Combined Power Research Articles

High power spectral beam combining based on four long-wave infrared quantum cascade laser emitters

In this study, we experimentally investigate spectral beam combining based on four long-wave infrared quantum cascade lasers (QCLs) with three dichroic mirrors. The coating curves of the dichroic mirrors were finely designed according to the output spectrum of the four adopted QCLs, whose central wavelength locates in 7.5 μm, 8.3 μm, 9.0 μm and 10.2 μm, respectively. At room temperature the highest combined power reaches as high as 2.39 W, corresponding to a combining efficiency of 83.0 %, and meanwhile, the combined beam keeps a high beam quality with average M2 of 1.78. To the best of our knowledge, this is the highest output power among spectral beam combining for QCLs. Due to the advantage of wide spectral range, high power, high beam quality and compact size, this demonstration may meet the demands of medical diagnosis, remote sensing, free-space optical communication and military application.

Comprehensive study of plasma polymerization parameters on thiol-coated LDPE films for effective fibronectin adsorption targeting biomedical applications

In the realm of biomedical applications, biocompatible materials with optimized surface properties are crucial for facilitating cellular interactions. To attain the perfect balance of these properties, surface modification of non-toxic and stable bulk materials is often required. Within this context, this research aimed to improve the physiochemical and cell-responsive properties of a low-density polyethylene film. This was achieved by depositing thiol-rich coatings using a dielectric barrier discharge plasma reactor operating at medium pressures, with 1-propanethiol serving as polymerization precursor. The study systematically investigated the impact of key plasma polymerization parameters, including DBD chamber pressure, treatment time, and the combination of precursor flow rate and discharge power represented by the Yasuda parameter, to identify optimal plasma processing conditions for the formation of thiol-rich coatings. To characterize the coating thickness, hydrophilicity and surface chemical composition, atomic force microscopy, water contact angle measurements, and X-ray photoelectron spectroscopy were employed. The findings indicated that reducing the chamber pressure to 10 kPa led to more hydrophilic and thicker deposits possessing a higher sulphur content. Deposition time (5 to 15 min) also significantly impacted coating thickness and surface chemistry, where long times increased thickness, but also led to a reduced sulphur and increased oxygen content because of more pronounced etching. The optimal deposition time was therefore set at 10 min resulting in the deposition of dense coatings possessing a high number of sulphur-containing functionalities. The Yasuda parameter (W/FM) analysis demonstrated optimal thiol incorporation in combination with high coating stability at an intermediate W/FM value of 72 MJ/kg. Following the determination of the optimal plasma polymerization parameters, the effectiveness of thiol plasma polymerization and subsequent fibronectin immobilization for enhancing cell adhesion and proliferation was investigated. The thiol-coated substrates were found to exhibit superior protein immobilization, because of the high affinity for protein binding of the available thiol groups. To assess cellular responses, Schwann cells were cultured on uncoated and coated samples before and after fibronectin immobilization. The results revealed a superior cellular response of the thiol-coated samples after fibronectin immobilization, showing the highest cell viability and significantly enhanced cell adhesion and proliferation. Collectively, these results underscore the synergistic effect of thiol plasma polymerization and fibronectin immobilization in promoting the cellular response of LDPE substrates, thus highlighting their potential as a surface modification strategy of biomaterials.

A High-Speed, High-Temperature, Micro-Cantilever Steam Turbine for Hot Syngas Compression in Small-Scale Combined Heat and Power

Abstract Coupling a biomass gasifier with a solid oxide fuel cell system through a high-temperature syngas compressor holds great promise to achieve low-emission, small-scale combined heat and power, since it reduces the number of heat exchangers and increases the system efficiency. However, due to the demanding operating conditions (high temperatures, toxic and explosive gases), electrical motors are not suitable to drive the syngas compressor. Therefore, a high-speed, small-scale cantilever steam turbine that can valorize the system?s waste heat to power the compression is designed and developed. An iterative process involving preliminary design, meanline analysis, commercial tools, and in-house codes is used for the design. The design is then numerically analyzed using computational fluid dynamics. The 2.8 kW cantilever steam turbine with a tip diameter of 21 mm runs up to 210 krpm at temperatures of 525°C while being supported on dynamic steam-lubricated bearings. A low-reaction, full-admission design has been chosen to lower the steam consumption, the axial forces, and the turbine backface leakage. The turbine rotor is made of Ti6Al4V and coated for structural integrity and to withstand high temperatures. Despite the small scale of this design, the results obtained from the established correlations based on large-scale turbines yield a remarkable concordance with the results from the numerical analysis, in particular for the isentropic expansion efficiency prediction.

