Energy, exergy, and economic analyses of an innovative energy storage system; liquid air energy storage (LAES) combined with high-temperature thermal energy storage (HTES)

Nabat, Mohammad Hossein; Zeynalian, Mirhadi; Razmi, Amir Reza; Arabkoohsar, Ahmad; Soltani, M.

doi:10.1016/j.enconman.2020.113486

Cited by 173 publications

(29 citation statements)

References 62 publications

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“…Source: https://www.nrcan.gc.ca/science-data/data-analysis/energy-dataanalysis/energy-facts/renewable-energy-facts/20069 system operation, and perform more accurate fault detection. Using current and past wind information, one may utilize different wind power prediction methods as a practical approach for turbine fault detection, power system simulation, load analysis, and wind farms management and maintenance Zhou et al, 2019;Wang et al, 2019;Nabat et al, 2020;Lydia et al, 2014).…”

Section: Wind Powermentioning

confidence: 99%

“…Using accurate power curve models will also contribute to easier, more reliable and faster forecasts of the wind generation. An accurate power curve model also is required to more realistically size the storage capacity for wind energy integration (Shokrzadeh et al, 2015;Nabat et al, 2020). These models also can aid in the early identification of faults, such as blade faults and yaw and pitch system faults (Park et al, 2014).…”

Section: Introductionmentioning

confidence: 99%

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A Multilevel Modeling Approach Towards Wind Farm Aggregated Power Curve

Mehrjoo

Jozani

Pawlak

et al. 2021

IEEE Trans. Sustain. Energy

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Wind turbine power curve modeling plays an important role in wind energy management. Accurate estimation of power curves can help reducing power systems maintenance costs. In this thesis, we use machine learning techniques such as clustering, spline regression as well as statistical learning approaches such as multilevel modeling and isotonic regression to reduce bias and/or variance of fitted power curves to improve their performance. First, we focus on reducing the effect of outliers in the wind speed-power data. To this end, we propose to enforce the inherent property of manufacturer power curve on fitted power curves to reduce outliers' impact. Manufacturer power curve is a worthy source of information about turbines' performance which has been ignored in the literature. So, we propose two nonparametric techniques based on the tilting method and monotonic spline regression methodology to preserve monotonicity on fitted power curves according to manufacturer power curve. Another challenging issue in fitting empirical power curve which was investigated seldom in the literature is heteroscedasticity of the wind speed-power data set. Age of turbine, location, air density, wind direction, and measurement errors are some of the reasons which may cause heteroscedasticity or non-homogeneity among observed data. To overcome this problem, we propose a novel methodology to use a hybrid estimation approach based on weighted balanced loss functions that account for both estimation error and goodness of fit by shrinking estimates toward standardized target models. Our proposed approach is very general and can be used with any desirable weighting scheme as an effective tool to improve the performance of existing power curve modeling approaches. Finally, we investigate improving wind farm aggregated power curve modeling instead of fitting power curves for individual turbines to reduce the complexity of wind farm management analyses. To solve this issue, we propose a novel clustering feature set based on turbines' overall performance and utilize K-Means clustering to classify turbines into homogeneous groups accordingly. We then apply multilevel modeling methods, including random intercept and random slope models on turbine clusters, to consider the hidden correlation among different clusters. We show that the proposed method is a solution for handling the complexity-accuracy trade-off issue since its accuracy is significantly higher than the single aggregated method alongside an equal complexity.

