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Title: Planning for a Distributed Disruption: Innovative Practices for Incorporating Distributed Solar into Utility Planning

Abstract

The rapid growth of distributed solar photovoltaics (DPV) has critical implications for U.S. utility planning processes. This report informs utility planning through a comparative analysis of roughly 30 recent utility integrated resource plans or other generation planning studies, transmission planning studies, and distribution system plans. It reveals a spectrum of approaches to incorporating DPV across nine key planning areas, and it identifies areas where even the best current practices might be enhanced. 1) Forecasting DPV deployment: Because it explicitly captures several predictive factors, customer-adoption modeling is the most comprehensive forecasting approach. It could be combined with other forecasting methods to generate a range of potential futures. 2) Ensuring robustness of decisions to uncertain DPV quantities: using a capacity-expansion model to develop least-cost plans for various scenarios accounts for changes in net load and the generation portfolio; an innovative variation of this approach combines multiple per-scenario plans with trigger events, which indicate when conditions have changed sufficiently from the expected to trigger modifications in resource-acquisition strategy. 3) Characterizing DPV as a resource option: Today’s most comprehensive plans account for all of DPV’s monetary costs and benefits. An enhanced approach would address non-monetary and societal impacts as well. 4) Incorporating the non-dispatchabilitymore » of DPV into planning: Rather than having a distinct innovative practice, innovation in this area is represented by evolving methods for capturing this important aspect of DPV. 5) Accounting for DPV’s location-specific factors: The innovative propensity-to-adopt method employs several factors to predict future DPV locations. Another emerging utility innovation is locating DPV strategically to enhance its benefits. 6) Estimating DPV’s impact on transmission and distribution investments: Innovative practices are being implemented to evaluate system needs, hosting capacities, and system investments needed to accommodate DPV deployment. 7) Estimating avoided losses associated with DPV: A time-differentiated marginal loss rate provides the most comprehensive estimate of avoided losses due to DPV, but no studies appear to use it. 8) Considering changes in DPV’s value with higher solar penetration: Innovative methods for addressing the value changes at high solar penetrations are lacking among the studies we evaluate. 9) Integrating DPV in planning across generation, transmission, and distribution: A few states and regions have started to develop more comprehensive processes that link planning forums, but there are still many issues to address.« less

Authors:
 [1];  [1];  [1];  [2];  [2];  [2];  [3]
  1. Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
  2. National Renewable Energy Lab. (NREL), Golden, CO (United States)
  3. Independent Consultant
Publication Date:
Research Org.:
Lawrence Berkeley National Lab. (LBNL), Berkeley, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1332539
Report Number(s):
LBNL-1006047
ir:1006047
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
14 SOLAR ENERGY; 29 ENERGY PLANNING, POLICY, AND ECONOMY

