Connectionist intelligent model estimates output power and torque of stirling engine

Ahmadi, Mohammad H.; Ahmadi, Mehdi; Sadatsakkak, Seyed Abbas; Feidt, Michel

doi:10.1016/j.rser.2015.04.185

Cited by 84 publications

(30 citation statements)

References 65 publications

(122 reference statements)

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“…The constraint (10) indicates the level of hydrogen stored in a tank. Charge and discharge rates of hydrogen are expressed by (11). In constraint (12), it is assumed that hydrogen at each time can only be charged or discharged.…”

Section: Fcmentioning

confidence: 99%

“…ANN modeling is employed in [10][11][12] which ensures the importance of this method in solving prediction problems. In [10], the power of the solar Stirling heat engine is estimated by employing a hybrid 8 genetic algorithm and particle swarm optimization-based neural network (HGAPSO-ANN).…”

mentioning

confidence: 99%

“…The authors have introduced a least square support vector machine (LSSVM) in [11] to predict the output power and shaft torque of Stirling engines. A parametric and GMDH-type neural network is employed in [12] for to study a 25-W fabricated PEM fuel cell.…”

mentioning

confidence: 99%

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Optimal economic dispatch of FC-CHP based heat and power micro-grids

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Abapour

Mohammadi‐Ivatloo

2017

Applied Thermal Engineering

220

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Section: Fcmentioning

confidence: 99%

mentioning

confidence: 99%

See 1 more Smart Citation

Optimal economic dispatch of FC-CHP based heat and power micro-grids

Nazari-Heris

Abapour

Mohammadi‐Ivatloo

2017

Applied Thermal Engineering

220

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“…In addition, the ants cannot see or hear, but they are able to transmit information using a sense of smell (known as stigmergy [32]). When an ant walks, it leaves behind itself a chemical substance called pheromone which evaporates over the time, and the more pheromones, the shorter the pass (perhaps the shortest) can be reached [33]. In other words, choosing a route to achieve the desired goal is not definitive.…”

Section: Ant Colony Optimization (Aco)mentioning

confidence: 99%

Higher order modeling of a free-piston Stirling engine: analysis and experiment

Zare

Shourangiz-Haghighi

2018

Int J Energy Environ Eng

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This paper focuses on higher order modeling and design of the free-piston Stirling engine (FPSE) based on Ant Colony Optimization (ACO). First, the governing thermodynamics and dynamical equations of the engine have been derived. Then, the design parameters of the engine are selected taking into account the finite heat transfer coefficient (resulting in a fifth-order model) and pressure drop (resulting in a sixth-order model) in the dynamical system and the corresponding differential equations are derived in detail. In the following, the mentioned methods and their performance in modeling the FPSE dynamics are investigated. The simulated results show that the effect of the pressure drop on the places of the closed-loop poles of the system is not significant, while the heat transfer coefficient has a considerable effect on the engine dynamics. Accordingly, a fifth-order model along with ACO algorithm is proposed to justify the FPSE behavior. To validate the presented modeling scheme, the prototype engine SUTECH-SR-1 was experimented. It is found that the values of parameters obtained from the proposed design method are close to those of the experiment. Besides, the presented higher order model predicts the engine behavior with an acceptable accuracy through which the validity of the design technique is affirmed. Initial pressure of working gas (Pa) P w Power generation (J/s) P Nonlinear pressure (Pa) R Ideal gas constant J kgVolume of expansion space m

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“…Energy use increase leads to several environmental problems . Several studies have focused on more environmentally benign energy systems to reduce greenhouse gas emissions …”

Section: Introductionmentioning

confidence: 99%

Thermodynamic and economic analysis of performance evaluation of all the thermal power plants: A review

Ahmadi

Nazari

Sadeghzadeh

et al. 2018

Energy Science & Engineering

Self Cite

101

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Surging in energy demand makes it necessary to improve performance of plant equipment and optimize operation of thermal power plants. Inasmuch as thermal power plants depend on fossil fuels, their optimization can be challenging due to the environmental issues which must be considered. Nowadays, the vast majority of power plants are designed based on energetic performance obtained from first law of thermodynamic. In some cases, energy balance of a system is not appropriate tool to diagnose malfunctions of the system. Exergy analysis is a powerful method for determining the losses existing in a system. Since exergy analysis can evaluate quality of the energy, it enables designers to make intricate thermodynamic systems operates more efficiently. These days, power plant optimization based on economic criteria is a critical problem because of their complex structure. In this study, a comprehensive analysis including energy, exergy, economic (3‐E) analyses, and their applications related to various thermal power plants are reviewed and scrutinized.

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Connectionist intelligent model estimates output power and torque of stirling engine

Cited by 84 publications

References 65 publications

Optimal economic dispatch of FC-CHP based heat and power micro-grids

Optimal economic dispatch of FC-CHP based heat and power micro-grids

Higher order modeling of a free-piston Stirling engine: analysis and experiment

Thermodynamic and economic analysis of performance evaluation of all the thermal power plants: A review

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