Aurora is ideal for lifecycle analysis and resource capacity expansion optimization studies.
Exceptionally fast, this transmission-constrained model uses market fundamentals to forecast marginal prices in each market zone over long-term planning horizons.
- Estimate price and dispatch using hourly demands
- Chronological dispatch algorithm
- Determine the economic value of each unit over time
- Optimize expansion capacity across all zones
- Construct new zones and consolidate multiple zones easily
- Gain greater understanding of resource options under various conditions
With its advanced logic, Aurora uses market economics to determine the long-term resource capacity expansion mix under varying future conditions including fuel prices, available generation technologies, environmental constraints, and future demand forecasts. Its recursive optimization process identifies the set of resources among existing and potential future resources with the highest and lowest market values to produce economically consistent capacity expansion and retirement schedules. Test Renewable Resource Standards (RPS) under the future conditions simulated.
- Solves interdependencies between prices and changes in resource schedules
- Quickly determines the optimal expansion plan for an entire system
- Factors in price-induced curtailments
Back to Aurora
- Marginal prices calculated for each hour by market zone
- Supply stack generated for each market zone
- Simultaneous whole system dispatch
- Fast, proprietary dispatch algorithms
- Forward-looking market valuation
- Unlimited definition of supply alternatives, including vintage technologies
- Constraints for rate of construction and retirements
- Build to meet planning reserve margin targets
- Calculates capacity prices
- Captures the effects of emissions on plant operations and costs