Transmission network planning for realistic Egyptian systems via encircling prey based algorithms

Abstract

Transmission network planning problem (TNPP) is one of the pertinent issues of the planning activities in power systems. It aims to optimally pick out the routs, types, and number of the new installed lines to confront the expected future loading conditions. In this line, this study proposes a new economic model to the TNPP. The aim of the model is to find the optimal transmission routes at least investment and operating costs. Three recent algorithms called grey wolf optimization algorithm (GWOA), spotted hyena optimization algorithm (SHOA) and whale optimization algorithm (WOA) are developed to solve the TNPP. The concept of these algorithms is based on encircling prey operation. The competitive methods are investigated to find the optimal TNPP solution for two realistic Egyptian networks. The first tested network is the 66 kV West Delta Region (WDR) system while the second one is the extra high voltage (EHV) 500 kV system. Their demand forecasting is extracted forward to 2030 dependent upon the adaptive neurofuzzy inference system (ANFIS). Tremendous technical and economic advantages through application of the encircling prey-based algorithms to handle the TNPP.