# Energy Sector Development: System Dynamics Analysis
## 2 Research Method  
### Formulating a Simulation Model  
A system dynamics model of the Australian energy sector is developed based on the causal loop diagram (CLD) designed in [PERSON] et al. [1]. In this research, CLD was used to describe the dynamics underlying interactions between constituent components of the sector. The limitation of this powerful qualitative tool is that it cannot be used to quantitatively simulate the dynamics of the energy sector over time. We have developed a stock-flow model (SFM) of the energy sector that enables an in-depth investigation of the dynamics of the Australian energy sector. The key components of the SFM are stocks, flows and auxiliary variables. The stocks represent variable accumulation or depletion over time, stock change is through flow into or out of the stock, and these mechanisms lead to feedback which can cause changes (accelerate or balance out); the feedback comes in two forms: positive (reinforcing feedback) arises when growth of a stock causes change leading to further growth of stock; negative (balancing feedback) arises when decline of a stock causes change leading to further changes to slow down. Stocks change by the flows, while stocks and auxiliary variables control the flows. Feedback loops in Figure 1a are taken from [PERSON] et al. [1], which contains two reinforcing loops (R1 and R2), and two balancing loops (B1, B2). Loops R1 and R2 are the inflows; they represent the rate at which new capacity--after a construction delay--comes on-stream. This adds to the total energy production capacity of the Australian energy sector. Loops B1 and B2 are the outflows, reflecting the total decline of both capacities resulted from capacity bankruptcy and capacity retirement. These outflows eliminate unprofitable and retired capacity from the total energy production capacity of the Australian energy sector. Figure 1b is an SFM that translated from CLD Figure 1a. In this example,energy production capacity is the stock; new renewable energy (RE) capacity and new non-RE capacity are the inflows; capacity retirement and capacity bankruptcy are the outflows; construction delay, unprofitable capacity and capacity lifespan are the auxiliary variables. The translation of other feedback loops to SFMs that were contained in [PERSON] et al. [1] went through the same process. However, not all feedback loops were translated due to data unavailability. Only feedback loops that are highlighted in Figure 2 were converted to our SFM. Our SFM was run during the period 1990-2050 (a 61-year time period), and the following parameter values are required to run simulations. These values include initial (e.g., initial energy production capacity) and constants (e.g., construction delay). Equations were also used to parametrise variables in the SFM (e.g., capacity retirement = energy production capacity/capacity lifespan). Furthermore, what if functions were used (e.g., if \"surplus or shortfall\" > 0 then \"energy production capacity\" * (1 -\"surplus or shortfall\"/100) else \"energy production capacity\"). The different forms of energy were put into the same unit: gigawatt-hour (GWh), in which one gigawatt is one billion watts. It is a unit that represents the energy used or the energy production capacity, and we used it to express all energy resources. This is used by many sources and it is the scientific way to compare and summarize energies [27]. In addition, Australian Energy Update, the Commonwealth of Australia annual report uses the same unit (PJ) for different forms of energy production, consumption and trade. It is important to remember that, after all, fossil fuels run out, GWh will be the dominant energy unit. Figure 1: Feedback loops (**a**) and stock-flow model (**b**). In this study, we divide energy resources into dispatchable resources (continuous resources) (coal, oil, gas, hydropower, biopower) and non-dispatchable resources (discontinuous resources) (wind and solar).