Citation Formats

Mill, Andrew, Barbose, Galen, Seel, Joachim, Dong, Changgui, Mai, Trieu, Sigrin, Ben, and Zuboy, Jarrett. Planning for a Distributed Disruption: Innovative Practices for Incorporating Distributed Solar into Utility Planning. United States: N. p., 2016. Web. doi:10.2172/1332539.
Mill, Andrew, Barbose, Galen, Seel, Joachim, Dong, Changgui, Mai, Trieu, Sigrin, Ben, & Zuboy, Jarrett. Planning for a Distributed Disruption: Innovative Practices for Incorporating Distributed Solar into Utility Planning. United States. doi:10.2172/1332539.
Mill, Andrew, Barbose, Galen, Seel, Joachim, Dong, Changgui, Mai, Trieu, Sigrin, Ben, and Zuboy, Jarrett. Fri . "Planning for a Distributed Disruption: Innovative Practices for Incorporating Distributed Solar into Utility Planning". United States. doi:10.2172/1332539. https://www.osti.gov/servlets/purl/1332539.
@article{osti_1332539,
title = {Planning for a Distributed Disruption: Innovative Practices for Incorporating Distributed Solar into Utility Planning},
author = {Mill, Andrew and Barbose, Galen and Seel, Joachim and Dong, Changgui and Mai, Trieu and Sigrin, Ben and Zuboy, Jarrett},
abstractNote = {The rapid growth of distributed solar photovoltaics (DPV) has critical implications for U.S. utility planning processes. This report informs utility planning through a comparative analysis of roughly 30 recent utility integrated resource plans or other generation planning studies, transmission planning studies, and distribution system plans. It reveals a spectrum of approaches to incorporating DPV across nine key planning areas, and it identifies areas where even the best current practices might be enhanced. 1) Forecasting DPV deployment: Because it explicitly captures several predictive factors, customer-adoption modeling is the most comprehensive forecasting approach. It could be combined with other forecasting methods to generate a range of potential futures. 2) Ensuring robustness of decisions to uncertain DPV quantities: using a capacity-expansion model to develop least-cost plans for various scenarios accounts for changes in net load and the generation portfolio; an innovative variation of this approach combines multiple per-scenario plans with trigger events, which indicate when conditions have changed sufficiently from the expected to trigger modifications in resource-acquisition strategy. 3) Characterizing DPV as a resource option: Today’s most comprehensive plans account for all of DPV’s monetary costs and benefits. An enhanced approach would address non-monetary and societal impacts as well. 4) Incorporating the non-dispatchability of DPV into planning: Rather than having a distinct innovative practice, innovation in this area is represented by evolving methods for capturing this important aspect of DPV. 5) Accounting for DPV’s location-specific factors: The innovative propensity-to-adopt method employs several factors to predict future DPV locations. Another emerging utility innovation is locating DPV strategically to enhance its benefits. 6) Estimating DPV’s impact on transmission and distribution investments: Innovative practices are being implemented to evaluate system needs, hosting capacities, and system investments needed to accommodate DPV deployment. 7) Estimating avoided losses associated with DPV: A time-differentiated marginal loss rate provides the most comprehensive estimate of avoided losses due to DPV, but no studies appear to use it. 8) Considering changes in DPV’s value with higher solar penetration: Innovative methods for addressing the value changes at high solar penetrations are lacking among the studies we evaluate. 9) Integrating DPV in planning across generation, transmission, and distribution: A few states and regions have started to develop more comprehensive processes that link planning forums, but there are still many issues to address.},
doi = {10.2172/1332539},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Aug 19 00:00:00 EDT 2016},
month = {Fri Aug 19 00:00:00 EDT 2016}
}

Technical Report:

