Joint Interaction Between Distributed Power Trading and Distribution Network Operation Considering Dynamic Network Tariffs

With the growth of the installed scale of distributed energy under the goals of carbon emission peak and carbon neutrality, the number and scale of peer-to-peer (P2P) for distributed power trading will keep increasing. By establishing a short-term network tariff model and dynamic adjustment mechanism for long-term interactive operation of distributed trading and distribution networks, this paper aims to effectively promote the transformation of the operation and cost recovery methods of distribution networks under the new energy structure. First, based on the additional short-term operation costs of P2P trading on the grid, this paper establishes a P2P trading network tariff model with three parts: line occupation cost, voltage adjustment cost and network loss cost, and adopts continuous two-way auction to match the trading aggregation for P2P trading with small volume, high frequency and real-time characteristics, and then further designs a dynamic network tariff update and adjustment model considering line utilization and incremental cost. At the same time, a quotation and quantity strategy adjustment model for electricity purchasing and selling users participating in P2P trading has been established. Based on the Vensim DSS platform and MATLAB software, a long time-scale joint interaction simulation is conducted. The case analysis shows that the proposed dynamic network tariff can release stronger price signals to stimulate the power flow distribution of P2P trading on the less utilized lines, while discouraging the higher utilized lines from generating more net power flow increments to achieve the effect of“low promotion and high suppression”and realize the effective utilization of network assets. Moreover, network tariff charging will not harm users’enthusiasm to participate in P2P trading for a long period of time in the future. Therefore, it can promote the benign synergistic development of distributed trading and distribution network, and realize the win-win situation of distribution network users and public distribution network operators. © 2023 Automation of Electric Power Systems Press. All rights reserved.