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Sen. Netw."],"published-print":{"date-parts":[[2018,11,30]]},"abstract":"<jats:p>The rapid expansion of intermittent grid-tied solar capacity is making the job of balancing electricity\u2019s real-time supply and demand increasingly challenging. Recent work proposes mechanisms for actively controlling solar power in the grid at individual sites by enabling software to cap it as a fraction of its time-varying maximum output. However, while enforcing an equal fraction of each solar site\u2019s time-varying maximum output results in \u201cfair\u201d short-term contributions of solar power across all sites, it does not result in \u201cfair\u201d long-term contributions of solar energy. Enforcing fair long-term energy access is important when controlling distributed solar capacity, since limits on solar output impact the compensation users receive for net metering and the battery capacity required to store excess solar energy. This discrepancy arises from fundamental differences in enforcing \u201cfair\u201d access to the grid to contribute solar energy, compared to analogous fair sharing in networks and processors. To address the problem, we first present both a centralized and distributed algorithm to enable control of distributed solar capacity that enforces fair grid energy access. We then present multiple policies that show how utilities can leverage this new distributed rate-limiting mechanism to reduce variations in grid demand from intermittent solar generation.<\/jats:p>","DOI":"10.1145\/3219811","type":"journal-article","created":{"date-parts":[[2018,12,5]],"date-time":"2018-12-05T13:04:59Z","timestamp":1544015099000},"page":"1-28","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":1,"title":["Mechanisms and Policies for Controlling Distributed Solar Capacity"],"prefix":"10.1145","volume":"14","author":[{"given":"Noman","family":"Bashir","sequence":"first","affiliation":[{"name":"University of Massachusetts Amherst"}]},{"given":"David","family":"Irwin","sequence":"additional","affiliation":[{"name":"University of Massachusetts Amherst"}]},{"given":"Prashant","family":"Shenoy","sequence":"additional","affiliation":[{"name":"University of Massachusetts Amherst"}]},{"given":"Jay","family":"Taneja","sequence":"additional","affiliation":[{"name":"University of Massachusetts Amherst"}]}],"member":"320","published-online":{"date-parts":[[2018,12,4]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"2017. 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D. Kempe, A. Dobra, and J. Gehrke. 2003. Gossip-based computation of aggregate information. In Proceedings of the 44th Annual IEEE Symposium on Foundations of Computer Science (FOCS'03)."},{"key":"e_1_2_1_11_1","volume-title":"IEEE Spectrum","author":"Kroposki B.","year":"2016","unstructured":"B. Kroposki . 2016 . Can Smarter Solar Inverters Save the Grid ? IEEE Spectrum , October 20, 2016. B. Kroposki. 2016. Can Smarter Solar Inverters Save the Grid? IEEE Spectrum, October 20, 2016."},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1145\/3077839.3077840"},{"key":"e_1_2_1_13_1","unstructured":"D. Lew L. Bird M. Milligan B. Speer X. Wang E. Carlini A. Estanqueiro D. Flynn E. Gomez-Lazaro N. Menemenlis A. Orths I. Pineda J. Smith L. Soder P. Sorensen A. Altiparmakis and Y. Yoh. 2013. Wind and Solar Curtailment. Technical Report. National Renewable Energy Laboratory.  D. Lew L. Bird M. Milligan B. Speer X. Wang E. Carlini A. Estanqueiro D. Flynn E. Gomez-Lazaro N. 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