Hybrid PSO-SQP for solving combined heat and power dynamic economic emission dispatch problem with non-smooth cost function

2017 ◽  
Vol 8 (1) ◽  
pp. 85 ◽  
Author(s):  
A. M. Shehata
Keyword(s):  
Optimal Solution ◽  
Combined Heat And Power ◽  
Test System ◽  
Primary Objective ◽  
Global Optimal Solution ◽  
Power Dynamic ◽  
Hybrid Particle Swarm Optimization ◽  
Global Optimal ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

In this paper we propose a hybrid particle swarm optimization (PSO) and sequential quadratic programming (SQP) for solving the combined heat and power dynamic economic emission dispatch (CHPDEED) problem. The primary objective of CHPDEED is to determine the optimal heat and power generation schedule of the online generating units over a fixed interval by simultaneously minimizing the generation cost and emission level and satisfying the dynamic constraints and other constraints. Taking into account the valve point effects, CHPDEED is considered as a multi-objective optimization problem with non-smooth characteristics. In the hybrid method, PSO is used as a global search to find near global optimal solution and this solution is used as initial for the SQP to find the global optimal solution at the end. The proposed method is verified using a test system consisting of eleven units and considering transmission line losses and valve point effects. The numerical results show the effectiveness and the superiority of the introduced method over other published methods.

scholarly journals Combined Heat and Power Dynamic Economic Dispatch with Emission Limitations Using Hybrid DE-SQP Method

2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
A. M. Elaiw ◽  
X. Xia ◽  
A. M. Shehata
Keyword(s):  
Optimal Solution ◽  
Combined Heat And Power ◽  
Fine Tuning ◽  
Ramp Rate ◽  
Sqp Method ◽  
Power Dynamic ◽  
Global Optimizer ◽  
Dynamic Economic Dispatch ◽  
Emission Dispatch ◽  
Constrained Multiobjective Optimization

Combined heat and power dynamic economic emission dispatch (CHPDEED) problem is a complicated nonlinear constrained multiobjective optimization problem with nonconvex characteristics. CHPDEED determines the optimal heat and power schedule of committed generating units by minimizing both fuel cost and emission simultaneously under ramp rate constraints and other constraints. This paper proposes hybrid differential evolution (DE) and sequential quadratic programming (SQP) to solve the CHPDEED problem with nonsmooth and nonconvex cost function due to 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 proposed hybrid DE-SQP method has been tested and compared to demonstrate its effectiveness.

A new multi-objective reserve constrained combined heat and power dynamic economic emission dispatch

Energy ◽  
2012 ◽  
Vol 42 (1) ◽  
pp. 530-545 ◽  
Author(s):  
Taher Niknam ◽  
Rasoul Azizipanah-Abarghooee ◽  
Alireza Roosta ◽  
Babak Amiri
Keyword(s):  
Combined Heat And Power ◽  
Power Dynamic ◽  
Multi Objective ◽  
Emission Dispatch ◽  
Economic Emission Dispatch

AO-BBO: A Novel Optimization Algorithm and Its Application in Plant Drug Extraction

2019 ◽  
Vol 19 (2) ◽  
pp. 139-145 ◽  
Author(s):  
Bote Lv ◽  
Juan Chen ◽  
Boyan Liu ◽  
Cuiying Dong
Keyword(s):  
Optimization Algorithm ◽  
Learning Strategy ◽  
Optimal Solution ◽  
Population Diversity ◽  
Global Optimal Solution ◽  
Plant Medicine ◽  
Suitability Index ◽  
Sensing Model ◽  
Local Optimal Solution ◽  
Global Optimal

