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Improving Simultaneous Cooling and Power Load-Following Capability for MGT-CCP Using Coordinated Predictive Controls

机译:使用协调预测控制改善MGT-CCP​​的同时冷却和功率负载跟随能力

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摘要

The distributed energy system is an energy supply method built around the end users, which can achieve energy sustainability and reduce emissions compared to traditional centralized energy systems. The micro gas turbine (MGT)-based combined cooling and power (CCP) system has received renewed attention as an important distributed energy system technology due to its substantial energy savings and reduced emission levels. The task of the MGT-CCP system is to quickly adapt to changes in various renewable energy sources to maintain the balance in energy supply and demand in a distributed energy system. Therefore, it is imperative to improve the load tracking capability of the MGT-CCP system with advanced control technologies toward achieving this goal. However, the difficulty of controlling the MGT-CCP system is that the MGT responds very fast while CCP responds very slowly. To this end, the dynamic characteristics and nonlinear distribution of the MGT and CCP processes are analyzed, and a coordinated predictive control strategy is proposed by utilizing the generalized predictive control for the MGT system and the Hammerstein generalized predictive control for the CCP system. The coordinated predictive control of generalized predictive control and Hammerstein generalized predictive control was implemented in an 80 kW MGT-CCP simulator to verify the effectiveness of the proposed method. The simulation results show that compared with PID and MPC, the proposed control method not only can greatly improve simultaneous cooling and power load-following capability, but also has the best control effect when accessing with renewable energy.
机译:分布式能量系统是围绕最终用户构建的能量供应方法,可以实现与传统集中能源系统相比的能量可持续性和减少排放。基于微量燃气轮机(MGT)的微型燃气轮机(MGT)的组合冷却和功率(CCP)系统由于其大量节能和减少排放水平而被称为重要的分布能源系统技术。 MGT-CCP​​系统的任务是快速适应各种可再生能源的变化,以维持分布式能量系统中的能量供应和需求的平衡。因此,必须提高MGT-CCP​​系统的负载跟踪能力,具有先进的控制技术实现实现这一目标。然而,控制MGT-CCP​​系统的难度是MGT非常快速地响应,而CCP响应非常缓慢。为此,分析了MGT和CCP过程的动态特性和非线性分布,并通过利用MGT系统的广义预测控制和CCP系统的HAMMERSEIN广义预测控制来提出协调的预测控制策略。在80 kW MGT-CCP​​模拟器中实施了广义预测控制和Hammerstein广义预测控制的协调预测控制,以验证所提出的方法的有效性。仿真结果表明,与PID和MPC相比,所提出的控制方法不仅可以大大提高同时冷却和电源负载跟随能力,而且在使用可再生能源时也具有最佳的控制效果。

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