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Book ChapterDOI

Application of WDO for Decision-Making in Combined Economic and Emission Dispatch Problem

01 Jan 2020-pp 907-923
TL;DR: Wind Driven Optimization (WDO), a heuristic global optimization technique to solve the CEED problem with good results was applied to three different test systems.
Abstract: A number of optimization techniques have been used by researchers to solve the combined economic and emission dispatch problem. In this paper, we have applied Wind Driven Optimization (WDO), a heuristic global optimization technique to solve the CEED problem. The technique was applied to three different test systems and the results obtained were compared and analyzed with the results obtained from other techniques. MATLAB R2017a was used for the coding and execution of the algorithm.
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References
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Journal ArticleDOI
TL;DR: The results based on Kapur's entropy reveal that CS, ELR-CS and WDO method can be accurately and efficiently used in multilevel thresholding problem.
Abstract: The objective of image segmentation is to extract meaningful objects. A meaningful segmentation selects the proper threshold values to optimize a criterion using entropy. The conventional multilevel thresholding methods are efficient for bi-level thresholding. However, they are computationally expensive when extended to multilevel thresholding since they exhaustively search the optimal thresholds to optimize the objective functions. To overcome this problem, two successful swarm-intelligence-based global optimization algorithms, cuckoo search (CS) algorithm and wind driven optimization (WDO) for multilevel thresholding using Kapur's entropy has been employed. For this purpose, best solution as fitness function is achieved through CS and WDO algorithm using Kapur's entropy for optimal multilevel thresholding. A new approach of CS and WDO algorithm is used for selection of optimal threshold value. This algorithm is used to obtain the best solution or best fitness value from the initial random threshold values, and to evaluate the quality of a solution, correlation function is used. Experimental results have been examined on standard set of satellite images using various numbers of thresholds. The results based on Kapur's entropy reveal that CS, ELR-CS and WDO method can be accurately and efficiently used in multilevel thresholding problem.

392 citations

Journal ArticleDOI
TL;DR: In this paper, a modified price penalty factor is proposed to solve the combined economic emission dispatch (CEED) problem by considering both the economy and emission objectives, which is converted into a single objective function using a Price Penalty Factor approach.
Abstract: Economic load dispatch (ELD) and economic emission dispatch (EED) have been applied to obtain optimal fuel cost and optimal emission of generating units, respectively. Combined economic emission dispatch (CEED) problem is obtained by considering both the economy and emission objectives. This biobjective CEED problem is converted into a single objective function using a price penalty factor approach. A novel modified price penalty factor is proposed to solve the CEED problem. In this paper, evolutionary computation (EC) methods such as genetic algorithm (GA), micro GA (MGA), and evolutionary programming (EP) are applied to obtain ELD solutions for three-, six-, and 13-unit systems. Investigations showed that EP was better among EC methods in solving the ELD problem. EP-based CEED problem has been tested on IEEE 14-, 30-, and 118-bus systems with and without line flow constraints. A nonlinear scaling factor is also included in EP algorithm to improve the convergence performance for the 13 units and IEEE test systems. The solutions obtained are quite encouraging and useful in the economic emission environment.

375 citations

Journal ArticleDOI
Mousumi Basu1
01 Mar 2011
TL;DR: Results obtained from the proposed approach have been compared to those obtained from pareto differential evolution, nondominated sorting genetic algorithm-II and strength pare to evolutionary algorithm 2.
Abstract: Economic environmental dispatch (EED) is an important optimization task in fossil fuel fired power plant operation for allocating generation among the committed units such that fuel cost and emission level are optimized simultaneously while satisfying all operational constraints. It is a highly constrained multiobjective optimization problem involving conflicting objectives with both equality and inequality constraints. In this paper, multi-objective differential evolution has been proposed to solve EED problem. Numerical results of three test systems demonstrate the capabilities of the proposed approach. Results obtained from the proposed approach have been compared to those obtained from pareto differential evolution, nondominated sorting genetic algorithm-II and strength pareto evolutionary algorithm 2.

369 citations

Journal ArticleDOI
TL;DR: Improved PSO approaches for solving EDPs that takes into account nonlinear generator features such as ramp-rate limits and prohibited operating zones in the power system operation are proposed.

271 citations

Journal ArticleDOI
TL;DR: Wind Driven Optimization can, in some cases, out-perform other well-known techniques such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) or Differential Evolution (DE) and that WDO is well-suited for problems with both discrete and continuous-valued parameters.
Abstract: A new type of nature-inspired global optimization methodology based on atmospheric motion is introduced. The proposed Wind Driven Optimization (WDO) technique is a population based iterative heuristic global optimization algorithm for multi-dimensional and multi-modal problems with the potential to implement constraints on the search domain. At its core, a population of infinitesimally small air parcels navigates over an $N$ -dimensional search space following Newton's second law of motion, which is also used to describe the motion of air parcels within the earth's atmosphere. Compared to similar particle based algorithms, WDO employs additional terms in the velocity update equation (e.g., gravitation and Coriolis forces), providing robustness and extra degrees of freedom to fine tune. Along with the theory and terminology of WDO, a numerical study for tuning the WDO parameters is presented. WDO is further applied to three electromagnetics optimization problems, including the synthesis of a linear antenna array, a double-sided artificial magnetic conductor for WiFi applications, and an E-shaped microstrip patch antenna. These examples suggest that WDO can, in some cases, out-perform other well-known techniques such as Particle Swarm Optimization (PSO), Genetic Algorithm (GA) or Differential Evolution (DE) and that WDO is well-suited for problems with both discrete and continuous-valued parameters.

254 citations