Multi-objective optimization and life cycle assessment of mass-integrated combined heat and power system

As the effects of climate change become more widely recognized, technical innovation and green energy will promote the growth of combined heat and power systems. This study proposes a novel mass-integrated combined heat and power system and conducts energy analysis, exergy analysis, and techno-economic analysis for the system. The optimization strategy integrated polynomial regression and non-dominated sorting genetic algorithm III is established, with system thermal efficiency, exergy efficiency, and return on investment (ROI) as objective functions. The system's environmental consequences are then assessed throughout its life cycle using life cycle assessment (LCA) under ideal operating circumstances. The findings reveal that the waste heat recovery heat exchanger has the highest exergy destruction in the system, with a value of 674.61 kW. Furthermore, the intermediate heat exchanger 1 and intermediate heat exchanger 2 (IHX2) with lesser exergy efficiency have an exergy destruction of less than 32.00 kW. The IHX2 is the most expensive equipment in the system, costing $90,931.19, but it also provides the most potential for system improvement. The multi-objective optimization findings suggest that the thermal efficiency, exergy efficiency, and ROI for the system are 0.17, 0.97, and 0.30, respectively. The LCA demonstrates that the system has a negligible influence on global warming and ozone generation with corresponding LCA findings of less than 4.20. The construction and operation phases of the investigation system have the most significant environmental consequences. The correlation between the raw materials necessary for the construction of the equipment in the system and the reaction temperatures, conditions, and waste composition during the preparation of the working fluids is large, so it is necessary to take corresponding environmental protection measures during production and processing to reduce the system's environmental emissions from the source and promote ecologically sustainable development.

A High-Temperature, High-Speed, Oil-Free Syngas Compressor for Small-Scale Combined Heat and Power

Abstract For low-emission, small-scale combined heat and power generation, integrating a biomass gasifier with a downstream solid oxide fuel cell system is very promising due to their similar operating conditions in terms of temperatures and pressures. This match avoids intermediate high-temperature heat exchangers and improves system efficiency. However, to couple both systems, a high-temperature and oil-free compressor is required to compress and push the low-density, high-temperature bio-syngas from the gasifier to the solid oxide fuel cell stack. The design and development of this high-temperature, high-speed, and gas-bearing supported compressor is presented in this work. An iterative process involving preliminary design, meanline analysis using commercial tools and in-house models is used for the design, which is then numerically analyzed using computational fluid dynamics. The goal is to achieve a design with a wide operating range and high robustness that withstands extreme working conditions. The 727 W machine is designed to run up to 210 krpm to compress 18.23kg/h of syngas at 350°C and 0.81bar. The centrifugal compressor has a tip diameter of 38 mm and consists of 9 backswept main and splitter blades. The impeller is made of Ti6Al4V and coated to prevent hydrogen embrittlement from the hot and highly reactive bio-syngas. The results obtained from the established models suggest a good concordance with the results from numerical analyses, despite the high temperatures and small scale of this design.

Multi-objective optimization of combined heat and power system integrated with multi-energy storage systems for rural communities

Renewable-based combined heat and power system (CHPS) benefit communities by enhancing energy resilience and reducing energy costs and emissions. Considering its reliability issues, previous studies integrated two or more energy sources or employed energy storage systems, compromising emission reduction or imposing an economic burden. To address this challenge, this study introduces three energy system schemes (ESSs) based on renewable, non-renewable, and hybrid energy resources. Each ESS includes various feasible configurations integrated with energy storage systems, such as batteries and hydrogen, resulting in 22 configurations modeled, optimized, and systematically investigated using HOMER software, considering energy-economic-environmental (3E) criteria to select the optimal system configuration (OSC). The introduced CHPS configurations are presented in a practical case study of a remote community in Pakistan. Results showcased that OSC belongs to a hybrid ESS with the following characteristics: (a) COE (0.127 $/kWh) and NPC (0.192 M$) are minimum among other configurations, (b) capacity shortage and unmet electric load are 0.21 % and 0.14 %, and (c) CO2 is reduced by 67.49 % compared to the base case. Furthermore, the 3E effect of adding a thermal load controller and batteries to the OSC is explored. The 3E results are inclusively compared with the existing literature, revealing that OSC is economical, reliable, and eco-friendly.

