Optimization of the design and manufacture of a solar-wind hybrid street light

Wilson R. Nyemba, Simon Chinguwa, Innocent Mushanguri, Charles Mbohwa

Research output: Contribution to journalConference articlepeer-review

21 Citations (Scopus)


The demand for electricity has escalated and cannot be fulfilled by conventional energy sources alone. There has been a rising demand to seek new renewable energy sources. Although solar and wind energy are the most cost effective renewable energy sources, they are unreliable due to the sporadic nature of their occurrence, if implemented as standalones. In Zimbabwe, solar street lighting has been implemented since 2014 as a solution to the erratic power supplies and outages. Wind potential in Zimbabwe has been identified at elevated heights, with Gweru having the maximum power density of 115 W/m2 at 50 m hub height. This paper presents the optimization of the design of a hybrid renewable energy system (HRES) of solar and wind energy to power a 160W streetlight. The system consisted of a wind turbine, photovoltaic modules, charge controller, battery bank and lights. The system sizing was done in Excel using wind and solar data obtained from the database, HOMER Software Package and PVSyst. The 3D streetlight was modelled using Inventor Professional and a working prototype was manufactured. The results showed that the HRES reduced the energy storage requirements by 38.75% with an overall cost reduction of 14.4%, relative to a standalone solar streetlight. The diffuser effect to the turbine was experimentally assessed, showing 69.3% increase in turbine power output and a 50% decrease in energy storage requirements. Further research can be carried to improve the reliability for standalone systems.

Original languageEnglish
Pages (from-to)285-290
Number of pages6
JournalProcedia Manufacturing
Publication statusPublished - 2019
Event2nd International Conference on Sustainable Materials Processing and Manufacturing, SMPM 2019 - Sun City, South Africa
Duration: 8 Mar 201910 Mar 2019

ASJC Scopus subject areas

  • Industrial and Manufacturing Engineering
  • Artificial Intelligence


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