scholarly journals Power system generation reliability assessment based on multi-agents technique

2014 ◽  
Author(s):  
Nadheer A. Shalash ◽  
◽  
Abu Zaharin Bin Ahmad
Keyword(s):  
Power System ◽  
Reliability Assessment ◽  
System Generation ◽  
Multi Agents

Research on Reliability Assessment of Power System with Wind Farms

2012 ◽  
Vol 608-609 ◽  
pp. 588-591
Author(s):  
Wen Jiang ◽  
Ye Xia Cheng ◽  
Ye Jian Cheng
Keyword(s):  
Power System ◽  
Wind Farm ◽  
Sequential Monte Carlo ◽  
Moving Average ◽  
Reliability Assessment ◽  
Arma Model ◽  
Wind Farms ◽  
Test System ◽  
Wind Speeds ◽  
State Models

Due to randomness and fluctuation of wind speed, reliability of power system will be affected severely with increasing wind energy injected into power grid. In order to evaluate the effect on reliability of power system with wind farms, the author considers feature of time-sequential and self-correlation of wind speeds and builds an auto-regressive and moving average (ARMA) model to forecast wind speeds. Combining with state models of conventional generating units, transmission lines and transformers, a time-sequential Monte Carlo simulation reliability model is proposed to do reliability assessment of composite generation and transmission system with wind farm. IEEE-RTS test system is introduced to prove the proposed model. Analysis and comparison of results show that reliability can be improved clearly after integration of wind farm.

scholarly journals A Multi-Communication-Based Demand Response Implementation Structure and Control Strategy

2019 ◽  
Vol 9 (16) ◽  
pp. 3218 ◽  
Author(s):  
Qi Wang ◽  
Hongru Wang ◽  
Lei Zhu ◽  
Xingquan Wu ◽  
Yi Tang
Keyword(s):  
Power System ◽  
Demand Response ◽  
System Architecture ◽  
Control Strategies ◽  
Communication Technologies ◽  
Terminal Design ◽  
Hardware In Loop ◽  
And Control ◽  
Scale Control ◽  
Multi Agents

Demand response (DR) is widely accepted as a feasible and potential solution to improve the operation of the power system. In this paper, an economical and practical DR system architecture based on internet and Internet of things (IoT) communication technologies is discussed to achieve wide-area DR control without using an expensive metering infrastructure. Multi agents are introduced with respective control strategies to implement multi-time-scale control in a power system. In order to support quick DR strategies, a novel smart terminal design for the proposed DR system is described with functions of local parameter detection and action. The practicality of the proposed system was validated on a developed hardware-in-loop co-simulation platform.

scholarly journals Reinforcement Learning in Adaptive Control of Power System Generation

2015 ◽  
Vol 46 ◽  
pp. 202-209 ◽  
Author(s):  
Leo Raju ◽  
R.S. Milton ◽  
Swetha Suresh ◽  
Sibi Sankar
Keyword(s):  
Adaptive Control ◽  
Reinforcement Learning ◽  
Power System ◽  
System Generation
Sign in / Sign up

Export Citation Format

Share Document