scholarly journals Thermodynamic Design of Organic Rankine Cycle (ORC) Based on Petroleum Coke Combustion

2021 ◽  
Vol 5 (3) ◽  
pp. 37
Author(s):  
Alon Davidy
Keyword(s):  
Deep Learning ◽  
Petroleum Coke ◽  
Radiative Forcing ◽  
Time Series Data ◽  
Organic Rankine Cycle ◽  
Gaseous Mixture ◽  
Rankine Cycle ◽  
Series Data ◽  
Working Fluid ◽  
Coke Combustion

Thermodynamic analysis of Organic Rankine Cycle (ORC) was performed in this work. The Petroleum Coke burner provided the required heat flux for the Butane Boiler. The simulation of pet-coke combustion was carried out by using Fire Dynamics Simulator software (FDS) version 5.0. Validation of the FDS calculation results was carried out by comparing the temperature of the gaseous mixture and CO2 mole fractions to the literature. It was discovered that they are similar to those reported in the literature. An Artificial Intelligence (AI) time forecasting analysis was performed on this work. The AI algorithm was applied to the temperature and soot sensor readings. Two Python libraries were applied in order to forecast the time behaviour of the thermocouple readings: Statistical model—ARIMA (Auto-Regressive Integrated Moving Average) and KERAS—deep learning library. ARIMA is a class of model that captures a suite of different standard temporal structures in time series data. Keras is a python library applied for deep learning and runs on top of Tensor-Flow. It has been developed in order to perform deep learning models as fast and easily as possible for research and development. The model accuracy and model loss plot shows comparable performance (train and test). Butane has been employed as a working fluid in the ORC. Butane is considered one of the best pure fluids in terms of exergy efficiency. It has low specific radiative forcing (RF) compared to Ethane and Propane. Moreover, it has zero ozone depletion potential and low Global Warming Potential. It is considered flammable, highly stable and non-corrosive. The thermodynamic properties of Butane needed to evaluate the heat rate and the power were calculated by applying the ASIMPTOTE online thermodynamic calculator. It was shown that the calculated net power of the ORC cycle is similar to the net power reported in the literature (relative error of 4.8%). The proposed ORC energetic system obeys the first and second laws of thermodynamics. The thermal efficiency of the cycle is 20.4%.

Model, simulation and experiments for a Buoyancy Organic Rankine Cycle

2020 ◽  
Vol 92 (1) ◽  
pp. 10906
Author(s):  
Jeroen Schoenmaker ◽  
Pâmella Gonçalves Martins ◽  
Guilherme Corsi Miranda da Silva ◽  
Julio Carlos Teixeira
Keyword(s):  
Model Simulation ◽  
Organic Rankine Cycle ◽  
Thermodynamic Cycle ◽  
Rankine Cycle ◽  
Test Body ◽  
Working Fluid ◽  
Proof Of Concept ◽  
Energy Scenario ◽  
New Type ◽  
Fluid Reservoir

Organic Rankine Cycle (ORC) systems are increasingly gaining relevance in the renewable and sustainable energy scenario. Recently our research group published a manuscript identifying a new type of thermodynamic cycle entitled Buoyancy Organic Rankine Cycle (BORC) [J. Schoenmaker, J.F.Q. Rey, K.R. Pirota, Renew. Energy 36, 999 (2011)]. In this work we present two main contributions. First, we propose a refined thermodynamic model for BORC systems accounting for the specific heat of the working fluid. Considering the refined model, the efficiencies for Pentane and Dichloromethane at temperatures up to 100 °C were estimated to be 17.2%. Second, we show a proof of concept BORC system using a 3 m tall, 0.062 m diameter polycarbonate tube as a column-fluid reservoir. We used water as a column fluid. The thermal stability and uniformity throughout the tube has been carefully simulated and verified experimentally. After the thermal parameters of the water column have been fully characterized, we developed a test body to allow an adequate assessment of the BORC-system's efficiency. We obtained 0.84% efficiency for 43.8 °C working temperature. This corresponds to 35% of the Carnot efficiency calculated for the same temperature difference. Limitations of the model and the apparatus are put into perspective, pointing directions for further developments of BORC systems.

scholarly journals Load forecasting of refrigerated display cabinet based on CEEMD–IPSO–LSTM combined model

Open Physics ◽  
2021 ◽  
Vol 19 (1) ◽  
pp. 360-374
Author(s):  
Yuan Pei ◽  
Lei Zhenglin ◽  
Zeng Qinghui ◽  
Wu Yixiao ◽  
Lu Yanli ◽  
...  
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Time Series Data ◽  
Load Forecasting ◽  
Series Data ◽  
Forecasting Model ◽  
Combined Model ◽  
Forecasting Accuracy ◽  
Forecasting Method ◽  
Consumption Reduction

Abstract The load of the showcase is a nonlinear and unstable time series data, and the traditional forecasting method is not applicable. Deep learning algorithms are introduced to predict the load of the showcase. Based on the CEEMD–IPSO–LSTM combination algorithm, this paper builds a refrigerated display cabinet load forecasting model. Compared with the forecast results of other models, it finally proves that the CEEMD–IPSO–LSTM model has the highest load forecasting accuracy, and the model’s determination coefficient is 0.9105, which is obviously excellent. Compared with other models, the model constructed in this paper can predict the load of showcases, which can provide a reference for energy saving and consumption reduction of display cabinet.

