A Pseudo Spot Price Algorithm Applied to Short-Term Hydrothermal Scheduling Problem

2001 ◽  
Vol 29 (11) ◽  
pp. 977-995 ◽  
Author(s):  
Salih Fadil, Celal Yaşar
Keyword(s):  
Spot Price ◽  
Scheduling Problem ◽  
Short Term ◽  
Hydrothermal Scheduling ◽  
Price Algorithm

scholarly journals Short-Term Hydrothermal Scheduling using Imperialist Competitive Algorithm

2021 ◽  
Vol 20 (1) ◽  
pp. 15-20
Author(s):  
Mohamed ahmed Ayoub
Keyword(s):  
Imperialist Competitive Algorithm ◽  
Scheduling Problem ◽  
Short Term ◽  
Hydrothermal Scheduling ◽  
Good Convergence ◽  
Thermal Plant ◽  
Competitive Algorithm ◽  
Generation Cost

In this study, the Imperialist Competitive Algorithm (ICA) is proposed to solve a multi-chain Short-Term Hydrothermal Scheduling problem (STHTS). It aims to minimize the generation cost of the thermal plants while satisfying the thermal and hydro plants constraints. In order to evaluate the effectiveness of the ICA, it has been tested on a system having a hydro plant with four-cascaded reservoir and a thermal plant. The results are compared with that obtained by other techniques. The ICA has the good convergence and the better results.

scholarly journals Statistical Performances Evaluation of APSO and Improved APSO for Short Term Hydrothermal Scheduling Problem

2019 ◽  
Vol 9 (12) ◽  
pp. 2440 ◽  
Author(s):  
Muhammad Salman Fakhar ◽  
Syed Abdul Rahman Kashif ◽  
Noor Ul Ain ◽  
Hafiz Zaheer Hussain ◽  
Akhtar Rasool ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Particle Swarm ◽  
Pso Algorithm ◽  
Search Space ◽  
Scheduling Problem ◽  
Short Term ◽  
Swarm Optimization ◽  
Hydrothermal Scheduling ◽  
Dynamic Search ◽  
Accelerated Particle Swarm Optimization

The Accelerated Particle Swarm Optimization (APSO) algorithm is an efficient and the easiest to implement variant of the famous Particle Swarm Optimization (PSO) algorithm. PSO and its variant APSO have been implemented on the famous Short-Term Hydrothermal Scheduling (STHTS) problem in recent research, and they have shown promising results. The APSO algorithm can be further modified to enhance its optimizing capability by deploying dynamic search space squeezing. This paper presents the implementation of the improved APSO algorithm that is based on dynamic search space squeezing, on the short-term hydrothermal scheduling problem. To give a quantitative comparison, a true statistical comparison based on comparing means is also presented to draw conclusions.

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