Addressing Flexibility in Energy System Models

Joseph Dillon, Damian Flynn, Mark O’Malley, Zakir Rather (UCD)

P. Deane, B. Ó Gallachóir (UCC) Eamonn Lannoye (EPRI)

University College Dublin (UCD), University College Cork (UCC), Electric Research Power Institute (EPRI)

4th December 2014

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Introduction to ERC, UCD and UCC

The Electricity Research Centre (ERC) is a unique collaboration between academia and major players in the electricity/energy industry. It is centred in UCD but incorporates elements in other Irish research entities most recently UCC. The ERC is the core of the UCD Energy Institute, chaired by David O’Reilly former CEO of Chevron. It has significant international collaborations in particular with NREL and DTU who are jointly promoting the International Institute of Energy Systems Integration. Mark O’Malley is the founder of the ERC and the director of the UCD Energy Institute.

The research collaboration between University College Dublin and University College Cork enables a unique research capability that brings together significant research capacity in both power systems engineering and in energy systems modelling within a single partnership.

Overview

Renewables integration and flexibility

The detail vs. scope dilemma

Managing uncertainty

Energy system modelling

Multi-model approach

Stochastic Unit Commitment

Key Research Questions

Renewables Integration and Flexibility

With variable renewables more flexibility is needed

16x103

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Steeper ramps Lower turn-down

Source: Michael Milligan , NREL

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With variable renewables more flexibility is needed

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Quantifying Flexibility

Planning and operations merging

Best practices report ref

Holttinen, H., Orths, A., Abildgaard, H., Van Hulle, H., Kiviluoma, J., Lange, B., O’Malley M., Flynn, D., Keane, A., Dillon, J., Carlini, E. M., Tande, J. O., Estanqueiro, A., Lazaro, E. G., Söder, L., “IEA wind Recommended Practices, Wind Integration Studies”, International Energy Agency, Sept 2013. http://www.ieawind.org/Task_25/PDF/HomePagePDF%27s/RP%2016%20Wind%20Integration%20Studies_Approved%20091213.pdf.

The Detail vs. Scope Dilemma

Shortt, A., Kiviluoma, J. and O’Malley, M., “Accommodating Variability in Generation Planning”, IEEE Transactions on Power Systems, 2013 Vol 28, pp. 158-169

The need for more detail driven by RES Integration

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Results: Ireland (Annual Generation GWh)

Deane J.P., Chiodi A., Gargiulo M. and Ó Gallachóir B.P. 2012 Soft-linking of a power systems model to and energy systems model. Energy Vol 42, Pages 303-312

The Detail vs. Scope Dilemma

Do we …….

a. Use conventional paradigms? +

b. Assess flexibility separately?

OR

c. Revise the paradigm?

with

Custom developed tools

Trade detail for scope

Increased patience and/or computing power

Grid and Flexibility

Grid poses challenges for flexibility assessment but it can be done

The impact may be marginal, or significant, depending on system characteristics

Lannoye, E., Flynn, D. and O'Malley, M.J. "Transmission, variable generation and power system flexibility”, IEEE Transactions on Power Systems, in press, 2014

T.C.F. IRRE vs. IRRE

T.C.F. IRRE vs. IRRE (Concentrated Wind)

TFC: Transmission constrained flexibility assessment IRRE: Insufficient Ramping Resource Expectation

Optimal Interconnection – No Renewables Targets

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Muireann Á. Lynch, Richard S.J. Tol, Mark J. O'Malley, Optimal interconnection and renewable targets for north-west Europe, Energy Policy, Volume 51, December 2012, Pages 605-617, ISSN 0301-4215, http://dx.doi.org/10.1016/j.enpol.2012.09.002. (http://www.sciencedirect.com/science/article/pii/S0301421512007604)

Optimal Interconnection – With Renewables Targets

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Muireann Á. Lynch, Richard S.J. Tol, Mark J. O'Malley, Optimal interconnection and renewable targets for north-west Europe, Energy Policy, Volume 51, December 2012, Pages 605-617, ISSN 0301-4215, http://dx.doi.org/10.1016/j.enpol.2012.09.002. (http://www.sciencedirect.com/science/article/pii/S0301421512007604)

Managing Uncertainty

16 Managing Uncertainty in the Operational Time Frame

Stochastic Scheduling

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Rolling planning

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Forecast error characterisation

Captures the process of decision making based on uncertain future production and demand

Increased model complexity, run times and data requirements

NTC between MS

Maryse Labriet , Amit Kanudia , Richard Loulou 2012 Climate mitigation under an uncertain technology future: A TIAM-World analysis Energy Economics 34 366 - 377

Figure 1 Role of Gas in elec gen in China in 2030 (in 3.7 W/m2 ~ 550 ppm scenario)

• Stochastic programming with TIAM-WORLD used to explore long term technical and climate uncertainty.

• Explores two contrasting technology outlooks RES and CONV

• Use of gas in China 50% higher in hedging rather than perfect foresight scenarios

Managing Uncertainty – Long Term

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Long Term Uncertainty with Full UC

Muireann Á. Lynch, Aonghus Shortt, Richard S.J. Tol, Mark J. O'Malley, Risk–return incentives in

liberalised electricity markets, Energy Economics, Volume 40, November 2013, Pages 598-608, ISSN

0140-9883

Energy System Modelling

Integrated Energy System Results from Irish TIMES

2050 – Low Carbon Scenario

Chiodi A., Gargiulo M., Rogan F., Deane J.P., Lavigne D., Rout U.K. & Ó Gallachóir B.P. 2013 Modelling the impacts of challenging 2050 mitigation targets on Ireland's energy system Energy Policy 53 pp 169 - 189

- Strong focus on coupling of energy system models with sectoral energy models (Power system, Residential heating and Transport sector)

- Multi-model approach has been applied to Ireland - Multi-model approach has been applied to EU

- Focus of the integration of high shares of variable RES-E and high shares of RES-T and RES-H&C

- New Approaches - Day ahead / Real time Stochastic Unit Commitment Integrated Gas and Electricity Modelling

Energy System Modelling Focus

Irish TIMES • Integrated Energy systems model to 2060 • 12 timeslices in 5 – 10 year intervals • Scenario analysis 2020 to 2050 PLEXOS_Ireland Power Systems Model • Use TIMES results to build single year power systems model • 5-15 minute, power plant detail, ramp rates, min load, cold start,

reserve modelling, market modelling etc • Impacts of TIMES results on power system operation • Use results to inform constraints in TIMES

Multi-Modelling Approach - Ireland

PLEXOS Integrated Gas and Electricity model links to PRIMES Energy system model or TIMES Integrated Energy System Model

Power System Model Provides:

- Detailed analysis of energy system model results using soft-linking techniques+

- High temporal resolution (15min)

- High technical detail, reserve modelling, hydro modelling, multi-stage stochastic UC

- Ramping costs, flexibility metrics EU 28 Model- 3,000 generators, 22 PHES Units, 53 IC

+ Deane, J.P., Chiodi, A., Gargiulo, M., Ó Gallachóir, B.P., 2012. Soft-linking of a power systems model to an energy systems model. Energy 42, 303–312.

Multi-Model Approach Applied to EU

NTC between MS NTC between MS

2030 Curtailment (%) PRIMES Ref Scenario

Wind Profiles

UC of Coal Units

Stochastic Day Ahead/Real Time Simulations

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Key Research Questions

What key details are missing from current energy system models?

What is their relative impact?

What do we do to ensure models are fit for purpose?