System dynamics archetypes for capacity management of energy systems

Energy systems are increasingly becoming more and more complex due to dynamic interactions of various supply-demand related variables in the systems. These variable interactions and the underlying feedback loop structures contribute to the realized overall system behavior. As a result, managing the capacity of energy systems is a complex task. The purpose of this paper is to present typical system dynamics archetypes for capacity management of energy systems. First, two archetypes are identified and modelled based on causal loop analysis: (i) limit to growth, and (ii) growth and underinvestment. The archetypes help the analyst to effectively visualize the entire system and forecast the reaction of the system. Second, stock flow analysis models are then presented. Third and finally, "what-if" simulation experiments are conducted to illustrate the key effects of limited capacity growth as well as growth with and underinvestment in the presence of time delays. The study demonstrates the importance of taking a systems thinking approach when managing the capacity of complex energy systems. Feedback loops and time delays must be considered seriously. By so doing, unwanted and unpredictable system fluctuations can be avoided when making capacity adjustment decisions.