Vertex scenario-based robust peer-to-peer transactive energy trading in distribution networks. (June 2022) - Chang, Xinyue; Xu, Yinliang; Sun, Hongbin
Highlights: A peer-to-peer transactive energy trading framework is proposed. A vertex scenario-based robust optimization is adopted to handle uncertainties. Taguchi's orthogonal array testing is utilized to reduce the scenario number. Various network constraints are incorporated to ensure reliable and safe operation. Abstract: The growing integration of distributed energy resources into the smart grid promotes the transition from passive into active distribution networks. However, this process also brings significant challenges to the system's operation. This paper investigates the peer-to-peer transactive energy trading framework among prosumers in the active distribution network. To handle uncertainties of renewable energy, this paper proposes a vertex scenario-based robust optimization method with Taguchi's orthogonal array testing method, which can effectively reduce the scenario number and improve computational efficiency. The developed model aims to minimize the overall cost of multi-energy resource owners considering the power loss incurred by the transactive energy trading. Various network constraints are incorporated to ensure the reliable and safe operation of the distribution network. The Nash bargaining theory is adopted in the transactive energy trading payment allocations, which can obtain mutually beneficial and fair solutions to encourage prosumers' participation. Finally, several case studies are conducted on a modified 69-bus distribution network to show the effectiveness and superiority of the proposed approach in terms of improving flexibility, economy, calculation speed, and security.