Global Collaboration Project: Quantum Computing-driven VPP for Multi-Carrier system

Greenest A.I. has launched a new international joint research project with Nanyang Technological University (NTU), Singapore, focusing on quantum computing–accelerated optimization of Virtual Power Plants (VPPs) for multi-energy carrier systems. This Korea–Singapore collaboration aims to develop an advanced optimization framework for the integrated operation of electricity, heat, gas, renewable energy, biogas, waste-to-energy (WtE), and energy storage systems. The research will integrate multi-energy system modeling, mathematical optimization (MINLP/MILP), and quantum computing to enable efficient scheduling, dispatch, energy trading, and demand-side management (DSM). Large-scale VPP optimization problems will be transformed into Quadratic Unconstrained Binary Optimization (QUBO) formulations and addressed using quantum annealing and the Quantum Approximate Optimization Algorithm (QAOA) within a hybrid quantum–classical optimization framework. By comparing conventional mathematical optimization with quantum and hybrid approaches, the project will evaluate solution quality, computational efficiency, constraint satisfaction, operating costs, carbon emissions, and renewable energy utilization. The collaboration combines Greenest A.I.’s expertise in biogas, waste-to-energy, process systems engineering, and energy system optimization with NTU’s strengths in quantum computing, smart grids, and multi-energy system validation. Through this international collaboration, we aim to advance scalable and computationally efficient optimization technologies for next-generation energy systems and contribute to reliable, low-carbon, and intelligent energy management in both Korea and Singapore.

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