scholarly journals Dispatching a 19-Unit Indian Utility System Using a Refined Differential Evolution Algorithm

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
J. Jasper ◽  
T. Aruldoss Albert Victoire
Keyword(s):  
Differential Evolution ◽  
Operating Cost ◽  
Differential Evolution Algorithm ◽  
New Mutation ◽  
Time Period ◽  
Utility System ◽  
Evolution Algorithm ◽  
Neighborhood Topology ◽  
The Cost ◽  
Dynamic Economic Dispatch

This paper presents a differential evolution with neighborhood based mutation (DE-NM) technique to solve Dynamic Economic Dispatch (DED) problem with valve point effects and multiple fuel options. A new mutation scheme based on neighborhood topology is presented with an aim to achieve the cost reduction together satisfying the dynamic behavior of the generating units over the considered time period. The neighborhood based mutation (NM) balances the exploration and exploitation of the search effort of differential evolution (DE) technique. The NM method enhances the convergence speed and the performance of the DE technique. The performance of the DE-NM is tested on a 10-unit and a real public Indian utility system with 19 generating units. Both the test systems are illustrated under different load patterns. The dispatch results obtained using the proposed method for the Indian system have considerably reduced the operating cost and optimized its operation.

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.

Enhanced Directed Differential Evolution Algorithm for Solving Constrained Engineering Optimization Problems

2019 ◽  
Vol 10 (1) ◽  
pp. 1-28 ◽  
Author(s):  
Ali Wagdy Mohamed ◽  
Ali Khater Mohamed ◽  
Ehab Z. Elfeky ◽  
Mohamed Saleh
Keyword(s):  
Differential Evolution ◽  
Optimization Problems ◽  
Differential Evolution Algorithm ◽  
Test Problems ◽  
New Mutation ◽  
De Algorithm ◽  
Engineering Problems ◽  
Evolution Algorithm ◽  
Mutation Scheme ◽  
Exploration Exploitation

The performance of Differential Evolution is significantly affected by the mutation scheme, which attracts many researchers to develop and enhance the mutation scheme in DE. In this article, the authors introduce an enhanced DE algorithm (EDDE) that utilizes the information given by good individuals and bad individuals in the population. The new mutation scheme maintains effectively the exploration/exploitation balance. Numerical experiments are conducted on 24 test problems presented in CEC'2006, and five constrained engineering problems from the literature for verifying and analyzing the performance of EDDE. The presented algorithm showed competitiveness in some cases and superiority in other cases in terms of robustness, efficiency and quality the of the results.

scholarly journals Dynamic Economic Dispatch in Thermal-Wind-Small Hydropower Generation System

2018 ◽  
Vol 246 ◽  
pp. 01085
Author(s):  
Guangbiao Liu ◽  
Jianzhong Zhou ◽  
Xiaogang Xiao ◽  
Li Mo ◽  
Yang Yuqi ◽  
...  
Keyword(s):  
Differential Evolution ◽  
Wind Power ◽  
Economic Dispatch ◽  
Differential Evolution Algorithm ◽  
Small Hydropower ◽  
Hydro Power ◽  
Thermal Wind ◽  
Hydropower System ◽  
Evolution Algorithm ◽  
Dynamic Economic Dispatch

With the large-scale wind power integration, the uncertainty of wind power poses a great threat to the safe and stable operation of the system. This paper proposes dynamic economic dispatch problem formulation in thermal power system incorporating stochastic wind and small-hydro (run-in-river) power, called thermal-wind-small hydropower system (TWSHS). Weibull and Gumbel probability density functions are used to calculate available wind and small-hydro power respectively. An improved differential evolution algorithm based on gradient descent information (DE-GD) is proposed to solve the dynamic economic dispatch (DED) problem considering uncertainty of wind power and small-hydro power, as well as complicated constraints in TWSHS. Based on the traditional differential evolution algorithm, the gradient information of the objective function is introduced after the mutation process to enrich the diversity of the population, thus increasing the possibility of convergence to the global optimization. Generation scheduling is simulated on a TWSHS with the proposed approach. Simulation results verify feasibility and effectiveness of the proposed method while considering various complex constraints in the thermal-windsmall hydropower system.

Diversifying Search Moves in a Shuffled Differential Evolution Algorithm

2016 ◽  
Vol 15 (01) ◽  
pp. 1650002
Author(s):  
Morteza Alinia Ahandani ◽  
Seyyed Sadegh Bibak Sareshkeh
Keyword(s):  
Differential Evolution ◽  
Spread Spectrum ◽  
Optimization Problem ◽  
Differential Evolution Algorithm ◽  
Code Design ◽  
Mutation Operator ◽  
Secondary Mutation ◽  
New Mutation ◽  
Phase Code ◽  
Evolution Algorithm

The shuffled differential evolution (SDE) is a recently proposed version of differential evolution (DE). However the SDE employs several efforts to compensate limited amount of search moves in the original DE, but these efforts are performed by the same operator. To vary search moves of the SDE, this research proposes employing a secondary mutation operator beside of first mutation operator. This new mutation operator can generate some different offspring than those generated by the first one. Experiments demonstrate a better performance of the proposed algorithm than the SDE. In a later part of the comparative experiments, performance comparisons of the proposed algorithm with some modern DE and other evolutionary algorithms reported in the literature confirm a better or at least a competitive performance of our proposed algorithm. Also a real-world optimization problem, namely, Spread Spectrum Radar Polly phase Code Design, is solved to show the wide applicability of the DSDE.

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