Hybridization of harmony search with Nelder-Mead algorithm for combined heat and power economic dispatch problem

Zhang, Feng; Guo, Huiru; Liu, Zhentao; Xu, Li; She, Jinhua

doi:10.23919/chicc.2017.8027787

Cited by 7 publications

(4 citation statements)

References 24 publications

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“…The metaheuristic algorithms such as gravitational search algorithm in [34], grey wolf optimization in [35], improved genetic algorithm (GA) in [36], [37], modified PSO in [38], Cuckoo optimization in [39], [40], civilized swarm optimization in [41], exchange market algorithm in [42], the differential algorithm in [43], bee colony optimization in [44], [45], artificial immune system algorithm in [46], oppositional teaching learning based optimization in [47], the harmony search algorithm in [48], [49] and its variants in [50], the squirrel search algorithm in [51], group search optimization in [52] and other methods such as Lagrangian relaxation in [53], benders decomposition approach in [54] are used in literature to obtain the optimal solution of the CHPED problem. The hybrid methods that have been successfully employed to solve the CHPED problem are the hybrid bat and ABC algorithm in [55], hybrid harmony search and PSO algorithm in [56], hybrid harmony search algorithm and Nelder-Mead numerical method in [57]. The survey of the metaheuristic optimization algorithms to solve CHPED problem along with the quality of the solution and computational performance of each algorithm is available in [58].…”

Section: A Literature Reviewmentioning

confidence: 99%

Combined Heat and Power Economic Emission Dispatch Using Hybrid NSGA II-MOPSO Algorithm Incorporating an Effective Constraint Handling Mechanism

Sundaram

2020

IEEE Access

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This research work proposes a synergistic hybrid metaheuristic algorithm a merger of Nondominated Sorting Genetic Algorithm II and Multiobjective Particle Swarm Optimization algorithm for solving the highly complicated combined heat and power economic emission dispatch problem to operate the power system economically and to reduce the impact of environmental pollution. During the iteration, based on ranking, the population is divided into two halves. The exploration is carried out by Nondominated Sorting Genetic Algorithm II using the upper half of the population. The modification of Multiobjective Particle Swarm Optimization to effectively exploit the lower half of the population is done by increasing the personal learning coefficient, decreasing the global learning coefficient and by using an adaptive mutation operator. To satisfy the linear, nonlinear constraints, and to ensure the populations always lie in the Feasible Operating Region of the cogeneration plant, an effective constraint handling mechanism is developed. The proposed hybrid algorithm with an effective constraint handling mechanism enhances the searching capability by effective information interchange. The algorithm is applied to standard test functions and test systems while considering the valve point effects of the thermal plants, transmission power losses, bounds of the units and feasible operating region of the cogeneration units. The hybrid algorithm can obtain a well spread and diverse Pareto optimal solution and also can converge to the actual Pareto optimal front faster than some of the existing algorithms. The statistical analysis reveals that the proposed hybrid algorithm is a viable alternative to solve this complicated and vital problem.

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Section: A Literature Reviewmentioning

confidence: 99%

Combined Heat and Power Economic Emission Dispatch Using Hybrid NSGA II-MOPSO Algorithm Incorporating an Effective Constraint Handling Mechanism

Sundaram

2020

IEEE Access

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“…The cost function of a CHP unit used in this paper can be expressed as follows [27,28]: (see 4 Moreover, from an economic point of view, it is not suitable for CHP units to run at their minimum fuel consumption point. Based on this, it can be seen from Fig.…”

Section: Chp Units Modelmentioning

confidence: 99%

“…In this paper, CHP units are used to increase efficiency and to decrease waste power by employing their retrieved heat–power for supplying a thermal load of a cruise ship next to the heat‐only unit. The cost function of a CHP unit used in this paper can be expressed as follows [27, 28]:

\begin{matrix} right leftthickmathspace.5em \\ {Cost}_{CH {normalP}_{i}}^{t} (P_{CH {normalP}_{i}}^{t}, H_{CH {normalP}_{i}}^{t}) & = a_{i} \cdot {(P_{CH {normalP}_{i}}^{t})}^{2} + b_{i} \cdot (P_{CH {normalP}_{i}}^{t}) + c_{i} \\ + d_{i} \cdot {(H_{CH {normalP}_{i}}^{t})}^{2} + e_{i} \cdot (H_{CH {normalP}_{i}}^{t}) + f_{i} \cdot (P_{CH {normalP}_{i}}^{t} H_{CH {normalP}_{i}}^{t}) \end{matrix}

̣ The output power of CHP units is constrained by their FOR. Two different types of CHP units with different FORs are shown in Fig.…”

Section: Basic Information Of the Intended Systemmentioning

confidence: 99%

Optimal power management of electrical energy storage system, CHP, conventional and heat‐only units considering both electrical and thermal loads for assessment of all‐electric ship's system

