Open AccessTwo-Stages Carbon Emission Pinch Analysis for Integrated System of Renewable Energy and Electric Vehicle
Author(s) -
Ahmad Fakrul Ramli,
Ahmad Muzammil Idris,
Zarina Ab Muis,
Wai Shin Ho,
Aziatul Niza Sadikin,
Syaza Izyanni Ahmad
Publication year - 2020
Publication title -
iop conference series. materials science and engineering
Language(s) - English
Resource type - Journals
eISSN - 1757-899X
pISSN - 1757-8981
DOI - 10.1088/1757-899x/884/1/012023
Subject(s) - renewable energy , electrification , electricity generation , electricity , electric vehicle , zero emission , greenhouse gas , environmental economics , energy mix , green vehicle , automotive engineering , environmental science , engineering , waste management , power (physics) , fuel efficiency , economics , electrical engineering , ecology , physics , quantum mechanics , biology
The introduction of electric vehicles to the transportation fleet has merged the power generation and transportation sectors into an integrated system. Rather than fuel sources, electricity is used to charge electric vehicles, so these vehicles play a vital role as an important green technology that could reduce carbon emissions in the transportation sector. This study aimed to develop a multi-stage carbon emission pinch analysis for an integrated system to optimise the energy mix for electricity generation. In the first stage, the minimum number of electric vehicles required to reduce transportation emissions was determined. In the second stage, the optimal energy mix for power generation sector was determined while including the electricity demand for the electric vehicle. Four scenarios, namely the business-as-usual scenario (S1); the public transport utilization scenario (S2); the electrification of vehicle scenario (S3); and the Integrated-Policies scenario (S4) were developed based on Peninsular Malaysia as a case study, to analyse the impact of different mitigation strategies on the country’s economy. S1 was set as baseline for all the cases i.e., without any mitigation strategies. The results reveal that S4 was the best scenario, yielding a total cost saving percentage of 51.42 % compared to S1. For the power generation sector, 52 % of renewable energy (solar PV, biomass and biogas) utilisation would be needed in the energy mix to achieve the emission reduction target.