scholarly journals Experiments on Waste Heat Thermoelectric Generation for Passenger Vehicles

Micromachines ◽  
2022 ◽  
Vol 13 (1) ◽  
pp. 107
Author(s):  
Jianfei Chen ◽  
Wei Xie ◽  
Min Dai ◽  
Guorong Shen ◽  
Guoneng Li ◽  
...  
Keyword(s):  
Pressure Drop ◽  
Electric Power ◽  
Direct Current ◽  
Waste Heat ◽  
Collection Efficiency ◽  
Electric Heater ◽  
Thermoelectric Efficiency ◽  
Passenger Vehicles ◽  
Power Load ◽  
Overall Efficiency

In order to utilize waste heat from passenger vehicles by a thermoelectric generator (TEG), a lab-scale TEG with a sufficient low-pressure drop was designed and tested. The waste heat from a 2.0 L petrol engine was simulated by using an air-circulation channel with an adjustable electric heater and a speed control motor. The TEG consisted of an integrated molding designed aluminum-finned heat collector, twenty thermoelectric modules, and a set of water-cooled heat sinks. Experiments were conducted in terms of power load feature, pressure drop, heat collection efficiency, thermoelectric efficiency and overall efficiency. It was found that the hot-end temperature was much lower (46.9%) than the flue gas temperature because the trade-off between fin area and pressure drop had to be considered. The obtained maximum electric power was 36.4 W, and the corresponding pressure drop was 36 Pa. The corresponding heat collection efficiency was 46.5%, and the thermoelectric efficiency was 2.88%, which agreed well with the theoretical prediction of 3.38%. As a result, an overall efficiency of 1.21% was reached. The present work firstly demonstrated a waste-heat-recovering TEG prototype with a balanced overall efficiency of over 1%, and a pressure drop of less than 50 Pa. On the other hand, the maximum electric power was difficult to fully extract. The charging power to a battery with a maximum power point tracking direct current–direct current converter was experimentally verified to work at a much higher conversion efficiency (15.3% higher) than regular converters.

scholarly journals Forecasting for Ultra-Short-Term Electric Power Load Based on Integrated Artificial Neural Networks

Symmetry ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1063 ◽  
Author(s):  
Horng-Lin Shieh ◽  
Fu-Hsien Chen
Keyword(s):  
Energy Efficiency ◽  
Electric Power ◽  
Production Efficiency ◽  
Load Forecasting ◽  
Short Term ◽  
Inference System ◽  
Power Load ◽  
Power Load Forecasting ◽  
New Energy ◽  
Electric Power Load

Energy efficiency and renewable energy are the two main research topics for sustainable energy. In the past ten years, countries around the world have invested a lot of manpower into new energy research. However, in addition to new energy development, energy efficiency technologies need to be emphasized to promote production efficiency and reduce environmental pollution. In order to improve power production efficiency, an integrated solution regarding the issue of electric power load forecasting was proposed in this study. The solution proposed was to, in combination with persistence and search algorithms, establish a new integrated ultra-short-term electric power load forecasting method based on the adaptive-network-based fuzzy inference system (ANFIS) and back-propagation neural network (BPN), which can be applied in forecasting electric power load in Taiwan. The research methodology used in this paper was mainly to acquire and process the all-day electric power load data of Taiwan Power and execute preliminary forecasting values of the electric power load by applying ANFIS, BPN and persistence. The preliminary forecasting values of the electric power load obtained therefrom were called suboptimal solutions and finally the optimal weighted value was determined by applying a search algorithm through integrating the above three methods by weighting. In this paper, the optimal electric power load value was forecasted based on the weighted value obtained therefrom. It was proven through experimental results that the solution proposed in this paper can be used to accurately forecast electric power load, with a minimal error.

scholarly journals Component-Oriented Modeling of a Micro-Scale Organic Rankine Cycle System for Waste Heat Recovery Applications

2021 ◽  
Vol 11 (5) ◽  
pp. 1984
Author(s):  
Ramin Moradi ◽  
Emanuele Habib ◽  
Enrico Bocci ◽  
Luca Cioccolanti
Keyword(s):  
Electric Power ◽  
Heat Recovery ◽  
Waste Heat Recovery ◽  
Waste Heat ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Operating Conditions ◽  
Working Fluid ◽  
Pump Efficiency ◽  
Micro Scale

