bluuebunny/crossref_metadata_2025_split huggingface dataset:
Yield and Empirical Relationship for a Stirling Cryocooler Liquid Air Energy Storage System
Authors: Girouard Christopher M. , Pollman Anthony G. , Hernandez Alejandro 
Published: October 2020

Abstract
Energy storage is a necessary design consideration to address intermittent generation on islanded, renewable microgrids. Using renewable energy in excess of immediate demand, Liquid Air Energy Storage (LAES) can produce and cryogenically store liquefied air for recovery and power generation later. While LAES has been demonstrated for large-scale energy storage, current designs use heat exchangers, expansion turbines, and co-located industrial processes. This study explores the use of simpler, low-pressure equipment, which may be suitable for smaller-scale applications. A prototype using a Stirling cryocooler for liquefaction, a vacuum dewar for storage, and a Stirling engine for energy recovery was built, tested, and analyzed. This paper focuses on quantifying the liquid air production for the prototype. A series of experiments was ran to gather data on liquid yield as a function of time for different power settings, dewar sizes and dewar shapes. An empirical relationship, useful for modeling, simulation, and design, was developed. Future work will include design, simulation, and construction of a new prototype for a specific capability. This work is part of a larger effort to determine the feasibility of different energy storage methods for small, mobile applications as well as fixed infrastructure energy storage systems.
Addressing the Energy Trilemma With LPG-Fuelled, Water-Free Combined Cycle Power Plants
Authors: Welch Michael 
Published: October 2020

Abstract
Many parts of the world are facing the triple challenge of providing secure energy to fuel economic growth at an affordable cost while minimizing the impact of energy production on the environment. Island nations especially struggle to address this trilemma, as renewable resources are usually limited and fossil fuels imported.
Traditionally such distributed power plants have relied on liquid fuels and multiple open cycle reciprocating engines to provide both redundancy and the ability to load follow across a broad load range to maximize efficiency. This approach has created high electricity prices and significant negative environmental impact, especially that attributed to CO2, NOx, and SOx.
With increasing natural gas production, the availability of Liquefied Petroleum Gas (LPG) has grown, and costs have fallen, allowing the potential to switch from fuel oils to LPG to reduce environmental impacts. Energy costs and environmental impact can be further reduced by using high efficiency Gas Turbine Combined Cycle plants with dry low emissions combustion technology. However, a further hurdle facing many locations is lack of the fresh water required for combined cycle operations.
LPG-fuelled Gas Turbine Combined Cycle using Organic Rankine Cycle (ORC) technology can address all aspects of this energy trilemma. This paper reviews the conceptual design of a proposed 100MW distributed power plant for an island location, based on multiple LPG-fuelled gas turbines to follow load demand, with an ORC bottoming cycle to maximize efficiency.
Stochastic Optimization for Long Term Capital Structures, Systems, and Components Refurbishment and Replacement
Authors: Wang Congjian , Mandelli Diego , St Germain Shawn , Smith Curtis , Morton David , Popova Ivilina , Hess Stephen 
Published: October 2020

Abstract
As commercial nuclear power plants (NPPs) pursue extended plant operations in the form of Second License Renewals (SLRs), opportunities exist for these plants to provide capital investments to ensure long-term, safe, and economic performance. Several utilities have already announced their intention to pursue extended operations for one or more of their NPPs via SLR2. The goal of this research is to develop a risk-informed approach to evaluate and prioritize plant capital investments made in preparation for, and during the period of, extended plant operations to support decisions in NPP operations. In order to prioritize project selection via a risk-informed approach we developed a single decision-making tool that integrates safety/reliability, cost, and stochastic optimization models to provide users with data analysis capabilities to more cost effectively manage plant assets. Both stochastic analysis methods — such as Monte Carlo-based sampling strategies — and multi-stage stochastic optimization strategies are employed to provide priority lists to decision-makers in support of risk-informed decisions. We applied the proposed method to a trial application of projected replacement/refurbishment expenditures for plant capital assets (i.e., structures, systems, and components [SSCs]). The objective is to optimize the SSC replacement/refurbishment schedule in terms of economic constraints, data uncertainties, and SSC reliability data, as well to generate a priority list for maximizing returns on investment.
Study on Basic Coal Consumption Characteristics in Dynamic Process of 660MW Ultra-Supercritical Coal-Fired Unit
Authors: Yin Junjie , Liu Ming , Yan Junjie , Zhao Yongliang 
Published: October 2020

