Conversion System Research Articles

A hybrid algorithm based on Bayesian optimization and Interior Point OPTimizer for optimal operation of energy conversion systems

Optimization methods are essential to improve the operation of energy conversion systems including energy storage equipment and fluctuating renewable energy. Modern systems consist of many components, operating in a wide range of conditions and governed by nonlinear balance equations. Consequently, identifying their optimal operation (e.g. minimizing operational costs) requires solving challenging optimization problems, with the global optimum often hidden behind many local ones. In this work, we propose a hybrid method that advantageously combines Bayesian optimization (BO) and Interior Point OPTimizer (IPOPT). The BO is a global approach exploiting Gaussian process regression to build a surrogate model of the cost function to be optimized, while IPOPT is a local approach using quasi-Newton updates. The proposed BO-IPOPT combination allows leveraging the parameter space exploration of the BO with the quasi-Newton convergence of IPOPT once solution candidates are in the neighborhood of an optimum. Using a challenging constrained test function, we test BO-IPOPT in accuracy and computational efficiency. Finally, we showcase the proposed method in the optimal operation of a renewable steam generation system. The results show that BO-IPOPT combines high accuracy and computational efficiency, achieving up to 50% better objective function values at the same CPU time than other state-of-the-art methods.

Increasing the Efficiency of Thermoelectric Conversion of Solar Energy

The article considers the latest achievements in the field of thermionic conversion of solar energy. The key aspects of thermionic emission, the problems of reducing the electrode work function and increasing the efficiency of devices are analyzed. It is shown that diamonds doped with phosphorus can be an attractive material for the purposes of thermionic emission. In this case, the presence of donor states can significantly narrow the space charge region, and at the same time reduce the potential barrier in the work function. The studies also found that the most successful and widely used method for overcoming the space charge effect is filling the interelectrode gap with cesium. The efficiency of thermionic conversion devices for solar energy increases by 1.6 times. Particular attention is paid to the use of new materials, such as nanostructures and carbon nanotubes, as well as promising technologies, such as photonic enhancement of thermionic processes. The analysis of the results showed that the photonic enhancement of the electron yield due to illumination is greater in p-type silicon, as predicted by theoretical models. The thermionic current increases by 1.7 times compared to silicon. The distance between the quasi-Fermi level and the Fermi level in n-type silicon is less than this distance in p-type silicon. As a consequence, the number of electrons in the conduction band is smaller. Methods for combating the space charge effect and optimizing the configuration of energy conversion systems are discussed.

Vertically Fluorinated Graphene Encapsulated SiOx Anode for Enhanced Li+ Transport and Interfacial Stability in High-Energy-Density Lithium Batteries.

Achieving high energy density has always been the goal of lithium-ion batteries (LIBs). SiOx has emerged as a compelling candidate for use as a negative electrode material due to its remarkable capacity. However, the huge volume expansion and the unstable electrode interface during (de)lithiation, hinder its further development. Herein, we report a facile strategy for the synthesis of surface fluorinated SiOx (SiOx@vG-F), and investigate their influences on battery performance. Systematic experiments investigations indicate that the reaction between Li+ and fluorine groups promotes the in situ formation of stable LiF-rich solid electrolyte interface (SEI) on the surface of SiOx@vG-F anode, which effectively suppresses the pulverization of microsized SiOx particles during the charge and discharge cycle. As a result, the SiOx@vG-F enabled a higher capacity retention of 86.4 % over 200 cycles at 1.0 C in the SiOx@vG-F||LiNi0.8Co0.1Mn0.1O2 full cell. This approach will provide insights for the advancement of alternative electrode materials in diverse energy conversion and storage systems.

Protection of rotor side converter of doubly fed induction generator based wind energy conversion system under symmetrical grid voltage fluctuations

This paper presents the protection of the rotor side converter in a grid-connected doubly fed induction generator (DFIG)-based wind energy conversion system (WECS) during a symmetrical voltage dip. In order to manage rotor current and regulate DC link voltage, an efficient active crowbar protection circuit is implemented in the rotor side converter (RSC). To improve the low-voltage ride-through capability for grid-connected wind turbine systems, an integrated DFIG-based WECS role is crucial because wind turbines must remain connected to the utility grid during faults to ensure continuity and reliability of power supply. This paper aims to design and implement an efficient active crowbar protection technique to protect the RSC and avoid excessive rotor current during a symmetrical voltage dip. Therefore, the efficient active crowbar protection circuit is designed using MATLAB-Simulink software, and its performance is validated using a real-time (RT) simulator. Finally, the existing methods are compared with the proposed work outcomes, and a conclusion is made.

ENERGY MANAGEMENT IN HYBRID PV-WIND-BATTERY STORAGE-BASED MICROGRID USING DROOP CONTROL TECHNIQUE

The paper presents an efficient energy management system designed for a small-scale hybrid microgrid incorporating wind, solar, and battery-based energy generation systems using the droop control technique. The heart of the proposed system is the energy management system, which is responsible for maintaining power balance within the microgrid. The EMS continuously monitors variations in renewable energy generation and load demand and adjusts the operation of the energy conversion systems and battery storage to ensure optimal performance and reliability. The primary objective of the energy management system is to maintain power balance within the microgrid, even in the face of fluctuations in renewable energy generation and load demand. This involves dynamically adjusting the operation of the renewable energy sources and battery storage system to match the instantaneous power requirements of the microgrid. Overall, the paper presents a comprehensive approach to designing and implementing an efficient energy management system for a small-scale hybrid wind-solar-battery-based microgrid to extract maximum profit from electricity generation. By integrating renewable energy sources with energy storage and advanced control algorithms, the proposed system aims to enhance the reliability, stability, and sustainability of the microgrid's power supply.

