A bottom-up demand model combined with multiobjective Harris Hawks Optimization plans EV charging capacity for Chongqing, projecting 1.8 million units by 2030 at a 9:1 private-to-public ratio with better spatial balance than current deployments.
Safe-AutoSAC: AutoML-enhanced safe deep reinforcement learning for integrated energy system scheduling with multi -channel informer forecasting and electric vehicle demand response
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Synergetic capacity planning of private and public EV charging piles via city-scale multiobjective optimization
A bottom-up demand model combined with multiobjective Harris Hawks Optimization plans EV charging capacity for Chongqing, projecting 1.8 million units by 2030 at a 9:1 private-to-public ratio with better spatial balance than current deployments.