An Educational Package for Environmentally Friendly, Economic Operation of Power Systems

This paper presents a Windows™-based educational package developed by the authors to provide power systems students with basic training on the environmentally friendly, economic operation of power systems. The suitability of the package has been demonstrated here with the help of a six-generator thermal power system.

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Application of Moth Flame Optimization Algorithm for AGC of Multi-Area Interconnected Power Systems

International Journal of Energy Optimization and Engineering ◽

10.4018/ijeoe.2018010102 ◽

2018 ◽

Vol 7 (1) ◽

pp. 22-49 ◽

Cited By ~ 5

Author(s):

Ajit Kumar Barisal ◽

Deepak Kumar Lal

Keyword(s):

Power Systems ◽

Power System ◽

Pid Controller ◽

Thermal Power ◽

Operating Conditions ◽

System Model ◽

Source Power ◽

Interconnected Power Systems ◽

Thermal Power System ◽

Moth Flame Optimization Algorithm

A novel attempt has been made to use Moth Flame Optimization (MFO) algorithm to optimize PI/PID controller parameters for AGC of power system. Four different power systems are considered in the present article. Initially, a two area thermal power system is considered for simulation. The superiority of the proposed MFO optimized PI/PID controller has been demonstrated by comparing the results with recently published approaches such as conventional, GA, BFOA, DE, PSO, Hybrid BFOA-PSO, FA and GWO algorithm optimized PI/PID controller for the same power system model. Then, a sensitivity analysis is carried out to study the robustness of the system to wide changes in the operating conditions and system parameters from their nominal values. The proposed approach is extended to different realistic multi-area multi-source power systems with diverse sources of power generations for simulation study. The acceptability and efficacy of the proposed technique is demonstrated by comparing with other recently published techniques.

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Fuzzy Based Intelligent Approach to AGC of Multi-Area Multi-Unit Power System with SMES under Random Load Disturbances

Applied Mechanics and Materials ◽

10.4028/www.scientific.net/amm.492.431 ◽

2014 ◽

Vol 492 ◽

pp. 431-438

Author(s):

Sathans Suhag ◽

A. Swarup

Keyword(s):

Power Systems ◽

Power System ◽

Intelligent Control ◽

Control Strategy ◽

Magnetic Energy ◽

Thermal Power ◽

Automatic Generation ◽

Pi Controller ◽

Random Load ◽

Thermal Power System

In reality, load variations in power systems are random in nature. Therefore, the automatic generation control (AGC) performance of the power system needs to be investigated under random load disturbances so as to have a realistic evaluation of the control strategy. This paper reports results for one such investigation. The intelligent control strategy, based on fuzzy gain scheduling of a proportional-integral (PI) controller, is developed and implemented for a multi-area multi-unit thermal power system with reheat nonlinearity. The paper also investigates the effect of superconducting magnetic energy storage (SMES) system on the AGC performance. For the sake of comparison, the behavior of the system for the same load disturbance is also investigated with a conventional PI controller. Simulation studies indicate that the proposed intelligent control strategy is very effective under random load disturbances and provides significant improvement over the conventional PI controller.

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