High Load Disturbance Research Articles

Optimal design of a cascade controller for frequency stability of photovoltaic–reheat thermal power systems considering nonlinearities

Automatic generation control (AGC) is essential for raising living standards because it enhances power supply quality. However, due to the constraints and challenges experienced in practice, an effective and computationally economical control method is necessary to improve AGC performance, particularly in the presence of renewable energy. Therefore, this study introduces a novel cascade controller (CC) of a proportional–integral–derivative (PIDn) controller followed by a proportional–integral (PI) controller, forming a PIDn-PI CC. This controller is used in a two-area model comprising a reheat thermal generator and a photovoltaic unit. The gains of the PI, PIDn, and PIDn-PI controllers are adjusted using the recently introduced chaos game optimization (CGO), which minimizes the objective function integral time multiplied absolute error. The CGO relies on chaos theory principals, wherein the organization of fractal geometry is perceived through the chaotic game and the fractals’ self-similarity properties are considered. At first, the CGO based PIDn controller is employed, to check the suitability of CGO in dealing with AGC problems. Furthermore, several scenarios are used to confirm the effectiveness of the CGO:PIDn-PI scheme when subjected to a high load disturbance and uncertainty, which can change system parameters by ± 50%. A random load pattern is used to ascertain the proposed method’s efficacy. Finally, nonlinearities, such as generation rate constraint and time delay, which have a significant impact on AGC performance, are considered. Compared with relevant current research, the suggested approach outperforms them in terms of settling time, frequency, and tie-line power deviations.

Harris Hawks-Based Optimization Algorithm for Automatic LFC of the Interconnected Power System Using PD-PI Cascade Control

This paper presents a new optimization tool-based population parameter called Harris hawks optimizer (HHO) and its application study to fine-tune the gains of well-designed proportional-derivative proportional-integral (PD-PI) cascade control to suppress the load frequency control (LFC) issues. The HHO based PID and PD-PI controllers are broadly implemented at two models with many circumstances for each model to ensure the effectiveness and the robustness of the proposed scheme at a high load disturbance, nonlinearity, and some critical parameters associated with the interconnected power system. First, a two-area non-reheat power plant is implemented, and the gains of PID and PD-PI controllers are adjusted using the proposed algorithm. In order to introduce extra realistic challenges, the governor-dead band is also modeled to ensure the robustness of the HHO/PD-PI in handling nonlinearity properties. Furthermore, to guarantee the suitability of the proposed HHO/PD-PI, a model with a mixture of power plants is carried out with and without the HVDC link, which is raised for the practical problems of LFC. Simulation results proved that; the proposed techniques HHO/PID and HHO/PD-PI provide superior performance compared to other reported strategies such as DE/PID, TLBO/PID, IGWO/PID, multi-objective/PID, and TLBO/2DOF-PID controllers. Finally, the dynamic investigation has also been completed using the random load pattern in system model-2, which shows the superior performance of HHO/PID and HHO/PD-PI schemes.

Technical Measures to Mitigate Load Fluctuation for Large-Scale Customers to Improve Power System Energy Efficiency

Industrial equipment such as electric arc furnaces and steel mills are often associated with rapid and high load disturbances, so their power systems require additional control equipment to limit the frequency. However, proper ancillary service fees are not paid in these cases with extreme and variable load demands. The frequency regulation reserve equipment adds to power generation costs. Therefore, variable power generation loads lead to increases in the cost of energy production. We propose a load frequency control method that is applied on the customer end instead of the power supply end to reduce the operating reserve required to improve the energy efficiency of the power system. We analyzed the load fluctuation of steel mill customers using real data sampled at two-second intervals from the energy management system in Korea. We developed an automatic generation control program to simulate the power system’s frequency characteristics. We also propose compensation techniques for mitigation of the system’s frequency deviation at the customer end based on an energy storage system, pump storage hydro generator, customer generator, and plant process adjustment. To recover the frequency deviation, we calculated the compensation facility capacity and analyzed static characteristics, and we proved the feasibility via simulations.

An Efficient Control Strategy for Enhancing Frequency Stability of Multi-Area Power System Considering High Wind Energy Penetration

This paper proposes an efficient control strategy to enhance frequency stability of three-area power system considering a high penetration level of wind energy. The proposed strategy is based on a combination of a Proportional Integral Derivative (PID) controller with a Linear Quadratic Gaussian (LQG) approach. The parameters of the proposed controller (i.e., PID-LQG) are optimally designed by a novel natural physical based-algorithm called Lightning Attachment Procedure Optimization (LAPO). The main objective is to keep the frequency fluctuation at its acceptable value in the presence of high penetration of wind energy, high load disturbance and system uncertainties. The superiority of the proposed PID-LQG controller is validated by comparing its performance with optimal Coefficient Diagram Method (CDM) controller, conventional CDM controller, optimal PID controller-based LAPO, and integral controller. Moreover, the exhaustive results completely demonstrate that the proposed controller gives better performance in terms of overshoot, undershoot, and settling time as well as provides reliable frequency stability for interconnected power systems considering high wind penetration and system uncertainties.

Linear and Non-linear Multi-Input Multi-Output Model Predictive Control of Continuous Stirred Tank Reactor

In this article, multi-input multi-output (MIMO) linear model predictive controller (LMPC) based on state space model and nonlinear model predictive controller based on neural network (NNMPC) are applied on a continuous stirred tank reactor (CSTR). The idea is to have a good control system that will be able to give optimal performance, reject high load disturbance, and track set point change. In order to study the performance of the two model predictive controllers, MIMO Proportional-Integral-Derivative controller (PID) strategy is used as benchmark. The LMPC, NNMPC, and PID strategies are used for controlling the residual concentration (CA) and reactor temperature (T). NNMPC control shows a superior performance over the LMPC and PID controllers by presenting a smaller overshoot and shorter settling time.

Regulation of the organic pollution level in anaerobic digesters by using off-line COD measurements

A sampled delayed scheme is proposed to regulate the organic pollution level in anaerobic digestion processes by using off-line COD measurements. The proposed scheme is obtained by combining an error feedback control with a steady state estimator to track constant references and attenuate process load disturbances. The controller performance is tested experimentally for the treatment of tequila vinasses over a period of 68days under different set-point values and several uncertain scenarios which include badly known kinetic parameters and load disturbances. Experimental results show that the COD concentration can be effectively regulated under the influence of set-point changes and high load disturbances by using only a daily off-line COD measurement, which makes the industrial application of the proposed control scheme feasible.