Abstract
With the spreading of intermittent renewable power, coal-fired power units should cycle frequently to balance the load between power supply side and demand side. Coal consumption of coal-fired units operating in dynamic processes is influenced by many factors, including thermal system, control system, heat storage variation, etc. Therefore, it is very difficult to evaluate the energy efficiency of coal-fired units operating in dynamic processes. It is important to ascertain the basic coal consumption rate in dynamic processes, which is the basis to evaluate the operation performance of coal-fired units.
In this study, an off-design calculation model of 660MW ultra-supercritical coal-fired unit is developed and validated with design parameters. The developed model can be used to predict the coal consumption rates under steady-state off-design conditions. The basic coal consumption means the coal consumption of coal-fired units with operating parameters the same as target values. To calculate the basic coal consumption rate, a load cycling process is differentiated into lots of short time periods and every period is regarded as a steady-state condition with constant load, therefore the coal consumption rates in every period are equal to that of the corresponding steady-state condition. The calculation formula of basic coal consumption rates in is derived for load cycling processes.
On the basis of the off-design calculation model and assumption of idealized condition, average coal consumption rates during different processes with constant load cycling rates can be calculated and analyzed. Results show that if the initial and final loads are both settled, the basic coal consumption rate remains unchanged and is independent of load cycling rate. If the load cycling amplitude remains unchanged, the basic coal consumption rate increases as the initial load decrease. The study aims to provide benchmark values for the energy consumption analysis in actual dynamic processes, and further study on coal consumption characteristics in dynamic processes will be developed based on it.
Thermo-Economic Analysis on Waste Heat and Water Recovery Systems of Boiler Exhaust in Coal-Fired Power Plants
Authors: Yang Kaixuan , Liu Ming , Yan Junjie 
Published: October 2020

Abstract
Waste heat and water recovery from boiler exhaust fluegas is significant for reducing coal and water consumption of coal-fired power plants. In this study, waste heat and water recovery system No.1 (WHWR1) and No.2 (WHWR2) were proposed with a 330MW air-cooling coal-fired power plant as the reference power plant. In these systems, boiler exhaust fluegas is cooled to 95 °C in fluegas coolers before being fed to the electrostatic precipitator. Moreover, a fluegas condenser is installed after the desulfurizer to recover water from fluegas. The recovered waste heat is used to heat the condensation water of the regenerative system, boiler feeding air and the fluegas after fluegas condenser. Then, thermodynamic and economic analyses were carried out. Heat exchangers’ areas of WHWRs are affected by heat loads and heat transfer temperature differences. For the unit area cost of heat exchangers is different, the cost of WHWRs may be decreased by optimizing multiple thermodynamic parameters of WHWR. Therefore, the optimization models based on Genetic Algorithm were developed to obtain the optimal system parameters with best economic performance. Results show that the change in coal consumption rate (Δb) is ∼ 4.8 g kW−1 h−1 in WHWR2 and ∼ 2.9 g kW−1 h−1 in WHWR1. About 15.3 kg s−1 of water can be saved and recovered when the fluegas moisture content is reduced to 8.5%. The investment of WHWR2 is higher than WHWR1, while the static recovery period of WHWR2 is shorter than that of WHWR1 for the additional Δb of pre air pre-heater.
Thermo-Economic Optimization on the Waste Heat Recovery System of SCO2 Coal-Fired Power Plants
Authors: Sun Ruiqiang , Yang Kaixuang , Liu Ming , Yan Junjie 
Published: October 2020

