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At present, more and more communication-based methods are proposed for reactive power adjustment in islanded microgrid (IMG). However, the use of communication data will inevitably cause communication problems, for e.g., delay, packet loss, and communication failure. Among them, the random communication failure (RCF) is common and harmful. To realize the stable operation of IMG and the rational sharing of reactive power under the consideration of this problem, a cyber-physical cooperative hierarchical control strategy is proposed in this article, which include cyber and physical layers in control structure. In these two layers, the main designs are as follows. In the cyber layer, to solve the RCF problem, we have designed the corresponding observer, controller, and prediction compensation part; and to improve the frequency stability, a secondary control method is designed. In the physical layer, to share reactive power reasonably, a reactive power control method based on synchronous voltage regulation is proposed; to suppress the possible disturbance in the data used in the physical layer, a novel sliding-mode controller is designed; and to improve the voltage stability during adjusting power, a voltage compensation strategy is proposed. The effectiveness of proposed methods is finally verified by experiments. [ABSTRACT FROM AUTHOR]

Frequency deviation and powers sharing error exist in a microgrid with multiple droop-controlled distributed generations. To solve the above problems, we propose an event-triggered multistage secondary control. First, to improve the synchronization accuracy, we divide secondary control into multiple stages based on frequency/voltage droop characteristics. The inputs of proportion-integration compensator for these stages are different. The corresponding stage will be activated when the value of frequency/voltage meets a certain “event” (given ranges). Then, we consider the network delay, use a discrete communication scheme to reduce the bandwidth utilization, and further avoid the oversized delay. To stabilize the interloop control with input delay, we derive the robustness criteria. Finally, simulations in RT-LAB confirm the effectiveness of the proposed control strategy. [ABSTRACT FROM AUTHOR]

This paper focuses on multi-agent-system-based bi-level bidding strategy of microgrid to make all power producers participate in electricity allocation as rational agents under electricity market transaction. Firstly, the multi-agent-system-based bidding system is constructed as bi-level MAS. Then, the bidding model is formulated as a bi-level optimization problem, which makes the best of renewable energy source, and subjects it to the object of obtaining maximum profits for all power producers. According to this model, electricity market is divided into two subsidiary markets, which involve the upper and the lower electricity market. The lower electricity market is composed of microgrids, which ally together in the upper electricity market to offset their shortages compared to traditional power producers, such as efficient market influence, the reliability of the energy supplying. Additionally, game theory is introduced for modeling and Nash equilibrium as the solution of bidding optimization problem is found through a series of iterative process based on the bi-level MAS. Finally, both the upper market and the lower market are illustrated in the case studies and corresponding proper conclusions are received. [ABSTRACT FROM AUTHOR]

For the droop-controlled distributed generation units (DGs) in microgrids (MGs), the power sharing error associated with voltage difference of DGs can be attributed to the mismatched line impedance. To improve the power sharing accuracy in islanded MGs, a neighbor-prediction based hierarchical control strategy is proposed. In secondary control, a consensus protocol is used to regulate the DGs voltages interacted by communication network to the state of tracking synchronization. Thus, the error-free power sharing is obtained. Network data-loss and delay problems are considered. To stabilize the DGs’ inner-loop control in which there is a delayed input, the H∞ robustness criteria of a dynamic model of DGs is derived. If the DG i ’s voltage in network transmission loses, the prediction system of a neighbor will be activated to forecast the lost voltage for secondary consensus control by extreme learning machine (ELM). Thus, the voltages regulation will be back to normalization. Simulations in MATLAB confirm the effectiveness of proposed control in MGs. [ABSTRACT FROM AUTHOR]

Summary: In this paper, a cyber‐physical cooperative control strategy considering communication interruption is proposed to improve the control effect on output voltages and frequency obtained by droop control of distributed energy resources (DERs). The control structure consists of the physical and cyber layers. And in the two layers, the interruption occurs mostly in sensors and data aggregators. To solve the problem of interruption among data aggregators, a path‐planning method combined with improved Dijkstra algorithm (IDA) and improved genetic algorithm (IGA) is proposed in the cyber layer. To solve the problem of interruption among sensors, a predictive compensation method combined with extreme learning machine (ELM) and model predictive control (MPC) is proposed in the physical layer. Meanwhile, so as to improve the control effect of DERs, a virtual leader‐following consensus control (VLFCC) method combined with double sliding mode control (SMC) is first proposed in cyber layer and then applied to the physical layer to accomplish the secondary control on DERs. Finally, the simulation results show that under the condition of communication interruption, the output voltage and frequency of each DER can be adjusted to their respective reference values through the proposed cooperative control strategy. [ABSTRACT FROM AUTHOR]