This paper develops a system frequency response (SFR) model and proposes a control parameter design strategy, accounting for the communication-free frequency support of offshore wind farm (OWF) connected through high voltage direct current (HVDC) transmission system. By incorporating the power dynamics of OWF and HVDC during frequency disturbance, the traditional SFR model is extended to quantitatively evaluate the contribution of HVDC-connected OWF to onshore grid frequency dynamics. Furthermore, the control parameters to provide frequency support are optimally designed based on the extended SFR model by considering constraints on wind turbine power variation and DC voltage fluctuation. Compared to the works relying on detailed simulations, the salient novelty of the paper lies in the fast and accurate system performance analysis and control parameter design, ensuring efficiency and practicality for real-world applications. Comprehensive case studies in the PSCAD/EMTDC and the MATLAB/SIMULINK platforms demonstrate that the system frequency response characteristics can be evaluated accurately and improved significantly while satisfying the operational constraints.

This paper proposes an improved vector current control (IVCC) strategy to integrate voltage source converter (VSC) based high voltage direct current (HVDC) to a very weak grid. In comparison to a constant value as used in the outer control loop in classical vector current control (VCC) strategy, the control references are adjusted according to the dynamic changes of system frequency. A small signal model including the system and the proposed control strategy is firstly developed. Based on the eigenvalue locus and the damping ratio analysis, the impact of adjusting different control loops is then investigated. Furthermore, an optimization model is built to coordinate the outer voltage control loop and the outer active power control loop of IVCC such that a wider range of phase-locked loop (PLL) gains can be applied, while reduced deviations of frequency and point of common coupling (PCC) voltage as well as a good enough fault-ride through capability can be achieved simultaneously. Finally, the effectiveness of applying IVCC in connecting VSC to a very weak grid is validated by detailed time domain simulations.

This paper proposes a methodology for radial medium-voltage distribution networks topology modeling with the voltage-power sensitivity based on smart meters data. Having different characteristic, partial least squares regression (PLS) and deep neural network (DNN) are respectively used to obtain the sensitivity. The relationship between the sensitivity and the topological position is analyzed, based on which, the topology is identified. The impendence of each line is estimated accordingly by the voltage value and the sensitivity obtained by DNN. The methods presented in this paper do not necessitate any prior topological information or additional data apart from voltage and power readings collected by smart meters. Their efficacy is initially evaluated using the IEEE-33 test case, followed by assessment across various states of the IEEE-69, demonstrating remarkable efficiency and accuracy.

This paper presents a hybrid model framework consisting of a self-organizing map clustering and the Scenario Fan Simulator model for hydropower scheduling. First, the clustering model groups hydro inflow scenarios according to their features, such as trend, distance, and variation. Then, the prominent scenarios are selected from groups to feed into the hydropower scheduling model. The results show how the proposed model is able to conduct a disaggregated level of energy dispatching and deal with the multiple energy generators. Furthermore, the proposed hybrid model can significantly reduce the computational time by 80%, with the same load shedding indications compared to the case without scenario reduction.