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  • The rapid growth of distributed solar photovoltaics (DPV) has critical implications for U.S. utility planning processes. This report informs utility planning through a comparative analysis of roughly 30 recent utility integrated resource plans or other generation planning studies, transmission planning studies, and distribution system plans. It reveals a spectrum of approaches to incorporating DPV across nine key planning areas, and it identifies areas where even the best current practices might be enhanced. (1) Forecasting DPV deployment: Because it explicitly captures several predictive factors, customer-adoption modeling is the most comprehensive forecasting approach. It could be combined with other forecasting methods tomore » generate a range of potential futures. (2) Ensuring robustness of decisions to uncertain DPV quantities: using a capacity-expansion model to develop least-cost plans for various scenarios accounts for changes in net load and the generation portfolio; an innovative variation of this approach combines multiple per-scenario plans with trigger events, which indicate when conditions have changed sufficiently from the expected to trigger modifications in resource-acquisition strategy. (3) Characterizing DPV as a resource option: Today's most comprehensive plans account for all of DPV's monetary costs and benefits. An enhanced approach would address non-monetary and societal impacts as well. (4) Incorporating the non-dispatchability of DPV into planning: Rather than having a distinct innovative practice, innovation in this area is represented by evolving methods for capturing this important aspect of DPV. (5) Accounting for DPV's location-specific factors: The innovative propensity-to-adopt method employs several factors to predict future DPV locations. Another emerging utility innovation is locating DPV strategically to enhance its benefits. (6) Estimating DPV's impact on transmission and distribution investments: Innovative practices are being implemented to evaluate system needs, hosting capacities, and system investments needed to accommodate DPV deployment. (7) Estimating avoided losses associated with DPV: A time-differentiated marginal loss rate provides the most comprehensive estimate of avoided losses due to DPV, but no studies appear to use it. (8) Considering changes in DPV's value with higher solar penetration: Innovative methods for addressing the value changes at high solar penetrations are lacking among the studies we evaluate. (9) Integrating DPV in planning across generation, transmission, and distribution: A few states and regions have started to develop more comprehensive processes that link planning forums, but there are still many issues to address.« less
  • The report contains a compilation of successful and innovative multimodal planning practices currently employed in a variety of settings, for both freight and passenger transportation. The report should be of interest to practitioners in state departments of transportation, metropolitan planning organizations, transit agencies, and other transportation planning and decisionmaking organizations. It should also serve as an educational resource on available tools that support effective transportation planning and decisionmaking.
  • Misforecasting the adoption of customer-owned distributed photovoltaics (DPV) can have operational and financial implications for utilities; forecasting capabilities can be improved, but generally at a cost. This paper informs this decision-space by using a suite of models to explore the capacity expansion and operation of the Western Interconnection over a 15-year period across a wide range of DPV growth rates and misforecast severities. The system costs under a misforecast are compared against the costs under a perfect forecast, to quantify the costs of misforecasting. Using a simplified probabilistic method applied to these modeling results, an analyst can make a first-ordermore » estimate of the financial benefit of improving a utility’s forecasting capabilities, and thus be better informed about whether to make such an investment. For example, under our base assumptions, a utility with 10 TWh per year of retail electric sales who initially estimates that DPV growth could range from 2% to 7.5% of total generation over the next 15 years could expect total present-value savings of approximately $4 million if they could reduce the severity of misforecasting to within ±25%. Utility resource planners can compare those savings against the costs needed to achieve that level of precision, to guide their decision on whether to make an investment in tools or resources.« less
  • Misforecasting the adoption of customer-owned distributed photovoltaics (DPV) can have operational and financial implications for utilities - forecasting capabilities can be improved, but generally at a cost. This paper informs this decision-space by quantifying the costs of misforecasting across a wide range of DPV growth rates and misforecast severities. Using a simplified probabilistic method presented within, an analyst can make a first-order estimate of the financial benefit of improving a utility's forecasting capabilities, and thus be better informed about whether to make such an investment. For example, we show that a utility with 10 TWh per year of retail electricmore » sales who initially estimates that the increase in DPV's contribution to total generation could range from 2 to 7.5 percent over the next 15 years could expect total present-value savings of approximately 4 million dollars if they could keep the severity of successive five-year misforecasts within plus or minus 25 percent. We also have more general discussions about how misforecasting DPV impacts the buildout and operation of the bulk power system - for example, we observed that misforecasting DPV most strongly influenced the amount of utility-scale PV that gets built, due to the similarity in the energy and capacity services offered by the two solar technologies.« less
  • Misforecasting the adoption of customer-owned distributed photovoltaics (DPV) can have operational and financial implications for utilities - forecasting capabilities can be improved, but generally at a cost.This paper informs this decision-space by quantifying the costs of misforecasting across a wide range of DPV growth rates and misforecast severities. Using a simplified probabilistic method presented within, an analyst can make a first-order estimate of the financial benefit of improving a utility's forecasting capabilities, and thus be better informed about whether to make such an investment. For example, we show that a utility with 10 TWh per year of retail electric salesmore » who initially estimates that the increase in DPV's contribution to total generation could range from 2 percent to 7.5 percent over the next 15 years could expect total present-value savings of approximately $4 million if they could keep the severity of successive five-year misforecasts within +/- 25 percent. We also have more general discussions about how misforecasting DPV impacts the buildout and operation of the bulk power system - for example, we observed that misforecasting DPV most strongly influenced the amount of utility-scale PV that gets built, due to the similarity in the energy and capacity services offered by the two solar technologies.« less