Vehicular electrification plays a major role in the reduction of toxic greenhouse gas emissions linked to the transportation sector. However, the differential margin between electricity supply and demand is chaotic; and only a production/consumption balance could reconcile both ends. The adaptation of energy flows is therefore necessary to confront the gigantic energy waste related to electricity storage challenges. Consequently, electric vehicle batteries recently emerged as a solution to the actual limitation of storage capability. Indeed, they are used in this study as means of storage and retrieval of energy.

Thus, this paper proposes a control and regulation algorithm aimed at reaching a balanced production/consumption system. The balance is acquired through the bidirectional control of the energy flows related to domestic residences, electric vehicles and the grid. Moreover, a multi-objective optimization of vehicular charging and discharging is assessed using the genetic algorithm to attain an optimal fulfillment of the system’s energetic needs. Once the regulation algorithm is set and the optimizations implemented, the algorithm’s simulation is performed using Matlab. Through the developed algorithm, we aim these major findings: 1. Regulate energy flows depending on supply and demand. 2. Optimize charging and discharging modes. 3. Flows merge towards the system’s equilibrium state.

车辆电气化在减少与运输部门有关的有毒温室气体排放中起着重要作用。然而，电力供需之间的差额是混乱的。而且只有生产/消费的平衡才能实现双方的平衡。因此，必须调整能量流以应对与储电挑战相关的巨大能源浪费。因此，近来出现了电动车辆电池作为对实际存储能力限制的解决方案。实际上，它们在这项研究中被用作能量的存储和回收手段。

因此，本文提出了一种旨在达到平衡的生产/消费系统的控制和调节算法。通过双向控制与住宅，电动汽车和电网有关的能量流来获取余额。此外，使用遗传算法评估了车辆充电和放电的多目标优化，以最佳地满足系统的能量需求。一旦设置了调节算法并实现了优化，就可以使用Matlab进行算法的仿真。通过开发的算法，我们针对以下主要发现：1.根据供需调节能量流。2.优化充电和放电模式。3.流量合并到系统的平衡状态。