The economic progress of any country majorly relies on the energy that can be regarded as the key input for the development. The rapid growth of industries, vehicles and domestic users led to the consumption of the energy on a large scale. The fossil fuels are depleting day by day and the pollution caused to the atmosphere, an increase of the global temperature is considered to be the dominant challenges to protect the environment. Hence there is a need to rely on renewable energy sources to produce electrical energy. Among all Renewable Energy Sources (RES) the Photovoltaic (PV) power generation has become significant because of its unique merits such as longer lifespan, eco-friendly, mobile and portability of various parts, the capability of the output power to meet the peak loads.
Solar power tracking has become a great issue because of the nonlinear behaviour in the PV panel’s current-voltage (I–V) characteristics that are operated employing a maximum power point (MPP). Since the power delivered by the PV panel depends on the atmospheric conditions generally referred to as the solar irradiance and accessible temperature of the cell. These parameters are not consistent and vary according to the atmospheric conditions. Hence it is necessary to employ maximum power point trackers [MPPT]. MPPT is a critical component in the solar PV system to draw the maximum power. Furthermore, the converter employed with an MPPT achieves the load matching and delivers the maximum power
ABSTRACT
In Space there is a Rover the Power Generated to the Rover through Solar Panels from the Solar Panels we are Using the Single DC to DC Converter Instead of Unique DC to DC Converters. With the help of DC to DC Converter (Buck, Boost, Buck Boost) the Energy got from the Solar Panels is Converted to Required Voltage and Stored in the Power Storing System (for ex, Battery). This manuscript details a design method for a 500kW solar power based micro grid system for space applications. The design method utilizes multi-objective optimization with the Genetic Algorithm considering four parameters that characterize solar power based micro grids (battery voltage, PV maximum power, PV maximum power point voltage, and number of panels per string). The final optimization metric is the ratio of daily average deliverable power to total system mass (W/kg) metric.
The micro grid system is composed of a number of modular DC-DC micro-converters, of which four topologies (buck, boost, buck-boost and non-inverting buck boost) are evaluated and compared. The non-inverting buck boost converter is determined to be the best candidate, and the optimal system characteristics are provided and analysed. The final system design achieves a specific power of 35.56W/kg, with optimized result of 743.7V battery voltage, 439.5W PV maximum power, 182.7V PV maximum voltage, and three panels per string. Based on the optimizations results, a prototype is designed, tested, and analysed in terms of efficiency and low temperature reliability. The converter achieved a peak efficiency of 98.4%, a power density of 3.54W/cm3, a specific power of 3.76W/g, and operated for over 267 hours of 11-minute low temperature cycles from 0oC to -140oC.
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