4.7 Article

Novel Linearized Power Flow and Linearized OPF Models for Active Distribution Networks With Application in Distribution LMP

Journal

IEEE TRANSACTIONS ON SMART GRID
Volume 9, Issue 1, Pages 438-448

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2016.2594814

Keywords

Distributed generation; active distribution network (ADN); linearized optimal power flow for distribution (LOPF-D); linearized power flow for distribution (LPF-D); locational marginal pricing (LMP); loss factor for distribution (LF-D)

Funding

  1. NSF [ECCS-1001999]
  2. Engineering Research Center Shared Facilities through CURENT
  3. NSF/DOE Engineering Research Center [EEC-1041877]

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The locational marginal price (LMP) methodology has been discussed for distribution networks/systems under the smart grid initiative. In this paper, a new distribution LMP (DLMP) formulation is presented which includes reactive power prices and voltage constraints. To solve DLMP, three modeling tools, namely, linearized power flow for distribution (LPF-D), loss factors for distribution (LF-D), and linear optimal power flow for distribution (LOPF-D) are proposed. LPF-D solves not only voltage angles but also magnitudes through linear expression between bus injections and bus voltages, specifically for distribution systems. LF-D is solved recursively based on the radial topology of typical distribution systems. With the integration of LPF-D and LF-D, conventional optimal power flow (OPF) can be reformulated as LOPF-D which is essentially a linear programming model. Test results on various systems show that: 1) LPF-D efficiently yields very close results if compared with AC power flow; 2) LOPF-D provides very close dispatch results in both real and reactive power if compared with ACOPF; and 3) the proposed DLMPs calculated with LF-D and LOPF-D give accurate price information if compared with the prices from ACOPF. Further, these three tools are not limited to DLMP but can be potentially applied to other distribution analyses.

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