Genetic algorithms based economic dispatch for cogeneration units considering multiplant multibuyer wheeling

2002 ◽  
Vol 17 (1) ◽  
pp. 134-140 ◽  
Author(s):  
Ying-Yi Hong ◽  
Chih-Yuan Li
Keyword(s):  
Genetic Algorithms ◽  
Economic Dispatch

scholarly journals A Novel Parallel SPEA2 for Solving the Environmental-Economic Dispatch Problem: Competitive vs Cooperative Approach

2020 ◽  
Author(s):  
João Pedro Augusto Costa ◽  
Omar Andres Carmona Cortes ◽  
Osvaldo Ronald Saavedra
Keyword(s):  
Genetic Algorithms ◽  
Particle Swarm Optimization ◽  
Environmental Economic ◽  
Differential Evolution ◽  
Economic Dispatch ◽  
Pareto Frontier ◽  
Parallel Model ◽  
Swarm Optimization ◽  
Cooperative Approach ◽  
Economic Dispatch Problem

This paper aims to compare two different parallel approaches (cooperative and competitive) of the SPEA2 for solving the environmental-economic dispatch problem. The idea is to solve the problem by executing the SPEA2 algorithm along with three different meta-heuristics (Genetic Algorithms, Particle Swarm Optimization, and Differential Evolution) to perform changes in the population. The different meta-heuristics work in parallel using two different approaches. The first one is the competitive approach, in which meta-heuristics compete for producing the best set of candidate solutions for solving the problem. Whereas, the cooperative approach selects the new population merging all individuals from all meta-heuristics, then selecting the solution set for the Pareto frontier. The proposal was implemented in C++ using MPI in a master-slave parallel model. Two  study cases were used: the first one with six generators and the second one with forty generators. Results showed that the cooperative approach presented the best Pareto frontier for the case of 40 generators.

Economic Dispatch Using Genetic Algorithm Based Hybrid Approach

2006 ◽  
Author(s):  
Tahir Nadeem Malik ◽  
Aftab Ahmad ◽  
Shahab Khushnood
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Economic Dispatch ◽  
Hybrid Approach ◽  
Optimization Techniques ◽  
Characteristic Functions ◽  
Steam Turbines ◽  
Large Power ◽  
Hybrid Approaches ◽  
Power Economic

Power Economic Dispatch (ED) is vital and essential daily optimization procedure in the system operation. Present day large power generating units with multi-valves steam turbines exhibit a large variation in the input-output characteristic functions, thus non-convexity appears in the characteristic curves. Various mathematical and optimization techniques have been developed, applied to solve economic dispatch (ED) problem. Most of these are calculus-based optimization algorithms that are based on successive linearization and use the first and second order differentiations of objective function and its constraint equations as the search direction. They usually require heat input, power output characteristics of generators to be of monotonically increasing nature or of piecewise linearity. These simplifying assumptions result in an inaccurate dispatch. Genetic algorithms have used to solve the economic dispatch problem independently and in conjunction with other AI tools and mathematical programming approaches. Genetic algorithms have inherent ability to reach the global minimum region of search space in a short time, but then take longer time to converge the solution. GA based hybrid approaches get around this problem and produce encouraging results. This paper presents brief survey on hybrid approaches for economic dispatch, an architecture of extensible computational framework as common environment for conventional, genetic algorithm & hybrid approaches based solution for power economic dispatch, the implementation of three algorithms in the developed framework. The framework tested on standard test systems for its performance evaluation.

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