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Document Type

Thesis - University Access Only

Award Date


Degree Name

Master of Science (MS)


Electrical Engineering and Computer Science

First Advisor

Wei Sun


Volt/var optimization, chance constrained programming, simulated annealing, smart PV inverter, and distribution power flow.


Existing electric distribution systems are designed to deliver power from distribution substations to consumer load centers. Since the last decade, distribution systems are revitalizing with the increasing integration of renewable sources. Solar photovoltaic (PV) is the fastest growing source of renewable electricity in the United States. The anticipated PV proliferation brings integration challenges on system volt/var control (VVC) at the utility scale. One of the greatest challenges is to maintain desirable feeder voltages in the utility distribution network. The intermittent PV sources cause more frequent operation of VVC devices to alleviate voltage regulation issues. This thesis work proposed a real-time volt/var optimization (VVO) strategy for coordinated control of voltage regulators, switched capacitors, and PV inverter reactive power support for minimizing active power loss and also substation demand. Chance constrained programming (CCP) was used to model solar uncertainty. The VVO problem was formulated as an optimization problem and solved using simulated annealing technique. The proposed VVO strategy was tested in the modified IEEE 37-bus system. Simulation results demonstrated that the coordination of VVC devices and reactive power support from PV inverters can optimally regulate the system voltage, enable high PV penetration, and minimize active power loss and substation demand.

Library of Congress Subject Headings

Electric power distribution
Distributed generation of electric power
Simulated annealing (Mathematics)


Includes bibliographical references (pages 77-83)



Number of Pages



South Dakota State University


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