Improved Firefly Algorithm: A Novel Method for Optimal Operation of Thermal Generating Units

Nguyen, Thang Trung; Quynh, Nguyen Vu; Đại, Lê Văn

doi:10.1155/2018/7267593

Cited by 35 publications

(26 citation statements)

References 66 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Such results confirm the superiority of the proposed method over SSSO in addition to a smaller population size and less iterations. Comparing with other methods also leads to approximately the same conclusion since the proposed method finds similar best solutions as CSA [14] and IFA [31], and finds a better best solution than other methods except for ORCSA [15]. For exact comparison, IP values indicate that the proposed method can get the same performance as some methods and can improve the performance to 1.04% as compared to the worst method.…”

Section: Results Comparisons On the Third Systemsupporting

confidence: 58%

A Novel Social Spider Optimization Algorithm for Large-Scale Economic Load Dispatch Problem

et al. 2019

Self Cite

View full text Add to dashboard Cite

The paper develops an improved social spider optimization algorithm (ISSO) for finding optimal solutions of economic load dispatch (ELD) problems. Different ELD problem study cases can bring huge challenges for testing the robustness and effectiveness of the proposed ISSO method since discontinuous objective functions as well as complicated constraints are taken into account. The improved method is different from original social spider optimization algorithm (SSSO) by performing several modifications directly related to three processes of new solution generation. Namely, the proposed method keeps one formula for the first and the second generations and modify them effectively while SSSO has two different formulas for each generation. In the third generation, the proposed method applies a new formula for determining the mating radius of dominant males and females with the intent to expand search space and avoid falling into local zones. The modifications can support the proposed ISSO method find better solutions with faster manner than SSSO while the number of control parameters and the number of computational processes can be reduced. As a result, the proposed method can find much less generation cost and achieve faster search speeds than SSSO for all considered systems. On the other hand, the search ability evaluation of the proposed method is also given by comparing results with other existing methods available in previous studies. The proposed method can obtain approximate or better results and faster convergence than nearly all compared methods excluding for the last system. Consequently, the proposed ISSO method can be recommended to be a strong method for ELD problem and it can be tried for other mathematical problems in engineering.

show abstract

Section: Results Comparisons On the Third Systemsupporting

confidence: 58%

A Novel Social Spider Optimization Algorithm for Large-Scale Economic Load Dispatch Problem

et al. 2019

Self Cite

View full text Add to dashboard Cite

show abstract

“…However, how to verify the effectiveness and robust of the BAs with other methods mentioned in the literature review may not be an easy mission because, in fact, different studies may select the different computer configurations and different values of the population size and maximum number of iterations. In order to adapt to the mentioned differences, the maximum number of fitness evaluations (FE max ) and the scaled computational time (SCT) introduced in [36] and [37] have been used, respectively, re-applied as two relative criteria for fair comparisons when different studies have run their proposed methods in different conditions as different population sizes, different iteration number, and different computer configuration. In fact, for meta-heuristics, FE max is also a comparison criterion to analyze the effectiveness among considered methods [36].…”

Section: Case Study and Discussionmentioning

confidence: 99%

“…In order to adapt to the mentioned differences, the maximum number of fitness evaluations (FE max ) and the scaled computational time (SCT) introduced in [36] and [37] have been used, respectively, re-applied as two relative criteria for fair comparisons when different studies have run their proposed methods in different conditions as different population sizes, different iteration number, and different computer configuration. In fact, for meta-heuristics, FE max is also a comparison criterion to analyze the effectiveness among considered methods [36]. For this study, we consider the FE max = N P × G max [37] to compare the performance of all methods.…”