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 Organic Rankine cycle for turboprop engine application

2021 ◽  
pp. 1-21
Author(s):  
G.E. Pateropoulos ◽  
T.G. Efstathiadis ◽  
A.I. Kalfas
Keyword(s):  
Waste Heat ◽  
Organic Rankine Cycle ◽  
Weight Ratio ◽  
Rankine Cycle ◽  
Aircraft Engine ◽  
Working Fluid ◽  
Engine Fuel ◽  
Exhaust Gases ◽  
Waste Heat Recovery System ◽  
Turboprop Engine

ABSTRACT The potential to recover waste heat from the exhaust gases of a turboprop engine and produce useful work through an Organic Rankine Cycle (ORC) is investigated. A thermodynamic analysis of the engine’s Brayton cycle is derived to determine the heat source available for exploitation. The aim is to use the aircraft engine fuel as the working fluid of the organic Rankine cycle in order to reduce the extra weight of the waste heat recovery system and keep the thrust-to-weight ratio as high as possible. A surrogate fuel with thermophysical properties similar to aviation gas turbine fuel is used for the ORC simulation. The evaporator design as well as the weight minimisation and safety of the suggested application are the most crucial aspects determining the feasibility of the proposed concept. The results show that there is potential in the exhaust gases to produce up to 50kW of power, corresponding to a 10.1% improvement of the overall thermal efficiency of the engine.

scholarly journals Deep Learning for Anomaly Detection in Time-Series Data: Review, Analysis, and Guidelines

IEEE Access ◽  
2021 ◽  
Vol 9 ◽  
pp. 120043-120065
Author(s):  
Kukjin Choi ◽  
Jihun Yi ◽  
Changhwa Park ◽  
Sungroh Yoon
Keyword(s):  
Time Series ◽  
Deep Learning ◽  
Anomaly Detection ◽  
Time Series Data ◽  
Series Data ◽  
Review Analysis

Theoretical and experimental investigation of an organic Rankine cycle for a waste heat recovery system

2009 ◽  
Vol 223 (5) ◽  
pp. 523-533 ◽  
Author(s):  
W Gu ◽  
Y Weng ◽  
Y Wang ◽  
B Zheng
Keyword(s):  
Heat Source ◽  
Entropy Generation ◽  
Waste Heat ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Entropy Generation Rate ◽  
Working Fluid ◽  
Total Entropy ◽  
Waste Heat Recovery System ◽  
Cycle Efficiency

This article describes and evaluates an organic Rankine cycle (ORC) for a waste heat recovery system by both theoretical and experimental studies. Theoretical analysis of several working fluids shows that cycle efficiency is very sensitive to evaporating pressure, but insensitive to expander inlet temperature. Second law analysis was carried out using R600a as a working fluid and a flow of hot air as a heat source, which is not isothermal, along the evaporator. The result discloses that the evaporator's internal and external entropy generation is the main source of total entropy generation. The effect of the heat source temperature, evaporating pressure, and evaporator size on the entropy generation rate is also presented. The obtained useful power is directly linked to the total entropy generation rate according to the Gouy—Stodola theorem. The ORC testing system was established and operated using R600a as a working fluid and hot water as a heat source. The maximum cycle efficiency of the testing system is 5.2 per cent, and the testing result also proves that cycle efficiency is insensitive to heat source temperature, but sensitive to evaporating pressure. The entropy result also shows that internal and external entropy of the evaporator is the main source of total entropy generation.

Hybrid Solar-Geothermal Power Generation to Increase the Energy Production From a Binary Geothermal Plant

2011 ◽  
Author(s):  
Giovanni Manente ◽  
Randall Field ◽  
Ronald DiPippo ◽  
Jefferson W. Tester ◽  
Marco Paci ◽  
...  
Keyword(s):  
Power Plant ◽  
Power Output ◽  
Energy Production ◽  
Organic Rankine Cycle ◽  
Rankine Cycle ◽  
Working Fluid ◽  
Solar Thermal Energy ◽  
Geothermal Fluid ◽  
Industrial Grade ◽  
Design Values

This article examines how hybridization using solar thermal energy can increase the power output of a geothermal binary power plant that is operating on geothermal fluid conditions that fall short of design values in temperature and flow rate. The power cycle consists of a subcritical organic Rankine cycle using industrial grade isobutane as the working fluid. Each of the power plant units includes two expanders, a vaporizer, a preheater and air-cooled condensers. Aspen Plus was used to model the plant; the model was validated and adjusted by comparing its predictions to data collected during the first year of operation. The model was then run to determine the best strategy for distributing the available geothermal fluid between the two units to optimize the plant for the existing degraded geofluid conditions. Two solar-geothermal hybrid designs were evaluated to assess their ability to increase the power output and the annual energy production relative to the geothermal-only case.

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