Abstract

The penetration of multi-carrier energy systems in distribution system gains more and more concerns. In this paper, a bi-level transactive energy trading framework is proposed to improve the energy scheduling and operation efficiency for multi-carrier energy systems which are modeled as energy hubs (EHs). In the upper level, each EH in the distribution system not only makes energy scheduling decisions considering supplies and demands of local energy, but also trades energy with each other to further maximize their social welfare. The associated trading payment among EHs is made in a fair manner by applying Nash bargaining theory. We solve the bargaining problem by decomposing it into two subproblems: operation cost minimization problem and payment bargaining problem. Then, based on the trading decision, the nodal equivalent loads of EHs are sent to the distribution system operator (DSO) without publishing trading details. By applying the second-order cone programming (SOCP), DSO reconfigures the network to reduce the transmission loss of the system in the lower level. The network reconfiguration and the trading behavior of EHs interact and iterate until the convergence. Numerical studies on modified IEEE 33-bus distribution system demonstrate the effectiveness of the proposed framework.

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