Uncertainty analysis of hierarchical energy systems models: Models versus real energy systems
Lead Research Organisation:
University of Edinburgh
Department Name: Sch of Mathematics
Abstract
Mathematical models are used widely in the planning and operation of energy systems, and in the development of public energy policy. The aim is to understand the impact of new policies, technologies and market operations. This is particularly significant at present due to the need to decarbonise energy systems over the coming decades, which is driving change in energy supply at a very rapid pace. Specific recent uses of large scale modelling studies in formal government policy Impact Assessments are the 2012 Energy Bill (which among other models uses economic modelling to project future generation investment under different policy options) and the 4th Carbon Budget (which provides the legal limit on GB carbon emissions from 2023 to 2027, and uses the UK MARKAL model for projecting evolution of the energy system under a given background scenario).
This project will study the relationship between mathematical and computer models of energy systems, and the real systems that they attempt to describe, with the purpose of enabling better model-based decisions in industry and government. Until such a relationship has been established between the model and the physical system that the model purports to represent, it is impossible to draw fully robust conclusions based on the model. This model/reality relationship will necessarily be probabilistic, expressing the degree to which uncertainty about the world can be resolved by careful use of the model. We will show, by a careful choice of exemplars, the ways in which such probabilistic relationships may be constructed for a wide range of energy systems models.
When we have linked the model and the physical system, the model can be embedded in a meaningful decision support system for choosing sensible future actions. This involves honest and careful assessment of all of the uncertainties involved in the planning process and consequent forecasting of the uncertainties associated with each possible planning choice. Using the selected exemplars, we will show how to replace current energy planning scenarios with a scrupulous uncertainty based guide to the consequences of current and future actions.
While much of this project involves specific exemplars, our intentions are general, namely to derive methodology which is widely applicable across the whole field of energy systems modelling and planning and therefore to show the potential for transformative analysis across the whole field. For this reason, our exemplars have been chosen to reflect general features common to a wide variety of energy models, which generally comprise systems of interconnected models which are each complex in their own right (e.g. a market model linking to an assessment of the engineering consequences of investment decisions, or a model describing interacting transmission and distribution networks). General methodology for the analysis of computer models will be tailored to the requirements of energy systems analysis. Further, some aspects, and in particular the development of effective uncertainty analysis for linked computer models, will have impact across modelling applications in many other fields.
Exemplars used will include studying the interaction between investment in generating capacity and the risks of supply shortages, the participation of resources embedded within distribution networks in the national energy market, and embedding a model of a particular sector of the energy economy within a model which projects the evolution of the whole energy economy. We will work on these exemplars in discussion with industrial collaborators, in order to identify how our methods must be designed and communicated in order for them to lead to eventual field application.
This project will study the relationship between mathematical and computer models of energy systems, and the real systems that they attempt to describe, with the purpose of enabling better model-based decisions in industry and government. Until such a relationship has been established between the model and the physical system that the model purports to represent, it is impossible to draw fully robust conclusions based on the model. This model/reality relationship will necessarily be probabilistic, expressing the degree to which uncertainty about the world can be resolved by careful use of the model. We will show, by a careful choice of exemplars, the ways in which such probabilistic relationships may be constructed for a wide range of energy systems models.
When we have linked the model and the physical system, the model can be embedded in a meaningful decision support system for choosing sensible future actions. This involves honest and careful assessment of all of the uncertainties involved in the planning process and consequent forecasting of the uncertainties associated with each possible planning choice. Using the selected exemplars, we will show how to replace current energy planning scenarios with a scrupulous uncertainty based guide to the consequences of current and future actions.
While much of this project involves specific exemplars, our intentions are general, namely to derive methodology which is widely applicable across the whole field of energy systems modelling and planning and therefore to show the potential for transformative analysis across the whole field. For this reason, our exemplars have been chosen to reflect general features common to a wide variety of energy models, which generally comprise systems of interconnected models which are each complex in their own right (e.g. a market model linking to an assessment of the engineering consequences of investment decisions, or a model describing interacting transmission and distribution networks). General methodology for the analysis of computer models will be tailored to the requirements of energy systems analysis. Further, some aspects, and in particular the development of effective uncertainty analysis for linked computer models, will have impact across modelling applications in many other fields.
Exemplars used will include studying the interaction between investment in generating capacity and the risks of supply shortages, the participation of resources embedded within distribution networks in the national energy market, and embedding a model of a particular sector of the energy economy within a model which projects the evolution of the whole energy economy. We will work on these exemplars in discussion with industrial collaborators, in order to identify how our methods must be designed and communicated in order for them to lead to eventual field application.
Planned Impact
The proposed research will benefit:
The government and electricity regulator. Improved systematic methods for analysing uncertainty in complex computer models will enable better public policy decisions to be made based on these models, helping deliver the required carbon reductions with improved cost and security of supply to customers.
The energy supply industry. The methods developed will enable better modelling-based decision making directly on the part of the industry; the Pathways to Impact document lists the various ways in which we will enable this transition of knowledge to the industry.
