Smart Grid Consortium offers utility photovoltaic forecasting models

PV forecasts are designed both to assist utility distribution planners and to provide a program evaluation tool

Content Dam Elp Online Articles 2015 June Solar Photovoltaic 2 Elp

The Smart Grid Research Consortium (SGRC) today announced new SGRC Utility Solar Photovoltaic Forecasting Models and Forecasting Service. The SGRC Solar Models and Service provide the first commercially available annual forecasts of residential solar PV system installations, energy and hourly load impacts, costs and benefits over a 10-year forecast horizon.

Forecasts are provided for distribution feeders, substations, ZIP areas, and the entire utility service areas. Low, medium and high forecasts are provided to reflect the range of likely PV installation and load impacts.

The consortium, which is known for its smart grid investment models (SGIM), recently extended its analysis to “grid-edge” new technology applications and, with the Solar PV Forecasting Models and Forecasting Service, is now addressing utility financial and load impacts of solar PV distributed energy resources.

Continuing PV cost reductions, growing popularity of power purchase agreements, tax incentives and other factors are responsible for year-over-year doubling, or more, of PV installations in many states. Recent Austin Energy and NV Energy utility-scale procurements at less than 4 cents/kWh portend a rapidly arriving transformation for residential utility customer installations with increasing solar PV penetrations in nearly all utility service areas. These PV impacts present both utility challenges and benefits that are quantified with the SGRC Solar PV Forecasting Models and Forecasting Service.

The consortium models and service provide utilities with annual, geographically detailed forecasts of the likely number and hourly load impacts of residential PV installations on their distribution systems over the next decade. The agent-based statistical models underlying these forecasts are estimated with data on more than 7 million utility customers and nearly 500,000 solar PV installations.

Models are applied at feeder/substation and ZIP level and reflect the “clustered” nature of PV installations resulting from geographic patterns of household, dwelling unit, neighborhood and other characteristics that drive PV sales.

PV forecasts are designed both to assist utility distribution planners and to provide a program evaluation tool for utility solar program development.

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