Cuckoo search algorithm for short-term hydrothermal scheduling

Nguyen, Thang Trung; Vo, Dieu Ngoc; Truong, Anh

doi:10.1016/j.apenergy.2014.07.017

Cited by 113 publications

(45 citation statements)

References 19 publications

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“…Among the optimization problems related to the optimal scheduling of hydrothermal systems, the fixed-head, short-term HTS problem has been widely and successfully studied so far . The fixed-head, short-term HTS problem has been classified into two sub-problems with different hydraulic constraints, namely the amount of discharged water available via the turbine [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17] and reservoir volume limits [2,3,[18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33][34]. In the two sub-problems, the water head of reservoirs is not supposed to be changed over the scheduled time, thus the water discharge function of the two problems has the same quadratic function model with respect to hydro generation and coefficients; however, the set of hydraulic constraints taken into account in the problems are almost completely different.…”

Section: Introductionmentioning

confidence: 99%

“…Several methods have been used to solve the first problem, such as Powell's hybrid method [1]; the Newton-Raphson method [1,2]; the lambda-gamma method (λ-γ method) [2]; the Lagrange-multiplier, factorization-based, Newton-Raphson method [3]; the Lagrange method based on the linearization of the coordination equation (LCEL) [4]; the Lagrangian relaxation approach [5]; Hopfield neural networks (HNN) [6]; evolutionary programming (EP) [7,8]; the artificial immune system method (AIS) [8]; particle swarm optimization (PSO) and the differential evolutionary method (DE) [8]; the modified bacterial foraging algorithm (MBFA) [9]; the optimal gamma-based genetic algorithm (OGB-GA) [10]; fast genetic algorithm (FGA) [11]; the predator-prey optimization technique (PPO) [12]; improved genetic with multiplier updating (IGA-MU) [13]; real-coded genetic algorithm (RCGA) [14]; a Hopfield Lagrange network (HLN) [15]; an augmented Hopfield Lagrange network (ALHN) [15]; the Cuckoo search algorithm (CSA) [16,17]; and a modified cuckoo search algorithm (MCSA) [17]. On the other hand, there has also been a number of methods proposed to solve the second problem, such as gradient search (GS) [2]; Newton's method [3]; the simulated annealing approach (SA) [18]; evolutionary programming (EP) [19][20][21]; genetic algorithms (GA) [22]; fast EP (FEP) [23]; improved fast EP (IFEP) [23]; hybrid EP (HEP) [24]; PSO [25]; the improved bacterial foraging algorithm (IBFA) [26]; self-organizing, hierarchical PSO …”

Section: Introductionmentioning

confidence: 99%

“…Furthermore, the solution and the computation for PSO are more effective than those for GA and EP. Recently, several applications of CSA for HTS problems in [16,17] for the first problem and in [33,34] for the second problem have shown very good results with fast execution times compared to GA variants, EP variants, and other methods such as AIS, DE and deterministic methods. CSA methods construct their search strategy based on Lévy flights and the probability of alien egg identification.…”

Section: Introductionmentioning

confidence: 99%

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Modified Differential Evolution Algorithm: A Novel Approach to Optimize the Operation of Hydrothermal Power Systems while Considering the Different Constraints and Valve Point Loading Effects

et al. 2018

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This paper proposes an efficient and new modified differential evolution algorithm (ENMDE) for solving two short-term hydrothermal scheduling (STHTS) problems. The first is to take the available water constraint into account, and the second is to consider the reservoir volume constraints. The proposed method in this paper is a new, improved version of the conventional differential evolution (CDE) method to enhance solution quality and shorten the maximum number of iterations based on two new modifications. The first focuses on a self-tuned mutation operation to open the local search zone based on the evaluation of the quality of the solution, while the second focuses on a leading group selection technique to keep a set of dominant solutions. The contribution of each modification to the superiority of the proposed method over CDE is also investigated by implementing CDE with the self-tuned mutation (STMDE), CDE with the leading group selection technique (LGSDE), and CDE with the two modifications. In addition, particle swarm optimization (PSO), the bat algorithm (BA), and the flower pollination algorithm (FPA) methods are also implemented through four study cases for the first problem, and two study cases for the second problem. Through extensive numerical study cases, the effectiveness of the proposed approach is confirmed.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Modified Differential Evolution Algorithm: A Novel Approach to Optimize the Operation of Hydrothermal Power Systems while Considering the Different Constraints and Valve Point Loading Effects

