Reduction of battery energy storage degradation in peak shaving operation through load forecast dependent energy management

Nils Collath, Stefan Englberger, Andreas Jossen, Holger Hesse

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Scopus citations

Abstract

One application for the increasing number of battery energy storage systems is the reduction of demand charges for industrial consumers through peak shaving. Commonly used lithium-ion batteries are subject to degradation due to a multitude of cell-internal aging processes that can have significant impact on the economics of a system. In this contribution, we propose a rule-based operation strategy to reduce battery degradation during peak shaving through the use of load forecasting. Since load forecasting methods include significant inaccuracies, the operation strategy focuses on means to handle forecast errors. The performance of this operation strategy is assessed through time series based simulations and comparison with reference scenarios. A state of health of 89.7 % is remaining with the proposed strategy after five operating years. This is a reduction of capacity loss of 4.9 % percentage points compared to an often implemented naive peak shaving strategy with 84.8 % remaining state of health, while achieving the same performance in terms of reducing load peaks successfully.

Original languageEnglish
Title of host publicationNEIS 2020 - Conference on Sustainable Energy Supply and Energy Storage Systems
EditorsDetlef Schulz
PublisherVDE VERLAG GMBH
Pages249-254
Number of pages6
ISBN (Electronic)9783800753598
StatePublished - 2020
Event8th Conference on Sustainable Energy Supply and Energy Storage Systems, NEIS 2020 - Hamburg, Germany
Duration: 14 Sep 202015 Sep 2020

Publication series

NameNEIS 2020 - Conference on Sustainable Energy Supply and Energy Storage Systems

Conference

Conference8th Conference on Sustainable Energy Supply and Energy Storage Systems, NEIS 2020
Country/TerritoryGermany
CityHamburg
Period14/09/2015/09/20

Keywords

  • Aging
  • Battery energy storage system
  • Degradation
  • Lithium-ion
  • Load forecasting
  • Peak shaving

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