Design and Techno-Economic Analysis of Hybrid Power Systems for Rural Areas: A Case Study of Bingöl

Today, many factors, especially the increasing world population and developing technology, increase the energy needs of people and societies day by day. The fact that fossil resources are both in danger of depletion and have negative environmental impacts has directed countries to new resources. The study focuses on the effective use of renewable energy sources (RES) and the evaluation of waste to meet the electricity and heat energy needs of Yiğit Harman Village, located in the Solhan district of Bingöl Province. For this purpose, a renewable-energy-based combined heat and power system (CHP) was designed using HOMER Pro software (version 3.14.2, Homer Energy LLC, Boulder, CO, USA). Solar, wind, biomass, and hydrogen energy sources were used, considering the resources of the region. Using the designed model, the entire electricity energy requirement and half of the heat energy were completely met by the region’s available RESs. In addition to the technical analysis, economic and environmental analyses were also conducted, and LCOE, NPC, and CO2 emission values were obtained as 0.271 USD/kWh, USD 739,772, and 37,958 kg/yr, respectively. These results indicate that with an investment of approximately USD 7000 per household, the electrical and thermal energy needs for 25 years can be met.

Intelligent modeling of combined heat and power unit under full operating conditions via improved crossformer and precise sparrow search algorithm

The flexible operation capability of combined heat and power (CHP) unit under full operating conditions must be promoted to suppress the power grid fluctuation in large-scale integration of renewable energy. However, obtaining CHP unit model under large-scale variable loads and deep peak shaving is extremely challenging. To this end, an intelligent modeling method incorporating improved crossformer and precise sparrow search algorithm is designed to provide reference for flexible controller design. Firstly, to address the strong time dependence of CHP unit boiler-turbine coupling process, a bidirectional gated recurrent unit is employed as the position encoding to extract the hidden temporal feature. Secondly, a novel encoder structure with multi-receptive field convolution module is designed to enhance the local feature extraction capability of the network, which is conducive to the analysis of multivariable coupling characteristics of CHP unit. On this basis, a precise sparrow search algorithm with stronger search ability is formed by combining Tent chaotic mapping, osprey optimization algorithm, Cauchy mutation and quantum behavior, which provides support for the dynamic characteristics analysis of CHP unit. The time dependence, local feature information and optimal parameter settings are fully considered in the comprehensive modeling scheme, which results in an accurate identification model for CHP unit under full operating conditions. Finally, the effectiveness of the proposed method is verified based on the actual operating data of a 350 MW CHP unit. The accuracy of established model is greater than 99.4 %, which can well reflect the nonlinear characteristics of the unit. Therefore, the built model can be used for controller design and simulation analysis.

Tailored microstructure control in Additive Manufacturing: Constant and varying energy density approach for nickel 625 superalloy

The main challenge in the L-PBF process is finding the right combination of laser power (LP), scan speed (SS), and energy density (ED). This combination is crucial in controlling the microstructure and texture. This study introduces a new process parameter matrix (PPM) and its variation within the ED to adjust the microstructure by changing the LP/SS while keeping the ED constant or varying in the L-PBF process. Twenty-five Inconel 625 cubes were produced at different LP and SS, ranging from 230 to 350 W and 790 to 1190 mm/s. The resulting microstructure indicated that textured grains increased with ED. It also indicates that increasing the ED reduced relative density (RD) and porosity formation, while constant ED did not significantly affect them. Consequently, the hardness of the cube at the highest ED was about 21 % higher than that of the cube at the lowest ED. This study demonstrates the effectiveness of adjusting PPM to tailor the microstructure and texture using the L-PBF technique, which could be applied to complex shapes.

