In this paper, restorations for both voltage and frequency in the droop-controlled inverter-based islanded microgrid (MG) are addressed. A distributed finite-time control approach is used in the voltage restoration which enables the voltages at all the distributed generations (DGs) to converge to the reference value in finite time and thus the voltage and frequency control design can be separated. Then a consensus-based distributed frequency control is proposed for frequency restoration, subject to certain control input constraints. Our control strategies are implemented on the local DGs and thus no central controller is required in contrast to existing control schemes proposed so far. By allowing these controllers to communicate with their neighboring controllers, the proposed control strategy can restore both voltage and frequency to their respective reference values while having accurate real power sharing, under a sufficient local stability condition established. An islanded MG test system consisting of 4 DGs is built in MATLAB to illustrate our design approach and the results validate our proposed control strategy.

In this paper, we present a distributed economic dispatch (ED) strategy based on projected gradient and finitetime average consensus algorithms for smart grid systems. Both conventional thermal generators and wind turbines are taken into account in the ED model. By decomposing the centralized optimization into optimizations at local agents, a scheme is proposed for each agent to iteratively estimate a solution of the optimization problem in a distributed manner with limited communication among neighbors. It is theoretically shown that the estimated solutions of all the agents reach consensus of the optimal solution asymptomatically. This scheme also brings some advantages, such as plug-and-play property. Different from most existing distributed methods, the private confidential information, such as gradient or incremental cost of each generator, is not required for the information exchange, which makes more sense in real applications. Besides, the proposed method not only handles quadratic, but also nonquadratic convex cost functions with arbitrary initial values. Several case studies implemented on six-bus power system, as well as the IEEE 30-bus power system, are discussed and tested to validate the proposed method.

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This paper presents a distributed cooperative control scheme for voltage unbalance compensation in an islanded microgrid (MG). By letting each distributed generator (DG) share the compensation effort cooperatively, unbalanced voltage in sensitive load bus (SLB) can be compensated. The concept of contribution level for compensation is first proposed for each local DG to indicate its compensation ability. A two-layer secondary compensation architecture consisting of communication layer and compensation layer is designed for each local DG. A totally distributed strategy involving information sharing and exchange is proposed, which is based on finite-time average consensus and newly developed graph discovery algorithm. This strategy does not require the whole system structure as a prior and can detect the structure automatically. The proposed scheme not only achieves similar voltage unbalance compensation performance to the centralized one, but also brings some advantages, such as communication fault tolerance and plug-and-play property. Case studies including communication failure, contribution level variation and DG plug-and-play are discussed and tested to validate the proposed method.

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We consider discrete event systems (DES) involving tasks with real-time constraints and seek to control processing times so as to minimize a cost function subject to each task meeting its own constraint. When tasks are processed over a single stage, it has been shown that there are structural properties of the optimal sample path that lead to very efficient solutions of such problems. When tasks are processed over multiple stages and are subject to end-to-end real-time constraints, these properties no longer hold and no obvious extensions are known. We consider a two-stage problem with homogeneous cost functions over all tasks at each stage and derive several new optimality properties. These properties lead to the idea of introducing "virtual" deadlines at the first stage, thus partially decoupling the stages so that the known efficient solutions for single-stage problems can be used. We prove that the solution obtained by an iterative virtual deadline algorithm (VDA) converges to the global optimal solution of the two-stage problem and illustrate the efficiency of the VDA through numerical examples.