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.

The testing of complex power components by means of power hardware in the loop (PHIL) requires accurate and stable PHIL platforms. The total time delay typically present within these platforms is commonly acknowledged to be an important factor to be considered due to its impact on accuracy and stability. However, a thorough assessment of the total loop delay in PHIL platforms has not been performed in the literature. Therefore, time delay is typically accounted for as a constant parameter. However, with the detailed analysis of the total loop delay performed in this paper, variability in time delay has been detected as a result of the interaction between discrete components. Furthermore, a time delay characterization methodology (which includes variability in time delay) has been proposed. This will allow for performing stability analysis with higher precision as well as to perform accurate compensation of these delays. The implications on stability and accuracy that the time delay variability can introduce in PHIL simulations has also been studied. Finally, with an experimental validation procedure, the presence of the variability and the effectiveness of the proposed characterization approach have been demonstrated. Index Terms-Time delay, power hardware-in-the-loop, delay identification, real-time simulation, component testing. NOMENCLATURE Abbreviations AC Alternating current. ADC Analog to digital converter. DAC Digital to analog converter. DC Direct current. DRTS Digital real time simulator. FPGA Field-Programmable Gate Array. GPS Global positioning system. HUT Hardware under test. IA Interface algorithm. ITM Ideal transformer method.

 Abstract-The reactive power of the photovoltaic (PV) inverters has great potential for voltage regulation of distribution networks. In this paper, a new three-level coordinated control method for PV inverters is proposed to address network voltage fluctuation and violation issues. In Level I, a ramp-rate control is designed to smooth the network voltage fluctuations, while in Level II, a droop control is designed to alleviate the network voltage deviations. If the local compensation provided by Level I and II is not enough to regulate the network voltages within the required limits, the Level III control based on dynamic average consensus can respond and share the reactive power requirement among other inverters in a distributed way. The proposed control method can smooth the voltage profiles, restrain the voltage rise/drop problem, and coordinate all PV inverters in real-time when there is no feasible local solution. The stability analysis of the proposed three-level coordinated control for network voltage regulation is provided. The power hardware-in-the-loop (PHIL) experiment has been conducted for validating the proposed control method under various scenarios. Index Terms-Voltage regulation, PV inverters, distributed control, power hardware-in-the-loop, distribution networks. T P P Q Q J J J J VV     S J J J J J J . It should be noted that although VQ S and VP S are functions of t, the variations of them respect to t are relatively small for a wide range of operating conditions [13], [23]. Equation (2) gives a linearized representation of ΔQ and ΔV near the equilibrium point, which is used to investigate the stability analysis in Section IV. In distribution networks, bus voltages are affected by both real and reactive power changes due to the high resistance to reactance ratio (R/X). For simplicity, the PV systems and load demand are aggregated at each bus. The PV inverters are operated to provide the maximum power output.

Smart grid systems are characterized by high complexity due to interactions between a traditional passive network and active power electronic components, coupled using communication links. Additionally, automation and information technology plays an important role in order to operate and optimize such cyber-physical energy systems with a high(er) penetration of fluctuating renewable generation and controllable loads. As a result of these developments the validation on the system level becomes much more important during the whole engineering and deployment process, today. In earlier development stages and for larger system configurations laboratory-based testing is not always an option. Due to recent developments, simulation-based approaches are now an appropriate tool to support the development, implementation, and rollout of smart grid solutions. This paper discusses the current state of simulation-based approaches and outlines the necessary future research and development directions in the domain of power and energy systems.