Ashley Jasso

Defining the Resilience of Stand Alone Microgrids for Rural Applications

This dissertation proposes a general definition of resilience and a methodology for measuring the resilience of standalone microgrids. Standalone microgrids powered by renewable energy are increasingly being hailed as the solution to rural electrification. However, there is a need to address the deep uncertainty in microgrid systems; this dissertation proposes this is best accomplished by engaging in resilience thinking. An ecologist, C.S. Holling, first defined resilience in 1973. Since then, resilience thinking has been applied to a variety of fields, including infrastructure, yet a common definition of resilience is lacking.  Because a common definition is lacking, so too, is a widely used method for assessing, or measuring, resilience also lacking. An additional gap in the resilience literature is that the resilience of standalone microgrids has yet to be specifically addressed. Therefore, this dissertation addresses the following key research questions:

1. What is resilience with respect to standalone microgrids?

2. How can the resilience of a microgrid in El Diptamo, Honduras be measured?

The proposed definition of resilience is ‘the ability of a system to pass through unpredictable, stochastic shock(s) and/or stress with the lowest total cost. A resilient system is one in which system managers are able to learn and adapt to changing system conditions in order to achieve the lowest possible total cost of dealing with shocks and stressors while avoiding total system failure.’The methodologies used to measure resilience include scenario planning, a case study and total cost. Total cost is a new methodology proposed in this dissertation. Scenario planning is applied to a case study of a microgrid in El Diptamo, Honduras, the scenarios are constructed in HomerPRO, and then total cost is used to measure the resilience of the microgrid in eight scenarios. The eight scenarios limit the uncertainty to the effects of climate change and population growth.

The case study results show that the scenario that undergoes the most disturbances has the highest total cost and the scenario that undergoes the least disturbances has the lowest total cost. The results also show that the microgrid in El Diptamo is more resilient when system managers engage in resilience thinking in the planning stage, rather than the operation stage of the microgrid lifecycle. For the microgrid in El Diptamo, the effects of climate change are costlier than the effects of a high population growth rate. The final result of the case study is that the soft costs, defined as the indirect cost of a blackout, are significantly higher than the hard costs, defined as the physical cost of the microgrid. The conclusion is that microgrid resilience can be measured via scenario planning and total cost. Doing so is a valuable addition to the risk management process and can be implemented by development practitioners as well as microgrid operators