On the Impact of Heat Pumps Electric Load on the Power Consumption of Lampedusa

2020 ◽  
Author(s):  
Marina Bonomolo ◽  
Mariano Giuseppe Ippolito ◽  
Giuliana Leone ◽  
Rossano Musca ◽  
Vincenzo Porgi ◽  
...  
Keyword(s):  
Power Consumption ◽  
Heat Pumps ◽  
Electric Load ◽  
The Impact

Estimating OLED Display Device Lifetime from pixel and screen brightness and its application

2019 ◽  
Vol 2019 (1) ◽  
pp. 331-338 ◽  
Author(s):  
Jérémie Gerhardt ◽  
Michael E. Miller ◽  
Hyunjin Yoo ◽  
Tara Akhavan
Keyword(s):  
Image Processing ◽  
Power Consumption ◽  
Model Parameters ◽  
Display Device ◽  
Image Processing Algorithm ◽  
Pixel Value ◽  
Device Lifetime ◽  
The Impact ◽  
Oled Display

In this paper we discuss a model to estimate the power consumption and lifetime (LT) of an OLED display based on its pixel value and the brightness setting of the screen (scbr). This model is used to illustrate the effect of OLED aging on display color characteristics. Model parameters are based on power consumption measurement of a given display for a number of pixel and scbr combinations. OLED LT is often given for the most stressful display operating situation, i.e. white image at maximum scbr, but having the ability to predict the LT for other configurations can be meaningful to estimate the impact and quality of new image processing algorithms. After explaining our model we present a use case to illustrate how we use it to evaluate the impact of an image processing algorithm for brightness adaptation.

scholarly journals Electrical Load Forecast by Means of LSTM: The Impact of Data Quality

Forecasting ◽  
2021 ◽  
Vol 3 (1) ◽  
pp. 91-101
Author(s):  
Alfredo Nespoli ◽  
Emanuele Ogliari ◽  
Silvia Pretto ◽  
Michele Gavazzeni ◽  
Sonia Vigani ◽  
...  
Keyword(s):  
Forecast Accuracy ◽  
Electric Load ◽  
Electrical Load ◽  
Autocorrelation Analysis ◽  
Load Forecast ◽  
Error Metrics ◽  
Input Dataset ◽  
Accurate Forecast ◽  
The Impact

Accurate forecast of aggregate end-users electric load profiles is becoming a hot topic in research for those main issues addressed in many fields such as the electricity services market. Hence, load forecast is an extremely important task which should be understood more in depth. In this research paper, the dependency of the day-ahead load forecast accuracy on the basis of the data typology employed in the training of LSTM has been inspected. A real case study of an Italian industrial load with samples recorded every 15 min for the year 2017 and 2018 was studied. The effect in the load forecast accuracy of different dataset cleaning approaches was investigated. In addition, the Generalised Extreme Studentized Deviate hypothesis testing was introduced to identify the outliers present in the dataset. The populations were constructed on the basis of an autocorrelation analysis that allowed for identifying a weekly correlation of the samples. The accuracy of the prediction obtained from different input dataset has been therefore investigated by calculating the most commonly used error metrics, showing the importance of data processing before employing them for load forecast.

Infrared Oscillators in Conventional Carbon Nanotube FET Technology

2015 ◽  
Vol 24 (04) ◽  
pp. 1550053
Author(s):  
Lobna I'msaddak ◽  
Dalenda Ben Issa ◽  
Abdennaceur Kachouri ◽  
Mounir Samet ◽  
Hekmet Samet
Keyword(s):  
Power Consumption ◽  
Response Time ◽  
Oscillation Frequency ◽  
Ring Oscillator ◽  
Propagation Time ◽  
Type C ◽  
P Type ◽  
Lc Tank ◽  
The Impact ◽  
Carbon Nanotube Fet

This paper presents the design of C-CNTFET oscillator's arrays for infrared 'IR' technology. These arrays are contained by both of the LC-tank and the voltage control 'coupled N- and P-type C-CNTFET LC-tank' oscillators. In this paper, the analysis of the impact of CNT diameter variations and the nonlinear capacitances (C GD and C GS ) were introduced, especially on propagation time, oscillation frequency and power consumption. The C-CNTFET inverter, ring oscillator, LC-tank and coupled N- and P-type C-CNTFET LC-tank oscillator structures were designed and their speeding and performances have been investigated with the proposed n-type of C-CNTFET model supplied by a 0.5 V power voltage. Simulation results show that the n- and p-types LC-tank oscillator circuit designs achieved an approximately equal oscillation frequency, response time and power consumption. Whereas the coupled N- and P-type C-CNTFET LC-tank oscillator has the lowest power consumption equal to 0.13 μW, the highest oscillation frequency (10.08 THz) and the fastest response time (1.81 ps).

