Combined heat and power economic dispatch problem solution by implementation of whale optimization method

Nazari-Heris, Morteza; Mehdinejad, Mehdi; Mohammadi‐Ivatloo, Behnam; Babamalek-Gharehpetian, Gevork

doi:10.1007/s00521-017-3074-9

Cited by 104 publications

(81 citation statements)

References 27 publications

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“…In the years since these pioneering works, the imaginativeness of researchers has continued to flourish. New metaheuristic methods have been applied to the CHP dispatch problem such as cuckoo search [23][24][25][26], invasive weed optimization [27], the artificial immune system algorithm [28], the firefly algorithm [29], krill herd optimization [30], the harmony search algorithm [31][32][33][34], grey wolf optimization [35,36], whale optimization [37], and the hybridizing bat algorithm with artificial bee colony [38]. This is by no means an exhaustive list of metaheuristic approaches investigated.…”

Section: Optimal Combined Heat and Power Dispatchmentioning

confidence: 99%

A Critical Review of the Modeling and Optimization of Combined Heat and Power Dispatch

Kazda¹,

Li²

2020

Processes

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Combined heat and power (CHP) systems are attracting increasing attention for their ability to improve the economics and sustainability of the electricity system. Determining how to best operate these systems is difficult because they can consist of many generating units whose operation is governed by complex nonlinear physics. Mathematical programming is a useful tool to support the operation of CHP systems, and has been the subject of substantial research attention since the early 1990s. This paper critically reviews the modeling and optimization work that has been done on the CHP economic dispatch problem, and the CHP economic and emission dispatch problem. A summary of the common models used for these problems is provided, along with comments on future modeling work that would beneficial to the field. The majority of optimization approaches studied for CHP system operation are metaheuristic algorithms. A discussion of the limitations and benefits of metaheuristic algorithms is given. Finally, a case study optimizing five classic CHP system test instances demonstrates the advantages of the using deterministic global search algorithms over metaheuristic search algorithms.

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Section: Optimal Combined Heat and Power Dispatchmentioning

confidence: 99%

A Critical Review of the Modeling and Optimization of Combined Heat and Power Dispatch

Kazda¹,

Li²

2020

Processes

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“…Nazari-Heris et al [26], Zhao et al [27], Sameer et al [28], Reddy et al [29], Stützle et al [30], Pijarski and Piotr [31], Yapici and Cetinkaya [32], Dede et al [33], Grzywiński et al [34], Kaveh et al [35], Kaveh et al [36] and Kaveh and Ilchi Ghazaan [37]. Following a description of the EVPS algorithm with a brief description of six other metaheuristic algorithms including VPS, GWO, HS, SSA, ECBO and GOA algorithms, is presented in the following subsections.…”

Section: Optimization Algorithmsmentioning

confidence: 99%

Optimal Design of Steel Curved Roof Frames by Enhanced Vibrating Particles System Algorithm

Kaveh¹,

Vaez²,

Hosseini³

et al. 2019

Period. Polytech. Civil Eng.

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The paper presents an optimal design of steel curved roof frames with its roof being part of a circular arc. The elements of frames are tapered I-section members. In the objective function for optimization, two factors affecting the weight of frames are considered simultaneously. First, the roof slope angle as an effective variable on the values of the structural loading and second, the cross-section of members that are considered as continuous and discrete variables, respectively. In the range of 3 to 70 degrees, the optimum range of roof slope angles for steel curved roof frames, as well as precise value of the best roof slope angle, will be reported. Enhanced Vibrating Particles System (EVPS) algorithm is utilized for the optimal design of steel curved roof frames with tapered members. The performance and efficiency of the EVPS algorithm is compared with six other recently developed optimization algorithms including VPS, GWO, HS, SSA, ECBO and GOA algorithms. The effectiveness and performance of EVPS algorithm is proven. Frames design are performed using ANSI/AISC 360-05 speciﬁcations which strength, displacement and stability constraints are imposed on the frames.

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“…They have no strict requirements on the form of optimization problems and can avoid the influences of the initial condition sensitivity and gradient information. Up to now, the successfully implemented metaheuristic methods include simulated annealing [3], genetic algorithm [4,5], particle swarm optimization [6][7][8], differential evolution [9,10], artificial bee colony [11,12], harmony search [13][14][15][16][17], biogeography-based optimization [18][19][20][21][22], teaching-learning-based optimization [23][24][25], firefly algorithm [26], crisscross optimization algorithm [27,28], bat algorithm [29], grey wolf optimizer [30,31], cuckoo search [32][33][34], ant lion optimizer [35], exchange market algorithm [36], symbiotic organisms search [37,38], backtracking search algorithm [39,40], interior search algorithm [41], whale optimization algorithm [42], mine blast algorithm [43], and hybrid methods [44][45]…”

Section: Introductionmentioning

confidence: 99%

A Novel Method for Economic Dispatch with Across Neighborhood Search: A Case Study in a Provincial Power Grid, China

et al. 2018

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Economic dispatch (ED) is of cardinal significance for the power system operation. It is mathematically a typical complex nonlinear multivariable strongly coupled optimization problem with equality and inequality constraints, especially considering the valve-point effects. In order to effectively solve the problem, a simple yet very young and efficient population-based algorithm named across neighborhood search (ANS) is implemented in this paper. In ANS, a group of individuals collaboratively navigate through the search space for obtaining the optimal solution by simultaneously searching the neighborhoods of multiple superior solutions. Four benchmark test cases with diverse complexities and characteristics are firstly employed to comprehensively verify the feasibility and effectiveness of ANS. The experimental and comparison results fully demonstrate the superiority of ANS in terms of the final solution quality, convergence speed, robustness, and statistics. In addition, the sensitivities of ANS to variations of population size and across-search degree are studied. Furthermore, ANS is applied to a practical provincial power grid of China. All the comparison results consistently indicate that ANS is highly competitive and can be used as a promising alternative for ED problems.

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Combined heat and power economic dispatch problem solution by implementation of whale optimization method

Cited by 104 publications

References 27 publications

A Critical Review of the Modeling and Optimization of Combined Heat and Power Dispatch

A Critical Review of the Modeling and Optimization of Combined Heat and Power Dispatch

Optimal Design of Steel Curved Roof Frames by Enhanced Vibrating Particles System Algorithm

A Novel Method for Economic Dispatch with Across Neighborhood Search: A Case Study in a Provincial Power Grid, China

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