An iterative algorithm for regret minimization in flexible demand scheduling problems
An iterative algorithm for regret minimization in flexible demand scheduling problems
复制标题
灵活需求调度问题中遗憾最小化的迭代算法
DOI：
10.1002/adc2.92
复制
发表时间：
2021
期刊：
影响因子：
--
通讯作者：
Dong Z
中科院分区：
文献类型：
--
作者：
Dong Z
制定灵活需求向智能电网范式分配的最优策略的主要挑战是与真实的时间价格和电力需求相关的不确定性。本文提出了一个基于遗憾的模型和一个新的迭代算法，解决了极小极大遗憾优化问题。与传统的线性规划方法相比，该算法具有较低的计算负担，并通过更新可行的功率计划提供迭代收敛，从而实现了大规模设备群的可扩展并行实现。具体而言，我们的方法旨在最大限度地减少所有价格场景中引起的最坏情况下的遗憾，并解决电气设备的最佳充电策略。证明了该方法的收敛性和计算解的最优性，并讨论了不同类型的价格实现和不确定性界限下单个设备操作的情况下的一些数值模拟。
A major challenge to develop optimal strategies for allocation of flexible demand toward the smart grid paradigm is the uncertainty associated with the real‐time price and electricity demand. This article presents a regret‐based model and a novel iterative algorithm which solves the minimax regret optimization problem. This algorithms exhibits low computational burden compared with traditional linear programming methods and affords iterative convergence through updates of feasible power schedules, thus enabling a scalable parallel implementation for large device populations. Specifically, our approach seeks to minimize the induced worst‐case regret over all price scenarios and solves the optimal charging strategy for the electrical devices. The convergence of the method and optimality of the computed solution is justified and some numerical simulations are discussed for the case of a single device operating under different types of price realizations and uncertainty bounds.