Energy customers. Ultimately the aim of enabling better model-based decision making by government and the energy industry is to enable the goals of decarbonisation and security of supply to be met at lower cost.
Users of complex computer models across the public, private and third sectors beyond the specific field of energy systems. The innovations in uncertainty analysis made in this project will find application wherever complex structures of linked models are used to support decisions. The methods developed bring potential benefits to any such organisation, resulting in better decision making and ultimately leading to more efficient and effective solutions for their citizens and customers.
The project will also have specific impact within the major industrial projects with which we will collaborate directly on modelling exemplars, notably the statutory Capacity Assessment project (feeding in to more robust design and operation of capacity mechanisms) and National Grid's work on transmission planning.
The government and electricity regulator. Improved systematic methods for analysing uncertainty in complex computer models will enable better public policy decisions to be made based on these models, helping deliver the required carbon reductions with improved cost and security of supply to customers.
The energy supply industry. The methods developed will enable better modelling-based decision making directly on the part of the industry; the Pathways to Impact document lists the various ways in which we will enable this transition of knowledge to the industry.
Energy customers. Ultimately the aim of enabling better model-based decision making by government and the energy industry is to enable the goals of decarbonisation and security of supply to be met at lower cost.
Users of complex computer models across the public, private and third sectors beyond the specific field of energy systems. The innovations in uncertainty analysis made in this project will find application wherever complex structures of linked models are used to support decisions. The methods developed bring potential benefits to any such organisation, resulting in better decision making and ultimately leading to more efficient and effective solutions for their citizens and customers.
The project will also have specific impact within the major industrial projects with which we will collaborate directly on modelling exemplars, notably the statutory Capacity Assessment project (feeding in to more robust design and operation of capacity mechanisms) and National Grid's work on transmission planning.
Organisations
Publications
Cuffe P
(2018)
Data Visualization: The Signal and the Noise
in IEEE Potentials
Du H
(2021)
Beyond Strictly Proper Scoring Rules: The Importance of Being Local
in Weather and Forecasting
MA Q
(2018)
Optimal dynamic pricing for smart grid having mixed customers with and without smart meters
in Journal of Modern Power Systems and Clean Energy
Wilson A
(2018)
Quantifying uncertainty in wholesale electricity price projections using Bayesian emulation of a generation investment model
in Sustainable Energy, Grids and Networks
Wilson A
(2022)
Varying Coefficient Models and Design Choice for Bayes Linear Emulation of Complex Computer Models with Limited Model Evaluations
in SIAM/ASA Journal on Uncertainty Quantification
Description | All is reported in the first version of this grant, this second grant number merely results from the PI moving institution |
Exploitation Route | n/a - see above |
Sectors | Energy Environment Government Democracy and Justice Transport |
Description | This is a duplicate of an award due to a move of university, so the question is not answered here. |
Description | Alan Turing Institute Partnership Project Scheme |
Amount | £403,000 (GBP) |
Organisation | Alan Turing Institute |
Sector | Academic/University |
Country | United Kingdom |
Start | 09/2018 |
End | 10/2018 |
Description | Alan Turing Institute Strategic Priorities Fund |
Amount | £64,000 (GBP) |
Organisation | Alan Turing Institute |
Sector | Academic/University |
Country | United Kingdom |
Start | 11/2018 |
End | 03/2019 |
Description | CReDo plus |
Amount | £650,000 (GBP) |
Organisation | Ofgem Office of Gas and Electricity Markets |
Sector | Public |
Country | United Kingdom |
Start | 03/2023 |
End | 03/2024 |
Description | CReDo plus, Water Catalyst scheme |
Amount | £1,000,000 (GBP) |
Organisation | Ofwat |
Sector | Public |
Country | United Kingdom |
Start | 06/2023 |
End | 06/2024 |
Description | Centre for Digital Built Britain Research Network |
Amount | £46,990 (GBP) |
Organisation | Digital Built Britain |
Sector | Private |
Country | United Kingdom |
Start | 06/2018 |
End | 12/2018 |
Description | Linking Whole Energy System Models to the Real World |
Amount | £250,000 (GBP) |
Organisation | University of Edinburgh |
Sector | Academic/University |
Country | United Kingdom |
Start | 05/2020 |
End | 06/2023 |
Description | Local Heat and Energy Efficiency Strategies |
Amount | £30,000 (GBP) |
Organisation | Government of Scotland |
Sector | Public |
Country | United Kingdom |
Start | 09/2021 |
End | 03/2022 |
Description | Mathematics Mobilised for the Energy Transition (M-MET) |
Amount | £56,000 (GBP) |
Organisation | International Centre for Mathematical Sciences (ICMS) |
Sector | Academic/University |
Country | United Kingdom |
Start | 06/2023 |
End | 06/2024 |
Description | National Digital Twin Programme CLimate Resilience Demonstrator |
Amount | £1,000,000 (GBP) |
Organisation | Department for Business, Energy & Industrial Strategy |
Sector | Public |
Country | United Kingdom |
Start | 03/2021 |
End | 03/2022 |
Description | Network DC - Strategic Innovation Fund Beta stage |
Amount | £7,000,000 (GBP) |
