Scalable Optimization Methods for Distribution Networks with High PV Integration

Swaroop S. Guggilam; Emiliano Dall'Anese; Yu Christine Chen; Sairaj V. Dhople; Georgios B. Giannakis

doi:10.1109/TSG.2016.2543264

Scalable Optimization Methods for Distribution Networks with High PV Integration

Swaroop S. Guggilam, Emiliano Dall'Anese, Yu Christine Chen, Sairaj V. Dhople, Georgios B. Giannakis

Electrical and Computer Engineering

Research output: Contribution to journal › Article › peer-review

83 Scopus citations

Abstract

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 language	English (US)
Article number	7446350
Pages (from-to)	2061-2070
Number of pages	10
Journal	IEEE Transactions on Smart Grid
Volume	7
Issue number	4
DOIs	https://doi.org/10.1109/TSG.2016.2543264
State	Published - Jul 2016

Bibliographical note

Funding Information:
The work of S. S. Guggilam, S. V. Dhople, and G. B. Giannakis were supported in part by the National Science Foundation under Grant CCF 1423316, Grant CyberSEES 1442686, and Grant CAREER Award ECCS-1453921, and in part by the Institute of Renewable Energy and the Environment, University of Minnesota, under Grant RL-0010-13. The work of E. Dall'Anese was supported by the Laboratory Directed Research and Development Program at the National Renewable Energy Laboratory.

Publisher Copyright:
© 2016 IEEE.

Keywords

Distribution networks
PV systems
linearization
optimization

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1109/TSG.2016.2543264

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title = "Scalable Optimization Methods for Distribution Networks with High PV Integration",

abstract = "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.",

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N2 - 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.

AB - 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.

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Scalable Optimization Methods for Distribution Networks with High PV Integration

Abstract

Bibliographical note

Keywords

UN SDGs

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