The influence of hydroelectric power generation and water level variability on market clearing prices: A case study of Türkiye
The escalating effects of climate change on hydrological patterns and the increasing reliance on renewable energy necessitate more precise electricity price forecasting. This study investigates how hydroelectric power generation influences the Market Clearing Price (MCP) in Türkiye’s electricity mar...
Saved in:
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
|
| Series: | International Journal of Electrical Power & Energy Systems |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0142061525004132 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Summary: | The escalating effects of climate change on hydrological patterns and the increasing reliance on renewable energy necessitate more precise electricity price forecasting. This study investigates how hydroelectric power generation influences the Market Clearing Price (MCP) in Türkiye’s electricity market, with particular attention to seasonal variability and market structure.The core research question addresses whether fluctuations in water levels and hydroelectric output exert a statistically and economically significant impact on MCP formation. To explore this, the study applies a comprehensive methodological framework combining multivariate regression, correlation analysis, impulse response functions (IRF), Granger causality tests, and machine learning models—specifically, Bidirectional LSTM and Stacked LSTM architectures.Findings reveal a weak correlation (R2 = 0.065) between hydroelectric generation and MCP, with no statistically significant causal relationship. IRF analysis indicates that while sudden increases in hydro production can reduce MCP in the short term, the effect diminishes rapidly. Machine learning models incorporating meteorological data outperform traditional methods, achieving improved short-term prediction accuracy.These results suggest that hydropower alone does not sufficiently stabilize prices, primarily due to regulatory constraints (e.g., YEKDEM) and operational limitations (e.g., cascade dependencies). Instead, MCP is more heavily influenced by fossil fuel prices and demand imbalances.Policy implications include the integration of AI-based forecasting tools, improved water resource management strategies, and enhanced coordination of cascade hydro operations. The study underscores the need for diversified, adaptive energy policies in response to climatic volatility and evolving market dynamics. |
|---|---|
| ISSN: | 0142-0615 |