Abstract Optimal management of thermal and energy grids with fluctuating demand and prices requires to orchestrate the generation units (GU) among all their operating modes. A hierarchical approach is proposed to control coupled energy nonlinear systems. The high level hybrid optimization defines the unit commitment, with the optimal transition strategy, and best production profiles. The low level dynamic model predictive control (MPC), receiving the set-points from the upper layer, safely governs the systems considering process constraints. To enhance the overall efficiency of the system, a method to optimal start-up the GU is here presented: a linear parameter-varying MPC computes the optimal trajectory in closed-loop by iteratively linearizing the system along the previous optimal solution. The introduction of an intermediate equilibrium state as additional decision variable permits the reduction of the optimization horizon, while a terminal cost term steers the system to the target set-point. Simulation results show the effectiveness of the proposed approach.

中文翻译：

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智能发电机组最优分级控制方案：在汽电联产中的应用

摘要 在需求和价格波动的情况下对热电网和能源电网进行优化管理需要在所有运行模式之间协调发电机组 (GU)。提出了一种分层方法来控制耦合能量非线性系统。高级混合优化定义了单元配置、最佳转换策略和最佳生产配置文件。低级动态模型预测控制 (MPC) 接收来自上层的设定点，在考虑过程约束的情况下安全地管理系统。为了提高系统的整体效率，这里提出了一种优化启动 GU 的方法：线性参数变化 MPC 通过沿先前的最优解迭代线性化系统来计算闭环中的最优轨迹。引入中间平衡状态作为附加决策变量可以减少优化范围，而终端成本项将系统引导至目标设定点。仿真结果表明了所提出方法的有效性。