Communication infrastructure (CI) in microgrids (MGs) allows for the application of different control architectures for the secondary control (SC) layer. The use of new SC architectures involving CI is motivated by the need to increase MG resilience and handle the intermittent nature of distributed generation units (DGUs). The structure of secondary control is classified into three main categories including centralized SC (CSC) with a CI, distributed SC (DISC) generally with a low data rate CI, and decentralized SC (DESC) with communicationfree infrastructure. To meet the MGs operational constraints and optimize performance, control and communication must be utilized simultaneously in different control layers. In this survey, we review and classify all types of SC policies from CI based methods to communication-free policies, including: CSC, averaging based DISC, consensus-based DISC methods, containment pinning consensus, event-triggered DISC, washoutfilter based DESC, and state-estimation based DESC. Each structure is scrutinized from the view point of the relevant literature. Challenges such as clock drifts, cyber-security threats, and the advantage of event-triggered approaches are presented. Fully decentralized approaches based on state-estimation and observation methods are also addressed. Although these approaches eliminate the need of any CI for the voltage and frequency restoration, during black start process or other functionalities related to the tertiary layer a CI is required. Power hardwarein-the-loop (PHiL) experimental tests are carried out to compare the merits and applicability of the different SC structures.
This paper proposes a novel secondary control strategy for power electronic-based ac microgrid (MG). This approach restores voltage and frequency deviations by utilizing only local variables with very high bandwidth. This is realized with a finite control set model predictive control (FCS-MPC) technique that is adopted in the inner level of primary control of voltage source converters (VSCs). In the outer level of primary control, droop control and virtual impedance loops are exploited to adjust power sharing among different DGs. As inner control level operates with a very high bandwidth, need for filtering of calculated active and reactive powers in the outer level of primary control is insignificant. Therefore, secondary control can be operated with far superior bandwidth compared to the case when conventional cascaded linear control is used. Merits of the proposed approach are investigated analytically with the help of describing function (DF) methodology that allows quasi-linear approximation of the inner control level. Finally, simulation and experimental results are presented.
This paper proposes a new modified model predictive control to compensate for voltage and frequency deviations with higher bandwidth for an AC shipboard microgrid. The shipboard power system (SPS) and islanded microgrids (MGs) have a reasonable analogy regarding supplying loads with local generations. However, a great number of vital imposing pulse loads and highly dynamic large propulsion loads in the SPS make the frequency and voltage regulation a complicated issue. Conventional linear control methods suffer from high sensitivity to parameter variations and slow transient response, which make big oscillations in the frequency and voltage of the SPS. This paper addresses the problem by proposing a novel finite control set model predictive control to compensate for primary frequency and voltage deviations with higher bandwidth and order of magnitude faster than state of the art. Furthermore, a single input interval type-2 fuzzy logic controller (SI-IT2-FLC) is applied in secondary level to damp the steady-state deviations with higher bandwidth. Finally, hardware-in-the-loop (HiL) experimental results prove the applicability of the proposed control structure.
Conventional model predictive control (MPC) of power converter has been widely applied to power inverters achieving high performance, fast dynamic response, and accurate transient control of power converter. However, the MPC strategy is highly reliant on the accuracy of the inverter model used for the controlled system. Consequently, a parameter or model mismatch between the plant and the controller leads to a sub-optimal performance of MPC. In this paper, a new strategy called model-free predictive control (MF-PC) is proposed to improve such problems. The presented approach is based on a recursive least squares algorithm to identify the parameters of an auto-regressive with exogenous input (ARX) model. The proposed method provides an accurate prediction of the controlled variables without requiring detailed knowledge of the physical system. This new approach and is realized by employing a novel state space identification algorithm into the predictive control structure. The performance of the proposed model-free predictive control method is compared with conventional MPC. The simulation and experimental results show that the proposed method is totally robust against parameters and model changes compared with the conventional model based solutions.
In this paper, a novel decentralized control structure is proposed to compensate voltage and frequency deviations of an ac microgrid (MG) with higher bandwidth compared to the conventional control structure with no need for a communication network. This approach is realized by firstly employing finite control set model predictive control of voltage source converter at the primary control level. Then, an adaptive droop control is presented to keep the voltage and frequency of the MG stable in steady state and serve as a secondary level of hierarchical control. Therefore, the MG voltage and frequency are restored to the nominal value with a decentralized communicationfree control structure. Simulation results verify the accurate frequency and voltage restoration as well as fast power-sharing during the transient and steady-state performance with no need for communication infrastructure.
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