Abstract
The development and optimization of a hybrid system composed of photovoltaic panels, wind turbines, converters, and batteries connected to the grid, is first presented. To generate the maximum power, two maximum power point tracker controllers based on fuzzy logic are required and a battery controller is used for the regulation of the DC voltage. When the power source varies, a high-voltage supply is incorporated (high gain DC-DC converter controlled by fuzzy logic) to boost the 24 V provided by the DC bus to the inverter voltage of about 400 V and to reduce energy losses to maximize the system performance. The inverter and the LCL filter allow for the integration of this hybrid system with AC loads and the grid. Moreover, a hardware solution for the field programmable gate arrays-based implementation of the controllers is proposed. The combination of these controllers was synthesized using the Integrated Synthesis Environment Design Suite software (Version: 14.7, City: Tunis, Country: Tunisia) and was successfully implemented on Field Programmable Gate Arrays Spartan 3E. The innovative design provides a suitable architecture based on power converters and control strategies that are dedicated to the proposed hybrid system to ensure system reliability. This implementation can provide a high level of flexibility that can facilitate the upgrade of a control system by simply updating or modifying the proposed algorithm running on the field programmable gate arrays board. The simulation results, using Matlab/Simulink (Version: 2016b, City: Tunis, Country: Tunisia, verify the efficiency of the proposed solution when the environmental conditions change. This study focused on the development and optimization of an electrical system control strategy to manage the produced energy and to coordinate the performance of the hybrid energy system. The paper proposes a combined photovoltaic and wind energy system, supported by a battery acting as an energy storage system. In addition, a bi-directional converter charges/discharges the battery, while a high-voltage gain converter connects them to the DC bus. The use of a battery is useful to compensate for the mismatch between the power demanded by the load and the power generated by the hybrid energy systems. The proposed field programmable gate arrays (FPGA)-based controllers ensure a fast time response by making control executable in real time.
Highlights
A hybrid energy system constituted by wind turbine generators (WTG), photovoltaic generators (PVG), and batteries has been applied for grid-connected operation [1] and in various autonomous applications [2]
It can be observed that the battery charge and discharge are estimated as the the difference between total powerprovided providedby bythe therenewable renewable sources sources and difference between thethe total power and the thepower power difference between the(power total power provided by the renewable sources and the power transferred to the load load)
The summary report shows the percentage of hardware resources usage required by various commands compared to the existing resources in the field programmable gate arrays (FPGA) board
Summary
Power converters and control units are essential for energy and its management, as well as for the maximum power supplied by PVG and WTG For this reason, there are different approaches to pursuing maximum power points (MPPs) in the relevant published literature, such as incremental conductance [8], the parasitic capacity method [9], or the perturbation and observation method [10]. These converters can achieve high-voltage gain by using a higher transformer ratio These converters absorb a discontinuous input current, making them unsuitable for renewable energy applications such as photovoltaic panels and wind turbines. A new high-voltage gain DC-DC converter was developed in [20] and it is used in this paper with a fuzzy logic controller to ensure a robust performance in variable environmental conditions (temperature, solar radiation, and wind speed). Architectures, simulations, and implementation steps of the various transfer level (RTL) architectures, simulations, and implementation steps of the various commands are illustrated illustratedand anddiscussed discussedinin
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