Abstract — Cross-Continental Electricity Price Prediction Using Quantum AI

Forecasting electricity prices has become increasingly challenging as modern power systems evolve with the rapid integration of renewable energy, distributed generation, and cross-border energy trading. These factors introduce high volatility, uncertainty, and nonlinear relationships that traditional forecasting models both statistical and deep learning struggle to capture effectively.

This research introduces a Quantum Artificial Intelligence (Quantum AI) framework for cross-continental electricity price prediction, combining the computational advantages of quantum computing with the learning power of artificial intelligence. Using a global day-ahead electricity price dataset covering Asia, Europe, North and South America, and Oceania, the study develops hybrid classical quantum models that embed quantum feature encoding and variational quantum circuits into advanced deep learning architectures such as Long Short-Term Memory (LSTM) and Transformer networks.

Implemented through IBM’s Qiskit simulator and IonQ’s cloud-based quantum processors, these models aim to identify long-term temporal dependencies and inter-market relationships while improving predictive accuracy and computational efficiency. Preliminary results indicate that introducing quantum layers accelerates convergence, enhances generalization, and reveals hidden relationships within complex, high-dimensional data, particularly during volatile market conditions.

Beyond technical performance, this work emphasizes the transformative potential of Quantum AI for real-world energy analytics and sustainability applications. By bridging theoretical quantum algorithms with practical forecasting needs, it establishes a foundation for next-generation energy systems capable of adaptive, data-driven decision-making. The project also promotes interdisciplinary education, engaging students in hands-on research that unites quantum simulation, artificial intelligence, and energy modeling.

Overall, this study demonstrates how Quantum AI can redefine electricity price forecasting by enabling more accurate, efficient, and scalable predictive models that support renewable energy integration, smart grid development, and a sustainable global energy future.