Hydropower Future: Between Climate Change, Renewable Deployment, Carbon and Fuel Prices
Abstract
:1. Introduction
2. Materials and Methods
2.1. The Hydrological Model
- Series of daily precipitation and temperature from the weather station(s) considered for the study basin. A pre-processing routine corrects measurement errors like snow plugging or wind-induced under-catch [59];
- Data terrain model (DTM) to evaluate the catchment area and extrapolate the hypsometric curve for the subdivision in elevation bands;
- Curve Number of the basin (CN);
- Average long-term temperatures to compute the evapotranspiration (ETP);
- Degree day parameters of the snow. They are calibrated using recorded daily temperature and processed solid precipitation series, minimizing the root-mean-square error (RMSE) (mm) by comparing values of simulated and real values of snow water equivalent (SWE).
2.2. The Hydropower Management Model
2.3. Future Scenarios
- Future-like-present (climate scenario 1): This reference allows us to evaluate the effect of climate change simulated with the other scenarios. We randomly extracted years of precipitation and temperature series from the historical data. This preserves the intra-year dependence, but not inter-year dependence [26]. The extraction is repeated 100 times to assess the uncertainty associated with the future scenarios.
- Warmer-future (climate scenarios 2–4): These scenarios assess the impact of warmer temperature only and neglect any trend in precipitation associated with a warming climate [67,68,69]. We modelled three rates of temperature increase: +0.03, +0.06 and +0.09 °C/year. Please note that the +0.03 °C trend is consistent with the Intergovernmental Panel on Climate Change (IPCC) Fifth Report scenario RCP8.5 [14]. Uncertainty is simulated by randomly extracting 100 series of precipitation and temperature which increase according to each trend.
- Liquid-precipitation-future (climate scenario 5): this scenario set up an extreme climate warming future for snow-dominated catchments. All the precipitation is assumed to be liquid, neglecting temperature trends. The procedure to generate uncertainty uses a Monte Carlo technique as done in Bongio et al. [26].
- Mixed scenarios (climate scenarios 6–8): these scenarios consider the combined effects of variations in temperatures and precipitation regimes. For each of these, 100 series of temperature and precipitation are extracted and then precipitation is assumed to be all liquid. Finally, all three temperature trends mentioned in the warmer-future scenarios are applied.
2.4. Case Study and Data
3. Model Calibration and Validation
3.1. Calibration and Validation of the Hydrological Model
3.2. Validation of the Management Model
4. Future Scenarios: Results and Discussions
4.1. Climate Change Effects on Flow Regimes
4.2. Impact of Climate Change on the Hydropower Plant
4.3. Impacts of Electricity Price Scenarios
4.4. Mixed Scenarios
5. Conclusions
Supplementary Materials
Author Contributions
Funding
Acknowledgments
Conflicts of Interest
References
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Scenario | Explanation |
---|---|
EU Reference Scenario (Scenario 1) | As in EU Energy Trends 1 |
Base Price 2015 Scenario (Scenario 2) | Carbon or fuel prices supposed to be equal to 2015 |
C+ (Scenario 3) | Slow increase of carbon price (35 €/t in 2030) |
C++ (Scenario 4) | Fast increase in carbon price (50 €/t in 2030) |
F+ (Scenario 5) | Slow increase in fuel price (+50% until 2030) |
F++ (Scenario 6) | Fast increase in fuel price (+100% until 2030) |
R+ (Scenario 7) | Stronger increase in wind and solar (+10% relative to EU Trend) |
R− (Scenario 8) | Weaker increase in wind and solar (−10% relative to EU Trend) |
Combinations (Scenarios from 9 to 28) | Combination of all the scenarios |
Tremorgio Basin and Power Plant | |
---|---|
Catchment area (km2) | 5.07 |
Glacier coverage (%) | 0 |
Maximum elevation (m a.s.l.) | 2635 |
Minimum elevation (m a.s.l.) | 1830 |
Reservoir volume available (Mm3) | 5.54 |
Maximum reservoir elevation (m a.s.l.) | 1830 |
Minimum reservoir elevation (m a.s.l.) | 1800 |
Power plant elevation (m a.s.l) | 950 |
Maximum discharge (m3/s) | 1.6 |
Type of turbine | Pelton |
Power installed (MW) | 10 |
Efficiency (-) | 0.75 |
n | kliq (days) | ksnow (days) | kbase (days) | DDFmin (mm/d°C) | DDFmax (mm/d°C) | TLR (°C/100 m) |
---|---|---|---|---|---|---|
3.5 | 0.06 | 18 | 14 | 1.05 | 3.35 | 0.58 |
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Ranzani, A.; Bonato, M.; Patro, E.R.; Gaudard, L.; De Michele, C. Hydropower Future: Between Climate Change, Renewable Deployment, Carbon and Fuel Prices. Water 2018, 10, 1197. https://doi.org/10.3390/w10091197
Ranzani A, Bonato M, Patro ER, Gaudard L, De Michele C. Hydropower Future: Between Climate Change, Renewable Deployment, Carbon and Fuel Prices. Water. 2018; 10(9):1197. https://doi.org/10.3390/w10091197
Chicago/Turabian StyleRanzani, Alessandro, Mattia Bonato, Epari Ritesh Patro, Ludovic Gaudard, and Carlo De Michele. 2018. "Hydropower Future: Between Climate Change, Renewable Deployment, Carbon and Fuel Prices" Water 10, no. 9: 1197. https://doi.org/10.3390/w10091197