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Modeled Utility-Scale Solar+Storage Operations 2020-2024

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In this project, we model optimized hourly dispatch under energy, capacity, and ancillary-service market opportunities using a linear optimizer with perfect price and generation foresight and are sharing the hourly solar and storage generation profiles for our sample here using the base scenario.

Large-scale (1MW+) co-located solar and battery storage projects are expanding rapidly in the United States, but their realized contribution to the bulk power system remains poorly understood because public project-level operating data are limited. The Lawrence Berkeley National Laboratory estimates the wholesale market value of 280 operational photovoltaic-plus-storage (PV+S) projects across the seven ISOs/RTOs and 19 additional balancing authorities, representing roughly 95% of the U.S. PV+S fleet in 2024.

In the full briefing compare the modeled optimized wholesale market value with the value of standalone PV, project-specific levelized cost estimates, and empirical operating or revenue data where available. Under optimized dispatch with perfect price foresight, adding batteries could have increased the national generation-weighted market value of solar from $29/MWh to $75/MWh in 2024, primarily through higher capacity value, followed by ancillary-service and energy shifting revenue. For projects with available cost data, optimized PV+S market value exceeded levelized generation cost by nearly $35/MWh from 2020-2024 when accounting for tax credits. Empirical operations of 51 projects captured substantial but incomplete value: in 2024, observed PV+S operations realized $39/MWh, or 62% of modeled optimized value, with the storage premium reaching only 38% of its optimized potential.

The gap between optimized and empirical value reflects multiple barriers that prevent projects from offering their full value to the bulk power system, including: limited participation in wholesale markets such as ancillary services that remain lucrative in some regions; tax-driven grid-charging restrictions for older projects; simplistic rule-based dispatch (charge in the middle of the day and discharge in the evening); imperfect price and generation forecasting; weak or missing price signals in non-ISO regions; and dispatch incentives tied to contracts or state programs rather than bulk-system value. These findings suggest that PV+S can be cost-effective from a wholesale-market perspective, but that improved market participation, forecasting, and alignment of operational incentives are needed for projects to realize their full system value proposition.

Citation Formats

TY - DATA AB - In this project, we model optimized hourly dispatch under energy, capacity, and ancillary-service market opportunities using a linear optimizer with perfect price and generation foresight and are sharing the hourly solar and storage generation profiles for our sample here using the base scenario. Large-scale (1MW+) co-located solar and battery storage projects are expanding rapidly in the United States, but their realized contribution to the bulk power system remains poorly understood because public project-level operating data are limited. The Lawrence Berkeley National Laboratory estimates the wholesale market value of 280 operational photovoltaic-plus-storage (PV+S) projects across the seven ISOs/RTOs and 19 additional balancing authorities, representing roughly 95% of the U.S. PV+S fleet in 2024. In the full briefing compare the modeled optimized wholesale market value with the value of standalone PV, project-specific levelized cost estimates, and empirical operating or revenue data where available. Under optimized dispatch with perfect price foresight, adding batteries could have increased the national generation-weighted market value of solar from $29/MWh to $75/MWh in 2024, primarily through higher capacity value, followed by ancillary-service and energy shifting revenue. For projects with available cost data, optimized PV+S market value exceeded levelized generation cost by nearly $35/MWh from 2020-2024 when accounting for tax credits. Empirical operations of 51 projects captured substantial but incomplete value: in 2024, observed PV+S operations realized $39/MWh, or 62% of modeled optimized value, with the storage premium reaching only 38% of its optimized potential. The gap between optimized and empirical value reflects multiple barriers that prevent projects from offering their full value to the bulk power system, including: limited participation in wholesale markets such as ancillary services that remain lucrative in some regions; tax-driven grid-charging restrictions for older projects; simplistic rule-based dispatch (charge in the middle of the day and discharge in the evening); imperfect price and generation forecasting; weak or missing price signals in non-ISO regions; and dispatch incentives tied to contracts or state programs rather than bulk-system value. These findings suggest that PV+S can be cost-effective from a wholesale-market perspective, but that improved market participation, forecasting, and alignment of operational incentives are needed for projects to realize their full system value proposition. AU - Seel, Joachim A2 - Julie Mulvaney Kemp, Julie A3 - Cheyette, Anna A4 - Gorman, Will A5 - Chuang, Jessalyn A6 - Millstein, Dev DB - Open Energy Data Initiative (OEDI) DP - Open EI | National Laboratory of the Rockies DO - KW - solar KW - storage KW - PV KW - batteries KW - operations KW - wholesale markets KW - energy value KW - capacity value KW - ancillary services KW - data KW - model KW - optimization KW - energy KW - capacity KW - market KW - linear optimizer KW - price KW - generation KW - hourly solar KW - generation profiles KW - United States KW - LBNL KW - PVS LA - English DA - 2026/05/12 PY - 2026 PB - Lawrence Berkeley National Lab T1 - Modeled Utility-Scale Solar+Storage Operations 2020-2024 UR - https://data.openei.org/submissions/8687 ER -
Export Citation to RIS
Seel, Joachim, et al. Modeled Utility-Scale Solar+Storage Operations 2020-2024. Lawrence Berkeley National Lab, 12 May, 2026, Open Energy Data Initiative (OEDI). https://data.openei.org/submissions/8687.
Seel, J., Julie Mulvaney Kemp, J., Cheyette, A., Gorman, W., Chuang, J., & Millstein, D. (2026). Modeled Utility-Scale Solar+Storage Operations 2020-2024. [Data set]. Open Energy Data Initiative (OEDI). Lawrence Berkeley National Lab. https://data.openei.org/submissions/8687
Seel, Joachim, Julie Julie Mulvaney Kemp, Anna Cheyette, Will Gorman, Jessalyn Chuang, and Dev Millstein. Modeled Utility-Scale Solar+Storage Operations 2020-2024. Lawrence Berkeley National Lab, May, 12, 2026. Distributed by Open Energy Data Initiative (OEDI). https://data.openei.org/submissions/8687
@misc{OEDI_Dataset_8687, title = {Modeled Utility-Scale Solar+Storage Operations 2020-2024}, author = {Seel, Joachim and Julie Mulvaney Kemp, Julie and Cheyette, Anna and Gorman, Will and Chuang, Jessalyn and Millstein, Dev}, abstractNote = {In this project, we model optimized hourly dispatch under energy, capacity, and ancillary-service market opportunities using a linear optimizer with perfect price and generation foresight and are sharing the hourly solar and storage generation profiles for our sample here using the base scenario.

