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Suggested Citation:"7 Strategies Going Forward." National Academies of Sciences, Engineering, and Medicine. 2015. Mathematical Sciences Research Challenges for the Next-Generation Electric Grid: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/21808.
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7

Strategies Going Forward

CONCLUDING REMARKS

In the final workshop session, Robert J. Thomas (Cornell University) and J. Thomas Overbye (University of Illinois, Urbana-Champaign) concluded by noting that the electrical industry is vitally interested in getting its analytical methods right. The discussions provided throughout the workshop provided great insight into key areas of importance in data and data analytics, control optimization, and uncertainty.

WORKSHOP THEMES

Several topics were discussed on different occasions throughout the workshop. Points that were addressed by multiple speakers or participants during the course of the workshop include the following:

  • Renewable energy integration. Several speakers (Bita Analui, Yonghong Chen, Steven Chu, and Pravin Varaiya) and breakout session participants discussed the importance and difficulty of integrating renewable energy into the grid. As distributed rooftop solar energy generation becomes increasingly prevalent, electrical providers need to find better ways to plan for and integrate these electricity sources. Chu discussed the possibility that individualized electricity storage for solar electricity (perhaps in the form of, or partnered with, electric vehicles) may help ease this transi-
Suggested Citation:"7 Strategies Going Forward." National Academies of Sciences, Engineering, and Medicine. 2015. Mathematical Sciences Research Challenges for the Next-Generation Electric Grid: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/21808.
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  • tion. Another option discussed was increasing the prevalence of shorter-timescale markets in which renewables are able to more easily compete, compared to day-ahead markets.

  • Consumer energy storage. Speakers (Steven Chu and David Sun) and breakout participants described the trend of some commercial and residential consumers moving to distributed personalized energy storage. As Chu discussed, this can come in the form of a large heat and power system, such as what is currently available at Texas Medical Center, or in the form of smaller individualized electricity storage for solar electricity (perhaps in the form of, or partnered with, electric vehicles).
  • Aged transmission and distribution infrastructure. The current transmission and distribution system was described as being outdated (Steven Chu and Louis Wehenkel) and often relying on failing infrastructure that has surpassed its planned life span.
  • Open-source software. A lack of open-source software was discussed by speakers Terry Boston and Matthew Gardner and breakout session participants. Gardner stated that increased use of, and comfort with, open-source solutions could help utilities update outdated models in multiple areas, and some breakout session participants stated that such a move could help engage a broader research community.
  • Sharing data. Several speakers (Judy Cardell, Steven Chu, Matthew Gardner, and Louis Wehenkel) and breakout session participants discussed the need to share data responsibly both between utility providers and researchers. Data of particular interest are those from phasor measurement units. Wehenkel commented that more data need to be available, especially for estimation of the remaining lifetime of transmission system assets and the estimation of joint probabilities of multiple faults. Cardell and breakout session participants emphasized the need to consider consumer privacy while designing and deploying new technology.
  • Evolving business models. Many speakers (Terry Boston, Michael Chertkov, Steven Chu, David Sun, and Pravin Varaiya) and breakout participants discussed the changing paradigm of the grid in the context of what it means for utility companies. Chu’s description was that as consumers move toward more rooftop solar, electric vehicles become commonplace, and large stationary batteries become widely available, more and better pricing and generation models are deployed and other alternatives, such as switching to a personalized gas generator, become more popular—compelling utilities to examine what this means for their current business models and how they will adapt. Sun believes that utility companies will adapt by unbundling existing services and offering new, more innovative services to consumers. Varaiya suggested that a potentially viable option
Suggested Citation:"7 Strategies Going Forward." National Academies of Sciences, Engineering, and Medicine. 2015. Mathematical Sciences Research Challenges for the Next-Generation Electric Grid: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/21808.
×
  • would be for utilities to modify their approach to meeting the flexible demands of consumers through means such as priority pricing, interruptible electrical power, demand response, price-responsive demand, and duration-differentiated energy service. The possibility of increased reliance on high-voltage direct-current technologies as a way to better transport electricity was also discussed.

