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Stochastic dynamic behavior of solar energy necessitates the use of robust controllers for photovoltaic (PV) power electronics interfaces. Such robust controller maximizes the energy harvest through continuous operation using a maximum power point tracker (MPPT). A model predictive control MPPT (MPC-MPPT) is proposed in this paper for a quasi-Z-source inverter (qZSI) based grid-connected PV power...
Variability in the solar irradiance level and ambient temperature of photovoltaic (PV) systems necessitates the use of maximum power point tracking (MPPT) of PV systems to ensure continuous harvesting of maximum power. This paper presents a sensorless current (SC) MPPT algorithm using model predictive control (MPC). The main contribution of this paper is the use of model-based predictive control principle...
Grid-connected energy storage systems have been implemented in ac power systems as uninterruptable power supplies (UPS). Batteries and bi-directional power converters provide electrical power when off-grid and recharge when grid-connected. In this paper, a packed U cells (PUC) seven-level inverter has been selected as the grid-interface due to the lower cost and fewer number of components compared...
Variability of the solar energy resources requires highly effective maximum power point tracking (MPPT) to ensure maximum energy harvesting from the photovoltaic (PV) modules. To accomplish this, a MPPT controller typically requires accurate knowledge of the voltage and current from the PV module, and must converge quickly with minimal hunting around the maximum power point (MPP). Conventional MPPT...
Stochastic dynamic behavior of solar energy necessitates the use of robust controllers for photovoltaic (PV) power electronics interfaces to maximize the energy harvest by continuous operation at maximum power point (MPP). This paper proposes a sensorless current model predictive control maximum power point tracking (SC-MPC-MPPT) algorithm. By predicting the future behavior of the power conversion...
Dynamic behavior of solar energy resource entails the need of robust controllers that can converge to the maximum power point (MPP) to maximize energy harvest. This paper explores an improved Perturb and Observe (P&O) technique that combines a fixed step model predictive controller (MPC), to speed up the control loop, applied to a boost converter. The proposed MPC Maximum Power Point Tracking...
This paper presents a Model Predictive Control (MPC) for grid-tied Packed U Cells (PUC) multilevel inverter. The system under study consists of a single-phase 3-cell PUC inverter connected to the grid through filtering inductor. The proposed topology allows the generation of 7-level output voltage with reduction of passive and active components compared to the conventional multilevel inverters. The...
Due to variability of solar energy resources, maximum power point tracking (MPPT) of photovoltaic (PV) is required to ensure continuous operation at the maximum power point (MPP) and maximize the energy harvest. Many standards are developed to ensure the safe and efficient power generation under dynamic weather conditions. This paper presents a high efficiency fixed-step model predictive control (MPC)...
Variability of the solar resource necessitates that Maximum Power Point Tracking (MPPT) techniques be used in photovoltaic (PV) systems to ensure maximum electrical energy is harvested. This paper presents a MPPT algorithm using Model Predictive Control (MPC) that does not require the use of current sensors. The main contribution is the use of the model based predictive control (MPC-MPPT) to eliminate...
Due to variability of solar energy resources, maximum power point tracking (MPPT) of photovoltaic (PV) is required to ensure continuous operation at the maximum power point (MPP) and maximize the energy harvest. This paper presents a digital model predictive control technique to employ the MPPT for flyback converter for photovoltaic applications. The MPP operating point is determined by using perturb...
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