Negotiation-based task scheduling and storage control algorithm to minimize user's electric bills under dynamic prices

Ji Li, Yanzhi Wang, Xue Lin, Shahin Nazarian, Massoud Pedram

Research output: Chapter in Book/Report/Conference proceedingConference contribution

14 Scopus citations

Abstract

Dynamic energy pricing is a promising technique in the Smart Grid to alleviate the mismatch between electricity generation and consumption. Energy consumers are incentivized to shape their power demands, or more specifically, schedule their electricity-consuming applications (tasks) more prudently to minimize their electric bills. This has become a particularly interesting problem with the availability of residential photovoltaic (PV) power generation facilities and controllable energy storage systems. This paper addresses the problem of joint task scheduling and energy storage control for energy consumers with PV and energy storage facilities, in order to minimize the electricity bill. A general type of dynamic pricing scenario is assumed where the energy price is both time-of-use and power-dependent, and various energy loss components are considered including power dissipation in the power conversion circuitries as well as the rate capacity effect in the storage system. A negotiation-based iterative approach has been proposed for joint residential task scheduling and energy storage control that is inspired by the state-of-the-art Field-Programmable Gate Array (FPGA) routing algorithms. In each iteration, it rips-up and re-schedules all tasks under a fixed storage control scheme, and then derives a new charging/discharging scheme for the energy storage based on the latest task scheduling. The concept of congestion is introduced to dynamically adjust the schedule of each task based on the historical results as well as the current scheduling status, and a near-optimal storage control algorithm is effectively implemented by solving convex optimization problem(s) with polynomial time complexity. Experimental results demonstrate the proposed algorithm achieves up to 64.22% in the total energy cost reduction compared with the baseline methods.

Original languageEnglish (US)
Title of host publication20th Asia and South Pacific Design Automation Conference, ASP-DAC 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages261-266
Number of pages6
ISBN (Electronic)9781479977925
DOIs
StatePublished - Mar 11 2015
Event2015 20th Asia and South Pacific Design Automation Conference, ASP-DAC 2015 - Chiba, Japan
Duration: Jan 19 2015Jan 22 2015

Publication series

Name20th Asia and South Pacific Design Automation Conference, ASP-DAC 2015

Other

Other2015 20th Asia and South Pacific Design Automation Conference, ASP-DAC 2015
CountryJapan
CityChiba
Period1/19/151/22/15

ASJC Scopus subject areas

  • Computer Science Applications
  • Electrical and Electronic Engineering
  • Control and Systems Engineering
  • Modeling and Simulation

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    Li, J., Wang, Y., Lin, X., Nazarian, S., & Pedram, M. (2015). Negotiation-based task scheduling and storage control algorithm to minimize user's electric bills under dynamic prices. In 20th Asia and South Pacific Design Automation Conference, ASP-DAC 2015 (pp. 261-266). [7059015] (20th Asia and South Pacific Design Automation Conference, ASP-DAC 2015). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASPDAC.2015.7059015