bluuebunny/crossref_metadata_2025_split huggingface dataset:
Design of Solar Powered Desalination System and Applications in a Luxurious Beach Resort
Authors: Khuri Siren , Ghaith Fadi A. 
Published: September 2024

Abstract
The efficacy of seawater desalination has a profound impact in terms of reducing the water demand-supply gap especially in dry and arid countries. In UAE, 90% of the country’s water supply relies solely on desalinated water where a high share of the desalination plant’s output is aimed towards water supply for residential buildings. The hospitality sector consumes 50% more than the global average. The purpose of this paper is to determine the technical and economic viability for the integration of a concentrated photovoltaic thermal (CPV/T) system with a hybrid reverse osmosis (RO) and multi effect desalination (MED) plant. The system was designed to meet the water demand of a luxurious beach resort located in Fujairah. The resort accommodates about 110 occupancies per day. The estimated water consumption is 51m3/hr. The proposed system was analyzed with the aid of numerical simulation and reverse engineering calculations. The capacity of the CPV/T module, which represents the electrical and thermal energy output supplied to the RO and MED plant was determined using TRNSYS software. The results showed an efficient solar system providing electricity of 3500 kWh/year and thermal energy of 14,100 kWh/year, that is required to meet the water consumption of the hotel. In addition, the proposed system proved to be economically feasible, achieving a payback period of 3.6 years under an average lifetime of 20 years.
Network Optimization for Sustainable Integration of Decentralized Biogas Production
Authors: Huber David , Birkelbach Felix , Hofmann René 
Published: September 2024

Abstract
Facing the urgent need to mitigate anthropogenic climate change, reducing emissions from the combustion of natural gas has become imperative. This is particularly challenging in the steel or cement industry, where high-temperature heat is essential. A promising solution is substituting natural gas with biogas or hydrogen. The typically highly decentralized gas production presents a transportation challenge due to the high costs of pipeline networks. In this paper, we propose a novel Mixed Integer Linear Programming (MILP) formulation to minimize the investment costs of pipeline networks. The pipeline network is modeled dendritically, allowing the efficient connection of multiple production plants and feed points. The topology of the network and the discrete pipe diameters are optimized simultaneously. A significant novelty is the use of a boolean matrix-vector multiplication in our formulation, allowing the usually non-linear formulation to be formulated linearly without loss of information. This enables hitherto unsolvable problems to be solved using highly efficient MILP solvers. The method is demonstrated using a case study with 37 biogas plants and seven feed points in Austria. The optimization results are the topology of the network and the pipe diameters at minimum specific costs of 3.24 €/(MW h). The results further highlight the economic efficiency of individual clusters, enabling decision-makers to implement step-by-step network expansion. The proposed method represents a novel contribution to optimizing the construction of gas transport infrastructure for biogas, offering potential applications in the broader context of renewable energy integration.
Improved Performance of Transcritical R744 Gas Coolers For Efficient Heat Pumps in the Northeastern US Winter Markets
Authors: Garraway David , Rob S. M. Abdur , Turbeville Geoffrey , Chussid Samuel , Ramamurthy Prathap , Gonzalez-Cruz Jorge E. 
Published: September 2024

Abstract
The main goal of our effort is to analyze, design, develop prototype and test electrical air source heat pumps (ASHPs) for hot water, space heating and cooling for multi-family buildings. Focusing on implementing the use of low Global Warming Potential refrigerants (e.g. TR-CO2) system to provide a cleaner and more sustainable alternative to society’s heating and cooling needs. This specific research is focused on the heating mode. A key challenge of TR-CO2 systems is the heat rejection which occurs in the gas cooler as a single gas phase. Identification of the pinch point is essential to avoid occurring within the gas cooler; leading to increases in efficiency.
We present here system performance of a TR-CO2 air source heat pump system using a customized python computer model coupled to commercial software for whole building analysis. This coupling enables variable heating load conditions for a mid-size multi-family building in New York City. The heat pump system is being modeled using proprietary code for the heat pump system coupled to EnergyPlus™ software with different gas cooler variations for constant and then variable loads. The TR-CO2 system is benchmarked against R410A with very optimistic results.
Nontechnical Barriers to Building Decarbonization in the U.S.
Authors: Osterwood Kristen , Monat Jamie 
Published: September 2024

