Hesan Vahedi

Distributed adaptive control design for cluster of converters in DC distribution systems

In this paper, we address the control design problem under the systems model uncertainty utilizing the adaptive control. First, the adaptive control based on the model reference adaptive control technique is presented. Subsequently, the adaptive control technique is applied to a multi-converter system to guarantee the bus-voltage stability and accurate current sharing. Simulation in MATLAB/Simulink is conducted to verify the effectiveness of the proposed control algorithm under typical scenarios including non-linear load change and network topology changes caused by converter failures.

Seamless inverter control scheme for shore-to-ship application

This paper proposes a general seamless control scheme of inverter for the purpose of ship-to-shore connection by means of active islanding detection method. In the proposed system, the Sandia Frequency Shift (SFS) method combined with a frequency protection scheme is used to detect the islanding instant. The SFS parameter selection is performed using a new phase criterion proposed in the literature. and implemented to add more functionality to the control algorithm.

Distributed power management for DC distribution system with model uncertainties

This paper presents an application of combined model reference adaptive control to a notional DC microgrid system for power sharing and bus voltage regulation. The algorithm is presented in detail and a brief stability analysis is provided. Then, the control algorithm is implemented on a two-converter system feeding a single load through a bus to demonstrate the current sharing accuracy and bus voltage stability provided by the method. MATLAB/Simulink is used to validate the effectiveness of the developed control algorithm through case studies representing typical operating scenarios.

Optimal sensor placement for MVDC ship power system

This paper offers a metric for the use of synchronized electrical sensor measurements for complete observability of the zonal MVDC ship power system. The placement of the multi-port sensors with the use of nodal voltage and the branch currents utilizing time synchronized measurements is studied in this paper. The Bacterial Foraging Algorithm (BFA), specifically desirable in high-dimensional function optimization, is used to minimize the total number of the sensors and the redundancy required for each of the system states. Simulation results on the 6 zone MVDC system are presented in this paper.

Predictive energy management for MVDC all-electric ships

The integration of energy storage devices is essential to handle the high-power ramp-rate loads in all-electric ships. This paper presents a novel predictive control method to manage the energy flow among distributed resources including generators and a bulk energy storage. The system objective, which guarantees the high-power ramp-rate operation of pulsed power load, will be formulated based on the state of charge of the energy storage. The solution of the formulated objective provides the optimal charging and discharging profile for the energy storage to handle high ramp-rate demands. Simulation results in a 12 kV–100 MW MVDC ship power system validate the proposed control algorithm.

Coordinating multiple energy storages using MPC for ship power systems

Pulsed power loads present a difficult scenario for ship power systems to handle. Loads such as radar or energy weapons often demand a large amount of power in a short amount of time. This creates issues for the generators that supply the power to these loads due to the ramp rate constraints. By incorporating energy storage and combining the energy producers and users into a single power system, the ability to service a wide variety of loads is enhanced greatly. However, coordinating the generators and energy storages to meet the load demand is necessary. An Energy Management control layer must be used to dictate the power output of each of the producers to meet the load demand. A model predictive control technique within the Energy Management is used to provide optimal power setpoints for the energy storages in cases where the generators ramp rates cannot meet the load demand.

Distributed control implementation for zonal MVDC ship power systems

In this paper, we present a potential distributed adaptive control architecture applied to a zonal medium voltage DC (MVDC) ship power systems. The power sharing in the MVDC network among distributed generators will be presented first. Second, the active and reactive power sharing among zones in the low voltage AC (LVAC) network will be addressed. The effect of control in LVAC network on the MVDC network and vice-versa regarding power sharing and voltage stability will be investigated in this paper for the first time. Simulation results in MATLAB/Simulink and PLECS validate the promising distributed control architecture for ship power systems.

Evaluation framework for power and energy management shipboard distribution controls

Automated power and energy management systems (APEMS) are unifying control systems that coordinate individual power system components and present appropriate information to system operators. This paper presents ongoing work to establish a methodology and framework for evaluating such systems. As the design space offers many degrees of freedom including functional decomposition, choice of sensors, means of communication, and controls, systematic exploration and comparison of viable options is critical to designing a solution that maximizes overall system performance. This paper presents on initial progress towards a new unified, flexible, and scalable methodology that effectively evaluates performance and objectively contrasts candidate APEMS solutions.

Dynamic Behavioral Observation in Power Systems Utilizing Real-Time Complexity Computation

In this paper, a novel real-time complexity measurement (RCM) through the approximate entropy calculation is put forward to detect the dynamical changes in the power system. These dynamical changes (can be seen as irregularities) are able to drive the system into instability. The detection of these irregularities based on the RCM technique brings a clear understanding of the system interactions when the system undergoes changes in terms of parameters or the topology. Unlike the conventional linear-based tools, which are highly reliant on the model, this technique is independent of the model. In this paper, three solid state transformers (SSTs) in a micro-grid are considered as a test system. The test system is evaluated under different scenarios implying different types of dynamics for each of three SSTs. The performance of the proposed RCM method is verified using a real-time processor coordinated with the test system.

High impedance fault detection utilizing real-time complexity measurement

This paper presents a High Impedance Fault (HIF) Detection method based on the Real-time Complexity Measurement (RCM). The proposed method is a passive technique which does not need any additional equipment to perturb the system parameters, i. e, voltage or current. Thus, it can be easily implemented in an industrial processor. Additionally, in the proposed method because no signal is injected to the system, it does not affect the power quality. In this study, a Solid State Transformer (SST) in a microgrid is considered as the test system. The instantaneous RMS voltage at the load side of the SST is imported to a real-time processor where the complexity of the time-series data is measured. Results confirm the dependability of the proposed method in the HIF detection.