Techno-economic analysis and optimization of a binary geothermal combined district heat and power plant for Puga Valley, India

This article investigates the energy, exergy, and economic performance of a Puga Valley-specific binary geothermal combined district heat and power plant, taking into account geotechnical data and related cost functions. The power plant uses an organic Rankine cycle (ORC) with R123 as the working fluid, utilizing waste heat for district heating to enhance efficiency. Variations in operating and design parameters such as geothermal fluid flow rate, temperature, and ORC temperature of the evaporator and condenser are found to have significant effects on the overall performance of the system and cost rate. A multi-objective grey wolf optimization technique based on artificial neural networks has been used to determine the ideal values of the above-mentioned parameters. The optimization study revealed a Pareto optimal curve with overall exergy efficiency and total cost rate as objective functions from which the optimal point was identified using the technique for order preference by similarity to the ideal solution (TOPSIS) method. While operating the proposed CHP plant at TOPSIS optimal point, the plant delivers a net electrical output of 1.08 MW alongside 4.19 MW of thermal energy, resulting in a total cost rate of 33.84 USD/h, with energy and exergy efficiencies peaking at 32.26 % and 36.8 %, respectively. The exergy analysis at the optimal point also revealed a notable reduction of 550 kW in the total exergy destruction rate compared with the base-case scenario. Furthermore, the design requirements of a 5 MW net power output CHP plant for effective recovery of the Puga Valley geothermal resource are discussed.

Assessing the emissions reduction potential and economic feasibility of small-scale (

Small-scale combined heat and power (CHP) for residential applications has been demonstrated in different regions throughout the world. CHP can enable resilience in energy supply and serve as a transitional technology as the grid progresses to higher fractions of low carbon electricity production. However, there are very limited feasibility assessments in the context of US climate zones, policies, and economic factors. To address this gap, we assess how the economic feasibility and emissions impact of a small-scale, natural gas CHP system compares considering the local electrical grid in seven climate zones and six subgrid regions across the United States. This is accomplished using an in-house Python program alongside EnergyPlus that is used to size the CHP and/or thermal storage systems according to representative electrical and thermal demand profiles for multifamily residential buildings, optimizes CHP and thermal storage energy dispatch throughout the year to meet demands, assesses the system’s economic feasibility, and calculates the carbon emission reduction or increase relative to the local electrical grid. For the baseline cases considered, carbon emissions can be reduced by up to 12% for regions with high required thermal load and/or electricity derived from high carbon emitting sources. In many scenarios, carbon emissions increased. Furthermore, the economic feasibility of the systems, even considering recent incentives, remains a significant barrier. The resulting Python program is open-source and designed for use by both researchers and building owners to conduct their own small-scale CHP feasibility assessments.

A multi-objective stochastic optimization model for combined heat and power virtual power plant considering carbon recycling and utilizing

In order to give full play to the energy supply potential of distributed energy resources, this paper studies the scheduling optimization of CHP-VPP. First, the CHP unit and various distributed energy sources are aggregated into VPP. Carbon recycling and utilizing are realized through carbon capture and power-to-gas devices. At the same time, carbon storage and hydrogen storage devices are added to decouple carbon capture and P2G procedures. Then, the risk of VPP real-time scheduling is quantified through uncertainty scenario generation and CVaR. Finally, with the goals of operating cost, carbon emission, and operation risk, a multi-objective stochastic scheduling optimization model of VPP is constructed, and the subjective and objective ensemble weighting method is used to solve the problem. The example results show that the proposed method can boost the wastage of wind and photovoltaic power, and also lower the carbon emissions of VPPs.

Design-Point Techno-Economics of Brayton Cycle PTES for Combined Heat and Power

Abstract Pumped thermal energy storage (PTES) systems are grid batteries that use heat pumps to create both hot and cold thermal energy stores when there is excess electricity and then use a power cycle to convert the thermal energy into electricity when there is demand for electricity. In normal operation, Joule-Brayton PTES discharges low-grade heat at temperatures useful for thermal energy consumers like district and industrial heating. Furthermore, PTES designs, like conventional combined heat and power (CHP) technology, can be modified to sacrifice some round-trip efficiency (RTE) to increase the temperature of heat rejection. This paper uses design-point performance and cost models that provide a detailed understanding of the efficiency and cost trade-offs of rejecting heat at various temperatures in ideal-gas Brayton PTES configurations. First, we keep the heat rejection in its nominal location in the PTES system. Next, we move the heat rejection to the discharge turbine exit. We define design-point metrics that isolate both the cost and performance penalty associated with the hotter heat rejection and attribute it exclusively to the heat economic metrics. We find that the levelized cost of heat, including the cost of thermal energy storage (TES) buffering the PTES and heat off-taker, compares favorably versus electric technologies and is less than the cost of natural gas for low temperature scenarios and competitive with the cost of natural gas in some regions of the contiguous United States in high temperature scenarios.

