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Multi-period Market Operation of Transmission-Distribution Systems Based on Heterogeneous Decomposition and Coordination

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The integration of shiftable/curtailment distribution generators (DGs) along with quick-response storage has not only increased the transaction’s flexibility but also puzzled the bidding willingness of transmission-connected market players (TMPs). In… Click to show full abstract

The integration of shiftable/curtailment distribution generators (DGs) along with quick-response storage has not only increased the transaction’s flexibility but also puzzled the bidding willingness of transmission-connected market players (TMPs). In this paper, the method of heterogeneous decomposition and coordination (HGDC) is applied to decompose the integrated transmission-distribution market framework into a bi-level problem with a transmission wholesale market master problem and several distribution retail market subproblems in a decentralized organization structure. The price-based bidding willingness of demand-side resources’ (DSRs’) aggregator is simulated considering the relation between distribution system operator’s (DSO’s) operation modes and its equivalent market transactive price. Besides the traditional mixed-integer linear programming (MILP) model, the active reconfiguration model of DSOs based on mixed-integer second-order conic programming (MI-SOCP) is proposed to rearrange its operation switch status and elaborate its operation cost according to the market transaction. Multi-period optimal operation modes could be obtained through an HGDC-based iteration process by coordinating the transmission system operator (TSO) with DSOs and considering the market energy equilibrium and reserve requirements for security considerations. Karush-Kuhn-Tucker (KKT) conditions are used to testify the optimality and convergence of the bi-level model in theory. The T5-3D33 case is employed to illustrate the efficiency of the proposed model and method.

Keywords: market; distribution; decomposition coordination; transmission; operation; heterogeneous decomposition

Journal Title: Energies
Year Published: 2019

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