteria Space aggregation
http://www.modelisation-prospective.org/en
More on criteria issues :V. Mazauric and N. Maïzi, A global approach of electromagnetism dedicated to further long-term planning,Proceedings in Applied Mathematics and Mechanics, vol. 7, issue 1, 2007.M. Drouineau, V. Mazauric, N. Maïzi, Impacts of intermittent sources on the quality of power supply: Thekey role of reliability indicators, Applied Energy 2014.N. Maïzi, E. Assoumou, Future prospects for nuclear power in France, Applied Energy (2014), pp. 849-859,DOI information: 10.1016/j.apenergy.2014.03.056.S. Bouckaert, V. Mazauric, N. Maïzi, Expanding renewable energy by implementing Demand-Response,Energy Procedia (2014), pp. 1844-1847.S. Bouckaert, P. Wang, V. Mazauric, and N. Maïzi, Expanding renewable energy by implementing Dynamicsupport through storage technologies, Energy Procedia, vol. 61, pp. 2000-2003, 2014.M. Drouineau, E. Assoumou, V. Mazauric, N. Maïzi, Increasing shares of intermittent sources in ReunionIsland: impacts on the future reliability of power supply, Renewable and Sustainable Energy Reviews.06/2015; 46. DOI: 10.1016/j.rser.2015.02.024V. Krakowski, E. Assoumou, N. Maïzi, Enjeux d’une transition vers une production d’électricité 100%renouvelable en France, dans Revue de l’Energie, No 627 (Septembre/Octobre 2015), pp. 381-394, 2015.V. Krakowski, E. Assoumou, V. Mazauric, N. Maïzi, Feasible path toward 40% - 100% renewable energyshares for power supply in France by 2050: A prospective analysis. Applied Energy 171 (2016) 501-522.V. Krakowski, N. Maïzi, V. Mazauric, A magnetic model dedicated to the stability of the power grid,Advances in Magnetics, IEEE Conference, Bormio, 2016.
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 31 / 32
Time reconciliation Reliability criteria Space aggregation
http://www.modelisation-prospective.org/en
More on other long term analysis subjects :
T. Le Gallic, E. Assoumou, N. Maïzi, P. Strosser, Les exercices de prospective énergétique à l’épreuve desmutations des modes de vie, VertigO, 2015.
F. Briens, N. Maïzi, Coping with the complexity of socio-ecological systems : Investigating the DegrowthParadigm through prospective Modeling,ÖkologischesWirtschaften 3.2014 (29)
S. Selosse, O. Ricci, N. Maïzi, Fukushima’s impact on the European power sector: The key role of CCStechnologies, Energy Economics, Vol. 39, pp 305-312, 2013.
A. Dubreuil, E. Assoumou, S. Bouckaert, S. Selosse, N. Maïzi, Water modeling in an energy optimizationframework - The water-scarce middle east context, Applied Energy 101, (2013), pp 268-279.
E. Assoumou, N. Maïzi, "Carbon value dynamics for France: A key driver to support mitigation pledges atcountry scale", Energy Policy, Volume 39, Issue 7, July 2011, Pages 4325-4336.
Analysis of the effect of environmental policies on the allocation of natural gas accross end-use sectors inFrance, E. Assoumou and N. Maïzi, CMA, MINES ParisTech, Working Paper n◦ 2011-02-02
N. Maïzi (MINES ParisTech) Short term vs long term energy planning 29 Avril 2016 32 / 32