Energy generation from renewable sources is a global trend due to the carbon emissions generated by fossil fuels, which cause serious harm to the ecosystem. As per the long-term goals of the ASEAN countries, the Malaysian government established a target of 31% renewable energy generation by 2025 to facilitate ongoing carbon emission reductions. To reach the goal, a large-scale solar auction is one of the most impactful initiatives among the four potential strategies taken by the government. To assist the Malaysian government’s large-scale solar policy as detailed in the national renewable energy roadmap, this article investigated the techno-economic and feasibility aspects of a 10 MW floating solar PV system at UMP Lake. The PVsyst 7.3 software was used to develop and compute energy production and loss estimation. The plant is anticipated to produce 17,960 MWh of energy annually at a levelized cost of energy of USD 0.052/kWh. The facility requires USD 8.94 million in capital costs that would be recovered within a payback period of 9.5 years from the date of operation. The plant is expected to reduce carbon emissions by 11,135.2 tons annually. The proposed facility would ensure optimal usage of UMP Lake and contribute to the Malaysian government’s efforts toward sustainable growth.

This data article presents a comprehensive dataset comprising experimentally tested characteristics of newly manufactured photovoltaic (PV) modules, which have been collected by using a commercial PV testing system from a solar panel manufacturer company. The PV testing system includes an artificial sunlight simulator to generate input light for the PV and the outputs of the PV are tested by a professional IV tracer in a darkroom environment maintaining IEC60904–9 standard. The dataset encompasses modules with power ratings of 10 W, 85 W, and 247 W, each represented by 40 individual module records. The tested and collected characteristics of each module include open circuit voltage, short circuit current, maximum power point voltage, maximum power point current, maximum power point power, and fill factor. The motivation for this dataset lies in addressing the challenges posed by manufacturing defects and a ± 5 % manufacturing tolerance, which can lead to mismatch power losses in newly installed PV arrays. These losses result in lower current in series strings and lower voltage in parallel branches, ultimately decreasing the array's output power. The dataset serves as a valuable resource for academic research, particularly in the domain of PV array optimization. To facilitate optimization efforts, different algorithms have been explored in the literature. This dataset supports the exploration of these optimization algorithms to find solutions that enhance the position of each module within the array, consequently increasing the overall output power and efficiency of the PV system. The objective is to mitigate mismatch power losses, which, if unaddressed, can contribute to increased degradation rates and early aging of PV modules. This dataset lays the groundwork for addressing critical PV array performance and efficiency issues. In future research, this dataset can be reused to explore and implement optimization algorithms, to improve the overall output power and lifespan of newly installed PV arrays. The smart solution proposed in [1], utilizing a genetic algorithm-based module arrangement, demonstrates promising results for maximizing PV array output power using this dataset.

Floating solar photovoltaic has emerged as a highly sustainable and environmentally friendly solution worldwide from the various clean energy generation technologies. However, the installation of floating solar differs from rooftop or ground-mounted solar due to the significant consideration of the availability of water bodies and suitable climatic conditions. Therefore, conducting a feasibility analysis of the suitable climate is essential for installing a floating solar plant on water bodies. These data are evaluated for the viability of installing a 6.7 MW floating solar power plant on Hatirjheel Lake in Dhaka, Bangladesh. The feasibility analysis incorporated various climatic data, such as temperature, humidity, rainfall, sunshine hours, solar radiation, and windspeed, obtained from Meteonorm 8.1 software and the archive of the Bangladesh Meteorological Department. Besides, this study gathered and analyzed the energy demands of the local grid substation operated by Dhaka Power Distribution Company, to determine the appropriate capacity and architecture of the power plant. The power plant design was conducted using the PVsyst 7.3 software, which determined the necessary equipment quantities, DC energy generation capacity, and the energy injected into the grid in MWh. The study also calculated the Levelized Cost of Energy per kilowatt-hour and the payback period for the system, which indicates the economic viability of installing the system. Furthermore, the acquired dataset possesses significant potential and can be utilized for the establishment of all sorts of solar power plants, including floating solar plants, in any location or body of water within the Dhaka Metropolitan area.