Optimal dynamic economic dispatch including renewable energy source using artificial bee colony algorithm

2012 ◽  
Author(s):  
Fahad S. Abu-Mouti ◽  
Mohamed E. El-Hawary
Keyword(s):  
Energy Source ◽  
Renewable Energy Source ◽  
Renewable Energy ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Economic Dispatch ◽  
Bee Colony ◽  
Optimal Dynamic ◽  
Dynamic Economic Dispatch

The Economic Dispatch of Wind Integrated Power System based on an Improved Differential Evolution Algorithm

2020 ◽  
Vol 13 (3) ◽  
pp. 384-395
Author(s):  
Haiqing Liu ◽  
Jinmeng Qu ◽  
Yuancheng Li
Keyword(s):  
Differential Evolution ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Economic Dispatch ◽  
Differential Evolution Algorithm ◽  
Bee Colony ◽  
Evolution Algorithm ◽  
Improved Differential Evolution Algorithm ◽  
Dynamic Economic Dispatch ◽  
Integrated Power System

Background: As more and more renewable energy such as wind energy is connected to the power grid, the static economic dispatch in the past cannot meet its needs, so the dynamic economic dispatch of the power grid is imperative. Methods: Hence, in this paper, we proposed an Improved Differential Evolution algorithm (IDE) based on Differential Evolution algorithm (DE) and Artificial Bee Colony algorithm (ABC). Firstly, establish the dynamic economic dispatch model of wind integrated power system, in which we consider the power balance constraints as well as the generation limits of thermal units and wind farm. The minimum power generation costs are taken as the objectives of the model and the wind speed is considered to obey the Weibull distribution. After sampling from the probability distribution, the wind speed sample is converted into wind power. Secondly, we proposed the IDE algorithm which adds the local search and global search thoughts of ABC algorithm. The algorithm provides more local search opportunities for individuals with better evolution performance according to the thought of artificial bee colony algorithm to reduce the population size and improve the search performance. Results: Finally, simulations are performed by the IEEE-30 bus example containing 6 generations. By comparing the IDE with the other optimization model like ABC, DE, Particle Swarm Optimization (PSO), the experimental results show that obtained optimal objective function value and power loss are smaller than the other algorithms while the time-consuming difference is minor. The validity of the proposed method and model is also demonstrated. Conclusion: The validity of the proposed method and the proposed dispatch model is also demonstrated. The paper also provides a reference for economic dispatch integrated with wind power at the same time.

Artificial Bee Colony Algorithm to Solve Dynamic Economic Dispatch Considering Wind Power Penetration

2013 ◽  
Vol 416-417 ◽  
pp. 2092-2096
Author(s):  
Xi He ◽  
Gao Xia Wang
Keyword(s):  
Wind Power ◽  
Artificial Bee Colony Algorithm ◽  
Artificial Bee Colony ◽  
Economic Dispatch ◽  
Integrated System ◽  
Swarm Optimization ◽  
Abc Algorithm ◽  
Reasonable Time ◽  
Bee Colony ◽  
Dynamic Economic Dispatch

This paper use artificial bee colony algorithm (ABC) to solve dynamic economic dispatch (DED) problem in wind power integrated system for generating units with value-point effect and system-related constrains. The feasibility of the proposed method is validated with ten-unit-test systems for a period of 6 and 24 hours respectively. The effectiveness and feasibility of the artificial bee colony algorithm are demonstrated by comparing its performance with improved particle swarm optimization. Numerical results show that the ABC algorithm can provide accurate dispatch solutions within reasonable time for certain type of fuel cost functions.

A Modified ABC Algorithm for Solving Non-Convex Dynamic Economic Dispatch Problems

2016 ◽  
Vol 6 (6) ◽  
pp. 2621
Author(s):  
Hardiansyah Hardiansyah
Keyword(s):  
Artificial Bee Colony ◽  
Economic Dispatch ◽  
Optimization Method ◽  
Population Based ◽  
Test System ◽  
Time Interval ◽  
Ramp Rate ◽  
Bee Colony ◽  
Mutation Strategy ◽  
Dynamic Economic Dispatch

<p>In this paper, a modified artificial bee colony (MABC) algorithm is presented to solve non-convex dynamic economic dispatch (DED) problems considering valve-point effects, the ramp rate limits and transmission losses. Artificial bee colony algorithm is a recent population-based optimization method which has been successfully used in many complex problems. A new mutation strategy inspired from the differential evolution (DE) is introduced in order to improve the exploitation process. The feasibility of the proposed method is validated on 5 and 10 units test system for a 24 h time interval. The results are compared with the results reported in the literature. It is shown that the optimum results can be obtained more economically and quickly using the proposed method in comparison with the earlier methods.</p>

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