A New Formulation for Optimal Tuning of Fast Frequency Support in Multi-Energy Systems

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Abstract

Power electronic dominated power systems formed nowadays are characterized by fast and frequent dynamics, limited short circuit support, low inertia conditions and lack of inertial support. Under these conditions, coping with active power imbalances in a power system may becomes a significant challenge for transmission system operators (TSOs) that may experience extensive frequency deviations and steep rates of change of frequency (RoCofs). To deal with the frequency stability issues encountered, power electronic interfaced (PEI) units can rapidly respond to provide fast frequency support (FFS) taking advantage of their controllability levels and their rapid response to setpoint changes. FFS may depend on the active power gradient (APG) control strategy that determines the required amount of active power, and the rate the power injection takes place. However, when multiple elements try to regulate simultaneously the frequency adverse control actions such as insufficient or over frequency regulation may be encountered. To solve this issue, this paper proposes a formulation for the optimal and coordinative tuning of the APG controllers of PEI elements installed in a multi-area, multi-energy hybrid HVDC/HVAC power system with modular multilevel converter (MMC) HVDC links and proton exchange membrane (PEM) electrolyzers. This formulation focuses on creating an artificially coupled frequency response for an electromagnetically decoupled multi-area system taking advantage of the available active power reserves and the inertia levels of each area. In that way, an active power imbalance can be optimally shared among the interconnected areas leading to effectively improved frequency response for the affected and supporting areas. The proposed formulation is solved using the mean variance mapping optimization (MVMO) algorithm after a series of RMS simulations is performed in DIgSILENT PowerFactory 2021.

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- Embargo expired in 28-04-2023