
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.
optimisation, battery storage plants, dynamic degradation, regulation services, dynamic lifetime degradation, battery employment, grid infrastructures, economic analysis, national grid, secondary cells, dynamic modelling, Batteries, Frequency response, pricing, techno-economic potential, profitability, sophisticated battery models, service participation, scheduling, smart grid, lower technical toll, particle swarm optimisation, power generation economics, optimal despatch schedule, price declarations, energy storage, highest profit, economic benefit, Engineering (General). Civil engineering (General), smart power grids, flexibility, dynamic frequency, balancing mechanism actions, technical cost, rigorous optimisation, optimum scenario, battery energy storage systems, TA1-2040, particle swarm optimisation algorithm, ordinarily frequency response
optimisation, battery storage plants, dynamic degradation, regulation services, dynamic lifetime degradation, battery employment, grid infrastructures, economic analysis, national grid, secondary cells, dynamic modelling, Batteries, Frequency response, pricing, techno-economic potential, profitability, sophisticated battery models, service participation, scheduling, smart grid, lower technical toll, particle swarm optimisation, power generation economics, optimal despatch schedule, price declarations, energy storage, highest profit, economic benefit, Engineering (General). Civil engineering (General), smart power grids, flexibility, dynamic frequency, balancing mechanism actions, technical cost, rigorous optimisation, optimum scenario, battery energy storage systems, TA1-2040, particle swarm optimisation algorithm, ordinarily frequency response
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