Negative Energy Consumption of Thermostats at Ambient Temperature: Electricity Generation with Zero Energy Maintenance

2019 ◽  
Vol 11 (2) ◽  
Author(s):  
J. Wang ◽  
J. Shang ◽  
J.P. Huang
2021 ◽  
Vol 13 (13) ◽  
pp. 7385
Author(s):  
Ibrahim Reda ◽  
Raouf N. AbdelMessih ◽  
Mohamed Steit ◽  
Ehab M. Mina

This study seeks to evaluate thermal comfort in naturally ventilated classrooms to draw sustainable solutions that reduce the dramatic energy consumed in mechanically ventilated spaces. Passive ventilation scenarios are generated using alternations of openings on the windward and leeward sides to evaluate their effects on thermal comfort. Twenty-eight experiments were carried in Bahrain during winter inside an exposed classroom, the experiments were grouped into five scenarios namely: “single-inlet single-outlet” SISO, “single-inlet double-outlet” SIDO, “double-inlet single-outlet” DISO, “double-inlet double-outlet” DIDO and “single-side ventilation” SSV. The findings indicate that single-side ventilation did not offer comfort except at high airspeed, while comfort is attained by using cross-ventilation at ambient temperature between 21.8–26.8 °C. The temperature difference between monitored locations and the inlet is inversely proportional to the number of air changes per hour. The DISO scenario accomplishes the lowest temperature difference. Using cross-ventilation instead of single-side ventilation reduces the temperature differences between 0.5–2.5 °C and increases airspeed up to three folds. According to the measured findings, the DISO cross-ventilation scenario is a valid sustainable solution adaptable to climatic variation locally and beyond with zero-energy consumption and zero emissions.


2021 ◽  
Vol 0 (0) ◽  
Author(s):  
Ammar Ali Abd ◽  
Samah Zaki Naji ◽  
Ching Thian Tye ◽  
Mohd Roslee Othman

Abstract Liquefied petroleum gas (LPG) plays a major role in worldwide energy consumption as a clean source of energy with low greenhouse gases emission. LPG transportation is exhibited through networks of pipelines, maritime, and tracks. LPG transmission using pipeline is environmentally friendly owing to the low greenhouse gases emission and low energy requirements. This work is a comprehensive evaluation of transportation petroleum gas in liquid state and compressible liquid state concerning LPG density, temperature and pressure, flow velocity, and pump energy consumption under the impact of different ambient temperatures. Inevitably, the pipeline surface exchanges heat between LPG and surrounding soil owing to the temperature difference and change in elevation. To prevent phase change, it is important to pay attention for several parameters such as ambient temperature, thermal conductivity of pipeline materials, soil type, and change in elevation for safe, reliable, and economic transportation. Transporting LPG at high pressure requests smaller pipeline size and consumes less energy for pumps due to its higher density. Also, LPG transportation under moderate or low pressure is more likely exposed to phase change, thus more thermal insulation and pressure boosting stations required to maintain the phase envelope. The models developed in this work aim to advance the existing knowledge and serve as a guide for efficient design by underling the importance of the mentioned parameters.


Author(s):  
Lohit Saini ◽  
Chandan Swaroop Meena ◽  
Binju P Raj ◽  
Nehul Agarwal ◽  
Ashok Kumar

2022 ◽  
Vol 0 (0) ◽  
Author(s):  
Qusay Hassan ◽  
Saadoon Abdul Hafedh ◽  
Ali Hasan ◽  
Marek Jaszczur

Abstract The study evaluates the visibility of solar photovoltaic power plant construction for electricity generation based on a 20 MW capacity. The assessment was performed for four main cities in Iraq by using hourly experimental weather data (solar irradiance, wind speed, and ambient temperature). The experimental data was measured for the period from 1st January to 31st December of the year 2019, where the simulation process was performed at a 1 h time step resolution at the same resolution as the experimental data. There are two positionings considered for solar photovoltaic modules: (i) annual optimum tilt angle and (ii) two-axis tracking system. The effect of the ambient temperature and wind on the overall system energy generated was taken into consideration. The study is targeted at evaluating the potential solar energy in Iraq and the viability of electricity generation using a 20 MW solar photovoltaic power plant. The results showed that the overall performance of the suggested power plant capacity is highly dependent on the solar irradiance intensity and the ambient temperature with wind speed. The current 20 MW solar photovoltaic power plant capacity shows the highest energy that can be generated in the mid-western region and the lowest in the northeast regions. The greatest influence of the ambient temperature on the energy genrated by power plants is observed in the southern regions.


Energies ◽  
2018 ◽  
Vol 11 (12) ◽  
pp. 3252 ◽  
Author(s):  
Xiaolong Xu ◽  
Guohui Feng ◽  
Dandan Chi ◽  
Ming Liu ◽  
Baoyue Dou

Optimizing key parameters with energy consumption as the control target can minimize the heating and cooling needs of buildings. In this paper we focus on the optimization of performance parameters design and the prediction of energy consumption for nearly Zero Energy Buildings (nZEB). The optimal combination of various performance parameters and the Energy Saving Ratio (ESR)are studied by using a large volume of simulation data. Artificial neural networks (ANNs) are applied for the prediction of annual electrical energy consumption in a nearly Zero Energy Building designs located in Shenyang (China). The data of the energy demand for our test is obtained by using building simulation techniques. The results demonstrate that the heating energy demand for our test nearly Zero Energy Building is 17.42 KW·h/(m2·a). The Energy Saving Ratio of window-to-wall ratios optimization is the most obvious, followed by thermal performance parameters of the window, and finally the insulation thickness. The maximum relative error of building energy consumption prediction is 6.46% when using the artificial neural network model to predict energy consumption. The establishment of this prediction method enables architects to easily and accurately obtain the energy consumption of buildings during the design phase.


Data in Brief ◽  
2018 ◽  
Vol 21 ◽  
pp. 2470-2474 ◽  
Author(s):  
Delia D'Agostino ◽  
Livio Mazzarella

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