This paper presents an automation strategy for multi-terminal HVDC (MT-HVDC) systems combining a dc optimal power flow (dc OPF) routine and a unified reference controller (URC). In the presented automatic framework, the dc OPF algorithm is implemented at the power dispatch center (PDC) of the MT-HVDC system to find optimal reference operation points of the power converters to minimize the losses during the operation of the MT-HVDC grid and solves the contradiction between minimizing losses and preventing commutation failure. At the local control systems, the operating points of the voltage-source converter (VSC) stations are tuned based on the calculations executed in the PDC, which enables fast response to power fluctuation and ensures a stable dc voltage. However, if the communication between the two control layers is lost, the MT-HVDC grid remains stable based on the pre-defined V -P droop characteristics for the power converter stations till the connection establishes again, and a set of new operating points is generated and sent. The static and dynamic simulations conducted on the CIGRE B4 HVDC test grid establish the efficient and effective grid control performance with the proposed automation strategy. The analysis shows that the proposed control scheme achieves the desired minimum losses while, at the same time, satisfying the system constraints.INDEX TERMS CIGRE B4 HVDC test system, DC optimal power flow, multi-terminal HVDC systems (MT-HVDC), power dispatch center (PDC), unified control strategy.
Although an analytical design approach-based digital controller—which is essentially a deadbeat controller—shows zero steady-state error and no intersampling oscillations, it takes a finite number of sampling periods to settle down to a steady-state value. This paper describes the application of a derivative-free Nelder–Mead (N–M) simplex method to the digital controller for retuning of its coefficients intelligently to ensure improved settling and rise times without disturbing the deadbeat controller characteristics (i.e., no ripples between the sampling periods and no steady-state error). A switching-mode buck regulator working at 1 MHz in continuous conduction mode (CCM) is considered as a plant. Numerical simulation results depict that the N–M algorithm-based optimized digital controller not only shows improved steady-state and transient performance but also guarantees rigorous robustness against model uncertainty and disturbance as compared to its traditional counterpart, as well as the other optimized digital controller fine-tuned through other derivative-free metaheuristic optimization techniques, such as the genetic algorithm (GA). A system generator-based hardware software co-simulation is also performed to validate the simulation results.
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