Modelling Approach and Summary

This chapter contain details of the efficient development of SD models and the modelling process.

Also highlighted, are the key examples applicable and details of the case study for this thesis.

Sterman (2000) cautioned that while there are certain key steps for modelling, it is not a cookbook procedure, but rather it is fundamentally a creative, disciplined, iterative and rigorous process. The approach used in this thesis is to develop multiple sub-models to emulate different aspects of the system and then to synthesise these sub-models into a single comprehensive model. A well-established approach was followed where greater in-depth learning can be achieved using an approach of smaller models to better demonstrate ab initio the dynamic behaviour of the system structure (Dyner, 1996; Shepherd, 2014).

The case study of this thesis work was initially analysed to assess whether it encompasses key drivers to the evolution of low-carbon electricity systems. Additionally, the process of scenario planning, as detailed in (Lindgren and Bandhold, 2009) was initially used to formulate different possible and probable paths of evolution of the case study island system. Subsequently, a mental model (as shown in Figure 3.4) was proposed to develop a theory of the behaviour of the system over time. This mental model was a direct consequence and driven by the fact that; CO2 emissions and energy security (fossil fuel import independence) in the future will be a problem so more renewable and less fossil fuel generation is needed within the electricity system. Then, the system variables that are directly relevant to this problem statement were listed within the description of the different sub-models and these variables were determined to be endogenous, exogenous or excluded from the modelling process. Over the course of this process, and for the different sub-models some variables were added or dropped as needed in the mental model descriptions of Chapters 4, 5 and 6.

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Three independent sub-models were developed over the course of this research work and then they were integrated into a single comprehensive model. The first sub-model developed was a fossil sub-model, which assumed an island system that has no renewables policy and accounts for endogenous fossil fuel capacity based on exogenous fossil fuel prices, electricity demand and renewables capacity. A mental model and the model formulation details were developed for this aspect of the system and are shown in Chapter 4. The second sub-model explored other aspects of the system for renewables integration into the system via (cost) learning curves. This sub-model accounted for endogenous renewables capacity, with exogenous electricity demand, renewables policy and fossil fuel capacity. The developed mental model and model formulation details of this sub-model are also shown in Chapter 4. Thirdly, the electricity demand sub-model was developed to capture the endogenous electricity demand within the system. Building on consumption factors such as economic growth, this sub-model emphasises aspects of low-carbon electricity policy factors such as electric vehicles and energy efficiency on the long-term demand. GDP and tourism growth were exogenous to this sub-model, whilst residential population and electric vehicles were endogenous. Details of the developed mental model and the model formulation details are shown in Chapter 5.

Finally, the three sub-models were synthesised into a comprehensive model which accounts for endogenous fossil fuel, renewables and energy storage capacities and electricity demand. The synthesised mental model, which captures the essence of Figure 3.4, but in much more detail along with the synthesised model formulations are explained in Chapter 6. It is important to note that the process of developing the sub-models and the final synthesised model was an iterative and lengthy process with numerous trial mental models in which many of those mental models were discarded.

The feedback "loop" structures representative of the system were then studied and the resulting feedback loops were identified as reinforcing or balancing loops. The guiding concept is that the sub-models and the comprehensive model were built for their specified problem and purpose and they should provide an understanding of the system for this problem.

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Figure 3.6 shows the subsystem architecture (Sterman, 2000 pg. 101) of the synthesised model.

This figure illustrates the key aspects of the different sub-models of the synthesis model. As seen in the figure, the electricity tariff, GDP, tourist visits and technical specifications of electricity generation plants are not endogenous to the system in any of the sub-models and are external to the modelled system. Four key assumptions are made:

(i) We assume that energy choices do not endogenously affect the GDP of São Miguel.

(ii) We do not include the possibility of local technological innovation.

(iii) We exclude the possibility that energy choices drive tourism growth.

(iv) We assume that electricity tariffs charged in the island tends to be unaffected by system investment choices.

All four assumptions of these exogenous factors are contestable. However, others might seek to build upon this work by making some of these exogenous variables endogenous.

Figure 3.6 Overall subsystem architecture diagram for the low-carbon electricity system model

The parts labelled within the diagram will be detailed in the relevant chapters that address the sub-models individually. The next chapter will give the system structure for the fossil and renewables sub-models and the insights gained will be highlighted.

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Chapter 4. Fossil Fuel Generation Futures and