FRAMEWORK FOR IDENTIFYING OPTIMAL RISK REDUCTION STRATEGIES TO MINIMIZE THE ECONOMIC IMPACTS OF SEVERE WEATHER INDUCED POWER OUTAGES
thesisposted on 29.07.2020, 21:10 by Arkaprabha Bhattacharyya
Every year power outages cost billions of dollars and affect millions of people. Historical data shows that between 2000 and 2016, 75% of power outages (in terms of duration) were caused due to severe weather events. Due to climate change these severe weather events are becoming more frequent. The National Association of Regulatory Commissioners have recently emphasized on the importance of building electricity sector's resilience thus ensuring long term reliability and economic benefits for the stakeholders. These severe weather events are called High Impact Low Frequency (HILF) events, which means that these events may not occur every year, but when they happen, the impact is likely to be severe. So, it is imperative that the risk of power outages due to severe weather events and their economic impact is persistent. To mitigate the risk, utilities need to invest heavily so that the impacts due to these HILF events can be minimized. Under this situation, utilities face three key questions (1) where to invest (2) how much to invest and (3) how to justify the investment. Therefore, there is a need to develop a framework for investment related decision-making, which can identify the optimal strategies for minimizing the economic impacts of severe weather induced power outages under different budget conditions. It is equally important to understand the cascading impacts of the sustained power outages during natural disasters before investment can be planned for building resilience in electricity sector. The existing frameworks to access the costs of severe weather induced power outages grossly undermines the overall economic impacts. This research has (1) assessed the economic loss due to severe weather induced power outages in terms of loss of Gross Domestic Product (GDP) and (2) developed a framework for identifying the optimal risk reduction strategies to minimize the economic impact. For assessing the economic impact, this research has adopted Inoperability Input-Output Model (IIM) using 20 years of historical data from the Bureau of Economic Analysis (BEA). The proposed framework has the flexibility to accommodate the risk appetite of the decision maker. The framework can be used by the Investor Owned Utilities (IOUs) for the rate approvals from the State Utility Regulatory Commissions by justifying the importance of their resilience building projects to the State's economy.