Organisation | Ofgem Office of Gas and Electricity Markets |
Sector | Public |
Country | United Kingdom |
Start | 08/2023 |
End | 09/2026 |
Description | THERMAL - Ofgem Network Innovation Allowance under NGET |
Amount | £1,000,000 (GBP) |
Organisation | Ofgem Office of Gas and Electricity Markets |
Sector | Public |
Country | United Kingdom |
Start | 03/2024 |
End | 07/2025 |
Description | Amy Wilson presentation at ISBA |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Presentation at International Society for Bayesian Analysis on statistical model emulation with limited model runs |
Year(s) Of Engagement Activity | 2018 |
Description | Amy Wilson seminars to government |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | Seminars to BEIS OR and energy groups |
Year(s) Of Engagement Activity | 2016 |
Description | BEIS Digital Twin steering group |
Form Of Engagement Activity | A formal working group, expert panel or dialogue |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | Member of advisory group for a Business, Energy and Industrial Strategy-funded pilot project at Energy Systems Catapult |
Year(s) Of Engagement Activity | 2021,2022 |
Description | Blog article on energy modelling |
Form Of Engagement Activity | Engagement focused website, blog or social media channel |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Policymakers/politicians |
Results and Impact | Blog article on good modelling practice, as part of a University of Edinburgh series relating to the Scottish Government's energy strategy |
Year(s) Of Engagement Activity | 2017 |
URL | http://blogs.sps.ed.ac.uk/global-environment-society-academy/2017/05/22/energy-systems-modelling-mod... |
Description | Chris Dent and Amy Wilson presentations on capacity markets and uncertainty quantification at the Isaac Newton Institute Mathematics of Energy Systems programme |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | Presentations to mixed audience of researchers, industry and policy - part of origin of subsequent consultancy work on decision support for energy network planning. |
Year(s) Of Engagement Activity | 2019 |
Description | Chris Dent tutorial talk at N American Electricity Reliability Corporation Probabilistic Analysis Forum |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | Invited talk at major N American workshop on resource adequacy assessment |
Year(s) Of Engagement Activity | 2019 |
Description | GO Science masterclass |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | Invited "Masterclass" by Chris Dent on modelling in public policy to the Government Office of Science Data Science Stream |
Year(s) Of Engagement Activity | 2018 |
Description | Hailiang Du Seminar talk at JHU |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Postgraduate students |
Results and Impact | Seminar presentation, "Uncertainty Quantification for Complex Systems", Department of Environmental Health and Engineering at Johns Hopkins University, July 2017 |
Year(s) Of Engagement Activity | 2017 |
Description | ICMS Energy Systems Workshop |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | Scoping workshop on mathematical science research needs in management of energy systems. Linked to Isaac Newton Institute programme on Mathematics of Energy Systems in 2019. |
Year(s) Of Engagement Activity | 2018 |
URL | http://www.icms.org.uk/energynetworks.php |
Description | Invited presentations in 2020-21 |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Industry/Business |
Results and Impact | Invited presentations to - International Conference on Probabilistic Methods Applied to Power Systems - Energy Regulators Regional Association - Cambridge Society of Edinburgh - European Union Agency for the Cooperation of Energy Regulators |
Year(s) Of Engagement Activity | 2020 |
Description | KTN Energy Study Group, Edinburgh, December 2018 |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Industry/Business |
Results and Impact | Brainstorming session between mathematical scientists and five industry/government challenges |
Year(s) Of Engagement Activity | 2009,2018 |
URL | http://www.icms.org.uk/KTN_Energy_SG.php |
Description | Schools outreach by Amy Wilson |
Form Of Engagement Activity | Participation in an activity, workshop or similar |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Schools |
Results and Impact | - Speaker at UK mathematics trust maths circle event, May 2015, Hutcheson's school Glasgow. - International Women in Engineering day, 23/6/2016 - went to Whitworth Park school in Durham to talk to students about being a female in STEM. |
Year(s) Of Engagement Activity | 2015,2016 |
Description | Seminar and research discussions at NREL |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | International |
Primary Audience | Professional Practitioners |
Results and Impact | Presentation and research discussions at National Renewable Energy Laboratory in Denver, CO, developing common interests in resource adequacy assessment and energy system modelling. Particular topics under energy system modelling are the incorporation of operational constraints into planning models, and uncertainty quantification in plannign models, linking to the Future Conventional Power project. |
Year(s) Of Engagement Activity | 2019 |
Description | Seminar at Ofgem on capacity markets and decision support, by Chris Dent, Amy Wilson and Stan Zachary |
Form Of Engagement Activity | A talk or presentation |
Part Of Official Scheme? | No |
Geographic Reach | National |
Primary Audience | Policymakers/politicians |
Results and Impact | Seminar at energy regulator. Part of series of events leading to consultancy on decision support for network planning. |
Year(s) Of Engagement Activity | 2019 |