Experimental investigation on the performances of a multilevel inverter using a field programmable gate array-based control system

The Field Programmable Gate Array (FPGA) represents a valid solution for the design of control systems for inverters adopted in many industry applications, because of both its high flexibility of use and its high-performance with respect to other types of digital controllers. In this context, this paper presents an experimental investigation on the harmonic content of the voltages produced by a three-phase, five level cascaded H-Bridge Multilevel inverter with an FPGA-based control board, aiming also to evaluate the performance of the FPGA through the implementation of the main common modulation techniques and the comparison between simulation and experimental results. The control algorithms are implemented by means of the VHDL programming language. The output voltage waveforms, which have been obtained by applying to the inverter the main PWM techniques, are compared in terms of THD%. Simulation and experimental results are analyzed, compared and finally discussed

Stand-alone hybrid power plant based on SiC solar PV and wind inverters with smart spinning reserve management

Stand-alone hybrid power plants based on renewable energy sources are becoming a more and more interesting alternative. However, their management is a complex task because there are many variables, requirements and restrictions as well as a wide variety of possible scenarios. Though a proper sizing of the power plant is necessary to obtain a competitive cost of the energy, smart management is key to guarantee the power supply at a minimum cost. In this work, a novel hybrid power plant control strategy is designed, implemented and simulated under a wide variety of scenarios. Thereby, the proposed control algorithm aims to achieve maximum integration of renewable energy, reducing the usage of non-renewable generators as much as possible and guaranteeing the stability of the microgrid. Different scenarios and case studies have been analyzed by dynamic simulation to verify the proper operation of the power plant controller. The main novelties of this work are: (i) the stand-alone hybrid power plant management regarding a battery energy storage system as a part of the spinning reserve, (ii) the characterization of the largest loads as non-priority loads, (iii) the minimization of the needed spinning reserve and fuel consumption from diesel generators

Energy Storage Management and Simulation for Nano-Grids

Energy storage has been utilized in many forms and applications from a flashlight to the Space Shuttle. There is a worldwide effort to develop battery model with high energy level and power densities for a variety range of applications, including hybrid electric vehicles (HEV) and photovoltaic system (PV). To improve battery technology, understanding the battery modeling is very important. So, modeling the thermal behavior of a battery is a vital consideration before designing an effective thermal management system which will operate safely and prolong the lifespan of an energy storage system. The first part of this work focused on the aging model of lithium-ion battery and a simple thermal model of lithium-ion and lead-acid battery using MATLAB/Simulink. After that, an artificial neural network model (ANN) is developed to predict various characteristics at wide temperature range. In this case, comparisons between the training/testing data outputs and targets validating both models with a regression accuracy of 99.839% and 98.727% respectively for Li-ion and Lead-Acid battery while it is 99.912% for the aging model of Li-ion battery. In the end, this energy storage device is used to interconnect with HOMER. This HOMER project aims at designing a solar-wind hybrid power system for Statesboro, Georgia. The cost analysis is performed utilizing HOMER software based on solar irradiance, wind speed, and residential load profile. The proposed HOMER model, using solar & wind with the grid was more cost efficient as the cost of energy (COE) was found 0.0618$/kWh where the average residential electricity rate in Statesboro is 0.116$/kWh. As a result of using this model, the total cost is reduced by 46.72% compared to other conventional power systems. In the second part of HOMER simulation, while comparing among three types of storage devices, another minimum COE is found using wind with grid connection. As the wind speed is good enough for Statesboro, Georgia, simulation shows that minimum COE is 0.0499$/kWh, 0.0386$/kWh and 0.0633$/kWh respectively for Li-ion, Lead-acid, and Vanadium