scholarly journals Distributed economic dispatch for power generation with time‐varying loads and external disturbances

2020 ◽  
Vol 15 (1) ◽  
pp. 88-95
Author(s):  
Bomin Huang ◽  
Qingfu Cui ◽  
Ziyang Meng ◽  
Fei Chen
Keyword(s):  
Power Generation ◽  
Economic Dispatch ◽  
Time Varying ◽  
External Disturbances

scholarly journals New Time-Varying Sliding Surface for Switching Type Quasi-Sliding Mode Control

Energies ◽  
2021 ◽  
Vol 14 (13) ◽  
pp. 3811
Author(s):  
Katarzyna Adamiak ◽  
Andrzej Bartoszewicz
Keyword(s):  
Sliding Mode Control ◽  
Continuous Time ◽  
Sliding Mode ◽  
Representative Point ◽  
Time Varying ◽  
Sliding Surface ◽  
External Disturbances ◽  
Mode Control ◽  
Switching Type ◽  
Time Systems

This study considers the problem of energetical efficiency in switching type sliding mode control of discrete-time systems. The aim of this work is to reduce the quasi-sliding mode band-width and, as follows, the necessary control input, through an application of a new type of time-varying sliding hyperplane in quasi-sliding mode control of sampled time systems. Although time-varying sliding hyperplanes are well known to provide insensitivity to matched external disturbances and uncertainties of the model in the whole range of motion for continuous-time systems, their application in the discrete-time case has never been studied in detail. Therefore, this paper proposes a sliding surface, which crosses the system’s representative point at the initial step and then shifts in the state space according to the pre-generated demand profile of the sliding variable. Next, a controller for a real perturbed plant is designed so that it drives the system’s representative point to its reference position on the sliding plane in each step. Therefore, the impact of external disturbances on the system’s trajectory is minimized, which leads to a reduction of the necessary control effort. Moreover, thanks to a new reaching law applied in the reference profile generator, the sliding surface shift in each step is strictly limited and a switching type of motion occurs. Finally, under the assumption of boundedness and smoothness of continuous-time disturbance, a compensation scheme is added. It is proved that this control strategy reduces the quasi-sliding mode band-width from O(T) to O(T3) order from the very beginning of the regulation process. Moreover, it is shown that the maximum state variable errors become of O(T3) order as well. These achievements directly reduce the energy consumption in the closed-loop system, which is nowadays one of the crucial factors in control engineering.

scholarly journals Dynamic Economic Dispatch On Micro Grid Electrical Systems Using Quadratic Programming

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Heri Suryoatmojo
Keyword(s):  
Power Generation ◽  
Quadratic Programming ◽  
Electric Power ◽  
Renewable Energy Sources ◽  
Economic Dispatch ◽  
Small Scale ◽  
Distributed Power Generation ◽  
Optimal Capacity ◽  
Micro Grid ◽  
Dynamic Economic Dispatch

Currently the needs of electric power increased rapidly along with the development of technology. The increase in power requirements is contrary to the availability of sources of energy depletion of oil and coal. This problem affects the national electrical resistance. To meet the needs of large electric power with wide area coverage is required small scale distributed power generation. This distributed generation (DG) of renewable energy sources sought to minimize the use of energy resources such as oil and coal and connected to the micro grid and use the battery as a power balance. Because of there are many DGs and the use of batteries, therefore it is important to determine the optimal power generation of each plant as well as the use of battery based on the optimal capacity so that requirement of electric power can be met with minimal cost each time. This optimization is known as Dynamic Economic Dispatch. In this study, the methods of Quadratic Programming is required to solve the optimization problem.

scholarly journals Disturbance Observer-Based Adaptive Neural Network Control of Marine Vessel Systems with Time-Varying Output Constraints

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-12
Author(s):  
Wei Zhao ◽  
Li Tang ◽  
Yan-Jun Liu
Keyword(s):  
Neural Network ◽  
Disturbance Observer ◽  
Continuous Functions ◽  
Network Control ◽  
Time Varying ◽  
Adaptive Neural Network ◽  
External Disturbances ◽  
Adaptive Neural Network Control ◽  
Output Constraints ◽  
Novel Strategy

This article investigates an adaptive neural network (NN) control algorithm for marine surface vessels with time-varying output constraints and unknown external disturbances. The nonlinear state-dependent transformation (NSDT) is introduced to eliminate the feasibility conditions of virtual controller. Moreover, the barrier Lyapunov function (BLF) is used to achieve time-varying output constraints. As an important approximation tool, the NN is employed to approximate uncertain and continuous functions. Subsequently, the disturbance observer is structured to observe time-varying constraints and unknown external disturbances. The novel strategy can guarantee that all signals in the closed-loop system are semiglobally uniformly ultimately bounded (SGUUB). Finally, the simulation results verify the benefit of the proposed method.

