Supercapacitors are energy storage devices with high electrical power densities and long spanlife. Therefore, supercapacitor-based energy storage systems have been employed for a variety of applications. The modelling and simulation of SCs have been of great interest to this objective. This paper presents an electrical schema and mathematical modelling of three models of supercapacitors. The first is the RC model, the second is the two-branch model and the third is the multi-branch model. The objective of this modelling is to choose the best model that can respect the same behaviour of the experimental model. These models are compared with an experimental model. This comparison prove that the response voltage of the multi-branch model correctly describes the behaviour of the experimental model of Belhachemi. The disadvantage of this model is the slow simulation duration in MATLAB/Simulink. The RC model represented the faster model in terms of simulation. The choice of 15 branches in parallel in multi-branch models gives good results and correctly describes the reel model. The automatic charge and discharge voltage of SCs reduce by reducing the charge current.

Inertia-Free Stand-Alone Microgrid, Part II: Inertia Control and Stability with PMSG Wind Turbine System

Recently, microgrids have faced a great challenge for the stable operation of converter-dominant system with very high renewable penetration. The converter-based-generator reduces inertia constant. In this case, very small power imbalance can cause large frequency variation. Therefore, the accurate load sharing between generators is important for the stable operation. This paper proposes the virtual multi-slack (VMS) droop control based on the power sensitivity analysis. In other words, one physical slack generator directly controls the magnitude and phase angle of its bus voltage. At the same time, the other generators indirectly control the magnitudes and phase angles of their bus voltages by using the VMS droop control. This results in the proper load sharing between the generators in the stand-alone microgrid. That is, all nonslack generators operate as virtual slacks so that they solve the power imbalances together with one physical slack generator. The proposed VMS control is realized with the multi-slack power flow analysis, which enables adaptive droop based power allocation between the generators. Then, its effectiveness is verified with several case studies on the practical stand-alone microgrid in South Korea by using the electromagnetic transient program.

The recent railway system is a huge microgrid assembling multiplex structure with distributed active loads, sources and storage devices. The active load represents the train. The sources are a microgrid based on renewable energies. The big problem of the most of electrical train is that they can’t recover energy recovery during regenerative breaking phases. another problem of the electrical train is the long charging time from the stations. This paper suggests a techno-economic process for the energy storage by using SCs in the train, with the aim to reduce the energy consumptions. The proposed design of railway station use PV and wind sources, and batteries for energy storage system (ESS). For the train, SCs are implemented to the ESS where they are alimented breaking phases and from stations by a pantograph installed in an air power line in each stop. SCs are distinguished by high characteristics power and a wide number of charge/discharge cycles, they provide low particular energy and a fast charging time. An energy management approach is suggested to control the DC bus by voltage and the buck-boost converter by current. The Sizing of PI controller used for the stabilization of the DC bus of train and station is given. The whole system is modeled in MATLAB-Simulink. Simulations for the train and station show the suitability of the suggested powertrain and control strategy.

The energy storage system (ESS) is developing into a very important element for the stable operation of power systems. An ESS is characterized by rapid control, free charging, and discharging. Because of these characteristics, it can efficiently respond to sudden events that affect the power system and can help to resolve congested lines caused by the excessive output of distributed generators (DGs) using renewable energy sources (RESs). In order to efficiently and economically install new ESSs in the power system, the following two factors must be considered: the optimal installation placements and the optimal sizes of ESSs. Many studies have explored the optimal installation placement and the sizing of ESSs by using analytical approaches, mathematical optimization techniques, and artificial intelligence. This paper presents an algorithm to determine the optimal installation placement and sizing of ESSs for a virtual multi-slack (VMS) operation based on a power sensitivity analysis in a stand-alone microgrid. Through the proposed algorithm, the optimal installation placement can be determined by a simple calculation based on a power sensitivity matrix, and the optimal sizing of the ESS for the determined placement can be obtained at the same time. The algorithm is verified through several case studies in a stand-alone microgrid based on practical power system data. The results of the proposed algorithm show that installing ESSs in the optimal placement could improve the voltage stability of the microgrid. The sizing of the newly installed ESS was also properly determined.

A new primary frequency controller in power grids undergoing massive wind power penetration is the focus of this paper. The inescapable problem in a largely wind penetrated power grid is to ensure the maintenance of its frequency in the nominal band prescribed by the power system operator (PSO). However, with the massive arrival of wind farms with conventional control schemes, the operation of maintaining and restoring the frequency to the regulatory regimes remains very complicated. In order to overcome the above problem, this paper proposes a new strategy for primary frequency control in power grids using model predictive control (MPC) for a multi-cluster doubly-fed induction generator (DFIG)-based wind farm (WF), with a main objective of reducing the frequency nadir (FN), eliminating the second frequency dip (SFD), and providing the optimal support during wind speed variations. In this approach, a rolling prediction and optimization control strategy is developed based on the dynamic power system model to ideally predict the additional power to be provided. Moreover, in order to avoid second frequency dips, the wind turbines (WTs) are not allocated to extract additional power from the grid during the frequency event, the rotor speeds are not recovered to the maximum power point tracking (MPPT) operating points during the primary frequency control. The performance of the proposed controller was evaluated using a two-zone electrical system in MATLAB/Simulink^®. The obtained results disclose that the frequency nadir is enhanced with more than 6.1% compared to the conventional schemes. In addition, the frequency response settling time has been improved with more than 10.51 s.