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Effects of Climate Change on the Power System: A Case Study of the Southeast U.S.

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thesis
posted on 30.03.2020, 21:37 by Francisco Ralston FonsecaFrancisco Ralston Fonseca
The U.S. power sector faces several vulnerabilities due to climate change. On the demand side, increasing temperatures may result in shifting electricity consumption patterns and increase need for energy. On the supply side, changes in air temperatures, water availability, and water temperatures could reduce the capacity and effi?ciency of thermal units, which currently represent 85% of generating capacity. Previous studies that analyze climate change effects in the power sector have mostly focused on analyzing these risks separately. Further, studies in the supply side risks usually looked only at eff?ects of climate change only in existing thermal generators. However, such studies fail to capture how these demand and supply risks interact with each other and with the operation of the power grid in general. In order to analyze these risks in more detail, it is important to integrate them into system-wide assessments. Such assessments should take into account the
economic dispatch of the complete generator effect and future economic decisions to expand this effect. This dissertation attempts to understand how climate change will aff?ect the power sector in the U.S. We implemented an integrated framework where we use di?fferent modeling
methods to represent the diff?erent risks the power sector faces due to climate change. We used our modeling framework in a case study of the SERC Reliability Corporation (SERC), one of eight regional electric reliability councils under North American Electric Reliability Corporation authority (NERC). Firstly, we used an econometric model to estimate changes in hourly electricity demand due to climate change. We used this model to analyze changes hourly electricity demand patterns in the Tennessee Valley Authority (TVA) region for diff?erent seasons of the year. Our results suggest that climate change could result in an average increase in annual electricity consumption in the TVA region. However, this increase was not uniformly distributed throughout the year. During summer, total electricity consumption could increase
on average by 20% while during winter it may decrease on average by 6% by the end of the century. Secondly, we combined the estimates of future hourly electricity demand described in Chapter 2 with simulations of decreases in available capacity of thermal generators due to climate
change. We integrated these simulations in a capacity expansion (CE) model. This CE model is a mixed integer linear programming (MILP) model that we adapted and developed for this study. It fi?nds the composition of the future generator effect that minimizes costs subject to the estimated eff?ects of climate change. We ran this model under different climate change scenarios from 2020 to 2050. Our results showed that by including these eff?ects due to climate change in the decision making process, the estimated participation of renewables in the generator
effect in 2050 increased from 24% to over 37{40%. Solar power plants could become more economically attractive. As they have higher energy output during the summertime, they could help to o?set the climate-induced loss of thermal capacity during this season because of higher air and water temperatures. Thirdly, we simulated the operation of SERC's power system assuming the diff?erent scenarios and generator effects presented in Chapter 3. To accomplish this, we used a unit commitment and economic dispatch (UCED) model. The UECD model is a mixed integer
linear programming (MILP) model that we adapted and developed for this study. We used this model to investigate the tradeo?s between investing or not in the generator
effect assuming diff?erent climate change scenarios. Our results suggest that by not including climate change eff?ects in the planning stage, SERC's power system could experience loss of load levels of 12% and overall energy costs could be 260% higher if climate change conditions do materialize by 2050.

History

Date

18/03/2020

Degree Type

Dissertation

Department

Engineering and Public Policy

Degree Name

  • Doctor of Philosophy (PhD)

Advisor(s)

Paulina Jaramillo