Dynamic optimal power flow based scheduling framework for battery energy storage system

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Battery energy storage systems (BESS) are identified as a key component in the transition to a low carbon, more flexible electrical network. Their operation must be properly scheduled to achieve the set objective. This paper describes a dynamic Optimal Power Flow (DOPF) based scheduling framework to optimise the day(s)-ahead operation of a grid-scale BESS in order to reduce the predicted limits on renewable generation and smooth the demand to be supplied by conventional generators on a network. In DOPF, the generators modelling exports and imports of the BESS along with other generating units across the entire network and across the time horizon are integrated within a single network. Then an AC OPF is applied to dispatch their power outputs to minimise the total generation cost while satisfying power balance equations, unit and network constraints at each time step along with intertemporal constraints associated with the state of charge (SOC). In addition, the DOPF developed here incorporates the commonly used constant current-constant voltage charging profile which is represented in the SOC domain. Taking into account the practical application of a 1 MW BESS on a particular 33 kV network, the scheduling framework is designed to fulfil realistic requirements of fully utilising the available energy capacity of the BESS in each cycle and completing up to one cycle per day.
Original languageEnglish
Number of pages9
JournalCSEE Journal of Power and Energy Systems
Publication statusAccepted/In press - 18 Mar 2021


  • battery energy storage
  • day(s)-ahead scheduling
  • dynamic optimal power flow
  • load smoothing
  • renewable energy

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