Abstract
The need to reduce anthropogenic carbon emissions into the atmosphere is abundantly clear. It is also becoming widely accepted that transitioning to air source heat pumps (ASHP) is an essential part of the solution to decarbonizing buildings. The technological barriers to such a transition are covered in the literature, but the nontechnical barriers of adoption of ASHP also need to be considered. The technical focus of the decarbonization problem has blossomed into complex models as an increasing number of factors are incorporated, yielding more accurate models. Although some challenges to ASHPs are mentioned, research into the barriers and evaluation of methods to overcome those barriers are essential to successfully reduce anthropogenic carbon. Technical barriers pair with technical solutions — but nontechnical barriers are often slightly ambiguous and messy and the corresponding solutions require input from other disciplines.
This research identifies the nontechnical challenges of heat pump adoption and potential solutions. First, we present a review of existing models to demonstrate the growing consensus that ASHP are an essential part of decarbonization. Second, we present the nontechnical barriers as covered in the literature and compare those with the discovered nontechnical challenges through a case study and firsthand accounts. We find that the theoretical ideas of nontechnical barriers do not all align with the barriers in reality, and that these, especially the perception of the ineffectiveness of ASHP, needs to be addressed to enable the level of adoption necessary to meet climate goals.
Of the many challenges, from training to financial, the hurdle that is most pervasive, and potentially the most challenging to overcome is, perception of the ineffectiveness of heat pumps at cold temperatures. The perception of the inability of ASHP to function in cold weather is held by those from all levels of education — from the average consumer to those doing academic research on the topic. The persistence of this misunderstanding impacts incentive programs, decreases consumer confidence in the technology, installer recommendations, and increases the overall cost to transition, as a backup source of heat is recommended. Other misunderstandings and non-technical obstacles also must be identified and addressed. Only by clearly identifying the real-world challenges to adoption, potential solutions, and evaluating the effectiveness of strategies to support ASHP adoption, can the United States reach the level of ASHP penetration necessary to achieve climate goals.
Optical Analysis and Optimization of a New Receiver for Solar Parabolic Trough Collectors (DETECTIVE)
Authors: Ebadi Hossein , Alarcón-Padilla Diego-César , Contreras Keegan Juan José , Guedez Mata Rafael Eduardo , Trevisan Silvia , Valenzuela Gutiérrez Loreto , Zarza Moya Eduardo , Savoldi Laura 
Published: September 2024

Abstract
DETECTIVE (Development of a novEl Tube-bundlE-CaviTy lInear receiVEr for CSP applications) is a project that aims at enhancing the overall performance of the current solar parabolic trough collectors. The proposed design focuses on improving such performance by substituting the traditional single metal absorber tube with a tubular bundle whose outer contour largely matches the outer circumference of the replaced tube. To assess the optical performance of the proposed receiver, a Monte Carlo ray tracing technique was employed by utilizing the SolTrace software. The effects of the two design parameters, such as cavity opening angle and cavity radius, on the overall optical behavior have been explored and the optimum design is determined with the maximum optical performance. The ray tracing data proved that the cavity-like space formed within the multi-tube arrangement results in a multi-reflection process between bundle tubes and could result in a higher ray absorption compared to the conventional design, leading to lower optical losses. The obtained numerical results indicated that an aperture angle of 60° could provide the highest optical performance among the studied options. Considering the second parameter, the rise in the cavity radius is shown to increase the ray intersection inside the cavity, while the optical efficiency decreases. Finally, the most efficient design reaches an enhancement of 10% in optical efficiency if compared to the conventional PTC design.
From Waste to Resource: A Techno-Economic Evaluation of a CO2 Heat Pump and ORC Combined System With Photovoltaic Integration and Thermal Storage
Authors: Liaqat Kashif , Soleimani Shima , Leibowitz Sophie , Temming Jörg , Kösters Heiner , Schaefer Laura 
Published: September 2024

