scholarly journals A Modified Teaching—Learning-Based Optimization for Dynamic Economic Load Dispatch Considering Both Wind Power and Load Demand Uncertainties With Operational Constraints

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 101665-101680
Author(s):  
Mohana S. Alanazi
Keyword(s):  
Wind Power ◽  
Economic Load Dispatch ◽  
Load Demand ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning ◽  
Operational Constraints

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 Solving Renewables-Integrated Economic Load Dispatch Problem by Variant of Metaheuristic Bat-Inspired Algorithm

Energies ◽  
2020 ◽  
Vol 13 (23) ◽  
pp. 6225
Author(s):  
Faisal Tariq ◽  
Salem Alelyani ◽  
Ghulam Abbas ◽  
Ayman Qahmash ◽  
Mohammad Rashid Hussain
Keyword(s):  
Power Generation ◽  
Renewable Energy Sources ◽  
Bat Algorithm ◽  
Optimization Techniques ◽  
Computational Time ◽  
Economic Load Dispatch ◽  
Good Convergence ◽  
Load Demand ◽  
Metaheuristic Techniques ◽  
Operational Constraints

One of the most important concerns in the planning and operation of an electric power generation system is the effective scheduling of all power generation facilities to meet growing power demand. Economic load dispatch (ELD) is a phenomenon where an optimal combination of power generating units is selected in such a way as to minimize the total fuel cost while satisfying the load demand, subject to operational constraints. Different numerical and metaheuristic optimization techniques have gained prominent importance and are widely used to solve the nonlinear problem. Although metaheuristic techniques have a good convergence rate than numerical techniques, however, their implementation seems difficult in the presence of nonlinear and dynamic parameters. This work is devoted to solving the ELD problem with the integration of variable energy resources using a modified directional bat algorithm (dBA). Then the proposed technique is validated via different realistic test cases consisting of thermal and renewable energy sources (RESs). From simulation results, it is observed that dBA reduces the operational cost with less computational time and has better convergence characteristics than that of standard BA and other popular techniques like particle swarm optimization (PSO) and genetic algorithm (GA).

scholarly journals Demand Side Management for Commercial Area Using Teaching Learning Based Optimization

2021 ◽  
Author(s):  
Dhanshri Narayane ◽  
Amarjeet S Pandey ◽  
D B Pardeshi ◽  
Renuka Rasal
Keyword(s):  
Smart Grid ◽  
Management Strategy ◽  
Optimization Problems ◽  
Demand Side Management ◽  
Demand Side ◽  
Load Shifting ◽  
Load Demand ◽  
Commercial Area ◽  
Teaching Learning Based Optimization ◽  
Teaching Learning

In Smart Grid Demand side management (DSM) plays a crucial role which permits customers to form educated selections concerning their energy consumption. It allows the strength to companies lessen the height load call for and reshape the burden profile. Most of the present demand aspect management ways utilized in ancient energy management system is with specific techniques and algorithms. In addition, the present ways handle solely a restricted range of governable a lot of restricted varieties of loads. This paper covers a requirement aspect management strategy supported load shifting technique for demand aspect management of future sensible grids with an outsized range of devices of many sorts. The day-in advance load shifting technique is proposed and mathematically formulated as a minimization problem. Teaching Learning Based Optimization (TLBO) is an efficient optimization is proposed. Considering Smart Grid with commercial customer, Simulations has been carried out. The respective results emphasis that the considered demand side management strategy attains substantial savings, whereas suppresses the mark of load demand of the smart grid. The outcome is by improve in sustainability of the smart grid, in addition to reduced standard operational value and carbon emission levels. The proposed algorithms can be easily applied to various optimization problems.

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.

Dynamic Multi-Objective Power Dispatch Considering Load and Wind Power Variations in Wind Power Integrated System

2014 ◽  
Vol 672-674 ◽  
pp. 316-319
Author(s):  
Chen Li ◽  
Zhi Jian Hu
Keyword(s):  
Wind Power ◽  
Wind Farm ◽  
Integrated System ◽  
Multi Objective ◽  
Operational Space ◽  
Power Dispatch ◽  
Proposed Model ◽  
Teaching Learning Based Optimization ◽  
Simulation Results ◽  
Teaching Learning

A modeling for dynamic multi-objective power dispatch considering load and wind power variations in wind power integrated system is presented. To deal with the random variables, probabilistic sequence theory is introduced and the operational space is extended. To solve the problem, an improved multi-objective teaching-learning-based optimization algorithm is proposed. Finally, the proposed model and algorithm are tested on a 10-units system including wind farm and the simulation results demonstrate that the proposed model and algorithm are feasible and effective.

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