access icon free Network allocation of BESS with voltage support capability for improving the stability of power systems

The stability of future power systems will be challenged by high shares of converter-based generation technologies (CBGTs). To prevent instability problems, it is essential to explore new technologies and control strategies able to counteract the negative effects that CBGTs may have. In this regard, promising technologies are battery energy storage systems (BESSs), which can provide a wide range of benefits from a stability viewpoint. Current methodologies that quantify and allocate BESSs in electrical networks have been developed from an economic perspective considering a steady-state formulation of the system. Accordingly, these allocation approaches do not exploit all the benefits that BESSs can offer to system stability. This study proposes a novel optimisation methodology for efficient BESS allocation in systems with high levels of CBGTs. The model improves system stability by considering BESSs with voltage support capability during contingencies. The allocation is solved by a genetic algorithm considering transient voltages throughout the network busbars and their short circuit levels. The methodology was implemented in the 39-busbar New England system. Compared to traditional approaches, the proposed BESS allocation method enables significant improvements in the stability of the system during critical contingencies.

Inspec keywords: busbars; genetic algorithms; power convertors; power grids; battery storage plants; power system transient stability

Other keywords: network allocation; transient voltages; control strategies; power system stability; novel optimisation methodology; converter-based generation technologies; CBGTs; voltage support capability; BESS allocation method; optimisation methodology; network busbars; instability problems; 39-busbar New England system; stability viewpoint; short circuit levels; steady-state formulation; battery energy storage systems; electrical networks; genetic algorithm

Subjects: Other power stations and plants; Optimisation techniques; Power convertors and power supplies to apparatus; Power system control

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