- 标题
- 摘要
- 关键词
- 实验方案
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Rooftop PV aspirations of Indiaa??s National Solar Mission and the green building codes: The missing links and the way ahead
摘要： Due to the large-scale and distributed characteristics of increasing renewable energy resources, dynamic economic emission dispatch (DEED) of hybrid energy resource system becomes more and more important in the power system operation. This paper proposes a distributed model predictive control (DMPC) method for hybrid energy resources system of dynamic economic optimal dispatch with large-scale decomposition coordination approach. First, the DEED model of hybrid energy resources is converted into predictive control model, which can provide rolling optimization mechanism for dealing with intermittent energy resources optimization. Second, predictive control model is decomposed into several subsystems with Lagrangian multipliers for coordinating those subsystems, which can greatly decrease the computational complexity. Third, due to the randomness or uncertainty of intermittent power generation, model predictive control can dynamically optimize random or uncertainty problem with rolling optimization mechanism. Furthermore, adaptive dynamic programming is utilized to solve those subsystem optimization problems, which can optimize the random or uncertain problem in real-time condition. In the optimization process, probability constraint is converted into deterministic constraint with its probability density function, and system load balance can be properly handled with coupled coarse-fine constraint-handling technique. According to the obtained results in the case studies, the proposed DMPC can optimize the DEED of hybrid energy resources well combining with the large-scale decomposition-coordination approach, while greatly decreasing the optimization complexity and computation time, which reveals that the proposed method can provide an alternative way for solving the DEED problem of hybrid energy resources.
关键词： large-scale decomposition-coordination,Renewable energy resources,model predictive control,dynamic economic emission dispatch
更新于2025-09-19 17:13:59
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[IEEE 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Chicago, IL, USA (2019.6.16-2019.6.21)] 2019 IEEE 46th Photovoltaic Specialists Conference (PVSC) - Thinned Germanium Substrates for III-V Multijunction Solar Cells
摘要： Due to the large-scale and distributed characteristics of increasing renewable energy resources, dynamic economic emission dispatch (DEED) of hybrid energy resource system becomes more and more important in the power system operation. This paper proposes a distributed model predictive control (DMPC) method for hybrid energy resources system of dynamic economic optimal dispatch with large-scale decomposition coordination approach. First, the DEED model of hybrid energy resources is converted into predictive control model, which can provide rolling optimization mechanism for dealing with intermittent energy resources optimization. Second, predictive control model is decomposed into several subsystems with Lagrangian multipliers for coordinating those subsystems, which can greatly decrease the computational complexity. Third, due to the randomness or uncertainty of intermittent power generation, model predictive control can dynamically optimize random or uncertainty problem with rolling optimization mechanism. Furthermore, adaptive dynamic programming is utilized to solve those subsystem optimization problems, which can optimize the random or uncertain problem in real-time condition. In the optimization process, probability constraint is converted into deterministic constraint with its probability density function, and system load balance can be properly handled with coupled coarse-fine constraint-handling technique. According to the obtained results in the case studies, the proposed DMPC can optimize the DEED of hybrid energy resources well combining with the large-scale decomposition-coordination approach, while greatly decreasing the optimization complexity and computation time, which reveals that the proposed method can provide an alternative way for solving the DEED problem of hybrid energy resources.
关键词： model predictive control,Renewable energy resources,large-scale decomposition-coordination,dynamic economic emission dispatch
更新于2025-09-19 17:13:59
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Optimal cascaded predictive control for photovoltaic systems: application based on predictive emulator
摘要： The present study sheds new light on advanced control methods of photovoltaic (PV) emulators using finite set model predictive control (FS-MPC). In the first part of the study, a predictive PV emulator (P-PVE) based on a Buck converter is proposed and tested under hard climatic conditions and load variations. The high performance of the P-PVE in terms of dynamic response, reference tracking, accuracy, simplicity, and efficiency is confirmed experimentally when compared with those of the commonly used one based PI controller. The second part of the study proposes an efficient cascaded predictive control (CPC) method applied on two topologies of PV systems, namely the stand-alone system and the grid-connected system. In each topology, the P-PVE is cascaded to a maximum power point tracking Boost converter in order to track efficiently the maximum power point. In addition to the high performance offered by the FS-MPC, the proposed control strategy allows to control all cascaded converters at the same time in one stage instead of controlling them separately, thus providing more flexibility and simple controllability. Extensive experimental results are done confirming the correctness and the effectiveness of the proposed CPC under hard climatic conditions, even in the presence of distorted grid voltage.
