论文标题
迈向平衡的三相充电：自适应充电网络中的相优化
Towards Balanced Three-phase Charging: Phase Optimization in Adaptive Charging Networks
论文作者
论文摘要
我们研究电动车（EV）充电的相相优化问题。我们将我们的问题提出为非凸层混合组件编程问题，其目的是最大程度地减少充电损失。尽管很难直接解决这个非凸问题，但我们通过提出PXA算法来解决原始问题的放松，其中“ P”，“ X”和“ A”在形成的相位优化问题中为三个可变矩阵代表。我们表明，在某些条件下，解决方案由PXA准确地收敛到全局最佳。此外，使用模型预测控制（MPC）的想法，我们设计{PXA-MPC}，这是PXA的在线实现。与其他经验阶段平衡策略相比，PXA算法通过最大化能源输送，最大程度地减少充电价格并协助未来的能源计划来显着提高充电性能。使用从现实世界自适应EV充电网络（ACN）收集的数据证明了我们算法的功效。
We study the problem of phase optimization for electric-vehicle (EV) charging. We formulate our problem as a non-convex mixed-integer programming problem whose objective is to minimize the charging loss. Despite the hardness of directly solving this non-convex problem, we solve a relaxation of the original problem by proposing the PXA algorithm where "P", "X", and "A" stand for three variable matrices in the formed phase optimization problems. We show that under certain conditions, the solution is given by the PXA precisely converges to the global optimum. In addition, using the idea of model predictive control (MPC), we design the {PXA-MPC}, which is an online implementation of the PXA. Compared to other empirical phase balancing strategies, the PXA algorithm significantly improves the charging performance by maximizing energy delivery, minimizing charging price, and assisting future energy planning. The efficacy of our algorithm is demonstrated using data collected from a real-world adaptive EV charging network (ACN).
