From an integration viewpoint, as higher penetrations of renewable energy are deployed onto the grid, the value of forecasting increases, as the costs associated with ancillary services and suboptimal market set up is amplified. This happens because additional intermittent resources are added and need to be balanced in real-time or mitigated by storage processes. Moreover, as the comparative uncertainty of solar power output during peak hours is higher than the uncertainty of wind and hydropower output, the value of solar forecasting is typically higher.
Typically, third-party studies underestimate the total value of high fidelity forecasts as they focus primarily at forecasting from a day ahead, market integration perspective. Currently available commercial state-of-the-art forecasting services are inadequate for addressing short (intra-hour) and very short (<5 minute) time horizons and were not included in most studies and analyses. For example, there are numerous total life cycle costs associated with suboptimal forecasting for solar generators such as penalties and tariffs from grid regulators (ISOs, LSEs); the need to purchase spot market energy at premium pricing when forecasted generation is below PPA amounts; and higher insurance premiums to cover against PPA shortfalls. While the value of high fidelity forecasting has not been quantified against these life cycle costs, these benefits are particularly significant to reduce the overall cost and increase penetration of utility scale solar generation.
Additionally, intra-hour forecasting is especially valuable for utility scale renewable generation to control fast ramp rate events. In the case of solar, fast ramp rate event changes in power production can exceed 60%-80% over one-minute time horizons. This presents numerous challenges for integrating high levels of utility scale solar generation onto the grid in terms of power and frequency stability, such as increased curtailment and generation costs, scheduling and dispatch of additional energy resources. High fidelity forecasting can mitigate these problems through integration of short and medium term horizons to prospectively determine optimal ramp rate strategies.
For utility scale power generators, forecast-driven critical ramp rate strategies can provide the backbone to a robust, automated energy management system that increases operational efficiencies though optimized scheduling and dispatch, management of reserves and, most importantly, lucrative participation in energy markets.
Managing critical ramp rates are also of critical importance to ISOs for planning and operations, with variations in short term solar output adversely impacting power and frequency stability of the grid. While substantial adjustment tolerance is already built in to most power networks, voltage and frequency fluctuations are amplified as higher penetrations of intermittent generation are brought online, increasing the potential for grid instability.
Forecast Energy, Inc. is