Peak power reduction in hybrid energy systems with limited load forecasts

Yash V. Pant, Truong X. Nghiem, Rahul Mangharam

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

3 Scopus citations

Abstract

Hybrid energy systems, which consist of a load powered by a source and a form of energy storage, find applications in many systems, e.g., the electric grid and electric vehicles. A key problem for hybrid energy systems is the reduction of peak power consumption to ensure cost-efficient operation as peak power draws require additional resources and adversely affect the system reliability and lifetime. Furthermore, in some cases such as electric vehicles, the load dynamics are fast, not perfectly known in advance and the on-board computation power is often limited, making the implementation of traditional optimal control difficult. We aim to develop a control scheme to reduce the peak power drawn from the source for hybrid energy systems with limited computation power and limited load forecasts. We propose a scheme with two control levels and provide a sufficient condition for control of the different energy storage/generation components to meet the instantaneous load while satisfying a peak power threshold. The scheme provides performance comparable to Model Predictive Control, while requiring less computation power and only coarse-grained load predictions. For a case study, we implement the scheme for a battery-supercapacitor-powered electric vehicle with real world drive cycles to demonstrate the low execution time and effective reduction of the battery power (hence temperature), which is crucial to the lifetime of the battery.

Original languageEnglish (US)
Title of host publication2014 American Control Conference, ACC 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages4212-4217
Number of pages6
ISBN (Print)9781479932726
DOIs
StatePublished - 2014
Externally publishedYes
Event2014 American Control Conference, ACC 2014 - Portland, OR, United States
Duration: Jun 4 2014Jun 6 2014

Publication series

NameProceedings of the American Control Conference
ISSN (Print)0743-1619

Conference

Conference2014 American Control Conference, ACC 2014
Country/TerritoryUnited States
CityPortland, OR
Period6/4/146/6/14

Keywords

  • Automotive
  • Optimization
  • Predictive control for linear systems

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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