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Distributed Online Generalized Nash Equilibrium Tracking for Prosumer Energy Trading Games
Optimization and Control · Submitted 5 Oct 2022
abstract compiled · 2026-09-23 · no language-model review
The authors' main claim Its regret is proved to be bounded by a sublinear function of learning time, which indicates that the online algorithm has an acceptable accuracy in practice.
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The abstract, sentence by sentence
With the proliferation of distributed generations, traditional passive consumers in distribution networks are evolving into "prosumers", which can both produce and consume energy. Energy trading with the main grid or between prosumers is inevitable if the energy surplus and shortage exist. To this end, this paper investigates the peer-to-peer (P2P) energy trading market, which is formulated as a generalized Nash game. We first prove the existence and uniqueness of the generalized Nash equilibrium (GNE). Then, an distributed online algorithm is proposed to track the GNE in the time-varying environment. Its regret is proved to be bounded by a sublinear function of learning time, which indicates that the online algorithm has an acceptable accuracy in practice. Finally, numerical results with six microgrids validate the performance of the algorithm.
background contribution method result interpretation main claim
| # | sentence | role | the authors' own work | states the main conclusion | strength |
|---|---|---|---|---|---|
| s0 | With the proliferation of distributed generations, traditional passive consumers in distribution networks are evolving into "prosumers", which can both produce and consume energy. | background 1.00 | 0.04 | 0.02 | asserted 1.00 |
| s1 | Energy trading with the main grid or between prosumers is inevitable if the energy surplus and shortage exist. | background 1.00 | 0.06 | 0.02 | asserted 0.97 |
| s2 | To this end, this paper investigates the peer-to-peer (P2P) energy trading market, which is formulated as a generalized Nash game. | contribution 0.74 | 0.76 | 0.05 | asserted 1.00 |
| s3 | We first prove the existence and uniqueness of the generalized Nash equilibrium (GNE). | result 0.76 | 0.94 | 0.12 | asserted 1.00 |
| s4 | Then, an distributed online algorithm is proposed to track the GNE in the time-varying environment. | method 0.76 | 0.95 | 0.14 | asserted 1.00 |
| s5 | Its regret is proved to be bounded by a sublinear function of learning time, which indicates that the online algorithm has an acceptable accuracy in practice. | result 0.53 | 0.94 | 0.34 | hedged possibility 0.51 |
| s6 | Finally, numerical results with six microgrids validate the performance of the algorithm. | result 0.81 | 0.95 | 0.23 | asserted 1.00 |
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Original abstract
With the proliferation of distributed generations, traditional passive consumers in distribution networks are evolving into "prosumers", which can both produce and consume energy. Energy trading with the main grid or between prosumers is inevitable if the energy surplus and shortage exist. To this end, this paper investigates the peer-to-peer (P2P) energy trading market, which is formulated as a generalized Nash game. We first prove the existence and uniqueness of the generalized Nash equilibrium (GNE). Then, an distributed online algorithm is proposed to track the GNE in the time-varying environment. Its regret is proved to be bounded by a sublinear function of learning time, which indicates that the online algorithm has an acceptable accuracy in practice. Finally, numerical results with six microgrids validate the performance of the algorithm.
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Moreover, compared with the algorithm in [ref] , the update is much simpler without the need of solving an optimization problem at each iteration, which reduces the computation cost.
Decentralized Online Learning for Noncooperative Games in Dynamic Environments · Algorithm design · 1.00
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