GA optimization of Hybrid Energy Systems for telecommunications in marginalised rural areas

Abstract

The Siyakhula Living Lab (SLL) is one of the numerous Information and Communication Technology for Development (ICTD) initiatives to bridge the technological divide between rural and urban South Africa. Given the power dependency of Information Communication Technology (ICT), the unreliable power supply which upon the ICTD infrastructure currently runs on is set to provide challenges if not addressed. Over the years, various ICT infrastructure installed in the SLL has been destroyed and communication compromised due to power outages. With problems of some parts of South Africa being off-grid, poorly supplied and serviced due to their geography, or under load-shedding, there is need to exploit other energy sources. This power problem has coincided with the advent of renewable and clean energy and environmentally aware computing and engineering. Such a coincident pushes for the research in optimizing locally available renewable energy sources such as wind and solar which when combined form Hybrid Energy Systems (HES). HES have been widely used as of late but still lack the financial and environmental constraint optimization capability to achieve their maximum potential. This paper therefore proposes Genetic Algorithms (GA) applied to HES for the optimal utilization and mix of the power sources for both economic and environmental dispatch to suit the low cost and minimal adverse health issues in rural South Africa.