Abstract
The escalating global energy demand has resulted in a corresponding increase in greenhouse gas emissions. Multiple energy sources of various quality levels and forms must be developed to reduce emissions. One promising approach involves utilizing low-grade heat sources such as industrial process heat. This work investigates a novel combined heating and power approach through a comprehensive techno-economic analysis of a hybrid system that combines a CO2 heat pump (HP) and an organic Rankine cycle (ORC) for utilizing low-grade waste heat. The HP is powered by photovoltaics (PV), enabling sustainable heat extraction from low-grade sources, and is further integrated with thermal energy storage (TES) for demand management. The system primarily aims to supply district heating, but it seamlessly transitions to an ORC-based power generation mode in scenarios with reduced district heating demand. The integration of PV, HP, ORC, and TES allows for the efficient utilization of diverse low-grade heat sources, with adaptability to various operational strategies and applications contingent upon demand and supply dynamics. The study’s techno-economic and parametric analysis explores component and system-level performance, with Miami, FL, serving as a case study. Lastly, multiple operational scenarios and trade-offs are presented based on heating demand, power generation requirement, and resource availability.
Numerical and Experimental Investigation of the Wind Influence on Scaled-Up Open Volumetric Cavity Receivers
Authors: Drexelius Maximilian , Schwarzbözl Peter 
Published: September 2024

Abstract
Solar tower power plants have the potential to become a valuable asset in renewable electricity and heat generation. Among the available receiver technologies, the open volumetric air receiver (OVR) offers a high level of technical readiness, robustness and the potential for high temperature applications with effective storage capabilities. Tests at the Solar Tower in Jülich have demonstrated the availability and promising receiver efficiencies at the level of a 1.5 MWe demonstration plant. Ongoing research projects at DLR are investigating the potential of the OVR in a scaled-up tower concept. The proposed design uses a multi-receiver concept where the receivers are arranged in cavities to further increase the receiver efficiency. A scale-up to 50 MWe is realized with tower heights of around 200 m, which increases the relevance of ambient wind. Compared to closed-loop surface receivers, the OVR is particularly sensitive to fluctuations in ambient conditions due to the open process design. To investigate the wind influence on cavity OVRs, the surface pressure distribution was analyzed in wind tunnel experiments under a range of wind conditions with Reynolds numbers up to 13.17E06. In addition, numerical simulations based on RANS and DES approaches were performed to further investigate the interaction between the receiver flow and the ambient wind. The CFD model was successfully validated against the experimental results and surface pressure fluctuations could be quantified for the expected wind conditions. Furthermore, the wind influence on the air return ratio and receiver efficiency of the cavity design is numerically evaluated for different wind speeds. In addition to that, counter-measures regarding the return air distribution are numerically evaluated to increase the receiver efficiency.
Evaluating Reduced Order Models for Training Reinforcement Learning Agents for Building HVAC Control
Authors: Kerr Matthew , Howard Bianca 
Published: September 2024

