Swarm Intelligence-Based Smart Energy Allocation Strategy for Charging Stations of Plug-In Hybrid Electric Vehicles

<table class="table-group" id="tab5"><tr><td><table class="table"><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr class="thead"><td align="left">Average best fitness for</td><td align="center">PSO</td><td align="center">GSA</td></tr><tr><td class="thead-hr" colspan="3"><hr/></td></tr><tr><td align="left">50 PHEVs</td><td align="center">142.839</td><td align="center">158.8289</td></tr><tr><td align="left">100 PHEVs</td><td align="center">171.102</td><td align="center">182.3097</td></tr><tr><td align="left">300 PHEVs</td><td align="center">169.312</td><td align="center">172.4296</td></tr><tr><td align="left">500 PHEVs</td><td align="center">150.869</td><td align="center">152.36437</td></tr><tr><td align="left">1000 PHEVs</td><td align="center">156.802</td><td align="center">161.52349</td></tr><tr class="table-tr"><td colspan="3"><hr class="tbody-hr"/></td></tr></table></td></tr></table>

Summarizes the comparisons of GSA with PSO algorithm in terms of average best fitness.

Mathematical Problems in Engineering

tab5

Table 5

Table 5: Swarm Intelligence-Based Smart Energy Allocation Strategy for Charging Stations of Plug-In Hybrid Electric Vehicles 