Welcome to the new version of CaltechAUTHORS. Login is currently restricted to library staff. If you notice any issues, please email coda@library.caltech.edu
Published May 2021 | Accepted Version
Journal Article Open

Approaching Prosumer Social Optimum via Energy Sharing With Proof of Convergence

Abstract

With the advent of prosumers, the traditional centralized operation may become impracticable due to computational burden, privacy concerns, and conflicting interests. In this article, an energy sharing mechanism is proposed to accommodate prosumers' strategic decision-making on their self-production and demand in the presence of capacity constraints. Under this setting, prosumers play a generalized Nash game. We prove main properties of the game: an equilibrium exists and is partially unique; no prosumer is worse off by energy sharing and the price-of-anarchy is 1−O(1/I) where I is the number of prosumers. In particular, the PoA tends to 1 with a growing number of prosumers, meaning that the resulting total cost under the proposed energy sharing approaches social optimum. We prove that the corresponding prosumers' strategies converge to the social optimal solution as well. Finally we propose a bidding process and prove that it converges to the energy sharing equilibrium under mild conditions. Illustrative examples are provided to validate the results.

Additional Information

© 2020 IEEE. Manuscript received June 18, 2020; revised October 17, 2020 and December 13, 2020; accepted December 24, 2020. Date of publication December 31, 2020; date of current version April 21, 2021. The work of Yue Chen and Shengwei Mei was supported by Shanxi Province Key Research and Development Project under Grant 201903D421029. The work of Changhong Zhao was supported in part by CUHK Research Startup Fund, and in part by the RGC Early Career Award under Grant 24210220. The work of Steven H. Low was supported by U.S. National Science Foundation under Grant CCF 1637598, Grant ECCS 1931662, and Grant CPS ECCS 1739355. Paper no. TSG-00927-2020.

Attached Files

Accepted Version - 2006.10332.pdf

Files

2006.10332.pdf
Files (965.7 kB)
Name Size Download all
md5:b79fdcd49d80329e23934ddb40f8debd
965.7 kB Preview Download

Additional details

Created:
August 20, 2023
Modified:
October 23, 2023