Open AccessEnvironmental feasibility of incorporation of electric taxis in South Africa
Author(s) -
Singh Ranjay,
Kumar Abhishek,
Singh Arvind R.,
Naidoo Raj,
Bansal R. C.,
Kumar Praveen
Publication year - 2019
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2018.9259
Subject(s) - renewable energy , greenhouse gas , electricity , electric vehicle , fossil fuel , environmental science , electricity generation , taxis , environmental economics , automotive engineering , business , environmental protection , natural resource economics , waste management , engineering , power (physics) , transport engineering , electrical engineering , economics , ecology , physics , quantum mechanics , biology
Public transport is very influential industry affecting our society due to its significant environmental and social impact. Policy makers have seen electric vehicle as a tool to reduce greenhouse gas emissions. Cleanliness of power from the electricity grid plays a vital role in environmental impact in the transition to electric vehicle. In countries like China, USA, India etc., majority of electricity generation is still dominated by fossil fuel fired generators. Thus, in some cases, the environmental impact of electric vehicle may be more adverse in comparison to conventional internal combustion engine vehicles (ICEV). This paper tries to study the environmental effect of incorporation of 100 Electric Vehicle taxies in Johannesburg (JNB), South Africa. Firstly, the current electricity generation scenario and vehicles standards of SA with its carbon emission is discussed. Secondly, it is shown that with the current generation mix the adoption of EV is not sustainable. Finally, penetration of Renewable Energy (RE) system at charging stations is proposed with Renewable Energy Fraction (REF) of 40% and 58% to make carbon mission from EV equivalent to Euro III and Euro V standards of petrol ICEV. The optimised size of RE system is found using the Electric System Cascade Analysis.