scholarly journals A Decentralized Informatics, Optimization, and Control Framework for Evolving Demand Response Services

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4191
Author(s):  
Sean Williams ◽  
Michael Short ◽  
Tracey Crosbie ◽  
Maryam Shadman-Pajouh
Keyword(s):  
Active Control ◽  
Demand Response ◽  
Control Strategy ◽  
Demand Forecasting ◽  
Time Operation ◽  
Control Framework ◽  
Control Scheme ◽  
Optimization And Control ◽  
And Control ◽  
Active Control Strategy

This paper presents a decentralized informatics, optimization, and control framework to enable demand response (DR) in small or rural decentralized community power systems, including geographical islands. The framework consists of a simplified lumped model for electrical demand forecasting, a scheduling subsystem that optimizes the utility of energy storage assets, and an active/pro-active control subsystem. The active control strategy provides secondary DR services, through optimizing a multi-objective cost function formulated using a weight-based routing algorithm. In this context, the total weight of each edge between any two consecutive nodes is calculated as a function of thermal comfort, cost (tariff), and the rate at which electricity is consumed over a short future time horizon. The pro-active control strategy provides primary DR services. Furthermore, tertiary DR services can be processed to initiate a sequence of operations that enables the continuity of applied electrical services for the duration of the demand side event. Computer simulations and a case study using hardware-in-the-loop testing is used to evaluate the optimization and control module. The main conclusion drawn from this research shows the real-time operation of the proposed optimization and control scheme, operating on a prototype platform, underpinned by the effectiveness of the new methods and approach for tackling the optimization problem. This research recommends deployment of the optimization and control scheme, at scale, for decentralized community energy management. The paper concludes with a short discussion of business aspects and outlines areas for future work.

Distributed Optimization and Control of Microgrid Considering Environmental Protection and Stability

2013 ◽  
Vol 732-733 ◽  
pp. 1297-1302
Author(s):  
Yu Chen Hao ◽  
Xiao Bo Dou ◽  
Zai Jun Wu ◽  
Min Qiang Hu ◽  
Tao Li ◽  
...  
Keyword(s):  
Environmental Protection ◽  
Real Time ◽  
Control Strategy ◽  
Distributed Optimization ◽  
Stability Control ◽  
Optimal Scheduling ◽  
Time Operation ◽  
Real Time Operation ◽  
Optimization And Control ◽  
And Control

In order to reduce pollutant emissions to improve environmental protection, and maintain microgrid stability during real-time operation, a distributed energy optimization scheduling and stability control strategy was proposed. According to the distributed nature of the microgrid, as well as operational objectives of different microsources, an optimal scheduling model for microgrid environmental protection was designed. Based on the proposed model, the tasks of each unit in optimal scheduling and stability control were described. Genetic algorithm (GA) and user datagram protocol (UDP) were used to implement distributed optimization and control of the microgrid. The simulation indicates that, compared with the traditional centralized optimization and control, the proposed distributed optimization and control strategy can clearly show the characteristics of each unit, and have a faster computation speed. Meanwhile, it can timely response once the voltage fluctuates due to power imbalance, so as to keep microgrid stability in real-time operation.

NEURAL MODELING AND CONTROL OF DYNAMIC SYSTEMS WITH HYSTERESIS

2007 ◽  
Vol 31 (1) ◽  
pp. 127-141
Author(s):  
Yonghong Tan ◽  
Xinlong Zhao
Keyword(s):  
Dynamic Systems ◽  
Control Strategy ◽  
Neural Modeling ◽  
Modeling And Control ◽  
Control Scheme ◽  
The Neural Networks ◽  
Adaptive Control Strategy ◽  
Set Up ◽  
Modeling Strategy ◽  
And Control

A hysteretic operator is proposed to set up an expanded input space so as to transform the multi-valued mapping of hysteresis to a one-to-one mapping so that the neural networks can be applied to model of the behavior of hysteresis. Based on the proposed neural modeling strategy for hysteresis, a pseudo control scheme is developed to handle the control of nonlinear dynamic systems with hysteresis. A neural estimator is constructed to predict the system residual so that it avoids constructing the inverse model of hysteresis. Thus, the control strategy can be used for the case where the output of hysteresis is unmeasurable directly. Then, the corresponding adaptive control strategy is presented. The application of the novel modeling approach to hysteresis in a piezoelectric actuator is illustrated. Then a numerical example of using the proposed control strategy for a nonlinear system with hysteresis is presented.

scholarly journals ACTIVE CONTROL STRATEGY FOR DENSITY-WAVE IN GAS-LIFTED WELLS

2006 ◽  
Vol 39 (2) ◽  
pp. 1075-1080 ◽  
Author(s):  
Laure Sinègre ◽  
Nicolas Petit ◽  
Thierry Saint-Pierre ◽  
Pierre Lemétayer
Keyword(s):  
Active Control ◽  
Control Strategy ◽  
Density Wave ◽  
Active Control Strategy

scholarly journals Optimization and Control Strategy Technology for User Comprehensive Energy Consumption

2021 ◽  
Vol 1871 (1) ◽  
pp. 012024
Author(s):  
Congcong Li ◽  
Qing Wang ◽  
Hongxia Zhu ◽  
Xinping Wang ◽  
Chao Yu
Keyword(s):  
Energy Consumption ◽  
Control Strategy ◽  
Optimization And Control ◽  
And Control

scholarly journals Semi-Active Magnetic Levitation System for Education

2021 ◽  
Vol 11 (12) ◽  
pp. 5330
Author(s):  
Gisela Pujol-Vázquez ◽  
Alessandro N. Vargas ◽  
Saleh Mobayen ◽  
Leonardo Acho
Keyword(s):  
Pid Control ◽  
Magnetic Levitation ◽  
Low Cost ◽  
Control Scheme ◽  
Hands On ◽  
Levitation System ◽  
Magnetic Levitation System ◽  
And Control ◽  
Active Control Strategy ◽  
Cost Components

