## 1 Introduction
### Intra-Hour Solar Forecasting
[30] proposed DNI forecasting models using images from a Yankee TSI 880 with hemispherical mirror as inputs to Artificial Neural Networks (ANN). The TSI has high capital and maintenance costs, uses a shadow band mechanism, and requires proprietary software. The UCSD Sky Imager described in [PERSON] et al. [31] captures images with an upward-facing charge-coupled device (CCD) Panasonic sensor and a 4.5 mm focal length fisheye lens. Compared with the TSI it has higher resolution, greater dynamic range, and lossless PNG compression. The Universitat Erlangen-Nurnberg [32] group used a five-megapixel C-mount camera equipped with a fisheye lens. They implemented the Thirions \"'daemons\"' algorithm for image registration and cloud-motion estimation similar to optical flow. In Australia, [PERSON] et al. [33] used off-the-shelf IP security cameras (Mobotix Q24, Vivotek FE8172V) for all-sky imaging. Inexpensive compared to the TSI, the cost of such systems still is ~800 euros. Rather than a feature-tracking strategy, they used dense optical flow to estimate cloud movement. See also [PERSON] [34]. Several research groups in China are working on the irradiance forecasting problem [35; 36] generally using a TSI imager, but in one case Geostationary Statellite data [37]. As mentioned before dramatic improvements in GOES-R technology and resolution (spatial and temporal) will make this approach more attractive for intra-hour forecasting. See also the historical review [38] of irradiance and PV power forecasting that was produced using text mining and machine learning. A recurring theme in the INTEGRATE project was that while all-sky imaging was a critical component of microgrid stability and control, it could not be developed in a stand-alone fashion but must be fully integrated into the microgrid management system (MGMS). [PERSON] et al. [39] discuss the importance of Ramp Rates (RR) on the inertial stability margin of a microgrid deployed at the Marine Corp Base at Twentynine Palms. They show that a large ramp in PV power can destabilize frequency when the PV load is suddenly transferred to the cogen. The inertia constant \(H\) of a generator is the ratio of stored kinetic energy to system capacity. Microgrids usually have \(H\) < 1 s compared to 2-10 s for large generation plants. Frequency stability is defined by the condition \(\left|\Delta f_{pu}\right|<\Delta f_{max}^{pu}\) where allowable frequency deviation \(\Delta f_{max}^{pu}\) in p.u. is typically 0.01-0.05 per unit. In [39] the authors derive the ODE \(\omega_{mech}\mathrm{d}\omega_{mech}/\mathrm{d}t+\omega_{mech}^{2}\mathrm{D}= P_{accel}\) where \(\omega_{mech}\) is the mechanical speed of the generator in rad/s, J the moment of inertia (kg:m\({}^{2}\)), D a damping coefficient (Nm/s), and P\({}_{\mathrm{accel}}\) the power imbalance exerted on a generator rotor, to model the microgrid stability control problem. The NREL microgrid has a 300 kW Caterpillar diesel generator, whereas JBSA has no cogen. However, the same issues of stability and frequency control apply when there are no spinning resources. Some electric  
Figure 4: Relationship between GHI (W/m\({}^{2}\)) and PV Power (Watts) determined at NREL. codes are specifying ancillary control must be added to the EMS in order to handle ramp events of a certain magnitude and duration. See [40; 41; 42] for details.