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EISSN : 1996-1073
Current Publisher: MDPI (10.3390)
Total articles ≅ 19,152
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SangMu Bae, Yujin Nam, Joon-Ho Choi
Published: 21 October 2020
by MDPI
Energies, Volume 13; doi:10.3390/en13205524

Abstract:
The zero-energy building (ZEB) concept has a high potential for securing energy savings in the building sector. To achieve ZEB, various active systems, including renewable systems such as photovoltaic, solar heating, and geothermal systems, have been developed. However, the existing systems are costly or not optimized. To overcome these issues, the authors previously developed an integrated tri-generation system. In this research, the previously developed system was comprehensively analyzed considering the indoor thermal comfort and energy efficiency to develop a design and operation method for the integrated system. Two different heating systems (convective heating and radiant floor heating) were employed in the tri-generation system, and their system performance, predicted mean vote (PMV), and predicted percentage of dissatisfied (PPD) were compared using simulations. The results showed that the heating coefficient of power of the radiant floor heating system was 18.8% higher than that of the convective heating system. Moreover, the radiant floor heating system (Case 4) met the PMV and PPD standards during all the heating periods. Overall, radiant floor heating was found to be more efficient than convective heating. The results confirm that radiant floor heating is more suitable than convective heating considering the indoor thermal comfort of occupants.
Pawel Zukowski, Przemyslaw Rogalski, Tomasz N. Koltunowicz, Konrad Kierczynski, Jan Subocz, Marek Zenker
Published: 21 October 2020
by MDPI
Energies, Volume 13; doi:10.3390/en13205511

Abstract:
This study investigates the frequency–temperature relations between the phase angle φ and admittance Y for composites of cellulose, synthetic ester, and water nanoparticles. We determined the activation energy value for the relaxation time of a phase shift angle ΔWφ ≈ (0.783 ± 0.0744) eV, which was related to the shift of φ(f) waveforms in higher frequency area with increasing temperature. We found that the position of admittance frequency waveforms in double logarithmic coordinates was simultaneously influenced by the temperature dependence of admittance and its relaxation time. Activation energy values for the relaxation time of admittance ΔWτ ≈ (0.796 ± 0.0139) eV and the activation energy value of admittance ∆WY ≈ (0.800 ± 0.0162) eV were determined. It was found that all three activation energy values were identical and their average was ΔW ≈ (0.793 ± 0.0453) eV. Impregnation with synthetic ester resulted in a decrease of activation energy by 0.26 eV compared to the impregnation with insulating oil. This was related to higher dielectric permittivity of the synthetic ester.
Shah Rukh Abbas, Syed Ali Abbas Kazmi, Muhammad Naqvi, Adeel Javed, Salman Raza Naqvi, Kafait Ullah, Tauseef-Ur-Rehman Khan, Dong Ryeol Shin
Published: 21 October 2020
by MDPI
Energies, Volume 13; doi:10.3390/en13205513

Abstract:
The integration of commercial onshore large-scale wind farms into a national grid comes with several technical issues that predominately ensure power quality in accordance with respective grid codes. The resulting impacts are complemented with the absorption of larger amounts of reactive power by wind generators. In addition, seasonal variations and inter-farm wake effects further deteriorate the overall system performance and restrict the optimal use of available wind resources. This paper presented an assessment framework to address the power quality issues that have arisen after integrating large-scale wind farms into weak transmission grids, especially considering inter-farm wake effect, seasonal variations, reactive power depletion, and compensation with a variety of voltage-ampere reactive (Var) devices. Herein, we also proposed a recovery of significant active power deficits caused by the wake effect via increasing hub height of wind turbines. For large-scale wind energy penetration, a real case study was considered for three wind farms with a cumulative capacity of 154.4 MW integrated at a Nooriabad Grid in Pakistan to analyze their overall impacts. An actual test system was modeled in MATLAB Simulink for a composite analysis. Simulations were performed for various scenarios to consider wind intermittency, seasonal variations across four seasons, and wake effect. The capacitor banks and various flexible alternating current transmission systems (FACTS) devices were employed for a comparative analysis with and without considering the inter-farm wake effect. The power system parameters along with active and reactive power deficits were considered for comprehensive analysis. Unified power flow controller (UPFC) was found to be the best compensation device through comparative analysis, as it maintained voltage at nearly 1.002 pu, suppressed frequency transient in a range of 49.88–50.17 Hz, and avoided any resonance while maintaining power factors in an allowable range. Moreover, it also enhanced the power handling capability of the power system. The 20 m increase in hub height assisted the recovery of the active power deficit to 48%, which thus minimized the influence of the wake effect.
Leonel J.R. Nunes, Jorge T. Pereira Da Costa, Radu Godina, João C.O. Matias, João P.S. Catalão
Published: 21 October 2020
by MDPI
Energies, Volume 13; doi:10.3390/en13205512