关键词： finite set model predictive control,stand-alone system,cascaded predictive control,grid-connected system,photovoltaic emulator
更新于2025-09-16 10:30:52
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A Novel Mode-Based Energy Storage Control Approach for Residential PV Systems
摘要： This paper presents a novel mode-based energy storage control approach. Assuming that an energy storage device (ESD) is equipped with a set of predetermined real-time control modes, the dispatch objective is to select an optimal mode instead of a continuous charging or discharging power value. A two-stage algorithm is developed for mode selection. In the first stage, a sliding 24-hour economic model predictive control (EMPC) algorithm is used to determine the power outputs of the ESD for the next 24 hours. In the second stage, the output sign for the next time step determines the class of modes to be selected (charging or discharging). The information from the first stage is used to compute the total cost for each selected mode. The mode with the lowest day-ahead cost is chosen. The residential electricity consumption data collected in the PECAN Street Project is used in the simulation to validate the performance of the proposed algorithm. Simulation results show that using a mode-based approach reduces the sensitivity to forecasting errors along with load and solar variability. The algorithm performance is consistent across different load patterns.
关键词： forecasting errors,residential PV systems,control modes,energy storage,economic model predictive control
更新于2025-09-11 14:15:04
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Improved Restricted Control Set Model Predictive Control (iRCS-MPC) Based Maximum Power Point Tracking of Photovoltaic Module
摘要： This paper presents a robust two stage maximum power point tracking (MPPT) system of the photovoltaic (PV) module using an improved restricted control set model predictive control (iRCS-MPC) technique. The suggested work is improved in two aspects; a revision in conventional P&O algorithm is made by employing three distinct step sizes for different conditions, and an improvement in conventional MPC algorithm. The improved MPC algorithm is based on the single step prediction horizon that provides less computational load and swift tracking of maximum power point (MPP) by applying the control pulses directly to the converter switch. The computer aided experimental results for various environmental scenarios revealed that compared with the conventional method (conventional P&O + MPC), for the PV power and inductor current, the undershoot and overshoot is decreased to 68% and 35% respectively under stiff environmental conditions. In addition, the settling time needed to reach a stable state is significantly reduced in the proposed system. The viability of the solution suggested is verified in MATLAB/Simulink and by hardware experimentation.
关键词： maximum power point tracking (MPPT),photovoltaic systems,MPC,Boost converter,dc-dc power conversion,model predictive control (RCS-MPC)
更新于2025-09-11 14:15:04
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New electrolytic capacitor-less LED driver based on model predictive control
摘要： The lifetime of light-emitting diode (LED) drivers is mainly affected by electrolytic capacitors. Therefore, it is necessary to eliminate electrolytic capacitors from LED drivers. Firstly, basic concept of LED driver without electrolytic capacitors is addressed in this paper. Then, a new electrolytic capacitor-less LED driver is proposed and its operation principles are analyzed in detail. In order to achieve better control effect, model predictive control (MPC) strategy is introduced in this topology. Following that, the mathematical model of the circuit which adopts MPC is derived. Finally, simulations and experiments on a 24 V, 3A laboratory prototype are carried out to verify the feasibility of the proposed topology and control strategy.
关键词： Flyback,Model predictive control,LED driver,Bidirectional cuk,Electrolytic capacitor-less
更新于2025-09-11 14:15:04
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An Adaptive Use Strategy for Solid-State Lasers by Combining Maximum Likelihood Estimation With Model Predictive Control
摘要： Solid-state lasers are widely applied in various fields, such as material processing, laser marking, and remote sensing. Long lifetime is always required for commercial solid-state lasers in practice. Thus, it is of great importance to carefully design the use strategy in order to efficiently utilize the available resources and prolong the lifespan of solid-state lasers. In this paper, the use strategy is investigated with the consideration of the performance degradation of solid-state lasers, for the general case that the values of the model parameters are all unknown. First, the degradation behavior of solid-state lasers is modeled on the basis of the Wiener process by taking into account normally distributed measurement errors. Then, an adaptive use strategy is proposed by combining maximum likelihood estimation (MLE) with model predictive control (MPC). The aim of the proposed use strategy is to maintain the actual output optical power of a solid-state laser at a stable and acceptable level by adaptively adjusting the input electrical power. Specifically, the estimates of the model parameters are updated based on the measured output optical powers up to the current time by applying MLE, and the input electrical power is optimized based on MPC. Finally, a numerical example is utilized to demonstrate the effectiveness of the proposed use strategy.
