  The rapid development of electric vehicle (EV) technologies promises cleaner
air and more efficient transportation systems, especially for polluted and
congested urban areas. To capitalize on this potential, the Indonesian
government has appointed PLN, its largest state-owned electricity provider, to
accelerate the preparation of Indonesia's EV infrastructure. With a mission of
providing reliable, accessible, and cost-effective EV charging station
infrastructure throughout the country, the company is prototyping a
location-optimized model to simulate how well its infrastructure design reaches
customers, fulfills demands, and generates revenue. In this work, we study how
PLN could maximize profit by optimally placing EV charging stations in urban
areas by adopting a maximal covering location model. In our experiments, we use
data from Surabaya, Indonesia, and consider the two main transportation modes
for the locals to charge: electric motorcycles and electric cars. Numerical
experiments show that only four charging stations are needed to cover the whole
city, given the charging technology that PLN has acquired. However, consumers'
time-to-travel is exceptionally high (about 35 minutes), which could lead to
poor consumer service and hindrance toward EV technologies. Sensitivity
analysis reveals that building more charging stations could reduce the time but
comes with higher costs due to extra facility installations. Adding layers of
redundancy to buffer against outages or other disruptions also incurs higher
costs but could be an appealing option to design a more reliable and thriving
EV infrastructure. The model can provide insights to decision-makers to devise
the most reliable and cost-effective infrastructure designs to support the
deployment of electric vehicles and much more advanced intelligent
transportation systems in the near future.
