Control Strategies for Using Battery Energy Storage Systems for Grid-scale Enhanced Frequency Response

  • Wenqi Ou

Student thesis: Masters ThesisMPhil


System frequency is one of the most important power quality factors. Frequency deviations would cause economic losses to the society and damage the generators. The integration of large-scale wind farms into national grids can increase the number of sudden frequency deviations. Moreover, the system inertia would fall because those renewable energy sources (RES) like wind and solar are not able to provide inertia like the conventional generators do. Therefore, it is desirable to find ways of dealing with these undesirable frequency excursions. Battery Energy Storage System (BESS) is a feasible solution to supply a certain amount of electric power and energy in a short time (about 10 times faster than the conventional generators). However, the cost to install and operate a BESS is still expense at this stage. Therefore, it is important to find optimal allocations and sizing of BESSs.

This dissertation describes a study for identifying the optimal frequency regulation within the UK national grid using Battery Energy Storage Systems (BESSs) distributed within the electrical power system. The starting point was historical generation, load and wind forecast data. From this a new dynamic model and simulation has been developed that exhibits the correct dynamic behavior observed in the actual data sets. The new dynamic simulation was then used to optimize the use of distributed BESSs to provide Enhanced Frequency Response (EFR) in the UK national power grid in the presence of large generation/load imbalances caused by variable renewable generation output.

The results of this work show that it is feasible to find a suitable optimal siting and sizing of BESS that can provide frequency response caused by the increasing integration of renewable energy source to meet low carbon obligations in the UK power system. The results also revealed that with the battery energy storage owners could make profit by bidding in to the National Frequency Response service.
Date of Award29 May 2019
Original languageEnglish
Awarding Institution
  • University of Bath
SupervisorRoderick Dunn (Supervisor) & Francis Robinson (Supervisor)

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