A Multi-Decadal Hourly Coincident Wind and Solar Power Production Dataset for the Contiguous United States
Not Available
14 SOLAR ENERGY↗
Engineering topics
Campbell, Allison M.
Publications and source records attributed to Campbell, Allison M..
Clustering Interval Load with Weather to Create Scenarios of Behind-the-Meter Solar Penetration
Forecasting load at the feeder level has become increasingly challenging with the penetration of behind-the-meter solar, as this self-generation is only visible to the utility as aggregated net-load. This work proposes a methodology for creation of scenarios of solar penetration at the feeder level for use by forecasters to test the robustness of their algorithm to progressively higher penetrations of solar. The algorithm draws on publicly available observations of weather condition (e.g., rainy/cloudy/fair) for use as proxies to sky clearness. These observations are used to mask and weight the interval deviations of similar native usage profiles from which average interval usage is calculated and subsequently added to interval net generation to reconstruct interval total generation. This approach improves the estimate of annual energy generation by 23%; where the net generation signal currently reflects 52% of total annual gener- ation, now 75% is captured. This methodology for creation of forecast testing scenarios is data driven and extensible to service territories which lack information on irradiance measurements and geocoordinates.
solar, load↗
EverGREEN 2045: An Energy mix to Decarbonize Washington State
The Clean Energy Transformation Act transitions Washington State to 100% clean energy by 2045. As the future resource mix will likely include intermittent renewables, hydropower, and new, carbon-free, flexible technologies including advanced nuclear reactors and enhanced geothermal systems, we assess the cost and feasibility of the future resource mix with proprietary cost data from our industry partners for new technologies. For plausible future resource mix scenarios, we find that revenues are sufficient to cover variable operations and maintenance costs for most technologies, but capacity payments or power purchase agreements will be necessary for new, flexible resources to participate in the future resource mix.
clean energy, energy policy, energy transition, re↗
EverGREEN 2045: An Energy Mix to Decarbonize Washington State
Washington State’s future resource mix is likely to be comprised of intermittent renewables and carbon-free generation including hydropower by 2045. Generation will likely be comprised of wind, solar photovoltaic (PV), batteries, pumped storage hydropower (PSH), existing nuclear power plants, and potentially enhanced geothermal systems and advanced nuclear reactor technologies. To assess the cost and stability of the future resource mix, we partner with X-energy (advanced reactor design) and AltaRock Energy (enhanced geothermal system) for proprietary cost data. After estimating the costs of these two new technologies, we design plausible future resource mix scenarios to meet Washington State’s Clean Energy Transformation Act which transitions the state to carbon-free generation by 2045. We assess the cost and stability of the future resource mix with power system analysis tools, finding revenues are sufficient to cover variable operating and maintenance costs for most technologies providing power in 2030 and 2045, but capacity payments or power purchase agreements will likely be necessary for flexible resources, including enhanced geothermal systems and advanced nuclear reactors, to participate in the future resource mix.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
WE-Validate: An Open-Source Framework For Wind Power Validation
Grid operators rely on historical weather time series at existing and planned wind power plants to make informed decisions when planning for a future power grid with very high penetration of renewable power. While synthetic wind power time series have been developed based on historical weather models, their validation with actual power production data remains complex due to variations in modeling practices and methodologies. This paper introduces the WE-Validate framework, originally designed for wind speed validation and now enhanced for wind power validation with a graphical user interface to support users with minimal programming experience. Validation of wind power with WE-Validate is based on robust metrics consisting of RMSE, centered RMSE, average bias, average percent bias, mean absolute error, mean absolute percent error, cross correlation, and calculation of ramping magnitude, rate, and duration. This paper showcases WE-Validate with validation of synthetically derived power for a wind plant in Washington state for one month in 2018. Validation of the synthetic power from two comparison data sets compared with observations shows both comparison series have strong correlation with observed across weekly and monthly aggregations while suffering from persistent negative bias. The suite of metrics within WE-Validate facilitates immediate insight into the utility of the comparison data sets through compression across multiple axes. This user-friendly, open-source tool can be extended beyond wind power, making it a valuable resource for system planners and operators in different domains.
Moncheur de Rieudotte, Malcolm P.↗