A hybrid BFA-PSO algorithm for economic dispatch with valve-point effects

Jayabarathi, T.; Bahl, Prateek; Ohri, Harsha; Yazdani, Afshin; Ramesh, V.

doi:10.1007/s11708-012-0189-7

Cited by 21 publications

(7 citation statements)

References 20 publications

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“…For two low-dimension cases which are not difficult, and the gap of cost function value between approaches is relatively small. They are briefly introduced as follows, 3unit with VPE case from [1,13], the corresponding optimal solution is not provided, but we can find the optimum solution (300.2669, 400, 149.7331) whose cost is equal to 8234.07. And in this case, the cost function value and the constraint violation of IMMSDE is 8234.071730 and 0 respectively.…”

Section: Experimental Results and Analysismentioning

confidence: 99%

An Improved Differential Evolution Algorithm Using Adaptive Multiple Mutation Strategies for the Economic Load Dispatch Problems

Zhang¹,

Zou²,

Shen³

et al. 2018

dtcse

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An improved differential evolution algorithm using adaptive multiple mutation strategies (IMMSDE) is proposed to solve the economic load dispatch (ELD) problems with or without valvepoint effects (VPE). Unlike classical differential evolution (DE) algorithm, three mutation strategies and five adaptive parameters participate in the IMMSDE. A mutation strategy is randomly selected from the strategy pool in order to enlarge the search range, which is beneficial for preventing the solutions from falling into location optima. On the other hand, the adaptive parameters with learning ability improve the search accuracy and the speed of convergence. Additionally, a repair method is used to handle equality constraints, which enables IMMSDE to find feasible solutions rapidly. Four ELD cases are selected to testify the effectiveness of four DE algorithms on solving ELD problems. Results show that IMMSDE performs better than the other algorithms for the ELD problems and can always find the solutions satisfying the equality constraints.

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Section: Experimental Results and Analysismentioning

confidence: 99%

An Improved Differential Evolution Algorithm Using Adaptive Multiple Mutation Strategies for the Economic Load Dispatch Problems

Zhang¹,

Zou²,

Shen³

et al. 2018

dtcse

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“…The aforementioned methodologies encompass particle swarm optimisation (PSO) [21], evolutionary computing (EP) [22], differential evolutionary (DE) [23], grey wolf optimisation (GWO), teaching learning-based optimisation (TLBO), the Krill's herd optimisation (KHO), Phasor PSO algorithms (PPSO), and improved beta hill-climbing the local search algorithm (CLS), among others. Hybrid techniques for optimization, such as learned genetic predisposition PSO [29], a mix of GA and PSO; Combining DE, quadratic programming sequences, and chaotic sequences (SQP), DECSQP [30]; Sequential quadratic programming (SQP) and DECSQP [30], which combines DE and chaos sequences; HBFA [31], this combines the PSO algorithm with the technique of bacterial gathering (BFA); Blended Approach (HYB) [32], a combination of the Butterfly and Bats Algorithms: modified randomised frog-leaping technique (MSFLA) [33] is a form of the frogleaping technique, which was derived from the multiobjective striped African hyena and emperor penguin (MOSHEPO) [34] are a few methods used frequently to address ELD and CEED issues.…”

Section: Introductionmentioning

confidence: 99%

Mountaineering Team-Based Optimization Technique to Solve Economic Load Dispatch Problem

Reddy

Ramanaiah²,

Sudhakar³

2023

Preprint

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Economical load dispatch (ELD) and combined economic emission dispatch (CEED) problems are solved using optimization approaches. In order to handle ELD and CEED problems, a novel metaheuristic optimization technique based on human intelligence called the mountaineering team based optimization (MTBO) algorithm is projected in this paper. The MTBO method implemented based on the human cooperation and social behaviour taking into account the usual occurrences to reach a mountain top, this represents the finest overall solution. The projected MTBO method is utilised to address optimisation problems. This approach involves analysing the stages of regular and climbing movements, which are based on the leader's experience, the obstacles encountered during the ascent, and the risk of being trapped in local optimum performance. Additionally, the group's coordination and social support are considered to safeguard members from common catastrophes. To evaluate the efficiency of the suggested method, considered six cases for the ELD problem and four cases for a CEED problem. Along with the MTBO, other optimization techniques like flower pollination algorithm (FPA), ant lion optimization (ALO) and grey wolf optimization (GWO) methods are used to solve ELD and CEED problem. The MTBO method outperforms the competition in terms of robustness, ease of implementation, effective optimization performance for a optimal global solutions.

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“…Here, the acceleration constant best value is selected based on the optimum number of fitness evaluations. In [11], a hybrid bacteria foraging (BFA) and PSO is suggested to solve ELDP by considering the valve-point effect. In this hybrid technique, the best particle's biased velocity vector is added by BFA random velocity to decrease the randomness during the search process and to increase the swarming.…”

Section: Introductionmentioning

confidence: 99%

Economic Emission Load Dispatch Problem with Valve-Point Loading Using a Novel Quasi-Oppositional-Based Political Optimizer

Vedik¹,

Rangarajan

Shiva³

et al. 2021

Electronics

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In the present paper, a novel meta-heuristic algorithm, namely quasi-oppositional search-based political optimizer (QOPO), is proposed to solve a non-convex single and bi-objective economic and emission load dispatch problem (EELDP). In the proposed QOPO technique, an opposite estimate candidate solution is performed simultaneously on each candidate solution of the political optimizer to find a better solution of EELDP. In the bi-objective EELDP, QOPSO is applied to simultaneously minimize fuel costs and emissions by considering various constraints such as the valve-point loading effect (VPLE) and generator limits for a generation. The effectiveness of the proposed QOPO technique has been applied on three units, six units, 10-units, 11-units, 13-units, and 40-unit systems by considering the VPLE, transmission line losses, and generator limits. The results obtained using the proposed QOPO are compared with those obtained by other techniques reported in the literature. The relative results divulge that the proposed QOPO technique has a good exploration and exploitation capability to determine the optimal global solution compared to the other methods provided in the literature without violation of any constraints and bounded limits.

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A hybrid BFA-PSO algorithm for economic dispatch with valve-point effects

Cited by 21 publications

References 20 publications

An Improved Differential Evolution Algorithm Using Adaptive Multiple Mutation Strategies for the Economic Load Dispatch Problems

An Improved Differential Evolution Algorithm Using Adaptive Multiple Mutation Strategies for the Economic Load Dispatch Problems

Mountaineering Team-Based Optimization Technique to Solve Economic Load Dispatch Problem

Economic Emission Load Dispatch Problem with Valve-Point Loading Using a Novel Quasi-Oppositional-Based Political Optimizer

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