Research on multi-subject collaborative decision-making of incremental distribution network equity investment based on game theory and optimized genetic algorithm

With the ongoing energy transition and deepening power sector reform in China, power grid enterprises are encountering increasingly complex investment scenarios. The rise of incremental distribution networks presents new opportunities but also introduces challenges such as diverse investment entities, uncertain revenue structures, and regional disparities. At the same time, grid companies must balance profitability, reliability, and broader socio-economic benefits within tight financial limits. To address this, a multi-agent game-theoretic framework is developed in this study, involving stakeholders such as investors, grid operators, users, and government bodies. The model captures strategic interactions in investment returns, cost-sharing, and risk control. A nested algorithm combining genetic and particle swarm optimization is introduced to efficiently solve the equilibrium problem. Case studies based on actual industrial park projects demonstrate the model’s practicality in guiding investment planning and risk prioritization. The findings offer valuable insights for power grid companies seeking accurate and coordinated investment strategies under evolving market conditions.