This paper proposes a state feedback primary control strategy for microgrids with multiple distributed energy resource units, improving their transient behavior in both islanded and grid-connected modes of operation. To that end, the interaction of each distributed energy resource unit within the microgrid is modeled as a lumped dynamic system, which results to be nonlinear and multivariable. For the closed-loop control of such multivariable systems, the full state feedback formulation is preferred which requires a suitable state observer. For the design of the observer and feedback gains, the solution of the linear-quadratic estimation and regulation problems is considered. For simplicity, an approximate linear model at a representative operating point is derived. The linear quadratic Gaussian/loop-transfer recovery is adopted as the design procedure to optimize the trajectory of the state variables subject to a desirable actuation effort, in this case of the voltage amplitude and frequency, yielding a solution that is robust to model uncertainties. The effectiveness of the strategy is assessed through time-domain simulation on the CIGRE benchmark medium-voltage distribution network with three distributed energy resource units. These results are compared to those obtained with conventional static droop gains and with a state-of-the-art technique from the literature.

The dynamic performance of a microgrid is governed by the decentralized primary control strategy that is embedded in each of its hosted Distributed Energy Resource (DER) units. The primary control computes the voltage synthesized by the interfacing voltage-sourced converter such that the DER unit contributes active and reactive powers in support of the microgrid voltage amplitude and frequency. These operational requirements must be satisfied with respect to the converter safety and physical limitations, such as the limited magnitude of the converter output current and terminal voltage. In this paper, all the control requirements mentioned above are taken into account in a single constrained optimization problem using the framework of Model-based Predictive Control (MPC). Solving the primary control problem in this way allows the microgrid to respond to major disturbances such short-circuit faults and transitions between modes of operation, while the electronically-interfaced DER units operate within operational and safety limits.

Doubly fed induction generators (DFIGs) are used in variable speed wind energy conversion systems. Field oriented control (FOC) of this type of generators requires the availability of a rotor position measurement or estimation. Hence, for sensorless implementations, rotor position observers have to be integrated to the control algorithm. In this paper, the observability of the DFIG is analyzed and an extended Kalman filter (EKF) is proposed as rotor position observer. The performance of the EKF is verified experimentally in a 4[kW] prototype.

The control law of electronically-interfaced distributed energy resources (DERs) must be able to maintain the stability and voltage regulation of the host microgrid in the two modes of operation. Ideally, this should be achieved by a decentralized primary control strategy that is independent of any communication infrastructure in order to increase the resilience of the microgrid. This is challenging as the primary control objectives in islanded and grid-connected modes of operation are conflicting. This paper proposes a decentralized control law for DER units based on state feedback and disturbance rejection. The controller provides an integral action which enables output current reference tracking. An ad-hoc partial input saturation technique is also proposed in order to prevent the integral action from having an adverse impact on the voltage amplitude and frequency regulation in the islanded mode of operation. The effectiveness of the proposed control strategy is demonstrated via a time-domain simulation of a mediumvoltage distribution network with three embedded DER units, as well as through an experimental three-bus microgrid with two DER units. The results demonstrate the robustness of the proposed control strategy to transitions between the modes of operation and other network topological changes.

This work proposes a control design procedure based on Linear Matrix Inequalities (LMI) for integrating Distributed Energy Resources (DERs) in microgrid systems. Each DER uses local measurements as feedback, so this proposal results in a method to design a decentralized primary control. The dynamic model employed to synthesize such a controller presents an unmeasured state vector, model uncertainties, and random disturbances. To simultaneously deal with all these difficulties while ensuring the closed-loop stability and multiple performance specifications, this work is formulated in terms of a single Lyapunov function. To find this Lyapunov function and synthesize the controller gains, a convex optimization problem that involves LMIs is required to be solved. The controller results in a linear discrete-time output-feedback form, facilitating its implementation. The time-domain simulation of a microgrid system is performed in the software PSCAD/EMTDC with four DERs to validate the control design procedure’s effectiveness.

The synchronous reluctance motor (SynRM) is gaining popularity for general purpose drivers, where the sensorless operation is important. It is well known that, at low-speed, the saliency of these machines can be exploited for sensorless control down to stand-still through high-frequency (HF) signal injection. Nevertheless, the use of a separate HF model makes more complex the integration with the fundamental model valid at higher speeds. In this paper, an observability analysis is presented, leading to a single observer that captures both the fundamental and high-frequency characteristics of the machine. This leads to the proposal of a single observer, based on the extended Kalman filter algorithm, that is able to merge the saliency information obtained through HF injection and the fundamental information from the back-EMF of the machine. This strategy maximizes the utilization of the available rotor position information, minimizing the amount of HF signal injection required. Hence, leading to increased efficiency and reduced acoustic HF noise while achieving smooth transitions between low-speed and high-speed operation regions.