Stochastic Dual Algorithm for Voltage Regulation in Distribution Networks with Discrete Loads: Preprint

Emiliano Dall-Anese, Xinyang Zhou, Zhiyuan Liu, Lijun Chen

Research output: Contribution to conferencePaper

Abstract

This paper considers distribution networks with distributed energy resources and discrete-rate loads, and designs an incentive-based algorithm that allows the network operator and the customers to pursue given operational and economic objectives, while concurrently ensuring that voltages are within prescribed limits. Four major challenges include: (1) the non-convexity from discrete decision variables, (2) the non-convexity due to a Stackelberg game structure, (3) unavailable private information from customers, and (4) different update frequency from two types of devices. In this paper, we first make convex relaxation for discrete variables, then reformulate the non-convex structure into a convex optimization problem together with pricing/reward signal design, and propose a distributed stochastic dual algorithm for solving the reformulated problem while restoring feasible power rates for discrete devices. By doing so, we are able to statistically achieve the solution of the reformulated problem without exposure of any private information from customers. Stability of the proposed schemes is analytically established and numerically corroborated.
Original languageAmerican English
Number of pages9
StatePublished - 2017
Event8th IEEE International Conference on Smart Grid Communications (SmartGridComm 2017) - Dresden, Germany
Duration: 23 Oct 201726 Oct 2017

Conference

Conference8th IEEE International Conference on Smart Grid Communications (SmartGridComm 2017)
CityDresden, Germany
Period23/10/1726/10/17

Bibliographical note

See NREL/CP-5D00-72262 for paper as published in IEEE proceedings

NREL Publication Number

  • NREL/CP-5D00-68609

Keywords

  • convex relaxation
  • discrete variables
  • distributed stochastic dual algorithm
  • voltage regulation

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