The study of power flow analysis for microgrids has gained importance where several methods have been proposed to solve these problems. However, these schemes are complicated and not easy to implement due to the absence of a slack bus as well as the dependence of the power on frequency as a result of the droop characteristics. This paper proposes simple and effective modifications to the conventional method (Newton Raphson) to compute the power flow for microgrids. The presented method provides a simple, easy to implement, and accurate approach to solve the power flow equations for microgrids. The proposed method is applied to two test systems: a 6-bus system and a 38-bus system. The results are compared against simulation results from PSCAD/EMTDC which validate the effectiveness of the developed method. The proposed technique can be easily integrated in current commercially available power system software and can be applied for power system studies. Index Terms-Distributed generation (DG), islanded microgrid, power flow.

Internet-of-Things concepts are evolving the power systems to the Energy Internet paradigm. Microgrids (MGs), as the basic element in an Energy Internet, are expected to be controlled in a corporative and flexible manner. This paper proposes a novel distributed control scheme for multi-agent systems (MASs) governed MGs in future Energy Internet. The control objectives are frequency/voltage restoration and proportional power sharing. The proposed control scheme considers both intra and inter MASs interactions, which offers group plug-and-play capability of distributed generators (DGs). The stability and communication delay issues in the control framework are analysed. A multi-site implementation framework is presented to explain the agent architecture as well as data exchange in local area networks and the cloud server. Then a cyber hardware-in-the-loop (C-HiL) experiment is conducted to validate the proposed control method with multi-site implementation. The experimental results prove the effectiveness and application potentials of the proposed approach. 1

In future power systems, widespread small-scale energy storage systems (ESSs) can be aggregated to provide ancillary services. In this context, this paper aims to integrate energy storage aggregators (ESAs) into the load frequency control (LFC) framework for power system frequency control. Firstly, a system disturbance observer is designed to supplement the secondary frequency control, where the ESA can respond to the estimated disturbance and accelerate the system frequency recovery. Then, within the ESA, a finite-time leader-follower consensus algorithm is proposed to control the small-scale ESSs via sparse communication network. This algorithm ensures that the ESAs can track the frequency control signals and the state-ofcharge balancing among each ESS in finite-time. The external characteristics of the ESA will resemble to that of one large-scale ESS. Numerical examples demonstrate the convergence of the ESA under different communication graphs. The effectiveness of the entire framework for power system frequency control is validated under a variety of scenarios.

Power flow studies are very important in the planning or expansion of power system. With the integration of distributed generation (DG), micro-grids are becoming attractive. So, it is important to study the power flow of micro-grids. In grid connected mode, the power flow of the system can be solved in a conventional manner. In islanded mode, the conventional method (like Gauss Seidel) cannot be applied to solve power flow analysis. Hence some modifications are required to implement the conventional Gauss Seidel method to islanded micro-grids. This paper proposes a Modified Gauss Seidel (MGS) method, which is an extension of the conventional Gauss Seidel (GS) method. The proposed method is simple, easy to implement and accurate in solving the power flow analysis for islanded microgrids. The MGS algorithm is implemented on a 6 bus test system. The results are compared against the simulations results obtained from PSCAD/EMTDC which proves the accuracy of the proposed MGS algorithm

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