contact us
Phone

+61 470 273 583

Fax

+61 470 273 583

Email

rosepubaust@gmail.com

Address

13 Ferndale Parade, Highton 3216, Victoria, Australia

Optimal Scheduling of PSHPPs and Wind Farms in Unit Commitment Program Using Advanced Genetic Algorithm Technique

06/15/2021

Received: 24 April 2021
Revised: 26 May 2021
Accepted: 27 June 2021

Babak Safari Chabok, Ahmad Ashouri

  Download Full Text


Abstract

Unit commitment problem has a great importance in power system operation planning. Recently, with restructuring process in power systems, and concern about economic and ecological issues, a need for efficient and green energy production with renewable resources such as wind power plants has risen. Wind energy does not impose any charge for its owners; but on the other hand, due to variable and stochastic nature of wind speed, wind farms generation changes, accordingly. Because of uncertainty in predicting wind power, even for short time, use of Pumped Storage Hydro Power Plants alongside wind resources has been proposed to achieve higher maneuver power in units operation and benefit of energy exchange in power market. In this paper, powerful advanced genetic algorithm is applied to solve common unit commitment problem at the presence of wind and pumped storage hydro power plants. Objective function of optimization problem is maximizing the sum of electrical energy generation benefit of various power plants in the day-ahead power pool market, considering all operational limits. Proposed advanced genetic algorithm and its formulation with coding procedure of unknown variable in chromosome is explained and then, the numerical studies are performed on a typical test system under power pool market conditions, which its generation system consists of 10 thermal units, 1 wind farm, and 1 PSHpower plants. Finally, the simulation results and effectiveness of proposed algorithm are evaluated.

Keywords: Unit Commitment (UC); Optimal Scheduling; Thermal units; Wind Farms; Pumped-Storage Hydro Power Plant(PSHPP); Advanced Genetic Algorithm Technique.

 

  Download Full Text


53
Related Content

Register Here
To submit your paper, please register first by clicking on the registration button. You will then be able to upload your paper within the control panel(cpanel)


Publication Information

Publisher
Rose Publication, Melbourne, Australia 

Editor-in-Chief
Dr. Liam Randall

Executive Manager
Mehrdad Fallahi Barzoki

Rosepub - Journal management system