Analysis of Energy Price Forecasting and Market Competition Strategy Based on Game Theory

Abstract

This study delves into the intricate dynamics of energy price forecasting and market competition strategy by employing game theory as a guiding framework. Energy price forecasting is crucial for strategic decision-making in the energy market, influencing investment, production, and consumption behaviors. Game theory provides a robust analytical tool to understand the strategic interactions among market participants, including producers, consumers, and regulatory bodies. By integrating game theory models with empirical data from energy markets, this research analyzes the strategic behaviors and market outcomes in response to various factors such as demand-supply dynamics, regulatory policies, and technological advancements. The study aims to provide insights into optimal strategies for energy market stakeholders, facilitating informed decision-making amidst complex market dynamics. Through theoretical analysis and empirical case studies, this research contributes to a deeper understanding of energy market dynamics and offers practical guidance for navigating this dynamic landscape. In the Cournot competition model, producers simultaneously decide on quantities of output to maximize their profits while taking into account the expected responses of their competitors