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Published on: September 8, 2023
Quantum Computing for Optimal Dispatch of Virtual Power Plants Under Wind and Solar Uncertainty.
Ningqiao Liu1, Yuxin Zhang1, Zhihang Liu2
1School of Electrical and Information Engineering, Changsha University of Science and Technology, Changsha 410114, China.
Entropy (Basel, Switzerland)
|June 26, 2026
Summary
Virtual Power Plants (VPPs) use quantum computing for optimal dispatch. A Coherent Ising Machine (CIM) significantly reduces computation time for VPP operations, enabling faster smart grid management.
Area of Science:
- Quantum Computing
- Smart Grids
- Optimization
Background:
- Modern power systems face operational challenges with integrated Distributed Energy Resources (DERs).
- Virtual Power Plants (VPPs) are a solution for managing DERs.
- VPP operations involve complex optimization problems (NP-hard).
Purpose of the Study:
- To address the VPP optimal dispatch problem under renewable energy uncertainty.
- To apply quantum computing for accelerating VPP operations.
- To demonstrate the effectiveness of the Coherent Ising Machine (CIM) for VPP dispatch.
Main Methods:
- Formulated classical and Quadratic Unconstrained Binary Optimization (QUBO) models for Model Predictive Control (MPC) based VPP dispatch.
- Utilized a Coherent Ising Machine (CIM) to solve the QUBO formulation.
- Compared CIM performance against classical solvers (Gurobi, Simulated Annealing, Tabu Search).
Main Results:
- CIM achieved significant computational time reductions: 75.25% vs. Gurobi, 99.95% vs. Simulated Annealing, and 99.96% vs. Tabu Search.
- CIM maintained competitive solution quality compared to classical methods.
- Demonstrated substantial acceleration potential for VPP intraday rolling dispatch.
Conclusions:
- The Coherent Ising Machine (CIM) is applicable and effective for VPP intraday rolling dispatch.
- Specialized photonic quantum computers like CIM show promise for practical smart grid applications.
- Quantum computing offers a pathway to overcome computational bottlenecks in power system optimization.
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