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Project

A Flexible Open-source Modelling Framework to Support Decision Making for Future Energy Systems

Energy system models are used to support decision making regarding the operation and design of energy systems. The transition towards more sustainable energy systems poses new requirements on energy system models. New challenges include representing more uncertainties, including short-term detail in long-term planning models, allowing for more integration across energy sectors, and dealing with increased model complexities.

To address these challenges, this dissertation contributes to the development of a flexible open-source energy system modelling framework, SpineOpt, to perform operational and planning case studies. Noteworthy design aspects of SpineOpt include a generic data structure, flexible temporal and stochastic structures, and model decomposition capabilities to reduce model complexities. Further, SpineOpt encompasses a wide range of features, including technical detail and sector-specific physics. SpineOpt’s functionality is used to address two relevant questions in the context of the operation and design of future energy systems.

Firstly, SpineOpt is applied to investigate the benefits of different levels of coordination of future European reserve markets. Results indicate that exchanging and sharing of balancing capacity lead to a more efficient day-ahead scheduling, while sharing of balancing capacities could potentially also reduce the need for flexible capacity, especially when combined with alternative sources of flexibility such as demand side management.

Secondly, an investment planning case study is performed using SpineOpt, investigating the potential trade-offs between transmission expansion and longterm storage investments, i.e., the trade-off between spatial and temporal smoothing. We use Modelling-to-Generate-Alternatives to explore different nearoptimal solutions. Results suggest that the two technology choices are inversely correlated potentially allowing the deferral or replacement of transmission expansion by long-term storage systems, especially when facing long permitting times or public opposition.

Date:23 Apr 2018 →  9 Dec 2022
Keywords:Energy system modeling, Renewables, modeling toolbox
Disciplines:Manufacturing engineering, Safety engineering, Mechanics, Mechatronics and robotics, Thermodynamics, Electrical power engineering, Energy generation, conversion and storage engineering
Project type:PhD project