Organic Rankine cycle (ORC) systems are some of the most suitable technologies to produce electricity from low-temperature waste heat. In this study, a non-regenerative, micro-scale ORC system was tested in off-design conditions using R134a as the working fluid. The experimental data were then used to tune the semi-empirical models of the main components of the system. Eventually, the models were used in a component-oriented system solver to map the system electric performance at varying operating conditions. The analysis highlighted the non-negligible impact of the plunger pump on the system performance Indeed, the experimental results showed that the low pump efficiency in the investigated operating range can lead to negative net electric power in some working conditions. For most data points, the expander and the pump isentropic efficiencies are found in the approximate ranges of 35% to 55% and 17% to 34%, respectively. Furthermore, the maximum net electric power was about 200 W with a net electric efficiency of about 1.2%, thus also stressing the importance of a proper selection of the pump for waste heat recovery applications.

scholarly journals A New Approach of Dedusting for IGCC by a Two-Stage Moving Granular Bed Filter

Energies ◽  
2021 ◽  
Vol 14 (9) ◽  
pp. 2534
Author(s):  
Chiawei Chang ◽  
Yishun Chen ◽  
Litsung Sheng ◽  
Shusan Hsiau
Keyword(s):  
Pressure Drop ◽  
Mass Flow ◽  
Power Plants ◽  
Collection Efficiency ◽  
Size Distributions ◽  
Granular Bed ◽  
Two Stage ◽  
Mass Consumption ◽  
Particulate Size ◽  
Dust Particulate

We propose a dust removal technology in which a two-stage moving granular bed filter was employed using coarse and fine filtering granules. The pressure drop, collection efficiency, and dust particulate size distributions were investigated using various mass flow rates for coarse and fine granules at room temperature. In addition, the ratio of mass consumption was used to reveal the actual mass flow. The ratio of mass consumption influenced the pressure drop, collection efficiency, and dust particulate size distributions. Particulates larger than 1.775 μm were removed by the filter. Our results showed that a mass flow of 330 g/min for coarse granules and a mass flow of 1100 g/min for fine granules provided optimal collection efficiency and particulate size distribution. The proposed design can aid the development of high-temperature systems in power plants.

scholarly journals High thermoelectric performance enabled by convergence of nested conduction bands in Pb7Bi4Se13 with low thermal conductivity

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Lei Hu ◽  
Yue-Wen Fang ◽  
Feiyu Qin ◽  
Xun Cao ◽  
Xiaoxu Zhao ◽  
...  
Keyword(s):  
Thermal Conductivity ◽  
Waste Heat ◽  
Low Frequency ◽  
Thermoelectric Performance ◽  
Environmental Crisis ◽  
Quality Factors ◽  
Thermoelectric Efficiency ◽  
Low Thermal Conductivity ◽  
Conduction Bands ◽  
Thermoelectric Energy

AbstractThermoelectrics enable waste heat recovery, holding promises in relieving energy and environmental crisis. Lillianite materials have been long-term ignored due to low thermoelectric efficiency. Herein we report the discovery of superior thermoelectric performance in Pb7Bi4Se13 based lillianites, with a peak figure of merit, zT of 1.35 at 800 K and a high average zT of 0.92 (450–800 K). A unique quality factor is established to predict and evaluate thermoelectric performances. It considers both band nonparabolicity and band gaps, commonly negligible in conventional quality factors. Such appealing performance is attributed to the convergence of effectively nested conduction bands, providing a high number of valley degeneracy, and a low thermal conductivity, stemming from large lattice anharmonicity, low-frequency localized Einstein modes and the coexistence of high-density moiré fringes and nanoscale defects. This work rekindles the vision that Pb7Bi4Se13 based lillianites are promising candidates for highly efficient thermoelectric energy conversion.

Building electric power load assessment

2020 ◽  
pp. 307-332
Author(s):  
Paul Tymkow ◽  
Savvas Tassou ◽  
Maria Kolokotroni ◽  
Hussam Jouhara
Keyword(s):  
Electric Power ◽  
Power Load ◽  
Electric Power Load
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