# A Machine Learning Approach for Solar Power Technology Review and Patent Evolution Analysis
## 2 Literature Review
### Solar Power Cells and Energy Storage
High concentration PV technology has received international attention due to advantages of efficient high-power generation, a low temperature coefficient, and the potential to reduce power generation costs. PV systems are frequently designed to operate and interconnect with the electric utility grid. The main component in grid-connected PV systems is the inverter, or power-conditioning unit (PCU). The PCU converts the DC power into AC power which is consistent with the voltage and power requirements of the grid and automatically stops supplying power when the grid meets the power demand [19]. Electricity must be used as it is produced, but it can be stored as long as it is converted to another energy form (such as chemical energy in batteries) or used to pump water uphill where the hydrostatic power can be used to power turbines. The limitation of solar power is that the technology of transforming electricity into storable energy has not matured. To overcome the intermittency problem of solar power, a storage medium or energy carrier is required. There are three technologies that are currently used as viable energy storage solutions for solar power, i.e., smart batteries, thermal energy storage and hydrogen fuel cells. First, smart batteries can store energy generated by solar panels, which means there is no waiting for sunshine before starting up machines or appliances. The energy generated during the day can supply power at night. Thermal energy storage is commonly used with thermal solar power plants which generate high temperatures using mirror arrays rather than photovoltaic panels. The stored heat (e.g., molten salt) vaporizes water into steam to activate the turbine and electric generators during the night [20]. Fuel cells can be used as part of a solar-hydrogen energy cycle where a system converts water to hydrogen and oxygen. Hydrogen and oxygen are further stored by a fuel cell to produce electricity without sunlight. Large-scale energy storage solutions are still in their infant stages, yet these technologies will greatly influence the renewable energy industry. Solar thermal systems concentrate sunlight to generate steam and require isothermal energy storage systems to store the energy. One storage option is the application of phase change materials to absorb or release energy [21]. [PERSON] et al. [22] provided a review of studies dealing with thermal energy storage using these materials. [PERSON] and [PERSON] [23] reviewed the current state of research in this particular field, focusing on the assessment of the thermal properties of various materials, methods of heat transfer enhancement and the design configurations of heat storage facilities. Some natural substances such as salt hydrates, paraffin, fatty acids and other compounds have high latent heat coefficients which are required for solar storage applications. The limitation of salt hydrates is chemical instability when heated, as they degrade at high temperatures and lose water in every heating cycle. Some salts are chemically aggressive towards structural materials. These two factors, poor stability in thermal cycling and corrosion between the phase change materials and the container, have limited the widespread utilization of latent heat storage technologies [22]. For parabolic trough power plants, heat storage systems with operation temperatures between 300 and 390 \({}^{\circ}\)C are widely used. [PERSON] et al. [24] developed a solid media heat storage system which was tested in a parabolic trough test loop in Spain. The experimental results show the effects of changing parameters on the storage system. While the effects of the storage material properties are limited, the selected geometry of the storage system is important. Weather forecasting errors affect the power and load demand, and the economic performance of the PV power systems. [PERSON] et al. [25] propose an adaptive solar power forecasting model for precise solar power forecasting.