Refraction displacement pulse sequence combination based on a fast steering mirror stabilization system

In this paper, a fast steering mirror (FSM) stabilization system is proposed for a refraction displacement pulse sequence beam-combining (PSBC) technique. The FSM system can effectively suppress pointing jitter in the PSBC and achieve high beam-quality laser output. A proof-of-principle experiment on the PSBC with FSM is performed with three ∼100W pulsed beams. The experimental results indicate that a combined output power of 302.5 W is achieved, corresponding to a high combining efficiency of 98.7%. Meanwhile, excellent pointing stability with root mean square pointing jitter = 4.2 µrad is confirmed with a beam quality β of 2.

Thermodynamic modeling and optimal short-term scheduling of a green H2-fueled combined heat and power generation system for industrial zones

This paper presents a novel green combined heat and power generation system for industrial applications. It composes of a hydrogen-fueled combined cycle power plant and a battery energy storage. Firstly, the hydrogen-air rich mixture enters the combustion chamber of the gas turbine cycle for generating electricity, while recovering the heating energy from the exhausted flue gases for driving a steam turbine cycle. The heating energy extracted from the condenser heat exchanger is also used to supply the heating demand of the end-user. Moreover, a comprehensive thermodynamic model and analysis of H2 combustion process is provided to estimate the adiabatic flame temperature based on enthalpies of reactants and products. The optimum operating point of the cogeneration system is found by solving a mixed-integer nonlinear problem using MATLAB and GAMS over a 24-h study horizon aiming to minimize its daily operation cost considering all technical constraints of system components and load-generation balance criterion. It is found that the energy efficiency of the hydrogen-fueled combined cycle changes from 46 to 58 % while generating 11.331–12.982 MW electricity and 4.436–4.984 MW heat. Two cases are studied without and with participation of battery in energy procurement strategy. It is demonstrated that the objective function of the optimization problem improves from 18 $ cost in case 1 to 29 $ revenue in case 2.

Integrating machine learning and thermodynamic modeling for performance prediction and optimization of supercritical CO2 and gas turbine combined power systems

The supercritical carbon dioxide (SCO2) cycle has drawn attention to extracting energy and generating power from low-grade heat resources due to its higher efficiency, lower cost, and compactness. Combining the SCO2 cycle with a gas turbine (GT) is a promising field of research with applications in industries such as waste heat recovery (WHR) systems. In this research, three different configurations of power generation SCO2 cycles, including recuperation, precompression, and reheating, were thermodynamically designed and modeled. Extracting the main parameters of cycles, and the appropriate objective, which is cycle energy efficiency, up to 80,000 data constructed. Random forest (RF) and support vector regression (SVR), machine learning (ML) techniques, are used for the performance prediction of cycles. The results show the strength of the RF method to predict the cycle efficiency with up to 3% error and the SVR method with more than 90% accuracy. Sensitivity analysis and Particle Swarm Optimization (PSO) algorithm are employed for optimizing the recuperation cycle. The outcomes of the optimization model, based on the prediction models as proxies, have results in nearly close to those of traditional optimization, which is based on a thermodynamic model. In conclusion, ML models can be used in industry for prediction and maintenance since the methods are up to 5 times faster than thermodynamic models.

Efficient standalone micro thermoelectric generator powered by low noise premixed combustion

The distributed backup power source is vitally important under emergency conditions. Micro combustion powered thermoelectric generator (μ-CPTEG) is a promising candidate as a distributed backup power source. This study innovatively designed an all-in-one configuration to develop an efficient, standalone, and silent μ-CPTEG. The newly proposed all-in-one configuration organically integrates air-preheating, fuel premixing, low-noise combustion, efficient heat collection, and smooth heat compensation and spreading. Such an all-in-one configuration creates a standalone μ-CPTEG with an overall efficiency greater than 4.2 %, which is much larger than those in previous standalone μ-CPTEGs. The present μ-CPTEG incorporates 8 TE modules, and generates an electric power of 53.2 W with a running sound pressure level of 48 dB. Such performance indicates that the average electric power per TE module reaches 6.65 W, corresponding to a TE potential release level of 80.7 % systematically. The overall efficiency, as well as the efficiency of heat recovery, combustion, heat collection, TE and combined heat and power, are explored in detail. Comprehensive discussions are conducted to uncover the dense fog of releasing the TE potential at a systematic level in an μ-CPTEG. The present study provides a concrete method to develop a powerful, standalone, and silent μ-CPTEG.

