Adaptive dynamic pricing for optimal electric vehicle charging and load balancing in smart distribution networks

Abstract

The growing use of electric vehicles (EVs) in distribution networks has brought both environmental benefits and operational problems. When people quickly adopt something without proper planning, it can cause grid congestion and voltage instability. This paper introduces an improved dynamic pricing system that evenly distributes the load between residential and commercial distribution networks by changing how EVs charge. The proposed framework uses localized demand profiles and time-of-use (TOU) rates to create dynamic charging incentives that encourage users to charge their devices at the best times. The system changes prices automatically based on how much the grid is being used, which makes load curves smoother and makes better use of assets. Simulation results show that when charging isn't coordinated, load imbalance causes mean absolute percentage errors (MAPE) to reach almost 28%. The proposed scheme, on the other hand, lowers this to less than 6%, showing a big improvement in the performance of the distribution network and voltage stability.