RETRACTED: Optimal performance of fuel cell-CHP-battery based micro-grid under real-time energy management: An epsilon constraint method and fuzzy satisfying approach

Nouri, Alireza; Khodaei, Hossein; Darvishan, Ayda; Sharifian, Seyedmehdi; Ghadimi, Noradin

doi:10.1016/j.energy.2018.06.141

Cited by 61 publications

(21 citation statements)

References 63 publications

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“…The AL mode uses demand change rates equal to the lower limits values of ranges given by Equations (5) and (6). The AL mode uses demand change rates equal to the lower limits values of ranges given by Equations (5) and (6).…”

Section: Real-time Simulations and Implementationmentioning

confidence: 99%

“…The system was programmed with four operational modes corresponding to the same number of proposed calculations of demand change rate parameters: AL, NL, intermediate load (IL), and variable load (VL). The AL mode uses demand change rates equal to the lower limits values of ranges given by Equations (5) and (6). In NL mode, the demand change rates take the upper limit values of the same ranges.…”

Section: Real-time Simulations and Implementationmentioning

confidence: 99%

“…2 Another important benefit of DSM is the contribution to the optimization and stabilization of the electrical grid issues that are becoming even more important with the increase in distributed generation systems and the proliferation of renewable energies such as wind power and solar energy. 5 Load forecast can also be applied to short-term scheduling of distributed generators to optimize cost and emissions, such as in Nouri et al, 6 or for optimal solution of the environmental/economic power dispatch problem by considering operational constraints of the generators. Dispatch optimization combined with demand management implemented at the customer-side aids grid operators in balancing intermittent generation from wind and solar units, particularly when the timing and magnitude of energy demand do not coincide with the renewable generation.…”

Section: Introductionmentioning

confidence: 99%

“…In power dispatch optimization, some studies combine heuristic algorithms with artificial neural networks for electricity load forecasting. 5 Load forecast can also be applied to short-term scheduling of distributed generators to optimize cost and emissions, such as in Nouri et al, 6 or for optimal solution of the environmental/economic power dispatch problem by considering operational constraints of the generators. 7 For the load management of energy-intensive loads, most studies are focused on load shedding and shifting to reduce peak demand and in the reduction of operation cost.…”

Section: Introductionmentioning

confidence: 99%

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Power demand control algorithm for single controllable load with parametric and variable load factors

Martell

Sánchez‐Chávez

Peña‐Cruz

et al. 2019

Int Trans Electr Energ Syst

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Summary Power demand control is required at steelmaking plants and other energy intensive industrial plants where the electrical bills include high demand charges and are subject to demand limit contracts. This paper introduces a novel and simplified algorithm for the implementation of a power demand controller. The presented algorithm does not require a model of the electrical load since it is based on a geometrical approach for the estimation of the disconnection time of the controllable load and only requires the nominal power values and the load factors of both the total (full) load and the noncontrollable (base) load as parameters. The power demand control method presented is verified with a computational simulation, and precise control of the demand limit is achieved under random variations of the base and full loads. The proposed control algorithm is simpler than commercial methods and achieves a competitive performance. Simulation results show a better performance by calculating the disconnection times based on load parameters specified as mean values between the average and nominal powers of the full and base loads. Some considerations to tune‐up the load factor parameters are also discussed. The presented control method has been successfully implemented on industrial controllers in two steelmaking facilities in Mexico, having an electric arc furnace as controllable load in both cases. This novel demand control is adequate for industrial plants with electrical loads that can be disconnected without affecting the quality of the product and with minor impact on productivity.

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Section: Real-time Simulations and Implementationmentioning

confidence: 99%

Section: Real-time Simulations and Implementationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Power demand control algorithm for single controllable load with parametric and variable load factors

Martell

Sánchez‐Chávez

Peña‐Cruz

et al. 2019

Int Trans Electr Energ Syst

View full text Add to dashboard Cite

show abstract

“…1 Unlike batteries that are energysaving devices, fuel cells can work continuously until their fuel is supplied. [2][3][4][5] High efficiency and environmental benefits are characteristics that have made fuel cells attractive and powerful converters. Polymer membrane fuel cells (PEMFCs) are kinds of useful fuel cells that use a polymer membrane as an electrolyte.…”

Section: Introductionmentioning

confidence: 99%

Application of the meta‐heuristics for optimizing exergy of a HT‐PEMFC

Han

Khodaei

2020

Int J Energy Res

Self Cite

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Summary The aim of this study is to analyze the exergy efficiency of a high‐temperature proton exchange membrane fuel cell. To do this purpose, meta‐heuristic technique has been used. First, the model of a membrane fuel cell is simulated and the polarization diagram shows a potent agreement with empirical data. Then, a new improved version of collective animal behavior algorithm is utilized for evaluating and optimizing the thermodynamic irreversibility, exergy efficiency, and work of the fuel cell. The algorithm uses opposition‐based learning and Lévy flight for improving the algorithm's premature convergence shortcoming. The result of this study shows that by comparison with standard collective animal behavior algorithm, genetic algorithm, and empirical results, the proposed algorithm has better achievements for both terms of optimal value finding and convergence strength.

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A method for virtual machine migration in cloud computing using a collective behavior‐based metaheuristics algorithm

Sha

Ebadi

Mavaluru

et al. 2019

Concurrency and Computation

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Summary Due to the growth of applications and the integration of new customers into the world of computing systems, computing needs to be changed and to become more powerful and flexible than before. Meanwhile, cloud computing is presented as a model beyond a system that is currently capable of answering most request needs. Flexible infrastructure for cloud computing and virtualization technology provide new features to support business activities. Clouds are a very important topic that used secure management tools for storage, security and securing data centers in a flexible manner. One of the important matters in cloud technologies is virtual machine migration (VMM). There are different ways to implement the VMM, but because of the limitation of resources' energy, energy management is also very important and challenging. Due to the NP‐hard nature of this problem, this paper presents an energy‐aware VMM engine for cloud computing using the discrete bacterial foraging algorithm as a new collective behavior‐based metaheuristics algorithm. The CloudSim simulator is employed to investigate the efficiency of this method. The obtained results have shown that the proposed method improves the energy consumption and the migration count.

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RETRACTED: Optimal performance of fuel cell-CHP-battery based micro-grid under real-time energy management: An epsilon constraint method and fuzzy satisfying approach

Cited by 61 publications

References 63 publications

Power demand control algorithm for single controllable load with parametric and variable load factors

Power demand control algorithm for single controllable load with parametric and variable load factors

Application of the meta‐heuristics for optimizing exergy of a HT‐PEMFC

A method for virtual machine migration in cloud computing using a collective behavior‐based metaheuristics algorithm

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