Joint chance‐constrained coordinated scheduling for electricity‐heat coupled systems considering hydrogen storage

AbstractStrong interdependence between power production and heat supply from combined power and heat units could restrict the wind power integration. Deploying hydrogen storage, typically formed by the electrolyser, hydrogen tank, and fuel cell, could be a promising measure to accommodate surplus wind power and facilitate the coordinated operation of power and heat. The authors consider coordinated scheduling under wind power uncertainty for an electricity‐heat coupled system with hydrogen storage and propose a distributionally robust joint chance‐constrained coordinated scheduling (DRJCC‐CS) model, where the waste heat from the electrolyser and fuel cell is incorporated. The authors design distributionally robust joint chance constraints to account for wind power uncertainty related constraints and derive their tractable inner and outer mixed‐integer convex approximations. Consequently, the proposed DRJCC‐CS model is casted into a mixed‐integer convex programme. Case studies are conducted to demonstrate the effectiveness of the proposed DRJCC‐CS method.

Progressing from first-of-a-kind to Nth-of-a-kind: Applying learning rates to carbon capture deployment in Sweden

The deployment of CO2 capture technologies presents opportunities to store fossil fuel emissions from industries and power generation (CCS) and to enable carbon utilization (CCU). However, the costs for early CCS projects are high, and this is a challenge in terms of their economic viability, requiring a strong climate policy with high carbon prices for implementation. This work details a techno-economic assessment of the cost of carbon capture based on a hybrid method and individual project approach, using first-of-a-kind contingency factors and learning rates to study the evolution of carbon capture costs as installed capacity increases over time. The work is based on a case study of 147 Swedish industrial and combined heat and power plants (total of 176 stacks). The results are presented as marginal abatement cost curves, with consideration of early mover CCS projects and learning rates. Deployment scenarios are also presented that take into account an expected increase in the CO2 price. The findings indicate that when accounting for first-of-a-kind contingencies (100 % and 200 % increases in Nth-of-a-kind costs), 90 and 17 projects, respectively, of the total 176 emission sources studied have specific CO2 costs of <300 €/t. However, high learning rates (12 %) can reduce the capture costs from first-of-a-kind to Nth-of-a-kind levels within some 30 project installations (100 % contingency). With lower learning rates (3 %), the first-of-a-kind costs are reduced by 10 %–20 %. With the expected increase in CO2 prices, a peak in carbon capture deployment is observed around Year 2035, at a carbon price of 200 €/t.

Thermodynamic analysis of a combined heating and power plant hybrid with compressed air energy storage and molten salt heat storage

In face of the increasing penetration of renewable energy, compressed air energy storage (CAES) is promising in improving the flexibility of the conventional coal-fired combined heating and power plant (CHPP). In order to further broaden the operational range and improve the overall efficiency, this paper introduces the molten salt heat storage (MSHS) into the CHPP-CAES system. Based on the thermodynamic model, the effect of the MSHS is discussed in terms of the energy efficiency, exergy efficiency, and the power regulation based on the topology with and without MSHS. The inclusion of the MSHS can improve the exergy efficiency and reduce the average coal consumption for power supply, while also effectively widening the power regulation range. Parameter analysis is carried out in terms of the compression and expansion stages of CAES, the steam extraction position of MSHS, throttle valve pressure drop, and the capacities of CAES and MSHS. It is revealed that, extracting steam from the boiler reheater and reducing the CAES capacity can lead to better efficiency but smaller operational range. Furthermore, reducing the throttle valve pressure drop and improving the MSHS capacity are simultaneously favorable for the overall performance and operating range. These conclusions can provide theoretical guidance for the structure and parameter design of the CHPP in hybrid with CAES and MSHS.