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Türkiye elektrik piyasasına katılan bir rüzgar çiftliği için optimal BESS kapasitelendirmesi ve operasyon planlaması

2024
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Advisor: Doç. Dr. Mevlüde Ebru Angün ; Doç. Dr. Kemal Sarıca

Abstract (EN)

In today's electric system, where decentralization, democratization, and decarbonization are gaining in importance, battery energy storage systems (BESSs) are frequently used for intermittent energy sources such as wind and solar while participating in markets that have price fluctuations and imbalance costs. In this study, an onshore wind farm in Türkiye with an installed capacity of 24 MW that benefits from the Renewable Energy Resources Support Mechanism (YEKDEM) tariff is examined and an incentive scenario for renewables is suggested. Three market participation cases, Cases 1, 2, and 3, are analyzed for the farm. Case 1 represents participating in day ahead market (DAM) by leaving YEKDEM while Cases 2 and 3 represent participating in DAM with actual and suggested YEKDEM tariff, respectively. This thesis presents a nonlinear optimization model (NLP) including battery degradation cost to determine optimal BESS capacity and operation for different participation cases. Scenarios generated with various depth of discharge (DOD) limit values, determination methods of committed energy amount in DAM and BESS cost projections are solved by IPOPT solver in GAMS. According to obtained results, under current BESS cost, BESS integration increases farm's profit compared to system without BESS for each market participation case. However, some scenarios are observed where farm's profit cannot be increased with BESS. Considering the analyses, DOD limit value of 0.3 enhances profit more than other examined DOD limits. When profits obtained by BESS integration under same scenario for three participation cases are evaluated, Cases 3 and 2 yield the highest and lowest profit, respectively.

Author

Dr. Ümmügülüsüm Erdağı

How to Cite

Ümmügülüsüm Erdağı (Master Thesis). Türkiye elektrik piyasasına katılan bir rüzgar çiftliği için optimal BESS kapasitelendirmesi ve operasyon planlaması, 2024, Galatasaray University.

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