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Owing to the stochastic behavior of renewable energy activity and the multiple design considerations, the advancement of hybrid renewable energy-based microgrid (HREMG) systems has become a complex task. This study proposes a design optimization algorithm for the long-term operation of an autonomous HREMG along with the optimal system capacities. The investigated energy system comprises photovoltaic panels, wind turbines, diesel generators, and batteries. It aims to energize a remote coastal community with a daily load demand of 400 kWh in Marsa Matruh, Egypt. Since most studies utilize commercial tools in the design optimization procedure, the African vultures optimization approach (AVOA) is developed to find the optimal energy alternative and determine the optimal component's capacity considering achieving the minimum energy cost and loss of power supply probability. Moreover, an adequate energy management strategy is suggested to coordinate the power flow within the energy system in which renewable energy sources are fully penetrated. To check the AVOA robustness and efficacy, its performance is compared with the HOMER Pro most popular commercial tool as well as with new metaheuristic algorithms, namely the grasshopper optimization algorithm (GOA) and Giza pyramid construction (GPC) under the same operating environment. The results revealed that the proposed AVOA achieved superior economic results toward the least net present cost ($346,614) and energy price (0.0947 $/kWh). Moreover, over 20 independent runs, the AVOA showed a better performance in terms of convergence and execution time compared to other tools/algorithms. The obtained findings could be a useful benchmark for researchers in the sizing problem of hybrid energy systems. [ABSTRACT FROM AUTHOR]

Achieving fast-tracking speed, high efficacy of maximum power point tracking (MPPT), absence of any wind speed measurement devices, and high performance under unpredictable wind speed along with an efficient control system is the recent trend in modern wind energy generation systems (WEGSs). This article studies two current control schemes for the control of a variable-speed WEGS based on a large-scale grid-connected permanent magnet synchronous generator (PMSG). An indirect optimal torque control (OTC) algorithm along with a fuzzy logic controller (FLC) have been implemented on the machine side converter (MSC) to diminish the installation cost and improve the overall efficiency of the studied wind system. Several distinct research studies highlighted that the PMSG suffers from the poor performance of the proportional-integral (PI) controller, especially in the event of variations in wind speed, FLC is proposed here as a substitute for the PI controller to eliminate its limitations. Both the FLC and PI controller are designed and implemented to fulfill the obedient performance of the current control loop of MSC. Moreover, a comparative study has been done between them under two different wind speed profiles (step change of wind speed, and real fluctuations of wind speed). MATLAB/SIMULINK software is used to validate the performance of the studied control schemes. The results of the simulation show the supremacy of the FLC compared to the PI controller and the veracity of the FLC as a vital option to the PI controller's drawbacks. [ABSTRACT FROM AUTHOR]

Owing to the significant number of hybrid generation systems (HGSs) containing various energy sources, coordination between these sources plays a vital role in preserving frequency stability. In this paper, an adaptive coordination control strategy for renewable energy sources (RESs), an aqua electrolyzer (AE) for hydrogen production, and a fuel cell (FC)-based energy storage system (ESS) is proposed to enhance the frequency stability of an HGS. In the proposed system, the excess energy from RESs is used to power electrolysis via an AE for hydrogen energy storage in FCs. The proposed method is based on a proportional-integral (PI) controller, which is optimally designed using a grey wolf optimization (GWO) algorithm to estimate the surplus energy from RESs (i.e., a proportion of total power generation of RESs: Kn). The studied HGS contains various types of generation systems including a diesel generator, wind turbines, photovoltaic (PV) systems, AE with FCs, and ESSs (e.g., battery and flywheel). The proposed method varies Kn with varying frequency deviation values to obtain the best benefits from RESs, while damping the frequency fluctuations. The proposed method is validated by considering different loading conditions and comparing with other existing studies that consider Kn as a constant value. The simulation results demonstrate that the proposed method, which changes Kn value and subsequently stores the power extracted from the RESs in hydrogen energy storage according to frequency deviation changes, performs better than those that use constant Kn. The statistical analysis for frequency deviation of HGS with the proposed method has the best values and achieves large improvements for minimum, maximum, difference between maximum and minimum, mean, and standard deviation compared to the existing method. [ABSTRACT FROM AUTHOR]

This paper describes the integration of a photovoltaic (PV) renewable energy source with a superconducting magnetic energy storage (SMES) system. The integrated system can improve the voltage stability of the utility grid and achieve power leveling. The control schemes employ model predictive control (MPC), which has gained significant attention in recent years because of its advantages such as fast response and simple implementation. The PV system provides maximum power at various irradiation levels using the incremental conductance technique (INC). The interfaced grid side converter of the SMES can control the grid voltage by regulating its injected reactive power to the grid, while the charge and discharge operation of the SMES coil can be managed by the system operator to inject/absorb active power to/from the grid to achieve the power leveling strategy. Simulation results based on MATLAB/Simulink® software prove the fast response of the system control objectives in tracking the setpoints at different loading scenarios and PV irradiance levels, while the SMES injects/absorbs active and reactive power to/from the grid during various events to improve the voltage response and achieve power leveling strategy. [ABSTRACT FROM AUTHOR]

Recently, hybrid generation systems (HGSs) are considered to be the optimal solution for supplying remote areas with the required electrical power. HGSs contain two or more renewable energy sources (RESs), such as wind power generators (WPGs), photovoltaic (PV) generation systems and the energy of the tides. Due to the intermittent nature of RESs, power and voltage fluctuations have appeared accordingly at the connection point with the utility power grid. Hence, energy storage technologies can play an effective role in mitigating power and voltage fluctuations caused by hybrid PV–wind generation systems. This paper proposes a robust control strategy for superconducting magnetic energy storage (SMES) combined with HGS. Fuzzy logic control (FLC) is used to control the chopper circuit of SMES in order to charge/discharge the active power from/to HGS. The proposed FLC strategy considers the fluctuations due to PV and wind power generation systems and the random load power variation. SMES with the proposed FLC method can effectively mitigate the fluctuation of active and reactive powers transfer between HGS and grid, and it can also regulate the voltage profile of the common connection point of SMES with HGS. Moreover, the system line power loss is clearly reduced by using the SMES system. The complete power system including loads is built in MATLAB/Simulink platform. The simulation results indicate that the proposed FLC–SMES can smooth both power and voltage fluctuations due to uncertain climate changes of PV and WPG systems. [ABSTRACT FROM AUTHOR]

The intermittent behavior of wind power generation results in a fast variation of both frequency and voltage magnitudes of isolated microgrids with high wind power penetration. In this paper, a hybrid energy microgrid with wind energy conversion system (WECS) and diesel synchronous generators are analyzed during wind gust conditions. Superconducting magnetic energy storage (SMES) is connected at the same node of the WECS to mitigate the intermittent wind power generation. A developed fuzzy logic controller has been applied to achieve active power sharing. The damping of voltage fluctuation depends on SMES reactive power, which is controlled by a voltage source converter. The studied microgrid comprises 33 nodes, two diesel SGs, and two WECSs of squirrel cage induction generator type at 30% penetration level. The results demonstrate the effectiveness of the proposed control strategy to mitigate the frequency fluctuations during the wind speed gusts by smoothing power output from WECSs/SMES system. Moreover, voltage control is achieved by injecting reactive power from the SMES system. All simulations are performed by MATLAB/Simulink package. [ABSTRACT FROM AUTHOR]