et al. 2018

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“…The evolutionary techniques known as “evolutionary computation methods” have successfully investigated SHTC problem without any loss of generality. These heuristic and evolutionary computation methods are successfully being applied in many industrial scaled as well as large‐scale real‐life system such as in as well as the problem of the electrical power system like . In literature, many heuristic techniques have been applied to solve SHTC problem.…”

Section: Introductionmentioning

confidence: 99%

Short-term hydrothermal coordination using water cycle algorithm with evaporation rate

Haroon

Malik

2017

Int. Trans. Electr. Energ. Syst.

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Summary The demand of electrical energy is increasing and so is its cost. The conventional means of generation of electrical are the hydel and thermal. Their optimized mutual operation results in the most economic electrical energy for the end user. Therefore, the optimized operation of hydel and thermal plants known as hydrothermal coordination (HTC) is one of the important and challenging tasks in the field of power system operation. This paper investigates a modified version of a new nature inspired algorithm, water cycle algorithm called as evaporation rate–based water cycle algorithm (ERWCA) for the solution of HTC. This algorithm has its roots from the natural water cycle. The raindrops form streams, which flow to the rivers and eventually into the sea. The streams either merge into rivers and sea or they are too slow to reach the rivers or sea; the evaporation process occurs, which again causes the rainfall. Hence, new streams will be created. In this paper, ERWCA has been successfully applied to the problem of HTC. The complex constraints of the hydel and thermal network especially the prohibited discharge zones of hydel plants and the ramp rates of thermal plants, which are rarely taken into account, have been incorporated. The comparison of the results with other nature inspired techniques already available in the literature like particle swarm optimization and differential evolution shows the strength and potential of this new technique ERWCA in obtaining the better quality result.

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“…Cuckoo search has been very popular in a short time and started to apply many engineering fields and optimization with promising efficiency and few control parameter settings. Due to these advantages, CS was used for clustering of web search results [7], hydrothermal scheduling [8,9], economic dispatch [10], multilevel thresholding [11], parameter estimation and optimization [12,13] , redundancy allocation problems [14], forecasting solar radiation [15] and so on. The main problem of the optimization techniques is balancing between exploration and exploitation.…”

Section: Introductionmentioning

confidence: 99%

A modified cuckoo search using different search strategies

Haklı¹

2016

ijisae

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Cuckoo search (CS) is one of the recent population-based algorithms used for solving continuous optimization problems. The most known problem for optimization techniques is balancing between exploration and exploitation. CS uses two search strategies to updating the nest: local and global search. Although cuckoo search are adequate for the exploration, it is not well enough the exploitation. Only one search equation is used for local search, this equation remains incapable and causes some deficiencies about the exploitation. To enhance the ability of exploitation and to balance between global search and local search, different search strategies were implemented in CS algorithm. The proposed method was compared with basic CS on well-known unimodal and multimodal benchmark functions. Experimental results show that the proposed method is more successful than the basic CS in terms of solution quality.

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Cuckoo search algorithm for short-term hydrothermal scheduling

Cited by 113 publications

References 19 publications

Modified Differential Evolution Algorithm: A Novel Approach to Optimize the Operation of Hydrothermal Power Systems while Considering the Different Constraints and Valve Point Loading Effects

Modified Differential Evolution Algorithm: A Novel Approach to Optimize the Operation of Hydrothermal Power Systems while Considering the Different Constraints and Valve Point Loading Effects

Short-term hydrothermal coordination using water cycle algorithm with evaporation rate

A modified cuckoo search using different search strategies

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