The integration of battery energy storage systems in modern distribution networks

  • Ahmed A.Raouf Mohamed

Student thesis: Doctoral ThesisDoctor of Philosophy


With the ongoing rapid deployment of renewable generation and low carbon technologies (LCT) in the electrical networks, network operators have been recently integrating smart solutions to actively manage their electricity networks while assuring supply security, stability and reliability. Battery energy storage systems (BESS) are one possible smart solution that is being embraced lately by network operators to provide a range of ancillary services. This thesis explores the potential applications of BESS in active distribution networks with high uptake of renewable generation and LCTs. Different BESS sizes are investigated that include grid-scale for medium voltage (MV) networks, community-scale for low voltage (LV) networks, and behind the meter residential units.

At the MV network level, a planning methodology is proposed to determine the best possible BESS sizes and locations to provide congestion management and solve network violations. To maximize BESS utilization, two operational strategies are introduced to enhance network performance by regulating voltage and line flows in addition to optimizing the power factor and losses. These strategies settle the BESS active/reactive power schedule on a look-ahead basis in addition to considering the forecasting uncertainties by employing real-time control phases. Whilst the viability of BESS investments is still an open question, in this thesis, this question is addressed by investigating the economic feasibility and profitability of deploying BESS for sole and stacked services on the island of Ireland. Furthermore, a novel forecasting model for the single electricity market is developed to be used in maximizing the BESS energy arbitrage revenues as well as assisting energy market participants in their bidding decisions.
At the LV network level, the impact of high uptake of electric vehicles and solar PV on the network performance is studied for different penetrations. The solution-based community BESS is investigated to improve network operation while maintaining technical constraints within acceptable limits by proposing sizing and scheduling methodologies. While many studies in the literature have addressed the potential impact of different types of LCTs on the LV networks, the impact of high residential BESS uptake on LV networks is not fully understood. Hence, this thesis explores the impact of the high uptake of autonomous residential BESS on the LV network. In addition, useful suggestions and control methods are introduced to assist network operators in maximizing the utilization of residential BESS with low costs and complexity. The objectives of the proposed methodologies for MV and LV networks align with recent projects trailed by the network operator of Northern Ireland (NIE Networks), particularly the Facilitation of Energy Storage Services, Nodal Controller, and FLEX.

At the residential level, control strategies for the behind the meter BESS are proposed that aim to mitigate the LCT impacts by flattening the household’s load profile as well as reducing the electricity bill. To boost profitability, sizing methodologies are introduced to find the optimal PV/BESS sizes that maximize revenues. In addition, comprehensive techno-economic analyses are provided for small-scale PV BESS systems under different scenarios and investment parameters.

Various case studies are conducted throughout the thesis and the technical results prove the efficacy of the proposed BESS methodologies in supporting networks to accommodate safely high penetrations of LCTs and renewable generation. The economic analysis shows that BESS investment is currently unattractive without incentives unless it is engaged in enhanced transmission services. However, with the ongoing reduction in BESS prices, their integration is expected to be attractive at all network levels in the near future.

Thesis embargoed until 31 July 2023
Date of AwardJul 2022
Original languageEnglish
Awarding Institution
  • Queen's University Belfast
SponsorsINTERREG VA Programme (European Union)
SupervisorRobert Best (Supervisor), Xueqin Amy Liu (Supervisor) & D John Morrow (Supervisor)


  • Energy storage systems
  • distributed generation
  • renewable energy
  • optimisation
  • power systems
  • solar PV systems
  • distribution networks
  • control and operation
  • batteries
  • smart grid
  • power dispatch
  • scheduling
  • forecasting
  • energy market
  • cost-effectiveness analysis
  • techno-economic analysis

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