Adaptive MPPT control algorithm for small-scale wind energy conversion systems

Abstract: Different types of renewable resources are need of the hour as fossil fuels are on The verge of extinction but electricity demand is increasing exponentially. In reality renewable energy is available in such a huge amount that it can provide 3078 times the present global energy need. Wind energy is one of these sources and having potential to generate 200 times energy than require globally. It is the oldest source of energy on the earth and from 1887 only it started to use for electricity generation. The efficiency of wind turbine, gear and generator decides the overall efficiency among this wind turbine is having scope of improvement. The wind turbine will generate maximum power if wind variation is less but it is not in someone's hand. Thus an MPPT technique comes into picture and maximizes power output. Various MPPT techniques are present till date, but in this paper we proposed perturb and observe, Incremental Conductance and Fuzzy logic control algorithms along with mechanical MPPT i.e. pitch control. These MPPT algorithms track the maximum power for varying wind conditions. Pitch control comes handy when speed increases more than rated speed, it will change pitch angle in such a way that it will rotate and constant speed to generate maximum power.

Abstract: This paper presents the control of single stage solar PV (Photovoltaic) array with variable speed WECS (Wind Energy Conversion System) using DFCE (Dual Fundamental Component Extraction) based control algorithm for power quality improvement of the distribution network. The variable speed WECS uses P&O (Perturb and Observer) based MPPT (Maximum Power Point Tracking) algorithm for peak power extraction, and it is accomplished by a generator side VSC (Voltage Source Converter). However, the solar PV array maximum power is extracted using INC (Incremental Conductance) based MPPT algorithm through the grid side converter. The solar PV array and WECS, are feeding active power to AC mains at unity power factor through grid side VSC. The grid side VSC control approach is capable of compensating the load harmonics and maintaining the three phase grid currents balanced at variable solar and wind powers. The proposed control algorithm uses the fundamental load current, and voltage components for estimation of reference grid currents. This control algorithm has a self-tuning filter for accurate and fast fundamental component extraction. Tests results have demonstrated the satisfactory performance of proposed grid-tied PV-WECS on a developd prototype in the laboratory.

Abstract: This paper proposes a novel undisturbed switching strategy based on gain self-regulation for wind turbine generation system (WTGS) to restrain extra power fluctuations and mechanical loads caused during the controller switching process between full-load region and partial-load region. The switching characteristics near rated wind speed is firstly analyzed, and theoretical foundation of gain regulation is discussed. Then the gain self-regulation method based on Fourier transform is presented to optimize the switching performance. The simulation results based on FAST reveal that, the proposed switching strategy reduces output power fluctuations and mechanical loads significantly, which is also friendly to power grid and wind turbine devices.

Abstract: A wind-generator (WG) maximum-power-point-tracking (MPPT) system is presented, consisting of a high-efficiency buck-type dc/dc converter and a microcontroller-based control unit running the MPPT function. The advantages of the proposed MPPT method are that no knowledge of the WG optimal power characteristic or measurement of the wind speed is required and the WG operates at a variable speed. Thus, the system features higher reliability, lower complexity and cost, and less mechanical stress of the WG. Experimental results of the proposed system indicate near-optimal WG output power, increased by 11%-50% compared to a WG directly connected via a rectifier to the battery bank. Thus, better exploitation of the available wind energy is achieved, especially under low wind speeds.

Abstract: This paper focuses on the development of maximum wind power extraction algorithms for inverter-based variable speed wind power generation systems. A review of existing maximum wind power extraction algorithms is presented in this paper, based on which an intelligent maximum power extraction algorithm is developed by the authors to improve the system performance and to facilitate the control implementation. As an integral part of the max-power extraction algorithm, advanced hill-climb searching method has been developed to take into account the wind turbine inertia. The intelligent memory method with an on-line training process is described in this paper. The developed maximum wind power extraction algorithm has the capability of providing initial power demand based on error driven control, searching for the maximum wind turbine power at variable wind speeds, constructing an intelligent memory, and applying the intelligent memory data to control the inverter for maximum wind power extraction, without the need for either knowledge of wind turbine characteristics or the measurements of mechanical quantities such as wind speed and turbine rotor speed. System simulation results and test results have confirmed the functionality and performance of this method.

Abstract: Variable rotor speed control of a fixed-pitch wind turbine is investigated on a system consisting of a wind turbine which can operate in a wide speed range, from 0 to 38 RPM. It produces any desired output from the rated (20 kW) to no-load, providing there is enough wind. A special technique is used to determine the operating point of the wind turbine by using the measured rotor speed and power. A difficult problem with this type of wind turbine control is to make the upper speed limit reasonably high to capture as much energy as possible but still low enough to avoid power peaks. >

Abstract: In this paper, a novel maximum power point tracking (MPPT) controller with an adaptive compensation control is first proposed for a microscale wind power generation system (WPGS) Based on the adaptive control, the dynamic response is improved and more wind energy can be captured during wind velocity variations For cost and reliability consideration, no mechanical sensors are used in this proposed WPGS A single-stage ac-to-dc converter is then proposed to replace the traditional two-stage converter and incorporate the MPPT control for achieving higher efficiency and lower total harmonic distortion (THD) To further improve the efficiency of the converter, a quasi-synchronous rectification (QSR) algorithm is proposed to control the active switches for reducing the conduction loss of the body diodes The analytic closed form duty ratios of the corresponding active switches are also derived for easy implementation Furthermore, a prototype system is constructed and the proposed MPPT controller and QSR algorithm are both implemented using a DSP, namely, TMS320F2812 Some experimental results are given to verify the validity of the proposed microscale WPGS It is found that the total output energy can be increased by 13% for the microscale WPGS

Abstract: This paper presents a new adaptive control algorithm for maximum power point tracking (MPPT) in wind energy systems. A mathematical model of a wind turbine system is also provided. The proposed control algorithm allows the generator to track the optimal operation points of the wind turbine system under fluctuating wind conditions and the tracking process speeds up over time. This algorithm does not require the knowledge of intangible turbine mechanical characteristics such as its power coefficient curve, power characteristic or torque characteristic. It employs a search and reuse concept, a modified Hill Climb Searching (HCS) method and two newly defined loops: change detection loop (CDL) and operation point adjustment loop (OPAL). The adaptive nature of the proposed algorithm eliminates the need for customized algorithms that are optimal for only one particular turbine. It is also a solution to achieve fast optimum power point detection after its initial learning process. A simulated system has been built in PSIM 7.0 for mathematical verification of the wind energy system and for the verification of the proposed algorithm. The algorithm is realized in C++ script and detailed descriptions of the proposed control algorithm are provided for illustration purposes.