Scalable Optimization Methods for Distribution Networks with High PV Integration

Emiliano Dall-Anese, Swaroop Guggilam, Yu Chen, Sairaj Dhople, Georgios Giannakis

Research output: Contribution to journalArticlepeer-review

137 Scopus Citations


This paper proposes a suite of algorithms to determine the active- and reactive-power setpoints for photovoltaic (PV) inverters in distribution networks. The objective is to optimize the operation of the distribution feeder according to a variety of performance objectives and ensure voltage regulation. In general, these algorithms take a form of the widely studied ac optimal power flow (OPF) problem. For the envisioned application domain, nonlinear power-flow constraints render pertinent OPF problems nonconvex and computationally intensive for large systems. To address these concerns, we formulate a quadratic constrained quadratic program (QCQP) by leveraging a linear approximation of the algebraic power-flow equations. Furthermore, simplification from QCQP to a linearly constrained quadratic program is provided under certain conditions. The merits of the proposed approach are demonstrated with simulation results that utilize realistic PV-generation and load-profile data for illustrative distribution-system test feeders.
Original languageAmerican English
Pages (from-to)2061-2070
Number of pages10
JournalIEEE Transactions on Smart Grid
Issue number4
StatePublished - 2016

NREL Publication Number

  • NREL/JA-5D00-66169


  • inverters
  • linear approximation
  • mathematical model
  • optimization
  • reactive power
  • renewable energy sources
  • scalability


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