scholarly journals Short-term optimal hydro-thermal scheduling using clustered adaptive teaching learning based optimization

2019 ◽  
Vol 9 (5) ◽  
pp. 3359
Author(s):  
Surender Reddy Salkuti
Keyword(s):  
Power Generation ◽  
Discharge Rate ◽  
Water Discharge ◽  
Thermal Power ◽  
Test System ◽  
Electric System ◽  
Reservoir Volume ◽  
Adaptive Teaching ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning

<span>In this paper, Clustered Adaptive Teaching Learning Based Optimization (CATLBO) algorithm is proposed for determining the optimal hourly schedule of power generation in a hydro-thermal power system. In the proposed approach, a multi-reservoir cascaded hydro-electric system with a non-linear relationship between water discharge rate, net head and power generation is considered. Constraints such as power balance, water balance, reservoir volume limits and operation limits of hydro and thermal plants are considered. The feasibility and effectiveness of the proposed algorithm is demonstrated through a test system, and the results are compared with existing conventional and evolutionary algorithms. Simulation results reveals that the proposed CATLBO algorithm appears to be the best in terms of convergence speed and optimal cost compared with other techniques.</span>

A Comparative Study of Improved Teaching Learning Based Optimization Technique on Economic Load Dispatch Problem with Generator Constraints

2016 ◽  
Vol 5 (4) ◽  
pp. 1-25 ◽  
Author(s):  
Sumit Banerjee ◽  
Chandan Chanda ◽  
Deblina Maity
Keyword(s):  
Optimization Technique ◽  
Inequality Constraints ◽  
Test System ◽  
Economic Load Dispatch ◽  
Thermal Plant ◽  
Equality And Inequality Constraints ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning ◽  
Operational Constraints ◽  
Rate Limit

This article presents a novel improved teaching learning based optimization (I-TLBO) technique to solve economic load dispatch (ELD) problem of the thermal plant without considering transmission losses. The proposed methodology can take care of ELD problems considering practical nonlinearities such as ramp rate limit, prohibited operating zone and valve point loading. The objective of economic load dispatch is to determine the optimal power generation of the units to meet the load demand, such that the overall cost of generation is minimized, while satisfying different operational constraints. I-TLBO is a recently developed evolutionary algorithm based on two basic concepts of education namely teaching phase and learning phase. The effectiveness of the proposed algorithm has been verified on test system with equality and inequality constraints. Compared with the other existing techniques demonstrates the superiority of the proposed algorithm.

scholarly journals An improved teaching learning–based optimization algorithm for congestion management with the integration of solar photovoltaic system

2020 ◽  
Vol 53 (7-8) ◽  
pp. 1231-1237
Author(s):  
S T Suganthi ◽  
D Devaraj
Keyword(s):  
Power Systems ◽  
Congestion Management ◽  
Test System ◽  
Photovoltaic System ◽  
Management Technique ◽  
Optimization Approach ◽  
Solar Photovoltaic ◽  
Teaching Learning Based Optimization ◽  
Solar Photovoltaic System ◽  
Teaching Learning

In restructured power systems, transmission congestion is an imperative issue. Establishment of solar photovoltaic system at appropriate areas is likely to relieve congestion in transmission lines in the restructured power systems. Congestion management technique by utilizing solar photovoltaic sources, using an improved teaching learning–based optimization, is investigated in this article. Bus sensitivity factors which have the direct influence on the congested lines are utilized to locate the solar photovoltaic sources at appropriate areas. Congestion management is figured as an optimization problem with a goal of limiting the congestion management price utilizing the improved teaching learning–based optimization approach, which espouses the self-driven learning principle. IEEE-30 bus test system is simulated and tested in MATLAB environment so as to demonstrate the viability of the suggested methodology than different methodologies.

Adaptive Teaching Learning Based Optimization Applied to Nonlinear Economic Load Dispatch Problem

2014 ◽  
Vol 5 (4) ◽  
pp. 1-16 ◽  
Author(s):  
Sk Md Ali Bulbul ◽  
Provas Kumar Roy
Keyword(s):  
Classroom Environment ◽  
Teaching And Learning ◽  
Dynamic Parameter ◽  
Economic Load Dispatch ◽  
System A ◽  
Suitable Parameter ◽  
Adaptive Teaching ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning ◽  
The Cost

Economic load dispatch (ELD) is a process of calculating real power dispatch by satisfying a set of constraints such a way as fuel cost can be minimized. Inclusion of the effect of valve-points and prohibited operation zones (POZs) in the cost functions make ELD problem a non-linear and non-convex one. For solving ELD in power system a newly proposed evolutionary technique namely adaptive teaching learning based optimization (ATLBO) is presented in this article. TLBO mimics the influence of a teacher on students in a classroom environment by social interaction. ATLBO is an improved version of TLBO which makes TLBO faster and more robust. An adaptive dynamic parameter control mechanism is adopted by the proposed ATLBO algorithm to determine the suitable parameter settings for teaching and learning phases of TLBO algorithm. The proposed ATLBO algorithm is tested in three different cases like 10-unit, 40-unit, and 80-unit systems. A comparison of numerical results with other well established techniques reveals optimization superiority of the proposed scheme both in quality of solution and computational efficiency.

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