The Impact of Oil and Sealing Air Flow, Chamber Pressure, Rotor Speed, and Axial Load on the Power Consumption in an Aeroengine Bearing Chamber

2005 ◽  
Vol 127 (1) ◽  
pp. 182-186 ◽  
Author(s):  
Michael Flouros
Keyword(s):  
Power Consumption ◽  
High Speed ◽  
Air Flow ◽  
Flow Chamber ◽  
Chamber Pressure ◽  
Power Losses ◽  
Rolling Element ◽  
Oil Flow ◽  
The Impact ◽  
Circle Diameter

Trends in aircraft engines have dictated high speed rolling element bearings up to 3 million DN or more with the consequence of having high amounts of heat rejection in the bearing chambers and high oil scavenge temperatures. A parametric study on the bearing power consumption has been performed with a 124 mm pitch circle diameter (PCD) ball bearing in a bearing chamber that has been adapted from the RB199 turbofan engine DN∼2×106. The operating parameters such as oil flow, oil temperature, sealing air flow, bearing chamber pressure, and shaft speed have been varied in order to assess the impact on the power consumption. This work is the first part of a survey aiming to reduce power losses in bearing chambers. In the first part, the parameters affecting the power losses are identified and evaluated.

Sustainable energy solutions for thermal load in buildings - Role of heat pumps, solar thermal, and hydrogen-based cogeneration systems

2021 ◽  
pp. 1-25
Author(s):  
Praveen Cheekatamarla ◽  
Vishaldeep Sharma ◽  
Bo Shen
Keyword(s):  
Energy Efficiency ◽  
Renewable Energy ◽  
Carbon Footprint ◽  
Energy Demand ◽  
Primary Energy ◽  
Heat Pumps ◽  
Total Carbon ◽  
Coefficient Of Performance ◽  
Renewable Energy Resources ◽  
The Impact

Abstract Economic and population growth is leading to increased energy demand across all sectors – buildings, transportation, and industry. Adoption of new energy consumers such as electric vehicles could further increase this growth. Sensible utilization of clean renewable energy resources is necessary to sustain this growth. Thermal needs in a building pose a significant challenge to the energy infrastructure. Supporting the current and future building thermal energy needs to offset the total electric demand while lowering the carbon footprint and enhancing the grid flexibility is presented in this study. Performance assessment of heat pumps, renewable energy, non-fossil fuel-based cogeneration systems, and their hybrid configurations was conducted. The impact of design configuration, coefficient of performance (COP), electric grid's primary energy efficiency on the key attributes of total carbon footprint, life cycle costs, operational energy savings, and site-specific primary energy efficiency are analyzed and discussed in detail.

scholarly journals Noise Reduction Power Stealing Detection Model Based on Self-Balanced Data Set

Energies ◽  
2020 ◽  
Vol 13 (7) ◽  
pp. 1763 ◽  
Author(s):  
Haiqing Liu ◽  
Zhiqiao Li ◽  
Yuancheng Li
Keyword(s):  
Power Consumption ◽  
Noise Reduction ◽  
Random Noise ◽  
Imbalanced Data ◽  
Gradient Boosting ◽  
Data Set ◽  
Detection Model ◽  
Adversarial Network ◽  
Consumption Data ◽  
The Impact

In recent years, various types of power theft incidents have occurred frequently, and the training of the power-stealing detection model is susceptible to the influence of the imbalanced data set and the data noise, which leads to errors in power-stealing detection. Therefore, a power-stealing detection model is proposed, which is based on Improved Conditional Generation Adversarial Network (CWGAN), Stacked Convolution Noise Reduction Autoencoder (SCDAE) and Lightweight Gradient Boosting Decision Machine (LightGBM). The model performs Generation- Adversarial operations on the original unbalanced power consumption data to achieve the balance of electricity data, and avoids the interference of the imbalanced data set on classifier training. In addition, the convolution method is used to stack the noise reduction auto-encoder to achieve dimension reduction of power consumption data, extract data features and reduce the impact of random noise. Finally, LightGBM is used for power theft detection. The experiments show that CWGAN can effectively balance the distribution of power consumption data. Comparing the detection indicators of the power-stealing model with various advanced power-stealing models on the same data set, it is finally proved that the proposed model is superior to other models in the detection of power stealing.

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