关键词： use strategy,Degradation,solid-state lasers,model predictive control,maximum likelihood estimation
更新于2025-09-11 14:15:04
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Direct grid-side current model predictive control for grid-connected inverter with LCL filter
摘要： On control of the grid-connected inverter (GCI) with LCL filter, the inverter-side current model predictive control is adopted conventionally. The ultimate grid-side current is controlled indirectly by control of inverter-side current. The ideal scenario is that grid-side current is directly controlled. However, the conventional control model is complicated and the calculation is heavy. This study proposed a novel direct grid-side current model predictive control (GSC-MPC) for GCI with LCL filter. Based on timing coordination of both forward and backward difference methods, a direct connection is established between the grid-side output current and the inverter-side output voltage. Meanwhile, a proper mathematical model is built for an improved model predictive control. The exact required voltage vector in the next sampling interval is predicted and calculated by this model. The output optimal voltage vector is modulated by space vector pulse width modulation technique to control the inverter. Furthermore, the proposed GSC-MPC is rather robust to parameter variation. Simulation and experimental results present that the proposed GSC-MPC can improve the current control performance effectively for GCI with LCL filter.
关键词： direct grid-side current control,space vector pulse width modulation,LCL filter,model predictive control,grid-connected inverter
更新于2025-09-10 09:29:36
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Model Predictive Control Via PV-Based VAR Scheme for Power Distribution Systems With Regular and Unexpected Abnormal Loads
摘要： This paper develops a model predictive controller (MPC) via photovoltaic (PV)-based volt-ampere reactive scheme to minimize the power loss and stabilize voltage ?uctuation when PV cells are connected to the power distribution line. The nominal power load data from California independent system operator is used to simulate dynamics of the system with DistFlow equations. Since power consumptions in fact may deviate from nominal values, an estimator is further developed to reconstruct the state variables and power loads from measurements. The integration of the MPC and estimator forms a closed-loop control framework and enables the system to quickly recover from undesired disturbances by effectively changing the real and reactive powers provided by PV cells. We use a bidirectional, single branch distribution circuit to demonstrate the performance of proposed scheme. The results show that our MPC indeed reduces power loss and keeps the voltage within a desired bound. Additionally, the estimator successfully detects and correctly estimates the abnormal change of power consumption and directs the MPC to compensate such unexpected power loads promptly.
关键词： Model predictive control (MPC),power distribution system,volt-ampere reactive (VAR) control,photovoltaic (PV)-cell
更新于2025-09-10 09:29:36
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Dynamic Optimization of High-Altitude Solar Aircraft Trajectories Under Station-Keeping Constraints
摘要： This paper demonstrates the use of nonlinear dynamic optimization to calculate energy-optimal trajectories for a high-altitude, solar-powered unmanned aerial vehicle (UAV). The objective is to maximize the total energy in the system while staying within a 3 km mission radius and meeting other system constraints. Solar energy capture is modeled using the vehicle orientation and solar position, and energy is stored both in batteries and in potential energy through elevation gain. Energy capture is maximized by optimally adjusting the angle of the aircraft surface relative to the sun. The UAV flight and energy system dynamics are optimized over a 24 h period at an 8 s time resolution using nonlinear model predictive control. Results of the simulated flights are presented for all four seasons, showing an 8.2% increase in end-of-day battery energy for the most limiting flight condition of the winter solstice.
关键词： solar-powered UAV,energy-optimal trajectories,nonlinear model predictive control,nonlinear dynamic optimization,high-altitude long-endurance
更新于2025-09-09 09:28:46