In this study, a novel methodology is proposed for sensitivity‐based tuning and analysis of derivative‐based fast active power injection (FAPI) controllers in type‐4 wind turbine units integrated into a low‐inertia power system. The FAPI controller is attached to a power electronic interfaced generation (PEIG) represented by a generic model of wind turbines type 4. It consists of a combination of droop and derivative controllers, which is dependent on the measurement of the frequency. The tuning methodology performs parametric sensitivity to search for the most suitable set of parameters of the attached FAPI that minimises the maximum frequency deviation in the containment period. The FAPI is adjusted to safeguard system stability when increasing the share of PEIG. Since the input signal of the FAPI is the measured frequency, the impact of different values and parameter settings of the phase‐locked loop used for the FAPI controller is also investigated. Detailed validation with a full‐scaled wind power converter is also provided with a real‐time digital simulator testbed. Obtained simulation results using a three‐area test system, identify the maximum achievable degree of increase in the share of wind power when a proper combination of wind park locations considering their suggested settings for inertia emulation.
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 multiarea 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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