21 research outputs found
Model Predictive based Energy Efficient Control of an On-Grid PV Inverter
No full textThis thesis is submitted to the Department of Electrical and Electronic Engineering, Khulna University of Engineering & Technology in partial fulfillment of the requirements for the degree of Masters of Science in Electrical and Electronic Engineering, March 2019.Cataloged from PDF Version of Thesis.Includes bibliographical references.Renewable energy is now one of the most interesting topics in the field of distributed energy
generation. Among the renewable energy sources, the solar photovoltaic (PV) source has become the most popular and effective one. Generally, PV system is connected to an ac grid through an inverter. The inverter should be controlled in such a way that it can penetrate maximum power to the grid. However, designing a controller for the inverter is a difficult task due to the intermittent PV source. The traditional pulse width modulation (PWM) based inverters produce high total harmonic distortion (THD) in the output current. This causes a significant amount of power loss and thus less power penetration to the grid. It makes the on-grid PV systems inefficient. Therefore, model predictive control (MPC) based energy efficient conversion of PV power is proposed in this research work. In the proposed MPC, the control objectives (current and switching frequency) are predicted using a finite number of voltage vectors produced by the inverter. MPC selects an optimal control action (i.e. switching state) in every sampling instant for the inverter by minimizing a predefined cost function. The cost function includes current tracking error and number of switching transitions. These two control objectives are combined in the cost function with a weighting factor. The first control objective provides a smooth current tracking accuracy, which increases the r.m.s amplitude of the injected current and thus increases the power penetration to the grid. The second control objective reduces the average switching frequency, which actually reduces the switching loss. The value of weighting factor in the cost function is selected by making a tradeoff between the current THD and the average switching frequency. Simulation results show that the proposed controller tracks the reference current accurately with mean absolute error of 2.5% which is 30% for the PWM based controllers. The low current tracking error for MPC based inverter yields low current THD of 2.07%, whereas in
traditional PWM based inverter the current THD is 7.26%. As a result, the proposed MPC based inverter penetrates 12.8% more active power to the grid than the PWM based inverter. The active power penetration is confirmed by load flow analysis using IEEE 13 bus test feeder. The energy efficient operation of the MPC based inverter is also verified by doing loss analysis. There are three types of loss considered in the research work: conduction, switching and harmonic losses. The conduction, switching, and harmonic losses of the inverter are reduced by 36.8%, 50%, and 91.9%, respectively, in comparison with the PWM control based inverter. The performance of the proposed controller is also analysed in terms of transient response, decoupling control, and fault tolerant ability. It is shown that the proposed MPC yields decoupled current control and fast transient response, and capable of handling the symmetrical and unsymmetrical faults in the grid. The research outcome from this comprehensive analysis proves that the proposed controller reduces the power loss to maximize the penetrated power and ensures the performance of the proposed controller as an energy efficient controller for an on-grid PV inverter.Amit Kumer PodderMasters of Science in Electrical and Electronic Engineerin
Dynamic Modeling, Control, and Cyber-security of Power Distribution Systems with DC Fast Charging Stations.
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Co-Optimization of EV Charging Control and Incentivization for Enhanced Power System Stability
No full textWe study how high charging rate demands from electric vehicles (EVs) in a
power distribution grid may collectively cause its dynamic instability, and,
accordingly, how a price incentivization strategy can be used to steer
customers to settle for lesser charging rate demands so that these
instabilities can be avoided. We pose the problem as a joint optimization and
optimal control formulation. The optimization determines the optimal charging
setpoints for EVs to minimize the -norm of the transfer function
of the grid model, while the optimal control simultaneously develops a linear
quadratic regulator (LQR) based state-feedback control signal for the
battery-currents of those EVs to jointly minimize the risk of grid instability.
A subsequent algorithm is developed to determine how much customers may be
willing to sacrifice their intended charging rate demands in return for
financial incentives. Results are derived for both unidirectional and
bidirectional charging, and validated using numerical simulations of multiple
EV charging stations in the IEEE 33-bus power distribution model
Design and performance analysis of a novel electromagnetic bandgap structure assisted phased array antenna
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Control Strategies of Different Hybrid Energy Storage Systems for Electric Vehicles Applications
No full textChoice of hybrid electric vehicles (HEVs) in transportation systems is becoming more prominent for optimized energy consumption. HEVs are attaining tremendous appreciation due to their eco-friendly performance and assistance in smart grid notion. The variation of energy storage systems in HEV (such as batteries, supercapacitors or ultracapacitors, fuel cells, and so on) with numerous control strategies create variation in HEV types. Therefore, choosing an appropriate control strategy for HEV applications becomes complicated. This paper reflects a comprehensive review of the imperative information of energy storage systems related to HEVs and procurable optimization topologies based on various control strategies and vehicle technologies. The research work classifies different control strategies considering four configurations: fuel cell-battery, battery-ultracapacitor, fuel cell-ultracapacitor, and battery-fuel cell- ultracapacitor. Relative analysis among different control techniques is carried out based on the control aspects and operating conditions to illustrate these techniques’ pros and cons. A parametric comparison and a cross-comparison are provided for different hybrid configurations to present a comparative study based on dynamic performance, battery lifetime, energy efficiency, fuel consumption, emission, robustness, and so on. The study also analyzes the experimental platform, the amelioration of driving cycles, mathematical models of each control technique to demonstrate the reliability in practical applications. The presented recapitulation is believed to be a reliable base for the researchers, policymakers, and influencers who continuously develop HEVs with energy-efficient control strategies
Power Loss Analysis of Solar Photovoltaic Integrated Model Predictive Control Based On-Grid Inverter
No full textThis paper presents a finite control-set model predictive control (FCS-MPC) based technique to reduce the switching loss and frequency of the on-grid PV inverter by incorporating a switching frequency term in the cost function of the model predictive control (MPC). In the proposed MPC, the control objectives (current and switching frequency) select an optimal switching state for the inverter by minimizing a predefined cost function. The two control objectives are combined with a weighting factor. A trade-off between the switching frequency (average) and total harmonic distortion (THD) of the current was utilized to determine the value of the weighting factor. The switching, conduction, and harmonic losses were determined at the selected value of the weighting factor for both the proposed and conventional FCS-MPC and compared. The system was simulated in MATLAB/Simulink, and a small-scale hardware prototype was built to realize the system and verify the proposal. Considering only 0.25% more current THD, the switching frequency and loss per phase were reduced by 20.62% and 19.78%, respectively. The instantaneous overall power loss was also reduced by 2% due to the addition of a switching frequency term in the cost function which ensures a satisfactory empirical result for an on-grid PV inverter
