考虑多能源协同的智慧能源站优化运行策略研究

分布式多能源技术的灵活性，促进了智慧能源站的发展。但由于系统非线性和建模的复杂性，智慧能源站优化问题中电力、热能网络和能源需求不确定性相关的约束常常被忽略。为此，提出了一种考虑系统不确定性的智慧能源站运行优化策略。该策略以能源支出成本为目标函数，使用迭代建模，包括混合整数线性规划(MILP)和非线性能源网络方程的线性近似。在MILP优化阶段，将所有能源网络中可控设备的运行计划都在考虑不确定性和综合网络的线性近似的情况下进行建模。建立非线性综合能源网络模型，并通过两种模型之间的迭代，提高线性模型的精度。使用了多维链表，有效地对不确定性进行建模并提高了计算效率。在仿真中对所提出的策略进行了测试，使用该策略进行优化后，测试系统的能源支出降低了约3%,验证了该策略的有效性。

Research on operation strategy optimization of smart energy station considering multi energy cooperation

The flexibility of distributed multi energy technology promotes the development of smart energy stations. However, due to the nonlinearity of the system and the complexity of modeling, the constraints related to the uncertainty of power, thermal network and energy demand are often ignored in the optimization problem of smart energy station. Therefore, a smart energy station operation optimization strategy considering system uncertainty is proposed. The strategy takes the energy expenditure cost as the objective function and uses iterative modeling, including mixed integer linear programming (MILP) and linear approximation of nonlinear energy network equations. In the MILP optimization stage, the operation plans of controllable equipment in all energy networks are modeled considering the uncertainty and the linear approximation of the integrated network. Then the nonlinear comprehensive energy network model is established, and the accuracy of the linear model is improved through the iteration between the two models. The multi-dimensional linked list is used to effectively model the uncertainty and improve the calculation efficiency. The proposed strategy is tested in the simulation. After using the strategy for optimization, the energy expenditure of the test system is reduced by about 3%, which verifies the effectiveness of the strategy.