Power optimizer

About: Power optimizer is a research topic. Over the lifetime, 10525 publications have been published within this topic receiving 199245 citations.

Coordinated Predictive Control of a Wind/Battery Microgrid System

Abstract: This paper presents the operation and controller design of a microgrid consisting of a direct drive wind generator and a battery storage system A model predictive control strategy for the ac-dc-ac converter of wind system is derived and implemented to capture the maximum wind energy as well as provide desired reactive power A novel supervisory controller is presented and employed to coordinate the operation of wind farm and battery system in the microgrid for grid-connected and islanded operations The proposed coordinated controller can mitigate both active and reactive power disturbances that are caused by the intermittency of wind speed and load change Moreover, the control strategy ensures the maximum power extraction capability of wind turbine while regulating the point of common coupling bus voltage within acceptable range in both grid-connected and islanded operations The designed concept is verified through various simulation studies in EMTDC/PSCAD, and the results are presented and discussed

Finding an optimal PV panel maximum power point tracking method

Abstract: The need for a maximum power point tracker in a photovoltaic system is explained A variety of photovoltaic panel maximum power point tracking methods are then briefly compared The optimal method from those compared, where the photovoltaic panel power-voltage curve is scanned periodically, and the maximum power point tracker is controlled by current, is discussed in detail Problems with this implementation are highlighted, and the design of a voltage-controlled implementation using the same power-voltage curve scan is presented Problems and advantages of this system are given

An Energy Management Scheme With Power Limit Capability and an Adaptive Maximum Power Point Tracking for Small Standalone PMSG Wind Energy Systems

Abstract: Due to its high energy generation capability and minimal environmental impact, wind energy is an elegant solution to the growing global energy demand. However, frequent atmospheric changes make it difficult to effectively harness the energy in the wind because maximum power extraction occurs at a different operating point for each wind condition. This paper proposes a parameter-independent intelligent power management controller that consists of a slope-assisted maximum power point tracking (MPPT) algorithm and a power limit search (PLS) algorithm for small standalone wind energy systems with permanent synchronous generators. Unlike the parameter-independent perturb & observe algorithms, the proposed slope-assisted MPPT algorithm preempts logical errors attributed to wind fluctuations by detecting and identifying atmospheric changes. The controller's PLS is able to minimize the production of surplus energy to minimize the heat dissipation requirements of the energy release mechanism by cooperating with the state observer and using the slope parameter to seek the operating points that result in the desired power rather than the maximum power. The functionality of the proposed energy management control scheme for wind energy systems is verified through simulation results and experimental results.

Simulation Comparisons and Implementation of Induction Generator Wind Power Systems

Abstract: This paper describes the performance comparison of a wind power systems based on two different induction generators as well as the experimental demonstration of a wind turbine simulator for the maximum power extraction. The two induction machines studied for the comparison are the squirrel-cage induction generator (SCIG) and the doubly fed induction generator (DFIG). The techniques of direct grid integration, independent power control, and the droop phenomenon of distribution line are studied and compared between the SCIG and DFIG systems. Both systems are modeled in Matlab/Simulink environment, and the operation is tested for the wind turbine maximum power extraction algorithm results. Based on the simulated wind turbine parameters, a commercial induction motor drive was programmed to emulate the wind turbine and is coupled to the experimental generator systems. The turbine experimental results matched well with the theoretical turbine operation.

Backstepping Control of Smart Grid-Connected Distributed Photovoltaic Power Supplies for Telecom Equipment

Abstract: Backstepping controllers are obtained for distributed hybrid photovoltaic (PV) power supplies of telecommunication equipment. Grid-connected PV-based power supply units may contain dc–dc buck–boost converters linked to single-phase inverters. This distributed energy resource operated within the self-consumption concept can aid in the peak-shaving strategy of ac smart grids. New backstepping control laws are obtained for the single-phase inverter and for the buck–boost converter feeding a telecom equipment/battery while sourcing the PV excess power to the smart grid or to grid supply the telecom system. The backstepping approach is robust and able to cope with the grid nonlinearity and uncertainties providing dc input current and voltage controllers for the buck–boost converter to track the PV panel maximum power point, regulating the PV output dc voltage to extract maximum power; unity power factor sinusoidal ac smart grid inverter currents and constant dc-link voltages suited for telecom equipment; and inverter bidirectional power transfer. Experimental results are obtained from a lab setup controlled by one inexpensive dsPIC running the sampling, the backstepping and modulator algorithms. Results show the controllers guarantee maximum power transfer to the telecom equipment/ac grid, ensuring steady dc-link voltage while absorbing/injecting low harmonic distortion current into the smart grid.