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Section: Wind Powermentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A Multilevel Modeling Approach Towards Wind Farm Aggregated Power Curve

Mehrjoo

Jozani

Pawlak

et al. 2021

IEEE Trans. Sustain. Energy

View full text Add to dashboard Cite

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“…27 • The energies and exergies of kinetic and potential are neglected. 28 • The energetic and exergetic analyses are made on the lower heating value (LHV) of the fuel (natural gas). 29 • The temperature and pressure of the dead (environmental) state are 298.15 K and 101.325 kPa, respectively.…”

Section: Mathematical Modelingmentioning

confidence: 99%

Energy, exergy, exergo‐environmental, and exergetic sustainability analyses of a gas engine‐based CHP system

Hassan

Barua

Das

2021

Energy Science & Engineering

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The electricity demand is ever increasing, and the worldwide power generation is largely dependent on the rapidly dwindling fossil fuel resources. It is no different in Bangladesh as well where the prevailing dynamic in the energy sector projects to a certain lack of sustainability. This makes the performance evaluation to determine and improve the efficiency of energy conversion systems an unavoidable requisite. This study investigates the energetic and exergetic performance of a gas engine-based (4 MW) combined heat and power system situated at Rajshahi District in Bangladesh. Different thermodynamic performance parameters along with the exergo-environmental effect and the sustainability of the system are also assessed additionally. The overall system and individual components are analyzed based on the actual data measured on site at 48% engine load and a constant engine speed of 1500 rpm. The results reveal that the maximum energy loss and exergy destruction occur in the reciprocating engine with values of 656.54 kW and 1835.04 kW, respectively, followed by the heat recovery steam generator with 465.51 kW energy loss and 671.51 kW exergy destruction.The overall system has energy and exergy efficiency of 29.95% and 23.12%, respectively. The exergetic sustainability index of the system is found to be 1.30.

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“…With the increase in environmental considerations and demand for next-generation smart wearable electronics, innovative power supply technologies for portable electronics have exhibited considerable potential [ 1 , 2 , 3 ]. Consequently, numerous attempts have explored innovative energy supply systems [ 4 , 5 , 6 ], which utilize mechanical motions as novel power sources. One of the energy supply systems is triboelectric nanogenerators, which is triboelectricity that output DC currents [ 7 ].…”

Section: Introductionmentioning

confidence: 99%

Boosting Performance of Self-Polarized Fully Printed Piezoelectric Nanogenerators via Modulated Strength of Hydrogen Bonding Interactions

Lim

2021

Nanomaterials

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Self-polarized piezoelectric devices have attracted significant interest owing to their fabrication processes with low energy consumption. Herein, novel poling-free piezoelectric nanogenerators (PENGs) based on self-polarized polyvinylidene difluoride (PVDF) induced by the incorporation of different surface-modified barium titanate nanoparticles (BTO NPs) were prepared via a fully printing process. To reveal the effect of intermolecular interactions between PVDF and NP surface groups, BTO NPs were modified with hydrophilic polydopamine (PDA) and hydrophobic 1H,1H,2H,2H-perfluorodecyltriethoxysilane (PFDTES) to yield PDA-BTO and PFD-BTO, respectively. This study demonstrates that the stronger hydrogen bonding interactions existed in PFD-BTO/PVDF composite film comparative to the PDA-BTO/PVDF composite film induced the higher β-phase formation (90%), which was evidenced by the XRD, FTIR and DSC results, as well as led to a better dispersion of NPs and improved mechanical properties of composite films. Consequently, PFD-BTO/PVDF-based PENGs without electric poling exhibited a significantly improved output voltage of 5.9 V and power density of 102 μW cm−3, which was 1.8 and 2.9 times higher than that of PDA-BTO/PVDF-based PENGs, respectively. This study provides a promising approach for advancing the search for high-performance, self-polarized PENGs in next-generation electric and electronic industries.

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Energy, exergy, and economic analyses of an innovative energy storage system; liquid air energy storage (LAES) combined with high-temperature thermal energy storage (HTES)

Cited by 173 publications

References 62 publications

A Multilevel Modeling Approach Towards Wind Farm Aggregated Power Curve

A Multilevel Modeling Approach Towards Wind Farm Aggregated Power Curve

Energy, exergy, exergo‐environmental, and exergetic sustainability analyses of a gas engine‐based CHP system

Boosting Performance of Self-Polarized Fully Printed Piezoelectric Nanogenerators via Modulated Strength of Hydrogen Bonding Interactions

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