Hybridization of bee colony optimization and sequential quadratic programming for dynamic economic dispatch

2013 ◽  
Vol 44 (1) ◽  
pp. 591-596 ◽  
Author(s):  
M. Basu
2018 ◽  
Vol 185 ◽  
pp. 00033 ◽  
Author(s):  
Chia-Sheng Tu ◽  
Hsi-Shan Huang ◽  
Ming-Tang Tsai ◽  
Fu-Sheng Cheng

Dynamic economic dispatch is to minimize the cost of power production of all the participating generators over a time horizon of 24 hours in one day. The dynamic economic dispatch with non-smooth cost functions, for which is formulated the optimal dispatch model of generations by considering the ramp up/down scheduling of power. This paper presents a Bee Colony Optimization (BCO) that applies the Taguchi Method (TM) to solve the Dynamic Economic Dispatch problem. The Taguchi method that involves the use of orthogonal arrays in estimating of the non-smooth cost function and Bee Colony Optimization is used to find the objective function under the operational of system constraints. The Taguchi method can global optimization for fast local convergence by minimizing the cost function in a few iterations. The effectiveness and efficiency of the TM-BCO is demonstrated by using a 10 unit of IEEE case with non-smooth fuel cost functions and is more effective than other previously developed algorithms. Moreover, the proposed approach presents significant computational benefits than traditional random search method especially for multi-unit systems with larger numbers of non-smooth cost functions and more complicated dynamic economic dispatch.


2012 ◽  
Vol 2012 ◽  
pp. 1-10 ◽  
Author(s):  
A. M. Elaiw ◽  
X. Xia ◽  
A. M. Shehata

This paper presents hybrid differential evolution (DE) and sequential quadratic programming (SQP) for solving the dynamic economic dispatch (DED) problem for generating units with valve-point effects. DE is used as a global optimizer and SQP is used as a fine tuning to determine the optimal solution at the final. The feasibility of the proposed method is validated with five-and ten-unit test systems. Results obtained by DE-SQP method are compared with other techniques in the literature.


Author(s):  
Haiqing Liu ◽  
Jinmeng Qu ◽  
Yuancheng Li

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.


Author(s):  
Heri Suryoatmojo

Currently the needs of electric power increased rapidly along with the development of technology. The increase in power requirements is contrary to the availability of sources of energy depletion of oil and coal. This problem affects the national electrical resistance. To meet the needs of large electric power with wide area coverage is required small scale distributed power generation. This distributed generation (DG) of renewable energy sources sought to minimize the use of energy resources such as oil and coal and connected to the micro grid and use the battery as a power balance. Because of there are many DGs and the use of batteries, therefore it is important to determine the optimal power generation of each plant as well as the use of battery based on the optimal capacity so that requirement of electric power can be met with minimal cost each time. This optimization is known as Dynamic Economic Dispatch. In this study, the methods of Quadratic Programming is required to solve the optimization problem.


2013 ◽  
Vol 416-417 ◽  
pp. 2092-2096
Author(s):  
Xi He ◽  
Gao Xia Wang

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.


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