Applying Spatial Downscaling and Smart Persistence to Provide an Improved Solar Forecast to Reduce Commercial Demand Charges

Commercial PV is an appealing way to reduce electricity costs, however due to the variable nature of PV power and the larger power needs of most commercial applications, demand charges induced by variable load and PV generation can offset savings of generating electricity on site. This paper will explore options to reduce these demand charge costs through forecast improvements by downscaling variability and smart persistence using real time site observations. This improved forecast will be used by a load control system which will employ strategies such as load shifting to attempt to reduce demand charges.