Abstract
The temperature of SCO2 fed to the boiler in SCO2 coal-fired power plants is relatively high, ∼500 °C. It leads to high boiler exhaust temperature, which is ∼120 °C according to previous studies. Waste heat recovery from low temperature fluegas in SCO2 coal-fired power plants is a key issue to be addressed to enhance power plant efficiency and electrostatic precipitator performance. Therefore, systems of waste heat recovery from low-temperature fluegas were proposed in this study. To evaluate the economic performances of the proposed systems and obtain the best system configurations, economic and thermodynamic models were developed. Moreover, multi-parameter optimization model based on Genetic Algorithm was developed. The waste heat recovery system is proposed and optimized by considering coupling and matching of the air preheating process, heat regenerative process and fluegas cooling process. With a 1000MW SCO2 coal-fired power plant as the reference case, thermodynamic and economic analyses were carried out. Results show that when the low temperature economizer is integrated together with the main compressor intercooling and flue bypass ahead the air-preheater, the temperature of exhaust fluegas can be decreased to ∼95 °C and the power plant efficiency can be enhanced by 1.39%-pts compared with basic system. Through the economic model analysis, the system levelized cost of electricity is 0.04158 $ kW−1 h−1.
A High-Power Ironless Ultra-Light Direct-Drive Wind Generator Based on Circular Flux
Authors: Zarghami Mahyar , Vann Charles , Steensnaes Frank 
Published: October 2020

Abstract
This paper introduces a novel type of direct-drive electric generator, suitable for producing high-power at low rpm in wind applications. The proposed patented design eliminates the magnetic core based on the concept of circular flux and characteristics of Halbach Array. By using circular flux crossing through patented Folded Electromagnetic Coils (FECs) on the stator, an optimal design with maximum use of space will be gained. Furthermore, through special configuration of diametric and axial magnets on the rotor, a pattern of circular flux can be produced, which is magnified only on the side of the stator (where needed), based on characteristics of the Halbach array. By using such design, the need for using magnets on both sides of armature windings (devised in certain designs such as the Yokeless and Segmented Armature (YASA) topology), will be eliminated, resulting in further reduction of the magnetic materials in the machine design. In the paper, we show how the proposed design results in better no-load voltage per kg by a factor of 1.52 when compared to a YASA design of the same physical size. Furthermore, we show how our calculations are based on experimental results verified through tests on a prototype of the proposed design.
Thermodynamic Analysis on a Heat-Power Decoupling System Integrated With Absorption Heat Pump
Authors: Wang Liyuan , Liu Ming , Fu Yue , Liu Jiping , Yan Junjie 
Published: October 2020

Abstract
Because of the continuous expanding of the district heating, the heating load of combined heat and power (CHP) plants increases year by year. The minimum power load of CHP plant increases with the heating load due to the heat-power coupling mechanism. Therefore, heat-power decoupling is necessary to improve the operation flexibility for CHP units. Integrating the absorption heat pump (AHP) is an effective method to realize the heat-power decoupling. In this study, a 330MW CHP unit model and AHP model have been developed and validated. The performance of the heat-power decoupling and energy saving performance has been investigated by comparing the thermodynamic performance indicators. Results show that, the proposed system can increase the maximum heating load and decrease the power generation when the primary network return temperature is decreased. When the heating steam extraction is kept constant, with the increase of the primary network return water temperature, the heat generation efficiency and the standard coal consumption rate of heating increases, the coal consumption rate of power generation and the heating efficiency decreases. And the primary network return water temperature increases from 40 °C to 70 °C, the coal consumption rate of power generation decreases by 4.3 g/kWh, and the coal consumption rate of heating increases by 0.67 kg/GJ.
Integration of Hydro and Renewable Energy Resources in Energy Planning
Authors: Luciano De La Cruz Lucero Cynthia , Celis Cesar 
Published: October 2020

