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Chao Long

Researcher at Cardiff University

Publications -  53
Citations -  3931

Chao Long is an academic researcher from Cardiff University. The author has contributed to research in topics: Distributed generation & Voltage regulation. The author has an hindex of 22, co-authored 50 publications receiving 2347 citations. Previous affiliations of Chao Long include Cranfield University & University of Manchester.

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Peer-to-Peer energy trading in a Microgrid

TL;DR: Test results in a LV grid-connected Microgrid show that P2P energy trading is able to improve the local balance of energy generation and consumption and the increased diversity of generation and load profiles of peers is ability to further facilitate the balance.
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Peer-to-Peer Energy Trading in a Prosumer-Based Community Microgrid: A Game-Theoretic Model

TL;DR: Simulation results show the convergence of the algorithms and the effectiveness of the proposed model to handle P2P energy trading, and it is emerging as an alternative to cost-intensive energy storage systems.
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Peer-to-peer energy sharing through a two-stage aggregated battery control in a community Microgrid

TL;DR: The proposed two-stage aggregated control method was applied to residential community Microgrids with photovoltaic (PV) battery systems and it was revealed that P2P energy sharing is able to reduce the energy cost of the community by 30% compared to the conventional P2G energy trading.
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Review of Existing Peer-to-Peer Energy Trading Projects

TL;DR: In this paper, the authors compared the similarities and differences of the P2P energy trading trails in different regions of the world and showed that although many of the trails focus on the business models acting similarly to a supplier's role in the electricity sector, it is also necessary to design the necessary communication and control networks that could enable P2PCE energy trading in or among local microgrids.
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Evaluation of peer-to-peer energy sharing mechanisms based on a multiagent simulation framework

TL;DR: Simulation results showed that both of the step length control and learning process involvement techniques improve the performance of P2P energy sharing mechanisms with moderate ramping/learning rates and showed that P2p energy sharing has the potential to bring both economic and technical benefits for Great Britain.