Optimizing integrated energy systems at park level: A cooperative game approach with exergy economics

This study presents a comprehensive framework for optimizing energy systems by integrating exergy analysis, energy economics, and game theory. The concept of exergy, which quantifies the usable energy within a system, is employed to evaluate energy efficiency and losses across various energy sources, including thermal, cooling, chemical, and electrical systems. Stoichiometric coefficients, denoted by the factor λ, are utilized to simplify exergy calculations for different energy types and processes. The economic evaluation of energy flows is conducted through energy economics principles, incorporating cost allocation and balance equations. The integration of game theory into the optimization model ensures strategic interactions among energy components, leading to a Nash equilibrium that balances economic performance, efficiency, and environmental sustainability. The model also accounts for emissions and the required proportion of renewable energy. To solve the complex optimization problem, a modified Particle Swarm Optimization (PSO) algorithm is employed, featuring adaptive mechanisms for velocity and inertia updates, enhancing the search process for the optimal solution. The proposed framework is designed to optimize the Integrated Energy System (IES) efficiently, ensuring sustainable and economically viable energy management. The analysis of optimization strategies highlights a trade-off between cost and efficiency. Strategy 1, focused on minimizing cost, achieves the lowest cost at 4069.37 CNY, 25.79 % less than Strategy 2, but with a reduced exergy efficiency of 59.82 %, which is 10.14 % lower than Strategy 2′s 68.47 %. Strategy 3 offers a balanced approach, with a cost of 4970.89 CNY, 9.43 % higher than Strategy 1 but 9.43 % lower than Strategy 2. It achieves an exergy efficiency of 67.87 %, only 0.60 % lower than Strategy 2, thus providing a practical compromise between economic performance and efficiency.