Abstract:
The biomass industry is growing due to the current search for greener and more sustainable alternatives to fossil energy sources. However, this industry, due to its singularity, presents several challenges and disadvantages related to the transportation of raw materials, with the large volumes that are usually involved. This project aimed to address this internal logistics situation in torrefied biomass pellets production with two different biomass storage parks, located in Portugal. The main park receives raw material coming directly from the source and stores it in large amounts as a backup and strategic storage park. The second park, with smaller dimensions, precedes the production unit and must be stocked daily. Therefore, a fleet of transport units with self-unloading cranes is required to help to unload the biomass at the main park and transport the raw material from this park to the one preceding the production unit. Thus, the main goal was to determine the dimensions of the fleet used in internal transportation operations to minimize the idle time of the transport units using a methodology already in use in the mining and quarrying industry. This methodology was analyzed and adapted to the situation presented here. The implementation of this study allows the elimination of unnecessary costs in an industry where the profit margins are low.
Chun-Yao Lee, Kuan-Yu Huang, Yi-Xing Shen, Yao-Chen Lee
Published: 21 October 2020
by MDPI
Energies, Volume 13; doi:10.3390/en13205520

Abstract:
In this paper, we propose using particle swarm optimization (PSO) which can improve weighted k-nearest neighbors (PWKNN) to diagnose the failure of a wind power system. PWKNN adjusts weight to correctly reflect the importance of features and uses the distance judgment strategy to figure out the identical probability of multi-label classification. The PSO optimizes the weight and parameter k of PWKNN. This testing is based on four classified conditions of the 300 W wind generator which include healthy, loss of lubrication in the gearbox, angular misaligned rotor, and bearing fault. Current signals are used to measure the conditions. This testing tends to establish a feature database that makes up or trains classifiers through feature extraction. Not lowering the classification accuracy, the correlation coefficient of feature selection is applied to eliminate irrelevant features and to diminish the runtime of classifiers. A comparison with other traditional classifiers, i.e., backpropagation neural network (BPNN), k-nearest neighbor (k-NN), and radial basis function network (RBFN) shows that PWKNN has a higher classification accuracy. The feature selection can diminish the average features from 16 to 2.8 and can reduce the runtime by 61%. This testing can classify these four conditions accurately without being affected by noise and it can reach an accuracy of 83% in the condition of signal-to-noise ratio (SNR) is 20dB. The results show that the PWKNN approach is capable of diagnosing the failure of a wind power system.
Marek Hajto, Anna Przelaskowska, Grzegorz Machowski, Katarzyna Drabik, Gabriel Ząbek
Published: 21 October 2020
by MDPI
Energies, Volume 13; doi:10.3390/en13205515

Abstract:
This paper presents a broad overview of laboratory methods for measuring thermal properties and petrophysical parameters of carbonate rocks, and analytical methods for interpreting the obtained data. The investigation was conducted on carbonate rock samples from the Kraków region of Poland in the context of shallow geothermal potential assessment. The measurement techniques used included standard macroscopic examinations; petrophysical investigations (porosity, density); analysis of mineral composition thermal conductivity (TC) and specific heat measurements; and advanced investigations with the use of computed tomography (CT). Various mathematical models, such as layer model, geometric mean, and spherical and non-spherical inclusion models, were applied to calculate thermal conductivity based on mineralogy and porosity. The aim of this paper was to indicate the optimal set of laboratory measurements of carbonate rock samples ensuring sufficient characterization of petrophysical and thermal rock properties. This concerns both the parameters directly characterizing the geothermal potential (thermal conductivity) and other petrophysical parameters, e.g., porosity and mineral composition. Determining the quantitative relationship between these parameters can be of key importance in the case of a shortage of archival thermal conductivity data, which, unlike other petrophysical measurements, are not commonly collected. The results clearly show that the best correlations between calculated and measured TC values exist for the subgroup of samples of porosity higher than 4%. TC evaluation based on porosity and mineral composition correlation models gives satisfactory results compared with direct TC measurements. The methods and results can be used to update the existing 3D parametric models and geothermal potential maps, and for the preliminary assessment of geothermal potential in the surrounding area.
Rodrigo De A. Teixeira, Werbet L. A. Silva, Guilherme A. P. De C. A. Pessoa, Joao T. Carvalho Neto, Elmer R. L. Villarreal, Andrés O. Salazar, Alberto S. Lock
Published: 21 October 2020
by MDPI
Energies, Volume 13; doi:10.3390/en13205523

Abstract:
This paper analyzes a Digital Signal Processor (DSP) based One Cycle Control (OCC) strategy for a Power Factor Corrector (PFC) rectifier with Common-mode Voltage (CMV) immunity. It is proposed a strategy that utilizes an emulated-resistance-controller in closed-loop configuration to set the dc-link voltage to achieve unity power factor (UPF). It is shown that if the PFC can achieve UPF condition and if the phase voltage is only affected by CMV, then phase current is free from CMV, as well as a lead-lag compensator (LLC) to average phase current.
Dianchen Lu, Muhammad Idrees Afridi, Usman Allauddin, Umer Farooq, Muhammad Qasim
Published: 21 October 2020
by MDPI
Energies, Volume 13; doi:10.3390/en13205506