This paper describes how to construct a low-cost magnetic levitation system (MagLev). The MagLev has been intensively used in engineering education, allowing instructors and students to learn through hands-on experiences of essential concepts, such as electronics, electromagnetism, and control systems. Built from scratch, the MagLev depends only on simple, low-cost components readily available on the market. In addition to showing how to construct the MagLev, this paper presents a semi-active control strategy that seems novel when applied to the MagLev. Experiments performed in the laboratory provide comparisons of the proposed control scheme with the classical PID control. The corresponding real-time experiments illustrate both the effectiveness of the approach and the potential of the MagLev for education.

scholarly journals Coordinated Frequency Control Strategy with the Virtual Battery Model of Inverter Air Conditionings

2019 ◽  
Vol 9 (15) ◽  
pp. 3052
Author(s):  
Jiafu Yin ◽  
Dongmei Zhao
Keyword(s):  
Control Strategy ◽  
Frequency Control ◽  
Hierarchical Control ◽  
Frequency Regulation ◽  
Consensus Protocol ◽  
Consensus Control ◽  
Response Characteristics ◽  
Battery Model ◽  
Control Framework ◽  
Control Scheme

Due to the potential of thermal storage being similar to that of the conventional battery, air conditioning (AC) has gained great popularity for its potential to provide ancillary services and emergency reserves. In order to integrate numerous inverter ACs into secondary frequency control, a hierarchical distributed control framework which incorporates a virtual battery model of inverter AC is developed. A comprehensive derivation of a second-order virtual battery model has been strictly posed to formulate the frequency response characteristics of inverter AC. In the hierarchical control scheme, a modified control performance index is utilized to evaluate the available capacity of traditional regulation generators. A coordinated frequency control strategy is derived to exploit the complementary and advantageous characteristics of regulation generators and aggregated AC. A distributed consensus control strategy is developed to guarantee the fair participation of heterogeneous AC in frequency regulation. The finite-time consensus protocol is introduced to ensure the fast convergence of power tracking and the state-of-charge (SOC) consistency of numerous ACs. The effectiveness of the proposed control strategy is validated by a variety of illustrative examples.

Investigating the dynamic characteristics of the hydrostatic bearing spindle system with active piezoelectric restrictors

2021 ◽  
pp. 1-20
Author(s):  
Yixin Zhang ◽  
Wei Pan ◽  
Shuo Zhan ◽  
Ran Huang ◽  
Shujiang Chen ◽  
...  
Keyword(s):  
Active Control ◽  
Dynamic Characteristics ◽  
Control Method ◽  
Spindle System ◽  
Optimization And Control ◽  
And Control ◽  
Pipeline Model ◽  
Structural Optimization And Control ◽  
Industrial Demand ◽  
Active Control Method

Abstract Studies show that active control technology can improve system performance and meet the increasing industrial demand in diverse applications. In the present study, the dynamic characteristics of the bearing-spindle system based on active piezoelectric (PZT) restrictors, including the amplitude-frequency and phase-frequency characteristics are analyzed theoretically and experimentally. In the analysis, the influence of the pipeline model on the system characteristics is studied. Then the feasibility and effectiveness of the active control method are verified through experiments. It is demonstrated that the theoretical and experimental results are consistent. The present study is expected to provide a guideline for further investigations on the structural optimization and control law design for active hydrostatic oil-film bearing spindle systems.

scholarly journals Active Control and Validation of the Electric Vehicle Powertrain System Using the Vehicle Cluster Environment

Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3642 ◽  
Author(s):  
Ming Ye ◽  
Yitao Long ◽  
Yi Sui ◽  
Yonggang Liu ◽  
Qiao Li
Keyword(s):  
Active Control ◽  
Control Strategy ◽  
Passive Control ◽  
Prediction Algorithm ◽  
Control Effect ◽  
Demand Forecast ◽  
Powertrain System ◽  
Cluster Environment ◽  
Active Control Strategy ◽  
Vehicle Powertrain

With the development of intelligent vehicle technologies, vehicles can obtain more and more information from various sensors. Many researchers have focused on the vertical and horizontal relationships between vehicles in a vehicle cluster environment and control of the vehicle power system. When the vehicle is driving in the cluster environment, the powertrain system should quickly respond to the driver’s dynamic demand, so as to achieve the purpose of quickly passing through the cluster environment. The vehicle powertrain system should be regarded as a separate individual to research its active control strategy in a vehicle cluster environment to improve the control effect. In this study, the driving characteristics of vehicles in a cluster environment have been analyzed, and a vehicle power-demanded prediction algorithm based on a vehicle-following model has been proposed in a cluster environment. Based on the vehicle power demand forecast and driver operation, an active control strategy of the vehicle powertrain system has been designed considering the passive control strategy of the powertrain system. The results show that the vehicle powertrain system can ensure a sufficient backup power with the active control proposed in the paper, and the motor efficiency is improved by 0.61% compared with that of the passive control strategy. Moreover, the overall efficiency of the powertrain system is increased by 0.6% and the effectiveness of the active control is validated using the vehicle cluster environment.

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