dc.contributor |
Graduate Program in Industrial Engineering. |
|
dc.contributor.advisor |
Korugan, Aybek. |
|
dc.contributor.author |
Gül, Aykut. |
|
dc.date.accessioned |
2023-03-16T10:30:08Z |
|
dc.date.available |
2023-03-16T10:30:08Z |
|
dc.date.issued |
2021. |
|
dc.identifier.other |
IE 2021 G85 |
|
dc.identifier.uri |
http://digitalarchive.boun.edu.tr/handle/123456789/13446 |
|
dc.description.abstract |
Renewable energy sources (RES) are expected to be dominant in near future. However, RES suffer from unavailability and intermittency that causes unreliable energy output due to daily or hourly weather conditions. (Liserre et al., 2010) As the share of renewables increases, electricity systems must gain more flexibility and reliability. Battery energy storage systems (BESS) stand as powerful tools to accelerate transition to sustainable energy. They can help reducing the variability between electricity generation and consumption by storing the excess energy at off-peak period and discharging the energy at peak periods. (Beltran et al., 2013) We considered a hypothetical question on the efficiency of wind power. We coupled wind power generation with BESS to see the impact of storage capacity on this problem. Our ultimate goal is to provide efficiency of wind power using storage. We aimed to determine the hourly optimal storage capacity for one year to utilize wind more and obtain smooth electricity production in national scale. We developed an optimization model that analyzes the system on hourly basis. We modeled BESS as inventory of energy. Using national data, statistical models were developed to capture the uncertainty of both wind energy and demand. We fitted probability distributions for both energy supply and demand. Using probability distributions, we generated different datasets that reffect the hourly energy supply and demand. We ran the optimization model with all possible combinations of supply and demand pairs. This way, we achieved the robustness in optimal storage capacity, utilization level of wind turbines and other resources. The analysis was extended to various scenarios considering different system configurations. |
|
dc.format.extent |
30 cm. |
|
dc.publisher |
Thesis (M.S.) - Bogazici University. Institute for Graduate Studies in Science and Engineering, 2021. |
|
dc.subject.lcsh |
Renewable energy sources. |
|
dc.subject.lcsh |
Energy storage. |
|
dc.subject.lcsh |
Wind power. |
|
dc.title |
Analyzing the impact of energy storage capacity on renewable energy generation using wind power :|the case of Turkey |
|
dc.format.pages |
xviii, 116 leaves ; |
|