Firouzmakan

Homayie

Hooshmand

2020

IET Electrical Systems in Transportation

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Using different types of generation systems in ships, which are known as all-electric ships, can play a key role in increasing economic benefits in the long term. On the other hand, electrical energy storage systems (EESSs) provide flexibility for supporting the electrical load of ships in the presence of renewable energy sources and the other generation units. Since power demands of a ship are not limited to an electrical load, combined heat and power (CHP) units can be considered as backup units for heat-only units in addition to their economic and environmental advantages. In this study, new optimal power management is presented to handle a generation scheduling problem of a cruise ship for 12 h time intervals. In this regard, this method is based on the Lagrangian relaxation approach, a subset of ɛ-constraint approaches, and the use of marginal cost to determine the performance of EESS in each time interval by taking all the constraints into account. The capability of the proposed algorithm is analysed by simulation results of a cruise ship, including conventional, CHP, EESS and heat-only units, in order to achieve minimum operation cost with a short runtime. t and μ CHP p, i t heat-power feasible region constraint multipliers

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“…Hybrid EAs: the combination of harmony search (HS) algorithm and PSO (IH-SPSO) [62], integrated civilized swarm optimization (CSO) and Powell's pattern search (PPS) [63], hybrid HS and Nelder-Mead (NM), called the NM-HS algorithm [64], integrated genetic algorithms and tabu search [65], hybrid heap-based and jellyfish search algorithm (HBJSA) [66], real coded genetic algorithm with improved Mühlenbein mutation (RCGA-IMM) [52], hybrid modified grasshopper optimization algorithm (MGOA) and the improved Harris hawks optimizer (IHHO), known as MGOA-IHHO [67], hybrid chameleon swarm algorithm (CSA) and mayfly optimization (MO), named CSMO [68], fuzzy adaptive ranking-based crow search algorithm (FRCSA) with modified artificial bee colony (ABC), known as (FRCSA-ABC) [69], weighted vertices-based optimizer (WVO) and PSO algorithm, or WVO-PSO [69], hybrid time varying acceleration coefficients-gravitational search algorithm-PSO (hybrid TVAC-GSA-PSO) [70], hybrid firefly and self-regulating PSO (FSRPSO) [71], bat algorithm (BA) and artificial bee colony (ABC) with chaotic based self-adaptive (CSA) search strategy (CSA-BA-ABC) [72], self-adaptive learning with time varying acceleration coefficient-gravitational search algorithm (SAL-TVAC-GSA) [73], fast non-dominated TVAC-PSO combined with EMA [74], and adaptive inertia weight PSO (AIWPSO) [75].…”

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confidence: 99%

Solving the Combined Heat and Power Economic Dispatch Problem in Different Scale Systems Using the Imperialist Competitive Harris Hawks Optimization Algorithm

Nazari,

Abdi

2023

Biomimetics

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The aim of electrical load dispatch (ELD) is to achieve the optimal planning of different power plants to supply the required power at the minimum operation cost. Using the combined heat and power (CHP) units in modern power systems, increases energy efficiency and, produce less environmental pollution than conventional units, by producing electricity and heat, simultaneously. Consequently, the ELD problem in the presence of CHP units becomes a very non-linear and non-convex complex problem called the combined heat and power economic dispatch (CHPED), which supplies both electric and thermal loads at the minimum operational cost. In this work, at first, a brief review of optimization algorithms, in different categories of classical, or conventional, stochastic search-based, and hybrid optimization techniques for solving the CHPED problem is presented. Then the CHPED problem in large-scale power systems is investigated by applying the imperialist competitive Harris hawks optimization (ICHHO), as the combination of imperialist competitive algorithm (ICA), and Harris hawks optimizer (HHO), for the first time, to overcome the shortcomings of using the ICA and HHO in the exploitation, and exploration phases, respectively, to solve this complex optimization problem. The effectiveness of the combined algorithm on four standard case studies, including 24 units as a medium-scale, 48, 84, units as the large-scale, and 96-unit as a very large-scale heat and power system, is detailed. The obtained results are compared to those of different algorithms to demonstrate the performance of the ICHHO algorithm in terms of better solution quality and lower fuel cost. The simulation studies verify that the proposed algorithm decreases the minimum operation costs by at least 0.1870%, 0.342%, 0.05224%, and 0.07875% compared to the best results in the literature.

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Hybridization of harmony search with Nelder-Mead algorithm for combined heat and power economic dispatch problem

Cited by 7 publications

References 24 publications

Combined Heat and Power Economic Emission Dispatch Using Hybrid NSGA II-MOPSO Algorithm Incorporating an Effective Constraint Handling Mechanism

Combined Heat and Power Economic Emission Dispatch Using Hybrid NSGA II-MOPSO Algorithm Incorporating an Effective Constraint Handling Mechanism

Optimal power management of electrical energy storage system, CHP, conventional and heat‐only units considering both electrical and thermal loads for assessment of all‐electric ship's system

Solving the Combined Heat and Power Economic Dispatch Problem in Different Scale Systems Using the Imperialist Competitive Harris Hawks Optimization Algorithm

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