Abstract
Reinforcement learning (RL) for controlling building heating, ventilation, and air conditioning (HVAC) systems has shown promise in delivering energy-efficient, energy-flexible and resilient buildings. However, training RL agents in real-time in buildings is generally considered time and cost prohibitive. RL agents can be trained offline in simulated environments, reducing the time to performance once online, but complex models for simulation can be difficult to generate. What level of complexity is required in an offline training model to produce acceptable online results is unknown. This work seeks to determine how simplified models can be used to train RL agents for building HVAC control. The work uses the EnergyPlus simulation environment paired with HVAC systems modeled in Modelica to act as the real-world analogue environment. Simplified reduced-order models of the building were developed using the lumped capacitance method. The results show that an RL agent trained using Deep Q Learning on a simplified building model can be transferable to a more complex building simulation environment with comparable performance. In virtually all cases, the RL agents were able to deliver improved performance over the baseline proportional controller. Online learning gave mixed results in terms of enhancing the policy transfer process. The implementation in this paper was more suitable for improving the performance of poor policy transfer rather than fine-tuning already well-performing policies.
Modeling of Small-Scale Hybrid Biogas Renewable Energy Facility
Authors: Salcido Ryan D. , Lockwood George W. , Rebullar Cedric I. , Anderson Kevin R. , Shafahi Maryam 
Published: September 2024

Abstract
In this study, a Khadi and Village Industries Commission (KVIC) biogas plant was designed to provide thermal energy input into an internal combustion engine. Additionally, a photovoltaic (PV) system was designed to supply energy for electric resistance heating in the biogas digester to maintain optimal temperatures for manure to decompose in. A MATHCAD based thermal model was built to predict the performance of the biogas plant. The methane gas weekly output by volume of 0.372 cubic meters from the KVIC digester was used to fuel an ACME AM-1500BG 1KW Biogas Generator. This resulted in 1.06 kWh energy output per week when storing biogas over the course of seven days and using the generator at the end of the seventh day. The total annual energy output of the KVIC plant was 55.2 kWh. Thermo-economic modeling of the PV system used carried out using National Renewable Energy Laboratory (NREL) System Advisor Model (SAM). The system nameplate capacity was calculated to be 6.30 kW with an annual AC energy output of 11,735 kWh, resulting in a Levelized Cost of Energy (LCOE) of 11.7¢/kWh and payback period of 9.6 years. The initial investment of the system is $19,261.
Techno-Economic Feasibility Analysis of Solar Industrial Process Heat Using Particle Thermal Energy Storage
Authors: Al-Ghussain Loiy , Johnson Taylor , Martinek Janna , Ma Zhiwen 
Published: September 2024

Abstract
U.S. industry sectors accounted for 33% of total energy consumption in 2021 according to the Energy Information Agency. Industrial process heat accounts for 70% of the industry energy use with application temperatures ranging from 60°–1100°C. Industrial processes heavily rely on fossil fuels including cheap coal or natural gas and differ widely in operating conditions and load requirements which makes them difficult to standardize and imposes challenges in decarbonization. To this end, we have developed a particle-based thermal energy storage (TES) technology integrated with renewable energy sources from concentrating solar thermal power (CST) and/or photovoltaic (PV) power. The particle TES system uses low-cost and highly stable silica sand and can provide industrial process heat (IPH) over a wide range of temperatures. The TES system can serve as a uniform energy supply configuration integrated with renewable power to supply 24/7 heat for industry decarbonization. This paper focuses on the Levelized Cost of Heat (LCOH) and investigated the sensitivity of the LCOH to various economic parameters including the capital costs of the particle-TES system and solar tower system. This paper shows the economic potentials of the particle-TES for IPH applications. Various scenarios of combined on-site CST, PV, electric heater, and TES system capacities were considered to determine configurations of the CSP/PV/TES system that could fulfill the heat demand with minor contributions from grid backup. Conditions necessary to approach an LCOH target of ∼$0.02/kWht were evaluated.
Assessing the Environmental Impacts of Electrified Cement Production
Authors: Nurdiawati Anissa , Terán-Cuadrado Glenda , Al-Ghamdi Sami G. 
Published: September 2024