Large-scale (1MW+) co-located solar and battery storage projects are expanding rapidly in the United States, but their realized contribution to the bulk power system remains poorly understood because public project-level operating data are limited. The Lawrence Berkeley National Laboratory estimates the wholesale market value of 280 operational photovoltaic-plus-storage (PV+S) projects across the seven ISOs/RTOs and 19 additional balancing authorities, representing roughly 95\% of the U.S. PV+S fleet in 2024.

In the full briefing compare the modeled optimized wholesale market value with the value of standalone PV, project-specific levelized cost estimates, and empirical operating or revenue data where available. Under optimized dispatch with perfect price foresight, adding batteries could have increased the national generation-weighted market value of solar from $29/MWh to $75/MWh in 2024, primarily through higher capacity value, followed by ancillary-service and energy shifting revenue. For projects with available cost data, optimized PV+S market value exceeded levelized generation cost by nearly $35/MWh from 2020-2024 when accounting for tax credits. Empirical operations of 51 projects captured substantial but incomplete value: in 2024, observed PV+S operations realized $39/MWh, or 62\% of modeled optimized value, with the storage premium reaching only 38\% of its optimized potential.

The gap between optimized and empirical value reflects multiple barriers that prevent projects from offering their full value to the bulk power system, including: limited participation in wholesale markets such as ancillary services that remain lucrative in some regions; tax-driven grid-charging restrictions for older projects; simplistic rule-based dispatch (charge in the middle of the day and discharge in the evening); imperfect price and generation forecasting; weak or missing price signals in non-ISO regions; and dispatch incentives tied to contracts or state programs rather than bulk-system value. These findings suggest that PV+S can be cost-effective from a wholesale-market perspective, but that improved market participation, forecasting, and alignment of operational incentives are needed for projects to realize their full system value proposition. }, url = {https://data.openei.org/submissions/8687}, year = {2026}, howpublished = {Open Energy Data Initiative (OEDI), Lawrence Berkeley National Lab, https://data.openei.org/submissions/8687}, note = {Accessed: 2026-07-07} }

Details

Data from May 12, 2026

Last updated May 14, 2026

Submitted May 12, 2026

Organization

Lawrence Berkeley National Lab

Contact

Joachim Seel

510.486.5087

Authors

Joachim Seel

Lawrence Berkeley National Lab

Julie Julie Mulvaney Kemp

Lawrence Berkeley National Lab

Anna Cheyette

Lawrence Berkeley National Lab

Will Gorman

Lawrence Berkeley National Lab

Jessalyn Chuang

Lawrence Berkeley National Lab

Dev Millstein

Lawrence Berkeley National Lab

DOE Project Details

Project Name Identifying Barriers to Solar and Storage Hybrids

Project Number 52952

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