A New Hybrid Quantum-Classical Algorithm for Solving the Unit Commitment Problem
- URL: http://arxiv.org/abs/2505.00145v1
- Date: Wed, 30 Apr 2025 19:32:18 GMT
- Title: A New Hybrid Quantum-Classical Algorithm for Solving the Unit Commitment Problem
- Authors: Willie Aboumrad, Phani R V Marthi, Suman Debnath, Martin Roetteler, Evgeny Epifanovsky,
- Abstract summary: We develop a hybrid quantum-classical algorithm for the Unit Commitment problem in power systems.<n>It aims at minimizing the total cost while optimally allocating generating units to meet the hourly demand of the power loads.<n> Convergence of the hybrid quantum-classical algorithm for select time periods is proven out on IonQ's Forte system.
- Score: 1.118478900782898
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 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.
Related papers
- Leveraging Quantum Computing for Accelerated Classical Algorithms in Power Systems Optimization [0.0]
This work presents a novel hybrid algorithm that leverages quantum and classical computing to solve Unit Commitment (UC) problems.<n>We introduce a novel Benders-cut generation technique for UC, thereby enhancing cut quality, reducing expensive quantum-classical hardware interactions, and lowering qubit requirements.<n>Results from both a simulated annealer and real QAH are compared, demonstrating the effectiveness of this algorithm in reducing qubit requirements and producing near-optimal solutions on noisy QAH.
arXiv Detail & Related papers (2025-03-24T19:59:36Z) - A hybrid classical-quantum approach to highly constrained Unit Commitment problems [0.0]
The unit commitment (UC) problem stands as a critical optimization challenge in the electrical power industry.<n>This paper introduces a novel hybrid quantum-classical algorithm designed to efficiently solve the UC problem in time.
arXiv Detail & Related papers (2024-12-15T21:21:36Z) - Bias-field digitized counterdiabatic quantum optimization [39.58317527488534]
We call this protocol bias-field digitizeddiabatic quantum optimization (BF-DCQO)
Our purely quantum approach eliminates the dependency on classical variational quantum algorithms.
It achieves scaling improvements in ground state success probabilities, increasing by up to two orders of magnitude.
arXiv Detail & Related papers (2024-05-22T18:11:42Z) - A hybrid Quantum-Classical Algorithm for Mixed-Integer Optimization in Power Systems [0.0]
We present a framework for solving power system optimization problems with a Quantum Computer (QC)
Our guiding applications are the optimal transmission switching and the verification of neural networks trained to solve a DC Optimal Power Flow.
arXiv Detail & Related papers (2024-04-16T16:11:56Z) - Nonlinear dynamics as a ground-state solution on quantum computers [39.58317527488534]
We present variational quantum algorithms (VQAs) that encode both space and time in qubit registers.
The spacetime encoding enables us to obtain the entire time evolution from a single ground-state computation.
arXiv Detail & Related papers (2024-03-25T14:06:18Z) - Quantum Subroutine for Variance Estimation: Algorithmic Design and Applications [80.04533958880862]
Quantum computing sets the foundation for new ways of designing algorithms.
New challenges arise concerning which field quantum speedup can be achieved.
Looking for the design of quantum subroutines that are more efficient than their classical counterpart poses solid pillars to new powerful quantum algorithms.
arXiv Detail & Related papers (2024-02-26T09:32:07Z) - Trainable Variational Quantum-Multiblock ADMM Algorithm for Generation
Scheduling [0.0]
This paper proposes a two-loop quantum solution algorithm for generation scheduling by quantum computing, machine learning, and distributed optimization.
The aim is to facilitate noisy employing near-term quantum machines with a limited number of qubits to solve practical power system problems.
arXiv Detail & Related papers (2023-03-28T21:31:39Z) - Optimizing Tensor Network Contraction Using Reinforcement Learning [86.05566365115729]
We propose a Reinforcement Learning (RL) approach combined with Graph Neural Networks (GNN) to address the contraction ordering problem.
The problem is extremely challenging due to the huge search space, the heavy-tailed reward distribution, and the challenging credit assignment.
We show how a carefully implemented RL-agent that uses a GNN as the basic policy construct can address these challenges.
arXiv Detail & Related papers (2022-04-18T21:45:13Z) - Q-FW: A Hybrid Classical-Quantum Frank-Wolfe for Quadratic Binary
Optimization [44.96576908957141]
We present a hybrid classical-quantum framework based on the Frank-Wolfe algorithm, Q-FW, for solving quadratic, linear iterations problems on quantum computers.
arXiv Detail & Related papers (2022-03-23T18:00:03Z) - A Hybrid Quantum-Classical Algorithm for Robust Fitting [47.42391857319388]
We propose a hybrid quantum-classical algorithm for robust fitting.
Our core contribution is a novel robust fitting formulation that solves a sequence of integer programs.
We present results obtained using an actual quantum computer.
arXiv Detail & Related papers (2022-01-25T05:59:24Z) - Hybrid Quantum-Classical Unit Commitment [0.0]
This paper proposes a hybrid quantum-classical algorithm to solve a fundamental power system problem called unit commitment (UC)
Using Qiskit on the IBM Q system as the simulation environment, simulation results demonstrate the validity of the proposed algorithm to solve the UC problem.
arXiv Detail & Related papers (2022-01-07T01:48:58Z)
This list is automatically generated from the titles and abstracts of the papers in this site.
This site does not guarantee the quality of this site (including all information) and is not responsible for any consequences.