Event-triggered tracking control for nonlinear systems subject to time-varying external disturbances

Automatica ◽  
2020 ◽  
Vol 119 ◽  
pp. 109070
Author(s):  
Ting Li ◽  
Changyun Wen ◽  
Jun Yang ◽  
Shihua Li ◽  
Lei Guo
Keyword(s):  
Nonlinear Systems ◽  
Tracking Control ◽  
Time Varying ◽  
External Disturbances ◽  
Event Triggered

scholarly journals Fuzzy-Based Optimal Adaptive Line-of-Sight Path Following for Underactuated Unmanned Surface Vehicle with Uncertainties and Time-Varying Disturbances

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Dongdong Mu ◽  
Guofeng Wang ◽  
Yunsheng Fan ◽  
Yiming Bai ◽  
Yongsheng Zhao
Keyword(s):  
Neural Network ◽  
Path Following ◽  
Line Of Sight ◽  
Time Varying ◽  
Parameter Learning ◽  
Learning Method ◽  
External Disturbances ◽  
Unmanned Surface Vehicle ◽  
Loop Control ◽  
Nussbaum Function

This paper investigates the path following control problem for an underactuated unmanned surface vehicle (USV) in the presence of dynamical uncertainties and time-varying external disturbances. Based on fuzzy optimization algorithm, an improved adaptive line-of-sight (ALOS) guidance law is proposed, which is suitable for straight-line and curve paths. On the basis of guidance information provided by LOS, a three-degree-of-freedom (DOF) dynamic model of an underactuated USV has been used to design a practical path following controller. The controller is designed by combining backstepping method, neural shunting model, neural network minimum parameter learning method, and Nussbaum function. Neural shunting model is used to solve the problem of “explosion of complexity,” which is an inherent illness of backstepping algorithm. Meanwhile, a simpler neural network minimum parameter learning method than multilayer neural network is employed to identify the uncertainties and time-varying external disturbances. In particular, Nussbaum function is introduced into the controller design to solve the problem of unknown control gain coefficient. And much effort is made to obtain the stability for the closed-loop control system, using the Lyapunov stability theory. Simulation experiments demonstrate the effectiveness and reliability of the improved LOS guidance algorithm and the path following controller.

NEW DEVELOPMENT OF ANALYSIS TOOL FOR OPTIMIZING GENERATION COST WITH GAS EMISSION VIA AN ELECTROMAGNETISM LIKE ALGORITHM

2016 ◽  
Vol 78 (6-3) ◽  
Author(s):  
F.Y.C. Albert ◽  
S.P. Koh ◽  
C. P. Chen ◽  
S. K. Tiong
Keyword(s):  
Power Generation ◽  
Objective Function ◽  
Environmental Concern ◽  
Economic Dispatch ◽  
Complex Problem ◽  
Analysis Tool ◽  
New Development ◽  
Generation Cost ◽  
Electric Power Generation Systems ◽  
Power Generation Systems

This paper addresses the preliminary new development results of the evolutionary algorithm technique to optimize the formulated problems incorporating the generation cost with emission gas as objective function or constraints. The power generation cost with emission gas are a complex problem which also the major concerns in electric power generation systems in the Environmental or Economic Dispatch Problems (EDP). Thus, due to environmental concern the electrical utilities required to minimize the emission level while optimizing the thermal generating units at a minimum generating cost and hence, satisfying the load demand and the emissions. In this work the electromagnetism-Like algorithm (EML) has been employed for optimizing generation cost and emission constraints economic dispatch problem. The proposed decision analysis tool software in this work will optimize the generation cost with emission gas objective function. The best generation cost with emission gas solution are obtained from different fuel technology via the developed software. 

Sign in / Sign up

Export Citation Format

Share Document