Dynamic Economic Emission Dispatch Using Multi-Objective Hybrid Evolutionary Algorithm

Dynamic economic emission dispatch (DEED) is an important optimization task for power plants. The problem is a highly constrained multi-objective optimization problem involving conflicting objectives with both equality and inequality constraints. This paper introduces two objective functions of DEED model: the lowest generation cost and the smallest carbon emissions with power balance constraints, unit output constraints and unit ramp rate limits. Then the paper presents a multi-objective hybrid evolutionary algorithm (MHEA) to solve the DEED model. The MHEA is a hybrid optimization algorithm based on orthogonal initialization, improved differential operation with migration strategy, parameter adaptive control, multi-objective selection strategy and analytic hierarchy process based fuzzy technique (AFT). Numerical results of one test system demonstrate the capabilities of the proposed approach. Compared with other classical methods, the proposed approach gets better result.

Download Full-text

NSGA-II/EDA Hybrid Evolutionary Algorithm for Solving Multi-objective Economic/Emission Dispatch Problem

Electric Power Components and Systems ◽

10.1080/15325008.2018.1488302 ◽

2018 ◽

Vol 46 (10) ◽

pp. 1160-1172

Author(s):

Kehinde Olukunmi Alawode ◽

Gabriel Adebayo Adegboyega ◽

Jubril Abimbola Muhideen

Keyword(s):

Evolutionary Algorithm ◽

Nsga Ii ◽

Hybrid Evolutionary Algorithm ◽

Multi Objective ◽

Emission Dispatch ◽

Economic Emission Dispatch

Download Full-text

Multi-objective Differential Evolution for Dynamic Economic Emission Dispatch

International Journal of Emerging Electric Power Systems ◽

10.1515/ijeeps-2013-0060 ◽

2014 ◽

Vol 15 (2) ◽

pp. 141-150 ◽

Cited By ~ 3

Author(s):

M. Basu

Keyword(s):

Differential Evolution ◽

Test System ◽

Nsga Ii ◽

Multi Objective ◽

Optimization Task ◽

Conflicting Objectives ◽

Sample Test ◽

Emission Dispatch ◽

Nondominated Sorting ◽

Economic Emission Dispatch

Abstract Dynamic economic emission dispatch is an important optimization task in fossil fuel–based power plant operation for allocating generation among the committed units with predicted load demands over a certain period of time such that fuel cost and emission level are optimized simultaneously. It is a highly constrained dynamic multi-objective optimization problem involving conflicting objectives. This paper proposes multi-objective differential evolution for dynamic economic emission dispatch problem. Numerical results for a sample test system have been presented to demonstrate the performance of the proposed algorithm. The results obtained from the proposed algorithm are compared with those obtained from nondominated sorting genetic algorithm-II (NSGA-II).

Download Full-text

Economic emission dispatch problems with stochastic wind power using summation based multi-objective evolutionary algorithm

Information Sciences ◽

10.1016/j.ins.2016.01.081 ◽

2016 ◽

Vol 351 ◽

pp. 48-66 ◽

Cited By ~ 66

Author(s):

B.Y. Qu ◽

J.J. Liang ◽

Y.S. Zhu ◽

Z.Y. Wang ◽

P.N. Suganthan

Keyword(s):

Evolutionary Algorithm ◽

Wind Power ◽

Multi Objective ◽

Emission Dispatch ◽

Economic Emission Dispatch

Download Full-text

Multi-objective economic emission dispatch considering wind power using evolutionary algorithm based on decomposition

International Journal of Electrical Power & Energy Systems ◽

10.1016/j.ijepes.2014.06.027 ◽

2014 ◽

Vol 63 ◽

pp. 434-445 ◽

Cited By ~ 61

Author(s):

Yongsheng Zhu ◽

Jie Wang ◽

Boyang Qu

Keyword(s):

Evolutionary Algorithm ◽

Wind Power ◽

Multi Objective ◽

Emission Dispatch ◽

Economic Emission Dispatch

Download Full-text

Hybrid Flower Pollination Algorithm with Sequential Quadratic Programming Technique for Solving Dynamic Combined Economic Emission Dispatch Problem

Mehran University Research Journal of Engineering and Technology ◽

10.22581/muet1982.2102.11 ◽

2021 ◽

Vol 40 (2) ◽

pp. 371-382

Author(s):

Rabia Noreen Gul ◽

Aftab Ahmad ◽

Saqib Fayyaz ◽

Muhammad Kashif Sattar ◽

Syed Saddam ul Haq

Keyword(s):

Quadratic Programming ◽

Sequential Quadratic Programming ◽

System Optimization ◽

Test System ◽

Flower Pollination Algorithm ◽

Time Interval ◽

Flower Pollination ◽

Conflicting Objectives ◽

Emission Dispatch ◽

Economic Emission Dispatch

This paper presents the solution of highly complex, non-linear, multi-objective Dynamic Combined Economic Emission Dispatch (DCEED) problem. DCEED is a power system optimization problem with conflicting objectives of fuel cost and emission. DCEED includes constraints like valve point loading effect, Transmission Losses and Ramp Rate limits. Solution of DCEED problem is given by a novel Hybridized Flower Pollination Algorithm (FPA) with Sequential Quadratic Programming (SQP). FPA is a nature inspired population based meta-heuristic optimization technique that models its search on the flower pollination process. The non-convex nature of generation because of numerous operational, physical and dynamic constraints, makes search space highly multi model and complex. This makes DCEED a challenging as well as an attractive problem for research. The effectiveness of FPA-SQP is tested and validated by applying it on IEEE Standard 5-unit and 10-unit non-convex test system in MATLAB environment for the time interval of 24 hours. The results achieved by this algorithm show significant reduction in cost and emission as compared to other available techniques in the literature.

Download Full-text