Nowadays, energy storage system is utilized in many countries for energy planning in the future. The changes in solar radiation lead to the overproduction of electricity in a solar photovoltaic generator. A hybrid energy storage system would play an important role in enhancing the reliability of power generation using the solar system. The microgrid is the indispensable infrastructure of the smart grid in photovoltaic systems. In this paper, the energy storage system within the microgrid of the PV system is analysed. The storage system configuration and topologies of the microgrid are analysed with power electronic interference, control scheme, and optimization of the renewable source and energy storage system. A general sizing technique for HESS in a PV system based on pinch analysis and design space. The size of HESS scales that connect generator ratings to storage capacity is created by utilizing the pinch analysis on load and resource data. The design space is a feasible combination of a short-, long-, and medium-sized energy storage system in a PV generator.

Solar energy conversion efficiency has improved by the advancement technology of photovoltaic (PV) and the involvement of administrations worldwide. However, environmental conditions influence PV power output, resulting in randomness and intermittency. These characteristics may be harmful to the power scheme. As a conclusion, precise and timely power forecast information is essential for the power networks to engage solar energy. To lessen the negative impact of PV electricity usage, the offered short-term solar photovoltaic (PV) power estimate design is based on an online sequential extreme learning machine with a forgetting mechanism (FOS-ELM) under this study. This approach can replace existing knowledge with new information on a continuous basis. The variance of model uncertainty is computed in the first stage by using a learning algorithm to provide predictable PV power estimations. Stage two entails creating a one-of-a-kind PI based on cost function to enhance the ELM limitations and quantify noise uncertainty in respect of variance. As per findings, this approach does have the benefits of short training duration and better reliability. This technique can assist the energy dispatching unit list producing strategies while also providing temporal and spatial compensation and integrated power regulation, which are crucial for the stability and security of energy systems and also their continuous optimization.