Socio-technical implication of renewable energy sources: African health care case study with Monte-Carlo simulations

John Holdren states there are three responses to climate change: mitigation, adaptation, and suffering. Research abounds in framing mitigation and adaptation policies. Furthermore, many suffering criteria exist in the health care literature as a physiological and psychological component to patients´ care, but not in the technological aspects to hospitals. In this paper, the socio-technological challenges of renewable electricity in Uganda are explored to frame the reality of unreliable electricity within a suffering criteria. For this paper, we define suffering criteria as avoidable damage (unmet power load) which is highly dependent on balancing variability and uncertainty. For example, there is a measurable variable solar radiance profile. On any specific day, dispatch microgrid control algorithms consider the measured variability as an uncertainty, but here we define uncertainty as adding random noise to the measured variability using Monte-Carlo simulations. By doing this, we have a renewable energy system defined within a suffering criteria that is clearly illustrated within bounds (no variability, measured variability, and simulated additional variability from uncertainty). Unmet load data is generated using HOMER Energy. This study can help further understand variability and uncertainty in renewable energy sources in hybrid microgrids as it is framed within a suffering criteria - avoidable damage on health care due to unmet power load. It is vitally important due to renewable energy system trade-offs between overdesign (levelized cost of electricity >;$1/kWh) and underdesign (capacity shortage >;50%). It leads to motivations for redundancy in microgrids similar to redundancy in large-scale centralized grids.