Parameter Identification and Sliding Pressure Control of a Supercritical Power Plant Using Whale Optimizer

Abstract

Sliding pressure control is a well-known method of controlling supercritical power plants that improves energy efficiency and reduces pressure dynamic stresses. This paper presents a novel approach for developing a supercritical cleaner coal power plant’s sliding pressure control strategy. First, using Whale Optimizer, a nonlinear identified transfer matrix model was created (WO). By comparing simulations and errors, the WO clearly outperforms the GA and Grey-Wolf Optimizer (GWO) techniques on parameter identification. The model also includes a multivariable PI/PD controller for improved plant operation. Again, WO controller tuning outperformed GA and GWO in terms of pressure deviations, power deviations, rise time, and fuel usage. It is now argued that the WO is superior to other techniques in modeling and controlling system dynamics, energy efficiency, and cleaner operation.

Synthetic Data-Integrated Li-Ion Battery Modeling for eVTOL Energy Systems

“…The battery's thermal mass is represented by 𝑀 𝑡ℎ , T is the battery temperature, 𝑉 𝑇,𝑖 is the voltage drop across the resistor 𝑅 𝑇,𝑖 . The Whale Optimizer previously showed its intelligence algorithm in optimizing and identifying the unknown parameters is used in this research to estimate model parameters by optimization of the HPPC test results at each SoC level separately for more accurate estimation [26]. However, these parameters are functions of temperature, SoC, and aging.…”

Reduction of emissions and improvement of dynamic responses of a supercritical clean coal generation unit via neural network inverse control strategy

“…6 The data signals have been extensively used in many different research applications concerning modeling and control. 6,11,14 The data can be used throughout lifespan of supercritical units and has no expiry date as long as this type of plants is still in operation. This is because they are subject to regular maintenance that avoids deterioration in equipment and/or dynamic performance and it is then confirmed that no significant change has occurred on the data in this period.…”

“…In control theory, the controlled reference correction, by predictive control or intelligent inverse control, is capable of increasing the speed of the response of the various actuators in the regulatory layer of control. 7,13,14,46 The load signal taken from set of data portion representing the once-through operation has been injected as an expected demand signal in order to observe the effect of the upgraded controller on the inputs, especially the coal consumption. As depicted in Figures 24 and 25, which represents the power output and coal flow input, respectively, the load demand is followed smoothly by the inverse controller, and that is also reflected in the coal consumption that has been robustly smoothed and minimized.…”

“…It is worth mentioning that, there are many design methods for enhancement of energy efficiency and hence reducing emissions and saving coal for coal-fired steam power plants, which include, but not limited to:- Supercritical boiler operation, advanced modeling, and control. 6,11–14 - Adoption of additional cooling towers. 15,16 - Increasing the condenser size.…”

Energy-Efficient Control of a Gas Turbine Power Generation System

“…From a deep investigation of the literature, Whale Optimizer (WO) is still not applied and evaluated in the field of gas turbines' modeling and control. Although WO has been applied for a coal unit [22], it is worth investigating specifically on GT control system because of the high number of differences in the design, characteristics, and practical viability between the two types of power plants, which offers an opportunity for more novel achievements in this research area. The contributions of this paper are then stated as follows:…”