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With ever increasing energy generation diversity and energy storage becoming affordable, distribution networks are becoming more complex than ever before. This complexity can be utilized to benefit the distribution networks as well as end consumers in the form of controlled Microgrids. Microgrids are not simply distributed generation and energy storage systems; solar systems and battery banks, rather a complete design of hardware and software for specific uses and users. All the different elements need to be designed to work together to provide stable, efficient and sustainable power delivery to the end user. An experimental Hybrid-Microgrid testing facility is presented in this paper that implements highefficiency distribution architectures combining both AC and DC networks. This testing facility provides a research testbed for investigating different aspects of Microgrid systems, employing a total of 15.5 kW of reconfigurable Solar PV and 80 kWh of lithium energy storage on a 145 kVA commercial building load located at Griffith University. Implementation results along with control system simulation results are presented in this paper for distributed renewable generation, Static Synchronous Compensators, advanced control methodologies and forecasting methods for energy management purposes.

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This paper investigates the use of synergetic control for voltage stability of a DC microgrid where the loads are interfaced through power electronic converters fed from a DC power source. When tightly regulated, these loads exhibit a constant power load (CPL) behavior. CPLs have negative incremental impedance behavior which may lead to system instability. The synergetic control approach is compared with a linearizing feedback approach, which was investigated by the authors before and therefore serves as a reference case. Both of the selected approach achieve stability at large signal level and overcome hereby the limits of existing small signal approaches. Both of the selected control techniques act on the interface converters at the generator side and leave the load side converters untouched. The real time performance of the system and their controllers is observed on a MVDC microgrid which is implemented in Opal-RT.Keywords -Constant Power Loads, MVDC distribution systems, microgrid, voltage control, nonlinear control systems, power system stability, negative feedback, closed loop systems, linear feedback control systems, DC-DC power converters, system analysis and design, DC power systems.

In this paper, an Internet of Things (IoT) platform is proposed for Multi-Microgrid (MMG) system to improve unbalance compensation functionality employing three-phase four-leg (3P-4L) voltage source inverters (VSIs). The two level communication system connects the MMG system, implemented in Power System Computer Aided Design (PSCAD), to the cloud server. The local communication level utilizes Modbus Transmission Control Protocol/Internet Protocol (TCP/IP) and Message Queuing Telemetry Transport (MQTT) is used as the protocol for global communication level. A communication operation algorithm is developed to manage the communication operation under various communication failure scenarios. To test the communication system, it is implemented on an experimental testbed to investigate its functionality for MMG neutral current compensation (NCC).To compensate the neutral current in MMG, a dynamic NCC algorithm is proposed, which enables the MGs to further improve the NCC by sharing their data using the IoT platform. The performance of the control and communication system using dynamic NCC is compared with the fixed capacity NCC for unbalance compensation under different communication failure conditions. The impact of the communication system performance on the NCC sharing is the focus of this research. The results show that the proposed system provides better neutral current compensation and phase balancing in case of MMG operation by sharing the data effectively even if the communication system is failing partially.Energies 2018, 11, 3102 2 of 22 control the neutral current directly [3], where the 3P-4L voltage source inverter (VSI) provides better unbalance compensation than other active and passive methods [4]. Traditionally, a fixed portion of the 3P-4L converter capacity is specified to compensate the neutral current. However, the drawback of this method is in case of higher neutral current compensation (NCC) necessity, where it can lead to increased capacity of the 3P-4L compensator [5]. Authors in Reference [6] employed the 3P-4L VSI with PV installation to compensate for the neutral current but case scenarios for network interaction with different loads are not presented. A fixed capacity neutral current compensation method employing 3P-4L VSI under various load scenarios for network contingencies cases is proposed in Reference [7]. Furthermore, the 3P-4L VSI is used to eliminate the leakage current from PV installations [8]. However, none of these researches have considered higher capacity requirement. Authors in Reference [9] propose a dynamic capacity distribution method to compensate for the neutral current utilizing the maximum capacity of the VSI in a Microgrid (MG) but no communication system in presented. Authors in References [10,11] have employed conservative power theory to share the residual neutral current among the VSIs in an MG. Although a communication system have been employed, its operational details are not presented. Cloud-based Internet of Things (IoT) platforms to manage energy of building...

Abstract. This paper aims to investigate a method of peak load shaving through the utilization of solar PV and battery energy storage whilst creating a cost effective Energy Management System (EMS). This is achieved by utilizing a rule-sets to manage and optimize a scheduling system with a forecasting algorithm. As Time of Use (ToU) tariffs change throughout the day, a cost benefit can be achieved when a smart energy storage system is appropriately employed. The EMS operation is tested on an experimental microgrid with commercial load considering payback period calculation.

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