Study of Different Boundary Constraint Handling Schemes in Interior Search Algorithm

2017 ◽  
pp. 547-564 ◽  
Author(s):  
Indrajit N. Trivedi ◽  
Amir H. Gandomi ◽  
Pradeep Jangir ◽  
Narottam Jangir
Keyword(s):  
Search Algorithm ◽  
Constraint Handling ◽  
Boundary Constraint

Adaptive boundary constraint-handling scheme for constrained optimization

2018 ◽  
Vol 23 (17) ◽  
pp. 8247-8280 ◽  
Author(s):  
Efrén Juárez-Castillo ◽  
Héctor-Gabriel Acosta-Mesa ◽  
Efrén Mezura-Montes
Keyword(s):  
Constrained Optimization ◽  
Constraint Handling ◽  
Boundary Constraint

scholarly journals Application of a new constraint handling method for economic dispatch considering electric market

2020 ◽  
Vol 9 (4) ◽  
pp. 1542-1549
Author(s):  
Thanh Long Duong ◽  
Ly Huu Pham ◽  
Thuan Thanh Nguyen ◽  
Thang Trung Nguyen
Keyword(s):  
Power Systems ◽  
Search Algorithm ◽  
Cuckoo Search ◽  
Cuckoo Search Algorithm ◽  
Constraint Handling ◽  
Effective Technique ◽  
Unit System ◽  
Electric Market ◽  
Optimal Load ◽  
Handling Method

In this paper, optimal load dispatch problem under competitive electric market (OLDCEM) is solved by the combination of cuckoo search algorithm (CSA) and a new constraint handling approach, called modified cuckoo search algorithm (MCSA). In addition, we also employ the constraint handling method for salp swarm algorithm (SSA) and particle swarm optimization algorithm (PSO) to form modified SSA (MSSA) and modified PSO (MPSO). The three methods have been tested on 3-unit system and 10-unit system under the consideration of payment model for power reserve allocated, and constraints of system and generators. Result comparisons among MCSA and CSA indicate that the proposed constraint handling method is very useful for metaheuristic algorithms when solving OLDCEM problem. As compared to MSSA, MPSO as well as other previous methods, MCSA is more effective by finding higher total benefit for the two systems with faster manner and lower oscillations. Consequently, MCSA method is a very effective technique for OLDCEM problem in power systems.

Environmental Economic Power Dispatch Using Bat Algorithm with Generalized Fly and Evolutionary Boundary Constraint Handling Scheme

2020 ◽  
Vol 11 (2) ◽  
pp. 171-191
Author(s):  
Latifa Dekhici ◽  
Khaled Guerraiche ◽  
Khaled Belkadi
Keyword(s):  
Environmental Economic ◽  
Thermal Power ◽  
Bat Algorithm ◽  
Pollutant Emissions ◽  
Constraint Handling ◽  
Pollutant Emission ◽  
Economic Power ◽  
Power Dispatch ◽  
Boundary Constraint ◽  
Economic Power Dispatch

This article intends to resolve the evolving environmental economic power dispatching problem (EED) using an enhanced version of the bat algorithm (BA) which is the Bat Algorithm with Generalized Fly (BAG). A good solution based on the Evolutionary Boundary Constraint Handling Scheme rather than the well-known absorbing technique and a good choice of the bi-objective function are provided to maintain the advantages of such algorithms on this problem. In the first stage, an individual economic power dispatch problem is considered by minimizing the fuel cost and taking into account the maximum pollutant emission. In the second stage and after weighting soft constraints satisfaction maximization and hard constraints abuse penalties, the proposed approach of the bi-objective environmental and economic load dispatch was built on a pareto function. The approach was tested on a thermal power plant with 10 generators and an IEEE30 power system of 6 generators. The results on the two datasets compared to those of other methods show that the proposed technique yields better cost and pollutant emissions.

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