Mini Modelling Series

Energy Systems Analysis. Mini-Modelling Series

At the Energy System Analysis group in the System Analysis Division, we aim to provide open source energy system analysis tools and analyses to the benefit of society. Our two main modeling tools are TIMES and Balmorel, but we also develop other modeling tools to support the analyses. We will present some of these tools at a number of small seminars, which are open to interested parties.
Please check this homepage for updates on more seminars and check our model homepage with links to the modeling tools and descriptions http://www.esymodels.man.dtu.dk/

Thursday 25 April 2018, 13-14, Building 426, Common Room, downstairs
Amalia Rosa Pizarro Alonso “My Balmorel toolbox”
Frequently used energy systems models have a limited flexibility with regards to representation of conversion pathways (e.g. Balmorel) or flexible spatial and temporal dimensions (e.g. TIMES). In order to overcome some of these drawbacks, and to benefit from the graphical thinking provided by network optimization, the OptiFlow model has been developed. OptiFlow is a generalized network flow model that represents any kind of network with a flexible spatial and temporal resolution, including resource transportation. OptiFlow is a data-driven model, which optimizes simultaneously the topological network design of a resource use under scarcity and competitive uses. It calculates preferred conversion pathways as well as dimensioning and operation of different technologies for its transformation and storage, subjected to defined boundary conditions, such as the surrounding energy system (through linkage or integration with Balmorel), specific market conditions or political goals. OptiFlow has been applied to represent biomass and waste value chains (combustible waste, straw, RE-gas production) and it is being applied to model cascading hydropower flows. 
Long-term energy systems analysis look into how the future could unfold, nonetheless assertions cannot be attested or verifiable, as the future is a field of uncertainty. During my research, I developed a framework to deal with a large number of uncertain parameters when using the Balmorel model for long-term energy planning, without constituting a computational burden and keeping the optimization as deterministic: global sensitivity analysis with Morris screening, followed by an uncertainty analysis with Monte Carlo and Latin Hypercube sampling. The aim of this framework is twofold: 1) Provide robust solutions from energy systems models to decision-makers, and 2) Identify the parameters that affect the most to the uncertainty of the desired outputs, which could represent the most efficient ways to reduce it, e.g. allocating research resources or prioritizing specific policies.
Other topics for discussion: modelling of economy of scale in Balmorel (binary vs. SOS2 variables) and linkage of the models TIMES-Balmorel-OptiFlow.

Thursday 7 June 2018, 13-14, Building 426, Common Room, downstairs.
Stefan Petrovic, " The Heating Model - A highly disaggregated model for potentials and costs of heat savings in the Danish building stock"  
Short abstract: The Heating Model is a heat loss model which has several functions:
1. Calculating existing demand for space heating and domestic hot water and adjusting it to statistics and/or local conditions. 
2.  Calculating potentials and costs of heat saving measures.
3. Approximating potentials and costs of heat saving measures and feeding them into one of energy system models.
4. Making projections of future heating demand based on the assumptions regarding renovation, construction and demolition rates.
5. Visualizing and geographically representing results in GIS-based tools.
The workflow of the model is presented in the figure below


Pertrovic Heat Model

The presentation will discuss the methodology behind the model, examples of previous applications and on-the-spot demonstration of potential applications. Finally, there will be room for questions and discussions. HeatingModel DTU 07-06-2018.pdf

Tuesday 12 June 2018, 14:30-15:30, Building 426, Common Room, downstairs.
Giada Venturini,
"Participatory perspective on scenario development – introducing the TIMES-DK scenario interface"
Public participation in the generation of future scenarios binds together communities in creating shared pictures about the future. Furthermore, stakeholders, such as scientists, policy makers and citizens, should be involved in the process of scenario planning to secure impact on policy-making. The creative process of building narrative storylines is explorative and stimulating in nature. It allows investigating future structures in the system under alternative combinations of trends and policies, thus interpreting causal relations and interdependencies. On the other hand, quantitative tools typically model the deterministic structure of the system, thus having the power to enhance the reliability and validity of input assumptions, and to present cumulative and long-term implications of policies. The Danish transport system represents a contextual example of rapid socio-technical transition, within which the co-evolution of several driving forces needs be assessed from an integrated perspective. In this presentation, we investigate the role and potential of a scenario interface tool in supporting the dialogue on future scenarios, thus bridging the qualitative and quantitative aspects of scenario creation. Presentation.

Wednesday 13 June 2018, 14-15, Building 426, Common Room, downstairs.
Juan Gea Bermudez. "The IPAT(D) tool: A simple model to illustrate the impact of population, affluence, technology and diet in climate change".
The equation I=P*A*T which combines population (P), affluence (A) and technological eco-intensity factor (T), has been known since Ehrlich and Holdren presented it in 1971. This equation aims to show that reducing climate change by means of only reducing T may be incredibly difficult if no measures are taken in the other two factors, i.e. P and A. In our version we have extracted diet (D) as a separate impact and therefore the equation I=PAT(D). The ecological impact is represented by CO2e emissions and the global concentration level is translated into mean global temperature increase until 2100. The impacts are tracked on 16 different regions of the world and equality within population growth and affluence can therefore be investigated. The ecological footprint is also tracked based on data from www.footprintnetwork.org and illustrates how much area is needed to maintain a sustainable production of food and energy to cover the global demand. The result is how many earths are needed with a given level of consumption. The results of the tool can be accessed in https://ipat.tokni.com/
Duration: 1 hour including questions.

 

Contact

Marie Münster
Professor MSO
DTU Management
+45 46 77 51 66