Abstract
The production of ordinary Portland cement (OPC) is responsible for approximately 5–7% of global anthropogenic carbon dioxide (CO2) emissions. As demand for cement is expected to rise due to increased urban and energy infrastructure projects, it is crucial to transform this sector sustainably to meet these needs while minimizing its significant contribution to environmental impacts. Electrification of heat supply is one of the interesting options for mitigating the generation of CO2 emissions resulting from the combustion of conventional fossil fuels. This study analyzes the cradle-to-gate environmental impacts of a cement plant enhanced with an electrified pre-calciner and plasma gas for high-temperature heat in the rotary kiln, integrated with CO2 capture. This assessment is performed using a life cycle assessment (LCA) and is compared against a reference cement plant. Different scenarios regarding fuels and the effect of using future decarbonization scenarios for the electricity mix in Saudi Arabia are evaluated. The findings show that electrified processes could lead to substantial reductions in global warming potential (GWP), with the carbon emission intensity of the electricity grid playing a pivotal role in determining the environmental performance of these technologies. The integration of low carbon electrification with CO2 capture has the potential to reduce the GWP by up to 73%, compared to a baseline scenario relying entirely on 100% Heavy Fuel Oil (HFO) as kiln fuel. Beyond GWP, the study also evaluates other non-climate impact indicators to identify potential environmental co-benefits and trade-offs associated with climate change mitigation efforts.
Decentralized Condition Monitoring for Distributed Wind Systems: A Federated Learning-Based Approach to Enhance SCADA Data Privacy
Authors: Li Gang , Wu Yusen , Yesha Yelena 
Published: September 2024

Abstract
The paper presents a new condition monitoring method for distributed wind systems (DWSs) by combining federated learning with supervisory control and data acquisition (SCADA) data. Federated learning facilitates training of a global model across decentralized SCADA datasets without actual data exchange. This method allows multiple DWSs to collectively contribute to training machine learning models without compromising data privacy. The framework aims to enhance the accuracy and efficiency of condition monitoring by leveraging operational data from SCADA systems. It enables collaborative learning across diverse geographical areas, identifying subtle patterns and anomalies indicative of potential faults or performance issues. The integration of SCADA data provides real-time insights into individual turbine health and performance, allowing for early detection of deviations from normal operating conditions. The federated learning model evolves to adapt to changing environmental and operational factors while maintaining data confidentiality. This condition monitoring method allows for collective improvement of monitoring models without exposing sensitive turbine-specific information, enhancing security and transparency. The synergy of federated learning and SCADA data represents a pioneering paradigm shift, promising to improve monitoring processes and knowledge sharing within the wind infrastructure, advancing reliability, performance, and sustainability in the face of operational challenges.
Optical Flow Diagnostics of Counter Fluidization of Gravity-Driven Moving Packed Bed for a CSP Receiver Section Featuring Staggered Array of Cylindrical Pins
Authors: Aider Youssef , Ma Zhiwen , Singh Prashant 
Published: September 2024

Abstract
Particle fluidized beds have the potential to improve the efficiency of heat transfer in concentrated solar receiver furnace for use in next generation concentrated solar power (CSP) plants. This study presents an experimental investigation on the flow characterization of vertically downward moving packed bed with counter fluidization through an array of jets. To control the bubble size and its distribution in the bubbling fluidized bed, an array of cylindrical pin fins was arranged uniformly across the test article. The flow visualization was performed on the surface of transparent glass coated with electrically conductive materials for electrostatic dissipation purposes. The image acquisition was carried out via high-speed camera at a frequency of ∼ 1kHz. The acquired images were analyzed in pairs with the help of a modern optical flow algorithm capable of calculating the movement of dense particle flow in the fluidized bed by tracking the light intensity of each predefined window of the frames. A comparison of fluidized beds with plane and pin-finned channels revealed distinct bubble behavior. Pin-finned channels were found to produce a larger number of small-sized bubbles, while plane channels generated fewer but larger bubbles at any given instant. The presence of pin fins was observed to reduce bubble size by preventing bubble merging and splitting larger bubbles when they encountered a pin.