Section: Case Study and Discussionmentioning

confidence: 99%

See 1 more Smart Citation

A Novel Method for Economic Dispatch of Combined Heat and Power Generation

et al. 2018

View full text Add to dashboard Cite

The paper proposes a modified Bat algorithm (MBA) for searching optimal solutions of Economic dispatch of combined heat and power generation (CHPGED) with the heat and power generation from three different types of units consisting of pure power generation units, pure heat generation units and cogeneration units. The CHPGED problem becomes complicated and big challenge to optimization tools since it considers both heat and power generation from cogeneration units. Thus, we apply MBA method with the purpose of enhancing high quality solution search ability as well as search speed of conventional Bat algorithm (BA). This proposed approach is established based on three modifications on BA. The first is the adaptive frequency adjustment, the second is the optimal range of updated velocity, and the third is the retained condition of a good solution with objective to ameliorate the search performance of traditional BA. The effectiveness of the proposed approach is evaluated by testing on 7, 24, and 48 units systems and IEEE 14-bus system and comparing results with BA together with other existing methods. As a result, it can conclude that the proposed MBA method is a favorable meta-heuristic algorithm for solving CHPGED problem.Energies 2018, 11, 3113 2 of 27 is a major challenge for the optimization tools for finding optimal solutions satisfying all constraints exactly and reducing total fuel cost effectively.Over several decades, the authors in [2][3][4][5][6][7] have introduced different methods to solve the CHPGED. The Newton [2] and Lagrange relaxation (LR) [3] methods are two of those methods that were first applied to solve the CHPGED issue. However, they have a common main disadvantage of being limited when dealing with a large-scale system. In order to overcome this disadvantage, the authors in [4] have proposed the combined method between the augmented Lagrange and Hopfield network (ALHN). As a result, a very good solution with a short computation time is obtained. In order to reduce the number of iterations and the loop time by speeding up the computation, the authors of [5] have presented the novel direct search (NDS) method based on a successive refinement search technique. The Newton method and other methods such as ALHN and NDS can solve nonlinear constrained optimization problems but Lagrange relaxation (LR) cannot deal with the issue. Thus, ref.[6] has proposed the combination of sequential quadratic programming (SQP) and LR, called SQP-LR method. In the method, SQP could solve nonlinear constraints successfully while LR could find optimal solution satisfying all remaining constraints. Unlike SQP-LR, meta-heuristic algorithms can solve non-linear problems simply and successfully although they do not need to use SQP method. LR with surrogate sub-gradient technique (LR-SST) [7] has been developed by using the main search function of LR and the updating function of SST. LR has also been used for the same purpose as the methods in [3,6] while SST has been used to calculate the values of Lagrange multipliers...

show abstract

“…For example, the authors in [3] could only solve 2 Mathematical Problems in Engineering the OLD problem successfully by separating three-curve objective function into three different single curve objective functions. In [7], a more realistic representation of the electric generation fuel function corresponding to multi fossil fuel sources was introduced, in which the authors considered a discontinuous cost function and the effects of valve loading process (EoVLP) of thermal units. More complicated models were also introduced.…”

Section: Introductionmentioning

confidence: 99%

Finding Optimal Load Dispatch Solutions by Using a Proposed Cuckoo Search Algorithm

Nguyen

Đại

et al. 2019

Mathematical Problems in Engineering

Self Cite

View full text Add to dashboard Cite

Optimal load dispatch (OLD) is an important engineering problem in power system optimization field due to its significance of reducing the amount of electric generation fuel and increasing benefit. In the paper, an improved cuckoo search algorithm (ICSA) is proposed for determining optimal generation of all available thermal generation units so that all constraints consisting of prohibited power zone (PPZ), real power balance (RPB), power generation limitations (PGL), ramp rate limits (RRL), and real power reserve (RPR) are completely satisfied. The proposed ICSA method performance is more robust than conventional Cuckoo search algorithm (CCSA) by applying new modifications. Compared to CCSA, the proposed ICSA approach can obtain high quality solutions and speed up the solution search ability. The ICSA robustness is verified on different systems with diversification of objective functions as well as the considered constraint set. The results from the proposed ICSA method are compared to other algorithms for comparison. The result comparison analysis indicates that the proposed ICSA approach is more robust than CCSA and other existing optimization approaches in finding solutions with significant quality and shortening simulation time. Consequently, it should lead to a conclusion that the proposed ICSA approach deserves to be applied for finding solutions of OLD problem in power system optimization field.

show abstract

Improved Firefly Algorithm: A Novel Method for Optimal Operation of Thermal Generating Units

Cited by 35 publications

References 66 publications

A Novel Social Spider Optimization Algorithm for Large-Scale Economic Load Dispatch Problem

A Novel Social Spider Optimization Algorithm for Large-Scale Economic Load Dispatch Problem

A Novel Method for Economic Dispatch of Combined Heat and Power Generation

Finding Optimal Load Dispatch Solutions by Using a Proposed Cuckoo Search Algorithm

Contact Info

Product

Resources

About