Fast Evolutionary Progranuning Techniques for Short-Term Hydrothermal Scheduling

Sinha,; Chakrabarti, Sujit Kumar; Chattopadhyay,

doi:10.1109/mper.2002.4311838

Cited by 2 publications

(6 citation statements)

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“…The result, i.e., the optimal cost obtained by the proposed IPSO is compared with those obtained from DP, NLP, IFEP and DE in Table 6 for case 3. From Table 6 it is observed that the minimum cost found to be 925978.84 ($) by the proposed IPSO method and 928236.94 ($) by the DE method as compared to the previous minimum cost reported in the literature obtained by IFEP method [11], i.e., 933949.25 ($). Similarly, the execution time needed for getting optimal solution are 31.11, 36.82 and 203.02 s by the proposed IPSO, DE and IFEP methods, respectively.…”

Section: Methodsmentioning

confidence: 63%

“…The improved fast evolutionary programming (IFEP) method as described in Ref. [11] was also implemented on same machine for comparison of computational efficiencies of proposed IPSO method along with DE and IFEP methods. …”

Section: Resultsmentioning

confidence: 99%

“…In the past decades, stochastic search algorithms like simulated annealing (SA) [6], genetic algorithm (GA) [7][8][9] and evolutionary programming (EP) [10,11] have been proved to be very efficient in solving complex power systems problems but, these heuristic methods do not always guarantee the globally optimal solution. Rather, quite often they can produce suboptimal or near globally optimal solution.…”

Section: Introductionmentioning

confidence: 99%

“…Its applications to few power system problems have also been reported in the literature that are found to be exciting. Therefore, to investigate the potential of the proposed IPSO approach, one example of hydrothermal system [8,11] has been considered and their simulation results are compared to those of recent approaches reported in the literature including the DE approach.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

An improved PSO technique for short-term optimal hydrothermal scheduling

Hota¹,

Barisal²,

Chakrabarti

2009

Electric Power Systems Research

Self Cite

169

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Section: Methodsmentioning

confidence: 63%

Section: Resultsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

An improved PSO technique for short-term optimal hydrothermal scheduling

Hota¹,

Barisal²,

Chakrabarti

2009

Electric Power Systems Research

Self Cite

169

View full text Add to dashboard Cite

“…Test case I has four cascade hydro power plants (HPP) and one thermal power plant having convex fuel cost characteristics [6] [8], [37] [39],- [46]. The HPP has multi chain cascade flow network as shown in Fig.…”

Section: Description Of Test Casesmentioning

confidence: 99%

Hydro-thermal-wind scheduling employing novel ant lion optimization technique with composite ranking index

2016

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Adaptive boundary shrinking Composite ranking index (CRI) Random walk mechanism Multi-objective hydro-thermal-wind scheduling (MOHTWS) Wind reserve and penalty coefficients a b s t r a c t A solution to the combined hydro-thermal-wind scheduling problem of multi reservoir cascaded hydro plants is presented employing a novel ant lion optimization (ALO) algorithm. Five objectives, cost, various emissions and power loss, are simultaneously optimized. The optimal schedules of thermal, hydro and wind power (WP) units are determined for continuously varying load subject to a large number of practical operational constraints. The effect of reserve and penalty coefficients and WP uncertainty is also investigated for the multi-objective (MO) problem. The newly proposed ALO algorithm has unique features like random walk, roulette wheel, and boundary shrinking. These operations provide a judicious balance between exploration and exploitation, and create a powerful optimization technique for complex real-world problems.Finding the best compromise solution (BCS) is a tedious task when multiple objectives are involved. A composite ranking index (CRI) is proposed as a performance metrics for MO problems. The CRI helps the decision maker in ranking the large number of Pareto-optimal solutions. The developed model is tested on three standard systems, having a mix of hydro, thermal and wind generators. The performance is found to be superior to published results and comparable with established algorithms like artificial bee colony (ABC) and differential evolution (DE).

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Fast Evolutionary Progranuning Techniques for Short-Term Hydrothermal Scheduling

Cited by 2 publications

References 0 publications

An improved PSO technique for short-term optimal hydrothermal scheduling

An improved PSO technique for short-term optimal hydrothermal scheduling

Hydro-thermal-wind scheduling employing novel ant lion optimization technique with composite ranking index

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