  • Security. The importance of protecting the grid from cyber and physical attacks was discussed by several speakers (Terry Boston, Steven Chu, and Matthew Gardner) and in multiple breakout sessions. This was a notable concern when discussing grid control architecture.
  • Moving to a smart grid. Transitioning from a legacy grid to a smart grid was discussed throughout the workshop by many speakers (Steven Chu, Sean Meyn, David Sun, Pravin Varaiya, and Louis Wehenkel) and breakout session participants. Chu noted that this will require the use of more modern technology, better models, and nimble electricity generators and providers. Sun discussed several demonstration projects (e.g., NiceGrid and the Pacific Northwest Demonstration Project) that will offer lessons for larger transitions to come, and Wehenkel discussed some of the innovations that would need to happen across the grid. Varaiya described some consumer-oriented approaches to modifying demand instead of load. Meyn discussed the importance of eliminating risk to consumers and the grid when using demand-side flexibility for reliable ancillary services in a smart grid.
  • Improved modeling needed. The role for mathematical and computational modeling is increasing, as explained by multiple speakers (Bita Analui, Robert Bixby, Yonghong Chen, Michael Chertkov, Steven Chu, Alexander Eydeland, Matthew Gardner, Miriam Goldberg, Sean Meyn, Cynthia Rudin, David Sun, and Louis Wehenkel) and breakout session participants. These include optimization models (such as linear programming and mixed-integer programming), dynamic game theory and mechanism design, power-flow models, human-in-the-loop models, nonlinear control and stability models, statistical models that represent observational data via probability densities (such as Gaussian processes, Markov chains/fields, logistic models, random forests, and support vector machines), physical models that represent deterministic constraints among physical quantities (such as algebraic and differential equations), consumer behavior and response models (for systems such as real-time pricing, priority pricing, interruptible electrical power, demand response, price-responsive demand, deadline-differentiated service, and duration-differentiated energy service), uncertainty analysis, causal analysis, and power market pricing (such as Black-Scholes theory).
Suggested Citation:"7 Strategies Going Forward." National Academies of Sciences, Engineering, and Medicine. 2015. Mathematical Sciences Research Challenges for the Next-Generation Electric Grid: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/21808.
×
  • Uncertainty. The importance of understanding uncertainty in models and physical systems was discussed by Yonghong Chen and Miriam Goldberg and in breakout sessions. Goldberg described the three main kinds of measurement and verification uncertainties in grid modeling: estimation/forecasting error, policy choices and conventions, and extrapolations.

Suggested Citation:"7 Strategies Going Forward." National Academies of Sciences, Engineering, and Medicine. 2015. Mathematical Sciences Research Challenges for the Next-Generation Electric Grid: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/21808.
×

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Suggested Citation:"7 Strategies Going Forward." National Academies of Sciences, Engineering, and Medicine. 2015. Mathematical Sciences Research Challenges for the Next-Generation Electric Grid: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/21808.
×
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Suggested Citation:"7 Strategies Going Forward." National Academies of Sciences, Engineering, and Medicine. 2015. Mathematical Sciences Research Challenges for the Next-Generation Electric Grid: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/21808.
×
Page 71
Suggested Citation:"7 Strategies Going Forward." National Academies of Sciences, Engineering, and Medicine. 2015. Mathematical Sciences Research Challenges for the Next-Generation Electric Grid: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/21808.
×
Page 72
Suggested Citation:"7 Strategies Going Forward." National Academies of Sciences, Engineering, and Medicine. 2015. Mathematical Sciences Research Challenges for the Next-Generation Electric Grid: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/21808.
×
Page 73
Suggested Citation:"7 Strategies Going Forward." National Academies of Sciences, Engineering, and Medicine. 2015. Mathematical Sciences Research Challenges for the Next-Generation Electric Grid: Summary of a Workshop. Washington, DC: The National Academies Press. doi: 10.17226/21808.
×
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If the United States is to sustain its economic prosperity, quality of life, and global competitiveness, it must continue to have an abundance of secure, reliable, and affordable energy resources. There have been many improvements in the technology and capability of the electric grid over the past several decades. Many of these advances to the grid depend on complex mathematical algorithms and techniques, and as the complexity of the grid has increased, the analytical demands have also increased.

The workshop summarized in this report was developed as part of an ongoing study of the Committee on Analytical Research Foundations for the Next-Generation Electric Grid. Mathematical Sciences Research Challenges for the Next-Generation Electric Grid summarizes the presentations and discussions from this workshop. This report identifies critical areas of mathematical and computational research that must be addressed for the next-generation electric transmission and distribution system and to identify future needs and ways that current research efforts in these areas could be adjusted or augmented.

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