Siyu Leng

Integration of a bi-directional dc-dc converter model into a large-scale system simulation of a shipboard MVDC power system

To improve energy flexibility and deal with peak energy demand in shipboard power system, a bi-directional dc/dc converter is investigated for a notional U.S. Navy Medium Voltage DC (MVDC) shipboard power system. Surplus energy due to light electric load or ship-speed variation can be captured by energy storages distributed in 800 V load zones and during heavy load or black starting condition, supplied to the rest of the 5 kV MVDC system through the bi-directional dc/dc converters. This paper presents the controller optimization process using the particle swarm optimization for an isolated-type bi-directional dc-dc converter. The control performance of the proposed controller is evaluated using small-signal average models and a large-scale simulation of the notional U.S. Navy MVDC system using the real-time digital simulator.

Active power filter for three-phase current harmonic cancellation and reactive power compensation

To address power quality problems in industrial power systems, a new control scheme for three-phase active power filter is proposed. The control scheme includes two functional modules such as a current harmonic cancellation module and a reactive power compensation module. The current harmonic cancellation module is based on a multiple adaptive feed-forward cancellation algorithm for selective current harmonic identification. The reactive power compensation module utilizes the measured voltage and the estimated fundamental current to calculate reactive power. After the above information has been calculated, the corrective current reference signals can be generated for the active filter. In this way, the two control functions are integrated together so that one active filter can accomplish two functions simultaneously. Simulation results under different operating conditions demonstrate that the proposed control scheme can successfully cancel harmonic current and compensate reactive power at the point of common coupling.

Real-time particle swarm optimization based current harmonic cancellation

As a powerful optimization algorithm, Particle Swarm Optimization (PSO) has been widely applied to power systems researches. However, because of the unavoidable evaluation time for tentative solutions, most of these applications have been implemented offline. Recently, PSO was realized in real time to identify parameters of a PMSM control systems. In this paper, the Real-Time PSO (RT-PSO) algorithm was applied to current harmonic cancellation problem. RT-PSO is used to identify the fundamental current from a measured current that contains harmonics. The identified fundamental current is then used as a reference current for current harmonics cancellation. Simulation studies show that the RT-PSO algorithm can provide accurate estimation of the reference current for harmonics cancellation control using active power filters. As a capable online optimization algorithm, RT-PSO can be extensively applied to many optimization and control problems.

Distributed operation of multiple shunt active power filters considering power quality improvement capacity

A decentralized control strategy is proposed to coordinate multiple shunt active power filters (APFs) to improve power quality at the point of common coupling (PCC) in terms of power factor correction and harmonic elimination. Under the proposed control strategy, each APF uses locally measured current signals to decide the amount of power quality improvement task, which is limited to its power rating. In this way, the overall power quality improvement task is automatically distributed to the APFs without control communications. Simulation results verify the performance of the proposed control strategy.

Reconfigurable active front-end of adjustable speed drives for power quality improvement

A new control scheme is proposed to utilize the active front-end of a high performance adjustable speed drives (ASD) to solve power quality problems caused by conventional diode/thyristor drives. Under the proposed control scheme, a fully controlled active front-end ASD acts as a local power quality conditioner in order to compensate harmonic currents as well as reactive power generated by other neighboring drives. In this way, power quality problems caused by multiple motor drives can be solved locally. The proposed solution can fully utilize the capability of the active front-end of ASDs and does not require vast replacement of conventional diode/thyristor ASD sets. Therefore, it can provide flexible and economical solutions for power quality improvement compared to other custom power devices. Simulation results verify the performance of the proposed active front-end configuration and control schemes.

Robust controller design for inverter-interfaced distributed generators considering islanded operation of a microgrid

Microgrids consist of multiple distributed generators, which are normally integrated via power inverters and can employ various sustainable energy resources. Therefore, the microgrid is a new promising concept for future power systems with improved energy security, reliability, quality of power, and energy efficiency. To this end, microgrids should survive during severe power system abnormalities so that the sub-areas in the microgrids can be protected all the time. This paper focuses on a robust controller design scheme for inverter-interfaced distributed generators considering various operating modes and loading conditions of microgrids. Especially, during the island mode, the voltage and system frequency can easily change due to instant power mismatch between distributed generators and loads in the microgrid. This paper presents the design procedure of a robust optimal controller against exogenous disturbances such as voltage and frequency variation in microgrids. L1 robust control theory is applied to optimize the robust controller and a Particle Swarm Optimization algorithm is used to solve the optimal problems.

Design, modeling, and position control of a single-phase reluctance machine

This paper discusses the whole design process of a position control system of a single-phase reluctance machine under mechanical and electrical constraints. A MIMO Neural network is used to model the nonlinear properties of the machine. Based on it, a neural network based control scheme is developed to precisely control the rotor position of the designed single-phase reluctance machine. Simulation results show that a MIMO neural network model can effectively capture the nonlinear characteristics of the designed machine and the proposed neural network control scheme can control the rotor position precisely.