标题： 一种求解机组组合问题的新混合量子-经典算法 显示英文标题

标题： A New Hybrid Quantum-Classical Algorithm for Solving the Unit Commitment Problem

摘要： 解决与大规模电力系统规划和运行相关的问题在经典计算机上具有挑战性，因为这些问题本质上是混合整数和非线性问题。 量子计算为此类问题提供了新的途径。 我们为电力系统的机组组合（UC）问题开发了一种混合量子-经典算法，旨在最小化总成本的同时最优分配发电单元以满足每小时的电力负荷需求。 该混合算法结合了变分量子算法（VQA）和经典的Bender启发式方法。 所得算法通过三个阶段计算UC的近似解：i）基于VQA生成一组能够以最低可能运行成本满足电力需求的UC向量；ii）利用经典的顺序最小二乘规划（SLSQP）程序找到对应于预定候选向量数量的最优功率水平；iii）在最后一阶段，提供UC的近似解以及发电单元的功率水平组合。 为了证明所提出方法的有效性，在不同的时间段内测试了三种不同系统，分别包含3个、10个和26个发电单元。 此外，在IonQ的Forte系统上证明了选定时间段内混合量子-经典算法的收敛性。 显示英文摘要

摘要： Solving problems related to planning and operations of large-scale power systems is challenging on classical computers due to their inherent nature as mixed-integer and nonlinear problems. Quantum computing provides new avenues to approach these problems. We develop a hybrid quantum-classical algorithm for the Unit Commitment (UC) problem in power systems which aims at minimizing the total cost while optimally allocating generating units to meet the hourly demand of the power loads. The hybrid algorithm combines a variational quantum algorithm (VQA) with a classical Bender's type heuristic. The resulting algorithm computes approximate solutions to UC in three stages: i) a collection of UC vectors capable meeting the power demand with lowest possible operating costs is generated based on VQA; ii) a classical sequential least squares programming (SLSQP) routine is leveraged to find the optimal power level corresponding to a predetermined number of candidate vectors; iii) in the last stage, the approximate solution of UC along with generating units power level combination is given. To demonstrate the effectiveness of the presented method, three different systems with 3 generating units, 10 generating units, and 26 generating units were tested for different time periods. In addition, convergence of the hybrid quantum-classical algorithm for select time periods is proven out on IonQ's Forte system.