Abstract
Renewable energy is the energy obtained from resources inexhaustible in the long term. Furthermore, in some countries, non-conventional renewable energy includes solar, wind, biomass, geothermal and mini-hydropower. The definition of mini-hydropower plants varies depending on the country. As an example, in Peru and Canada, mini-hydropower plants have different installing capacities, below 20MW and 50MW, respectively. Accordingly, this work (i) discusses the Energy Balance and challenges that renewable energies have to face on their way to the energy transition, (ii) highlights the forecast models to generate renewable energy in short-term energy planning. The historical data about the renewable energy resources and the energy produced have been obtained by COES. The R studio software was used for statistical analysis of renewable resources and electricity generation. Also, a forecast model was developed using a neural network to forecast renewable energy generation. The results show a strong correlation between hydro resources and non-conventional renewable energy resources. Finally, the data obtained from the renewable generation forecast model were used as input to carry out a short-term dispatch model using GAMS software to determine the forecast of daily marginal cost in SEIN.
Advancements of a Piston Engine and Electrochemical Combined Hybrid System for Unmanned Aerial Systems
Authors: Welles Thomas S. , Ahn Jeongmin 
Published: October 2020

Abstract
This work investigates the integration of solid oxide fuel cells (SOFCs) and a small methanol/nitromethane fueled piston engine as a prospective hybrid powertrain for small unmanned aerial systems (UASs). The increased chemical energy density of a liquid fuel when compared to traditional batteries, along with ease of storage, accessibility, and refuel time make the use of a liquid fuel powered UAS preferable when compared to battery only power UAS’.
Currently small UAS’ of increasing interest as a research area, as they have a wide application to a variety of fields. UAS’ are currently being used for precision agricultural crop management and water resource visual inspection. UAS’ are a cost effective avenue to survey water resources and track water runoff that is contaminating water resources. UAS’ can be easily automated and fitted with sensors and cameras capable of providing actionable feedback to the user. The use of UAS’ for land management and survey is expected to continue to expand. However, nearly all UAS’ are powered by a typical lithium polymer battery pack, giving an average endurance of approximately twenty minutes. This is acceptable to most hobbyists and for short filming duration; however, it limits UAS’ to only being able to be operated in close proximity to the user. Current power plants for UAS’ are not suited for long duration missions, such as the survey of water resources. Therefore, the development of a hybrid power plant is crucial for UAS’ to be utilized to their full potential as a survey tool.
This work introduces a small internal combustion engine to act as a partial oxidation fuel reformer, producing high temperature exhaust and syngas. The exhaust of this engine is then analyzed as a fuel source for tubular SOFC’s. The SOFC is integrated into the exhaust of a 3.3 cm3 nitromethane fueled two-stroke engine, achieving a maximum power of 680 mW/cm2. A theoretical comparison of flight time indicates that the modular hybrid system could increase a typical small UAS’ flight time beyond 1 hour. The system is capable of achieving a significantly higher energy density than traditional lithium polymer batteries.
Optimized Intake Manifold Designs and Their Effects on the Operation and Emissions of a Gas-to-Liquid Diesel Engine
Authors: Abdellatif Y. M. , Saker A. T. , Elbashir A. M. , Ahmed S. F. 
Published: October 2020

