Optimal Capacity Allocation in Electricity Industry in accordance with Renewable Energy Sources: The US Case

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2021-3-15

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Gölbaşı, Umut

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Electricity generation cost and environmental effects of electricity generation continue to be among central themes in energy planning. The choice of electricity generation technology and energy source affect the environment through released greenhouse gases and other waste. United States is the worlds second-largest CO2 emitter and electricity consumer. This thesis aims to estimate the optimal capacity expansion of electric power sector in the United States for 2022-2050. We develop a fuzzy multi-objective linear program to minimize cost and environmental effects. In sensitivity analyses, we show how different policies and price evolution may alter the mix. Later on, we examine the effects of the new capacity mix and implied generation on the cost of electricity and emissions. We find that direct modeling of capacity factors give meaningful results. According to this thesis, renewable energy is expected to reach more than 1100 GW installed capacity by 2050. This reduces average cost of electricity generation by more than 70 percent and reduces CO2 emissions by more than 80 percent compared to expected end-2021 levels.

Subject Keywords

Electricity system, fuzzy sets, multi-objective programming, capacity expansion, variable renewable energy

URI

https://hdl.handle.net/11511/90042

Collections

Graduate School of Applied Mathematics, Thesis

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Citation Formats

U. Gölbaşı, “Optimal Capacity Allocation in Electricity Industry in accordance with Renewable Energy Sources: The US Case,” M.S. - Master of Science, Middle East Technical University, 2021.