Techno‐economic potential of battery energy storage systems in frequency response and balancing mechanism actions

Batteries offer a combination of balancing and regulation services within a smart grid to improve its resilience and flexibility. Maintaining an acceptable state of health and the highest rate of return requires dynamic modelling of the asset and rigorous optimisation. The authors compare the technical cost and economic benefit of battery employment in dynamic frequency and balancing mechanism actions in a smart grid. They use the services procured by National Grid in the UK as a case study but the methodology is globally applicable, including developing grid infrastructures. Their methodology yields the most optimum scenario of service participation, accounting for the dynamic degradation and considering variable pricing of electricity throughout the day. Additionally, it advises the most optimal despatch schedule and price declarations for the battery over the course a day and a year, employing particle swarm optimisation algorithm and historic data. Their results demonstrate that ordinarily frequency response is preferred due to its lower technical toll and payments for availability rather than despatch. However, the proposed despatch schedule including both services provides the highest profit. They anticipate this methodology to become the basis for more sophisticated battery models that integrate the service despatch optimisation, dynamic lifetime degradation and economic analysis.

[1]  Ali T. Al-Awami,et al.  Coordinated bidding of ancillary services for vehicle-to-grid using fuzzy optimization , 2015, IEEE Transactions on Smart Grid.

[2]  Verena Jülch,et al.  Comparison of electricity storage options using levelized cost of storage (LCOS) method , 2016 .

[3]  Markus Mueller,et al.  A Numerical and Graphical Review of Energy Storage Technologies , 2014 .

[4]  Yun Seng Lim,et al.  Frequency response services designed for energy storage , 2017 .

[5]  A. Mullane,et al.  An Assessment of the Impact of Wind Generation on System Frequency Control , 2010, IEEE Transactions on Power Systems.

[6]  Willett Kempton,et al.  Vehicle-to-grid power implementation: From stabilizing the grid to supporting large-scale renewable energy , 2005 .

[7]  Youngsik Kim,et al.  Commercial and research battery technologies for electrical energy storage applications , 2015 .

[8]  Hamidreza Zareipour,et al.  Operation Scheduling of Battery Storage Systems in Joint Energy and Ancillary Services Markets , 2017, IEEE Transactions on Sustainable Energy.

[9]  Sadrul Ula,et al.  Customer-Side SCADA-Assisted Large Battery Operation Optimization for Distribution Feeder Peak Load Shaving , 2019, IEEE Transactions on Smart Grid.

[10]  Martin P. Foster,et al.  A Battery Energy Management Strategy for U.K. Enhanced Frequency Response and Triad Avoidance , 2018, IEEE Transactions on Industrial Electronics.

[11]  Diego Luca de Tena,et al.  Integrated modelling of variable renewable energy-based power supply in Europe , 2017 .

[12]  Chris Jones,et al.  Battery storage for post-incentive PV uptake? A financial and life cycle carbon assessment of a non-domestic building , 2017 .

[13]  R. Ghorbani,et al.  Providing frequency regulation reserve services using demand response scheduling , 2016 .

[14]  Surya Santoso,et al.  Battery Energy Storage State-of-Charge Forecasting: Models, Optimization, and Accuracy , 2019, IEEE Transactions on Smart Grid.

[15]  Tomoyuki Matsuda,et al.  Degradation diagnosis of lithium-ion batteries with a LiNi0.5Co0.2Mn0.3O2 and LiMn2O4 blended cathode using dV/dQ curve analysis , 2018, Journal of Power Sources.

[16]  Hongseok Kim,et al.  Data-driven battery degradation model leveraging average degradation function fitting , 2017 .

[17]  Ross Baldick,et al.  Governor Rate-Constrained OPF for Primary Frequency Control Adequacy , 2014, IEEE Transactions on Power Systems.

[18]  Chongqing KANG,et al.  Optimal operation strategy for distributed battery aggregator providing energy and ancillary services , 2018 .

[19]  Sanjib Kumar Panda,et al.  A Siting and Sizing Optimization Approach for PV–Battery–Diesel Hybrid Systems , 2018, IEEE Transactions on Industry Applications.

[20]  R. Saravanan,et al.  Scheduling optimisation of flexible manufacturing systems using particle swarm optimisation algorithm , 2005 .

[21]  Ma Qian,et al.  Economic Operation Optimization for 2nd Use Batteries in Battery Energy Storage Systems , 2019, IEEE Access.

[22]  Yang Gao,et al.  Lithium-ion battery aging mechanisms and life model under different charging stresses , 2017 .

[23]  Dipti Srinivasan,et al.  An improved particle swarm optimisation algorithm applied to battery sizing for stand-alone hybrid power systems , 2016 .

[24]  Bala Venkatesh,et al.  Short-term scheduling of thermal generators and battery storage with depth of discharge-based cost model , 2015, 2016 IEEE Power and Energy Society General Meeting (PESGM).

[25]  Hrvoje Pandzic,et al.  Optimal Operation and Services Scheduling for an Electric Vehicle Battery Swapping Station , 2015 .