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A multifunctional control strategy for a singlephase Asymmetrical Cascaded H-Bridge Multilevel Inverter (ACHMI), suitable for microgrid systems with nonlinear loads, is presented. The primary advantage of ACHMI is to produce a staircase output voltage with low harmonic content utilizing unequal DC voltages on the individual H-bridge cells. In gridconnected mode of operation, the control strategy of the ACHMI is based on the Conservative Power Theory (CPT), providing selective disturbing current compensation besides injecting its available energy. In autonomous mode of operation, two different control methods along with a damping resistor in the filter circuit are developed for regulation of the ACHMI instantaneous output voltage in a variety of load conditions. The first method is a single-loop voltage control scheme without the need of any current measurement. The second one is multi-loop voltage control scheme with a load current feed-forward compensation strategy and preservation of the grid-connected current control scheme. The steady state response and stability of both voltage control schemes are analyzed, and based on the application requirement, the control schemes are implemented individually. The effectiveness of each control strategy is experimentally verified using a hardware-in-the-loop (HIL) setup with the control algorithm implemented in the TMSF28335 DSP microcontroller.

A c c e p t e d M a n u s c r i p t 2 This paper presents interactive smart battery-based storage (BBS) for wind generator (WG) and Photovoltaic (PV) systems. The BBS is composed of an Asymmetric Cascaded H-Bridge Multilevel Inverter (ACMI) with staircase modulation. The structure is parallel to the WG and PV systems, allowing the ACMI to have a reduction in power losses compared to the usual solution for storage connected at the DC-link of the converter for WG or PV systems.Moreover, the BBS is embedded with a decision algorithm running real-time energy costs, plus a battery state-of-charge (SOC) manager and power quality (PQ) capabilities, making the described system in this paper very interactive, smart and multi-functional. The paper describes how BBS interacts with the WG and PV and how its performance is improved. Experimental results are presented showing the efficacy of this battery-based storage for renewable energy applications.

Participation of a wind turbine (WT) in primary frequency control (PFC) requires reserving some active power. The reserved power can be used to support the grid frequency. To maintain the required amount of reserve power, the WT is de-loaded to operate under its maximum power. The objective of this article is to design a control method for a WT system to maintain the reserved power of the WT, by controlling both pitch angle and rotor speed simultaneously in order to optimize the operation of the WT system. The pitch angle is obtained such that the stator current of the permanent magnet synchronous generator (PMSG) is reduced. Therefore, the resistive losses in the machine and the conduction losses of the converter are minimized. To avoid an excessive number of pitch motor operations, the wind forecast is implemented in order to predict consistent pitch angle valid for longer timeframe. Then, the selected pitch angle and the known curtailed power are used to find the optimal rotor speed by applying a nonlinear equation solver. To validate the proposed de-loading approach and control method, a detailed WT system is modeled in Matlab/Simulink (The Mathworks, Natick, MA, USA, 2017). Then, the proposed control scheme is validated using hardware-in-the-loop and real time simulation built in Opal-RT (10.4.14, Opal-RT Inc., Montreal, PQ, Canada).

This paper proposes a fuzzy logic-based controller for a wind turbine system to provide frequency support for a smart grid. The designed controller is aimed to provide an appropriate dynamic droop rate depending on the local measurements of each wind turbine of a wind farm such as the maximum power available and the amount of power reserve. The designed fuzzy controller depends on the rate of change of frequency (ROCOF) at the point of common coupling (PCC). The main advantage of the proposed fuzzy controller is to provide frequency support by the wind turbine system connected to a smart grid. The dynamic rate of the controller is defined by the fuzzy sets considering the change in the grid’s frequency and the available reserve power. First, the response of static droop curves is investigated for different scenarios of wind turbines connected to a smart grid. Then, the proposed fuzzy logic-based droop controller is integrated into the system, and its performance and response are evaluated, and the results are compared with static-droop based controller. The proposed controller is tested using Matlab\Simulink.