Peak demand shaving and load-levelling using a combination of bin packing and subset sum algorithms for electrical energy storage system scheduling

An algorithm that uses demand profile information and a minimal set of energy storage system (ESS) parameters is formulated in this study for obtaining ESS operation schedules to achieve peak demand shaving and load-levelling. The algorithm is developed by formulating an electricity demand profile a...

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Published inIET science, measurement & technology Vol. 10; no. 5; pp. 477 - 484
Main Authors Agamah, Simon U, Ekonomou, Lambros
Format Journal Article
LanguageEnglish
Published The Institution of Engineering and Technology 01.08.2016
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ISSN1751-8822
1751-8830
DOI10.1049/iet-smt.2015.0218

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Abstract An algorithm that uses demand profile information and a minimal set of energy storage system (ESS) parameters is formulated in this study for obtaining ESS operation schedules to achieve peak demand shaving and load-levelling. The algorithm is developed by formulating an electricity demand profile and ESS as a combination of the one-dimensional bin packing problem and the subset sum problem using sets of mathematical equations. The electrical system undergoes specific transformations in the charging and discharging phases of the ESS and heuristic algorithms for solving these problems are applied to obtain a viable operation schedule to meet these objectives. A comparative analysis with another algorithm is presented for verification. Results for a case study are also presented alongside a discussion to show a practical application of the algorithm.
AbstractList An algorithm that uses demand profile information and a minimal set of energy storage system (ESS) parameters is formulated in this study for obtaining ESS operation schedules to achieve peak demand shaving and load‐levelling. The algorithm is developed by formulating an electricity demand profile and ESS as a combination of the one‐dimensional bin packing problem and the subset sum problem using sets of mathematical equations. The electrical system undergoes specific transformations in the charging and discharging phases of the ESS and heuristic algorithms for solving these problems are applied to obtain a viable operation schedule to meet these objectives. A comparative analysis with another algorithm is presented for verification. Results for a case study are also presented alongside a discussion to show a practical application of the algorithm.
Author Agamah, Simon U
Ekonomou, Lambros
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  givenname: Lambros
  surname: Ekonomou
  fullname: Ekonomou, Lambros
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  organization: Department of Electrical and Electronic Engineering, City University London, Northampton Square, London EC1V 0HB, United Kingdom
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10.1109/TPWRS.2012.2230277
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10.1109/TPWRS.2012.2187315
10.1109/TEC.2005.853746
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Issue 5
Keywords one-dimensional bin packing problem
heuristic algorithms
electrical energy storage system scheduling
discharging phase
electricity
discharges (electric)
set theory
subset sum algorithms
electricity demand profile
bin packing
load-levelling
charging phase
energy storage
viable operation schedule
mathematical equations
peak demand shaving
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SubjectTerms Algorithms
bin packing
charging phase
discharges (electric)
discharging phase
electrical energy storage system scheduling
electricity
electricity demand profile
Energy storage
heuristic algorithms
load‐levelling
Mathematical analysis
mathematical equations
one‐dimensional bin packing problem
peak demand shaving
Peak load
Phases
Regular Papers
Schedules
set theory
Shaving
subset sum algorithms
Transformations (mathematics)
viable operation schedule
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Title Peak demand shaving and load-levelling using a combination of bin packing and subset sum algorithms for electrical energy storage system scheduling
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