The Contribution of Wind Energy Capacity on Generation Systems Adequacy Reliability using Differential Evolution Optimization Algorithm

Abstract

Currently, increasing penetration of the Wind Energy Conversion System (WECs) in Power generation systems has influenced the supply of electrical power reliability for the consumer in comparison with other traditional sources. In this paper, the performance and efficiency of a new optimization approach referred to as the "Differential Evolution Optimization Algorithm" (DEOA) to measure the reliability of power adequacy systems (RPAs). The proposed intelligent algorithm which relies on the Population-based Intelligent Search (PBIs) technique is viewed as a feasible alternative for the Monte Carlo simulation (MCS) method in the assessment of the non-chronological system. The benefit of utilizing this algorithm is apparent in the manner it expedites the calculation and achieves greater precision with less calculation effort. Additionally, there is a deeper understanding of the effect of the increasing levels of wind energy on generation adequacy from the WECs sources to satisfy future power electricity demands. In addition, the effectiveness of the suggested algorithm in assessing the RPAs was compared to the analytical and MCS method.

Ecological impact due to the implementation of a modeled and optimized hybrid system

“…The modeling of the wind system [19] concerns primarily the wind power generated and commonly a wind turbine on the market is characterized by its nominal power. This power is provided when there is a wind blowing at a nominal speed.…”