An innovative fast iterative process algorithm computerization for intermittency LSSPV generation reconfiguration

Abstract

The recent implementation of solar photovoltaic (SPV) power generation in low-voltage distribution networks has increased due to its environmentally friendly technology, low cost, and high efficiency. However, SPV generation carried both the availability of uncertainty and intermittency on power energy exceeding voltage range, increased losses during reverse power flow action, and energy transmission problems. This paper presents a new capabilities methodology with accurate analysis to simulate the intermittent nature of SPV energy including normal generators associated with uncertain customer demand of high resolution with 1-minute temporal resolution using a fast iterative process algorithm (FIPA) simulated by Python programming. The primary goal is to address the unpredictable nature of SPV using computer operation technology connected to a real network with a fast iteration process. The result shows that in 0-10% of standard generators, grid energy (GE) is still required in daily supply, and the intermittent nature influences voltage violations and losses. Besides, the prediction typical SPV method (zero fluctuation) can serve as guidelines for engineers to design the photovoltaic (PV) module reducing its fluctuating nature and battery installation area. The research provides utilities with accurate information to plan for various difficulties at different levels of PV penetration while reducing time, effort, and resource utilization.