<P>Introduction: It is well-known that the biogeography-based optimization (BBO) algorithm lacks searching power in some circumstances. </P><P> Material & Methods: In order to address this issue, an adaptive opposition-based biogeography-based optimization algorithm (AO-BBO) is proposed. Based on the BBO algorithm and opposite learning strategy, this algorithm chooses different opposite learning probabilities for each individual according to the habitat suitability index (HSI), so as to avoid elite individuals from returning to local optimal solution. Meanwhile, the proposed method is tested in 9 benchmark functions respectively. </P><P> Result: The results show that the improved AO-BBO algorithm can improve the population diversity better and enhance the search ability of the global optimal solution. The global exploration capability, convergence rate and convergence accuracy have been significantly improved. Eventually, the algorithm is applied to the parameter optimization of soft-sensing model in plant medicine extraction rate. Conclusion: The simulation results show that the model obtained by this method has higher prediction accuracy and generalization ability.</P>

scholarly journals Best Proximity Point Results in Complex Valued Metric Spaces

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Binayak S. Choudhury ◽  
Nikhilesh Metiya ◽  
Pranati Maity
Keyword(s):  
Minimum Distance ◽  
Metric Spaces ◽  
Optimal Solution ◽  
Global Optimal Solution ◽  
Complex Valued Metric Space ◽  
Fixed Point Equation ◽  
Point Equation ◽  
Global Optimal ◽  
Metric Function ◽  
Complex Valued

We introduce the concept of proximity points for nonself-mappings between two subsets of a complex valued metric space which is a recently introduced extension of metric spaces obtained by allowing the metric function to assume values from the field of complex numbers. We apply this concept to obtain the minimum distance between two subsets of the complex valued metric spaces. We treat the problem as that of finding the global optimal solution of a fixed point equation although the exact solution does not in general exist. We also define and use the concept of P-property in such spaces. Our results are illustrated with examples.

scholarly journals Prototype Filter Design Based on Channel Estimation for FBMC/OQAM Systems

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Yongjin Liu ◽  
Xihong Chen ◽  
Yu Zhao
Keyword(s):  
Genetic Algorithm ◽  
Channel Estimation ◽  
Optimization Problem ◽  
Filter Design ◽  
Stop Band ◽  
Optimal Solution ◽  
Improved Genetic Algorithm ◽  
Global Optimal Solution ◽  
Prototype Filter ◽  
Global Optimal

A prototype filter design for FBMC/OQAM systems is proposed in this study. The influence of both the channel estimation and the stop-band energy is taken into account in this method. An efficient preamble structure is proposed to improve the performance of channel estimation and save the frequency spectral efficiency. The reciprocal of the signal-to-interference plus noise ratio (RSINR) is derived to measure the influence of the prototype filter on channel estimation. After that, the process of prototype filter design is formulated as an optimization problem with constraint on the RSINR. To accelerate the convergence and obtain global optimal solution, an improved genetic algorithm is proposed. Especially, the History Network and pruning operator are adopted in this improved genetic algorithm. Simulation results demonstrate the validity and efficiency of the prototype filter designed in this study.

scholarly journals A Shearlets-Based Method for Rain Removal from Single Images

2019 ◽  
Vol 9 (23) ◽  
pp. 5137 ◽  
Author(s):  
Guomin Sun ◽  
Jinsong Leng ◽  
Carlo Cattani
Keyword(s):  
Optimal Solution ◽  
Single Image ◽  
Split Bregman ◽  
Global Optimal Solution ◽  
Rain Removal ◽  
Rain Drops ◽  
Global Optimal ◽  
Removal Model ◽  
Split Bregman Algorithm ◽  
Sparse Priors

This work focuses on the problem of rain removal from a single image. The directional multilevel system, Shearlets, is used to describe the intrinsic directional and structure sparse priors of rain streaks and the background layer. In this paper, a Shearlets-based convex rain removal model is proposed, which involves three sparse regularizers: including the sparse regularizer of rain streaks and two sparse regularizers of the Shearlets transform of background layer in the rain drops’ direction and the Shearlets transform of rain streaks in the perpendicular direction. The split Bregman algorithm is utilized to solve the proposed convex optimization model, which ensures the global optimal solution. Comparison tests with three state-of-the-art methods are implemented on synthetic and real rainy images, which suggests that the proposed method is efficient both in rain removal and details preservation of the background layer.

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