This paper proposes a neural network control voltage tracking scheme of a DC-DC Flyback converter. In this technique, a back propagation learning algorithm is employed. The controller is designed to improve performance of the Flyback converter during transient and steady state operations. Furthermore, to investigate the effectiveness of the proposed controller, some operations such as starting-up and reference voltage variations are verified. The numerical simulation results show that the proposed controller has a better performance compare to the conventional PI-Controller method.
Developing countries need to make use of sufficient potential of PV power sources to cover the incremental demand of energy security. Though the PV-diesel microgrid system involving maximum supervising action as well as without having energy storage system can afford the continual power supply in the unelectrified rural area, it may not be circumstantially companionable because of the dependence on fossil-fuels and total dispatched energy cost [1][2]. Moreover, an individual PV system is an incomplete basis of electricity supplier due to the power instability produced by unpredictable solar irradiance and atmospheric temperature. Hence, MPPT is used commonly with PV solar systems to maximize power extraction from PV supply. Reference [3] presented an exhaustive literature review on on-line and off-line procedures for PV MPPT system. Reference [4] evaluated the application of Incremental Conductance, Perturb & Observe (P&O) MPPT procedure depending of European Efficiency Test EN 50530 that was specially contrived for Abstract: One of the major challenges for battery energy stowage system is to design a supervisory controller which can yield high energy concentration, reduced self-discharge rate and prolong the battery lifetime. A regulatory PV-Battery Management System (BMS) based State of Charge (SOC) estimation is presented in this paper that optimally addresses the issues. The proposed control algorithm estimates SOC by Backpropagation Neural Network (BPNN) scheme and utilizes the Maximum Power Point Tracking (MPPT) scheme of the solar panels to take decision for charging, discharging or islanding mode of the Lead-Acid battery bank. A case study (SOC estimation) is demonstrated as well to depict the efficiency (Error 0.082%) of the proposed model using real time data. The numerical simulation structured through real-time information concedes that the projected control mechanism is robust and accomplishes several objectives of integrated PV-BMS for instance avoiding overcharging and deep discharging manner under different solar radiations.
Solar power is mainly harnessed from photovoltaic (PV) panels which are arranged in multiple arrays in a solar farm or solar system. Though, power generation from PV solar system is characterised by uncertain efficiency, many countries with high insolation prefer solar as an alternative way of generating clean energy. However, the efficiency of energy generated from PV panels is affected by the accumulation of dust and debris, even on one panel in an array. This condition leads to the need for regular cleaning of the surface of PV panels. Current labour-based cleaning methods for photovoltaic arrays are costly in time, water and energy usage as well as lacking in automation capabilities. To overcome this problem, a fully automatic solar panel cleaning system with/without water is proposed. Hence, in this paper, the design of a robot for automated cleaning of the surface of PV panel is presented. The design utilizes an Arduino controller system to control the robot movement during the cleaning process. In addition, it is equipped with two rough sponge and a water pump system that can be used to clean dust or debris found on PV panel surfaces. The efficiency of the PV panels before and after the cleaning process is also observed. The result shows that the developed solar panel cleaning robot is able to clean the panel effectively and increase back the output current as well as the maximum power of the panel by 50%, after the dust on the PV panel is cleaned.
Abstract. A renewable energy source that works alone can't achieve customers' requirements for a stable power supply. Therefore, the paper proposes a multi-input converter for hybrid renewable energy system. This converter is designed for two input sources, PV and wind generator in order to design high efficiency and high performance converters for renewable energy applications. The proposed multi-input converter is composed by interleaved technique with two step-up converters and the two inputs are accommodated with some extra semiconductors, inductances and diodes. The modes of operation based on the status of the four switches, where S1 and S2 operate as main switches in order to deliver energy from both voltage sources. A constant output power to the load is provided by switching S3 switch, which guarantied the appropriate output voltage by reduce the ripple and improve the reliability. Simulations of multi-input converter has been performed using MATLAB/SIMULINK. The simulation results confirm the validity of the proposed method, which can be seen as a promising new topology that ensure multi-input converter suitable for renewable energy applications. IntroductionRenewable sources are the requisite for the expansion of epidermal community and economical. These days, scorbutic resource, the basic part of the energy, is almost exhaustive, and the environment is becoming worst. Renewable energy sources like PV and wind have the characteristics like non-pollution and superabundant reservation. The evolution of the renewable energy sources have been became an important [1,6].However, wind and PV are influenced by some factors like climatic conditions and seasons, and they are discontinuous. Thus, the renewable source that works individually can't achieve customers' demands for a steady energy supply. Multiple-input assortment of renewable energy sources work with each other for electrical serving to solve this problem is proposed [2].Applications like wind and PV systems use converters susceptible to be accepted more than one input source [3]. Therefore, in order to develop the performance of the renewable energy system is choosing to have wind systems create a relatively low voltage and some to have a low voltage with the PV. The converters in these implementations are then normally of the boost mode.The energy supplied from these systems is unstable and depended on the climatological conditions, this create that the power that can be provided to the load is also unstable [4,5]. Thus, the converters used in these implementations have to allow demanding power to both input sources simultaneously or individually, depending on the availability of the input sources.In this paper is offered a new converter susceptive two input voltage sources, and the power can be requested from converters individually depending on the availability of the voltage sources.
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