Zhang Jianhua, Pu Jinzhu, Lin Mingming, Ma Qianxiong
State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China.
School of Control and Computer Engineering, North China Electric Power University, Beijing 102206, China.
Entropy (Basel). 2022 Apr 6;24(4):513. doi: 10.3390/e24040513.
The Organic Rankine Cycle (ORC) is one kind of appropriate energy recovery techniques for low grade heat sources. Since the mass flow rate and the inlet temperature of heat sources usually experience non-Gaussian fluctuations, a conventional linear quadratic performance criterion cannot characterize the system uncertainties adequately. This paper proposes a new model free control strategy which applies the (,)-entropy criterion to decrease the randomness of controlled ORC systems. In order to calculate the (,)-entropy, the kernel density estimation (KDE) algorithm is used to estimate the probability density function (PDF) of the tracking error. By minimizing the performance criterion mainly consisting of (,)-entropy, a new control algorithm for ORC systems is obtained. The stability of the proposed control system is analyzed. The simulation results show that the ORC system under the proposed control method has smaller standard deviation (STD) and mean squared error (MSE), and reveals less randomness than those of the traditional PID control algorithm.
有机朗肯循环（ORC）是一种适用于低品位热源的能量回收技术。由于热源的质量流量和入口温度通常会经历非高斯波动，传统的线性二次性能准则无法充分表征系统的不确定性。本文提出了一种新的无模型控制策略，该策略应用（，）熵准则来降低受控ORC系统的随机性。为了计算（，）熵，采用核密度估计（KDE）算法来估计跟踪误差的概率密度函数（PDF）。通过最小化主要由（，）熵组成的性能准则，得到了一种新的ORC系统控制算法。分析了所提出控制系统的稳定性。仿真结果表明，所提出控制方法下的ORC系统具有更小的标准差（STD）和均方误差（MSE），并且比传统PID控制算法具有更少的随机性。
