Energy provided by microgrids should be considered, especially because their purpose is to supply loads from the available power source of the combined sources of energy, including the grid, optimally and efficiently to satisfy the load demand securely and economically. Sensing the accuracy of the different physical parameters of the combined power sources and energy storage plays a crucial part in the efficiency and resilience of microgrids. The present microgrids mostly use conventional sensors, which are greatly impacted by ambient conditions such as high-voltage (HV) and electromagnetic interference (EMI). So, this paper presents an enhanced microgrid based on replacing the conventional sensors with fiber Bragg grating (FBG) sensors renowned for their immunity to EMI and HV, in addition to the virtue of distributing sensing capability. The enhanced microgrid based on FBG sensing was tested experimentally at different potential points predefined on the microgrid and validated with a microgrid simulation model. Real-time measurements of FBG and conventional sensors were recorded at the potential points and applied to the Simulink model to compare the performance for both cases. The unit and integration tests showed an obvious improvement in the accuracy and resiliency of the microgrid by using FBG sensors.
Wind energy has the fastest and highest growth rate of any other Renewable energy sources (RES). Investigating the Wind Energy Conversion Systems (WECS) is very important for improving efficiency. However, It is required a monumental accessible land space for installing Wind turbines(WT). Consequently, this paper presents the design and implementation of a Wind turbine emulator (WTE) to substitute WTs. The proposed WTE includes a new Maximum Point Power Tracking(MPPT) technique based on integrating binary search technique and genetic algorithm. The proposed emulator has an SQLite database as a repository of wind turbine information. Also, it has a graphical user interface(GUI) to facilitate the operation. System components have been modeled and simulated using MATLAB Simulink. Furthermore, a prototype is implemented based on a series excited DC motor and permanent magnet synchronous (PMSG). All static and dynamic characteristics have been investigated to prove the capabilities of the developed emulator. Also, an integration test has been conducted on real-time conditions of wind speed profile and working load for 24 hours to check the reliability. The experimental results are compared with the simulation results for validation and showed the capability of the proposed WTE of emulating a wide range of Wind turbines.
Fiber Bragg grating (FBG) technology has shown a mutation in developing fiber optic-based sensors because of their tiny size, high dielectric strength, distributed sensing, and immunity to high voltage and magnetic field interference. Therefore, FBG sensors significantly improve performance and accuracy in the world of measurements. The reflectivity and bandwidth are the main parameters that can dramatically affect the sensing performance and accuracy. Each industrial application has its requirements regarding the reflectivity and bandwidth of the reflected wavelength. Optimizing such problems with multi-objective functions that might t with each other based on applications’ needs is a big challenge. Therefore, this paper presents an optimization method based on the nondominated sorting genetic algorithm II (NSGA-II), aiming at determining the optimum grating parameters to suit applications’ needs. To sum up, the optimization process aims to convert industrial applications’ requirements, including bandwidth and reflectivity, into the manufacturing setting of FBG sensors, including grating length and modulation refractive index. The method has been implemented using MATLAB and validated with other research work in the literature. Results proved the capability of the new way to determine the optimum grating parameters for fulfilling application requirements.
The popularity of the eBus has been increasing rapidly in recent years due to its low greenhouse gases (GHG) emissions and its low dependence on fossil fuels. This incremental use of the eBus increases the burden to the power grid for its charging. Charging eBus requires a high amount of power for a feasible amount of time. Therefore, developing a fast-charging station (FCS) integrated with Micro Energy Grid (MEG) and hybrid energy storage is crucial for charging eBuses. This paper presents a design of FCS for eBus that integrates MEG with hybrid energy storage with the energy management system. To reduce the dependency on the main utility grid, a hybrid micro energy grid based on a renewable source (i.e., PV) have been included. In addition, hybrid energy storage of batteries and flywheels has also been developed to mitigate the power demand of the fast-charging station during peak time. Furthermore, a multiple-input DC-DC converter has been developed for managing the DC power transfer between the common DC bus and the multiple energy sources. Finally, an energy management system and the controller has been designed to achieve an extensive performance from the fast charging station. MATLAB Simulink has been used for the simulation work of the overall design. Different test case scenarios are tested for evaluating the performance parameters of the proposed FCS and also for evaluating its performance.
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