Abstract:
The present study explores the entropy generation, flow, and heat transfer characteristics of a dissipative nanofluid in the presence of transpiration effects at the boundary. The non-isothermal boundary conditions are taken into consideration to guarantee self-similar solutions. The electrically conducting nanofluid flow is influenced by a magnetic field of constant strength. The ultrafine particles (nanoparticles of Fe3O4/CuO) are dispersed in the technological fluid water (H2O). Both the base fluid and the nanofluid have the same bulk velocity and are assumed to be in thermal equilibrium. Tiwari and Dass’s idea is used for the mathematical modeling of the problem. Furthermore, the ultrafine particles are supposed to be spherical, and Maxwell Garnett’s model is used for the effective thermal conductivity of the nanofluid. Closed-form solutions are derived for boundary layer momentum and energy equations. These solutions are then utilized to access the entropy generation and the irreversibility parameter. The relative importance of different sources of entropy generation in the boundary layer is discussed through various graphs. The effects of space free physical parameters such as mass suction parameter (S), viscous dissipation parameter (Ec), magnetic heating parameter (M), and solid volume fraction (ϕ) of the ultrafine particles on the velocity, Bejan number, temperature, and entropy generation are elaborated through various graphs. It is found that the parabolic wall temperature facilitates similarity transformations so that self-similar equations can be achieved in the presence of viscous dissipation. It is observed that the entropy generation number is an increasing function of the Eckert number and solid volume fraction. The entropy production rate in the Fe3O4−H2O nanofluid is higher than that in the CuO−H2O nanofluid under the same circumstances.
Foster Lubbe, Jacques Maritz, Thomas Harms
Published: 21 October 2020
by MDPI
Energies, Volume 13; doi:10.3390/en13205509

Abstract:
The proliferation of solar power systems could cause instability within existing power grids due to the variable nature of solar power. A well-defined statistical model is important for managing the supply-and-demand dynamics of a power system that contains a significant variable renewable energy component. It is furthermore important to consider the inherent uncertainty in the data when modeling such a complex power system. Gaussian process regression has the potential to address both of these concerns: the probabilistic modeling of solar radiation data could assist in managing the variability of solar power, as well as provide a mechanism to deal with uncertainty. In this paper, solar radiation data was obtained from the Southern African Universities Radiometric Network and used to train a Gaussian process regression model which was developed especially for this purpose. Attention was given to constructing an appropriate Gaussian process kernel. It was found that a carefully constructed kernel allowed for the successful interpolation of global horizontal irradiance data, with a root-mean-squared error of 82.2W/m2. Gaps in the data, due to possible meter failure, were also bridged by the Gaussian process with a root-mean-squared error of 94.1 W/m2 and accompanying confidence intervals. A root-mean-squared error of 151.1 W/m2 was found when forecasting the global horizontal irradiance with a forecasting horizon of five days. These results, achieved in modeling solar radiation data using Gaussian process regression, could open new avenues in the development of probabilistic renewable energy management systems. Such systems could aid smart grid operators and support energy trading platforms, by allowing for better-informed decisions that incorporate the inherent uncertainty of stochastic power systems.
M. Rezwan Khan, Intekhab Alam
Published: 21 October 2020
by MDPI
Energies, Volume 13; doi:10.3390/en13205507

Abstract:
The cost of solar PV has been reduced to a level such that the levelized cost of solar electricity is either cheaper or competitive relative to the grid electricity. So, a low-cost integration of solar PV with grid can be a cost-effective solution for clean cooking. The usual technique of using grid-tied inverters contribute ~20% towards the energy cost. The proposed system incorporates a control circuit that connects grid electricity to the solar PV via a DC link and provides a DC output eliminating the requirement of grid-tied inverters. Most of the cooking utensils either have a resistive heating element or an electronic control circuit that is insensitive to input AC or DC and no modification is needed for the cooking utensils while using with DC voltage. In the proposed system, preference for power delivery is always given to the solar PV and the grid effectively operates as the backup for the system when solar PV output fluctuates due to varying weather and climatic conditions. As the absence of a grid-tied inverter in the system restricts the excess solar energy to be transferred to the grid, some kind of energy storage device is essential to run the system efficiently. A novel idea of storing solar PV energy in the form of hot water has been presented in this paper, with a cost-effective clean cooking concept. A simple and low-cost heat preservation technique has been suggested that requires a minimal change in habit for the users. Experimental results with multiple cooking utensils and foods have been presented and energy cost for cooking has been found to be as low as 4.75 USD/month, which is significantly lower (32%) than that of the grid-connected regular cooking system.
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