Abstract
Two simultaneous strategies have been used in this work to reduce the diesel engine emissions. First, using novel manifold designs to generate strong turbulence and improve the fuel-air mixing inside the cylinder. The second strategy is the usage of alternative fuels, namely Gas-To-Liquid (GTL) fuel and its blends with diesel fuel. In this study, six new spiral-helical manifolds designs have been tested, which could be divided into two groups. The first group is m(2.6,30,1t), m(2.6,30,2t), m(2.6,330,3t) and m(2.6,30,4t) which contains manifolds that have the same inner diameter (2.6 cm), same outlet angle (30°), but different number of spiral turns (1t, 2t..etc). The second group is m(2.1,30,3t), m(2.6,30,3t) and m(2.9,30,3t) which contains the same parameters but different inner diameters. It should be mentioned that the outlet angle of all manifolds has been tested in previous investigations [18, 52] and 30° showed the best performance.
The results of the current study showed that the highest pressure and heat release achieved by manifold m(2.6,30,1t) for the blended diesel-GTL fuel. It was observed that the heat release rate decreases with the increase in number of turns. The lowest pressure raise rate was recorded for the combination of m(2.6,30,1t) and diesel fuel. Same combination also reduced the pressure raise rate (dP/dθ) by about 24% compared to the normal manifold. The bsfc for all fuels and m(2.6,30,1t) were almost the same as the normal manifold. For the emissions, NO emissions were reduced by about 25% compared to normal manifold when m(2.6,30,4t) and GTL are used. On the other hand, the normal manifold recorded the least NO emissions for the other fuels. The manifold m(2.6,30,1t) recorded slightly higher NO emissions compared to the normal manifold for all fuels. The total particulate matters (PM) were the lowest for m (2.6,30,1t) and normal manifold in case of diesel fuel. In general, It was found that the combination of m(2.6,30,1t) with diesel fuel gave the optimum performance among all manifolds, while using m (2.6,30,4t) with GTL fuel produced low emission levels.
Numerical Study on Renewable and Sustainable Fuels for HPDF Engines
Authors: Frankl Stephanie G. , Gelner Alexander D. , Gleis Stephan , Härtl Martin , Wachtmeister Georg 
Published: October 2020

Abstract
Renewable and sustainable fuels (based on electricity) will play a key role in future scenarios for power supply. Enabling storage and distribution of local and temporal fluctuations of renewable energies, different e-fuels with varying production processes and characteristics get interesting for different locations. For reconversion of the chemical energy, a fuel-flexible internal combustion engine with a High Pressure Dual Fuel (HPDF) combustion process is suitable for different e-fuels. As the combustion process is the main influence on emissions, combustion behavior of the studied fuels hydrogen, methane, methanol and ammonia, ignited by the pilot fuels Fischer-Tropsch diesel and polyoxymethylene dimethyl ethers (OME), is investigated in varying fuel pairings. In addition, a review of production efficiencies and important characteristics like toxicity and storage method is given. Afterwards, the application of the investigated fuels in HPDF-combustion is investigated. The investigations are conducted with a numerical 3D-CFD model of a large bore high speed single cylinder research engine. The differences in ignition and combustion when using diesel or OME as pilot fuel are shown and a comparison of the emissions for the used main fuels is given.
A Hybrid Wind Speed Prediction Approach Based on Ensemble Empirical Mode Decomposition and BO-LSTM Neural Networks for Digital Twin
Authors: Hu Weifei , He Yihan , Liu Zhenyu , Tan Jianrong , Yang Ming , Chen Jiancheng 
Published: October 2020

Abstract
Precise time series prediction serves as an important role in constructing a Digital Twin (DT). The various internal and external interferences result in highly non-linear and stochastic time series data sampled from real situations. Although artificial Neural Networks (ANNs) are often used to forecast time series for their strong self-learning and nonlinear fitting capabilities, it is a challenging and time-consuming task to obtain the optimal ANN architecture. This paper proposes a hybrid time series prediction model based on ensemble empirical mode decomposition (EEMD), long short-term memory (LSTM) neural networks, and Bayesian optimization (BO). To improve the predictability of stochastic and nonstationary time series, the EEMD method is implemented to decompose the original time series into several components, each of which is composed of single-frequency and stationary signal, and a residual signal. The decomposed signals are used to train the BO-LSTM neural networks, in which the hyper-parameters of the LSTM neural networks are fine-tuned by the BO algorithm. The following time series data are predicted by summating all the predictions of the decomposed signals based on the trained neural networks. To evaluate the performance of the proposed hybrid method (EEMD-BO-LSTM), this paper conducts a case study of wind speed time series prediction and has a comprehensive comparison between the proposed method and other approaches including the persistence model, ARIMA, LSTM neural networks, B0-LSTM neural networks, and EEMD-LSTM neural networks. Results show an improved prediction accuracy using the EEMD-BO-LSTM method by multiple accuracy metrics.