Exploring an economic and highly efficient genetic transformation and genome-editing system for radish through developmental regulators and visible reporter.

Radish (Raphanus sativus L.) is one of the most important root vegetable crops worldwide. However, gene function exploration and germplasm innovation still face tremendous challenges due to its extremely low transformation efficiency. Here, an economic and highly efficient genetic transformation method for radish was explored by Agrobacterium rhizogenes-mediated transformation with the help of combining special developmental regulator (DR) genes and the visual identification reporter. Firstly, the RUBY gene, a betalain biosynthesis system, could result in a visual red-violet color used as a convenient and effective reporter for monitoring transgenic hairy roots screening of radish. However, the hairy roots-to-shoots conversion system of radish still stands as a barrier to the obtainment of whole transgenic plants, although different hormone combinations and various culture conditions were tried. Following, two DR genes including Wuschel2 (Wus2) and isopentenyl transferase (ipt), as well as their combination Wus2-ipt were introduced for the shoot regeneration capacity improvement. The results showed that the transgenic shoots could be directly generated without externally supplying any hormones in the presence of a Wus2-ipt combination. Then, Wus2-ipt along with the RUBY reporter was employed to establish an efficient genetic transformation system of radish. Moreover, this system was applied in generating gene-edited radish plants and the phytoene desaturase (RsPDS) gene was effectively knockout through albino phenotype observation and sequencing analysis. These findings have the potential to be widely applied in genetic transformation and genome-editing genetic improvement of other vegetable species.

Structure-Stability Relation of Single-Atom Catalysts under Operating Conditions of CO2 Reduction.

Single-atom catalysts (SACs) have exhibited exceptional atomic efficiency and catalytic performance in various reactions but suffer poor stability. Understanding the structure-stability relation is the prerequisite for stability optimization but has been rarely explored due to complexity of the degradation process and reaction environments. Herein, we successfully established the structure-stability relation of N-doped carbon-supports SACs (MN4 SACs) under working conditions of CO2 reduction, by using advanced constant-potential density functional theory calculations. Systematic mechanism investigation that considered different factors identifies the key role of initial hydrogen adsorption on the coordination N atom in catalytic stability, where the feasibility of the adsorption eventually determines the leaching of the metal atom. On this basis, a simple descriptor consisting of electron number and electronegativity is constructed, realizing accurate and rapid prediction of the stability of SACs. Furthermore, strategies via modifying the local geometric structure to improve the stability without changing the active centers are proposed accordingly, which are supported by related experiments. These findings fill the current void in understanding SAC stability under practical working conditions, potentially advancing the widespread application of SACs in sustainable energy conversion systems.

Laser-driven synthesis of functional materials for advanced energy applications: A short review

Since the initial exploration of synthesis possibilities at a liquid–solid interface through pulsed laser irradiation of iron in water, the pulsed laser ablation in liquid media (PLAL) process has garnered significant attention for constructing various nanostructures due to its simple, ultrafast, and clean methodology that avoids byproduct formation. Recent advances in functionalized heterostructures via the PLAL process suggest a broad range of applications for energy- conversion systems, including water splitting and energy harvesting. This review surveys recent advancements in PLAL for energy applications, with a specific focus on its applications in oxygen evolution reaction (OER) electrocatalysts and energy harvesting devices. The review discusses the synthesis mechanisms, advantages, challenges, and future research directions of PLAL, aiming to provide a comprehensive understanding of its potential and limitations.

Highly thermally conductive and shape-stabilized phase change materials with desirable solar/electric-to-thermal conversion performance based on high-modulus graphite/PVA foam

The widespread utilization of phase change materials (PCMs) has been impeded by challenges such as leakage, low thermal/electrical conductivity, and inadequate light absorption. Although constructing interconnected three-dimensional (3D) carbon networks within PCMs can mitigate these issues, their complex and energy-intensive fabrication processes, coupled with insufficient mechanical strength causing significant leakage and collapse of liquefied PCMs under external loads or impacts, hinder their practical application. Herein, we present a novel approach for the preparation of 3D graphite/polyvinyl alcohol foam (GPF) through a simple vacuum foaming combined with air-drying method. The obtained GPF-5 exhibits impressive compression strength (4.46 MPa) and compression modulus (93.1 MPa) at low density of 0.30 g/cm3. Upon impregnation with polyethylene glycol (PEG), GPF-5/PEG exhibits notable mechanical strength (7.62 MPa), contributing to its thermal shape stability and resistance to leakage. Even when subjected to temperatures above the melting point of PEG under external loads, GPF-5/PEG maintains its original shape without any liquid leakage. Due to the efficient construction of 3D thermal conductivity pathways within GPF, GPF-5/PEG demonstrates a high thermal conductivity of up to 3.48 W/m K−1 with graphite contents of 21.1 wt%, representing an increase of 136 % and 1640 % compared to graphite/PEG (with equivalent graphite content) and pure PEG, respectively. Additionally, GPF-5/PEG displays high latent heat of melting (136.8 J/g) and superior thermal cycling stability. Moreover, GPF-5/PEG demonstrates high solar-to-thermal and electric-to-thermal energy conversion capabilities, highlighting their potential for diverse applications. The work offers a rational strategy for fabricating high-modulus carbon foam, which can be used for PCMs-based multi energy conversion and storage systems with high thermo-mechanical properties.

User Experience and the Role of Personalization in Critiquing-Based Conversational Recommendation

Critiquing—where users propose directional preferences to attribute values—has historically been a highly popular method for conversational recommendation. However, with the growing size of catalogs and item attributes, it becomes increasingly difficult and time-consuming to express all of one’s constraints and preferences in the form of critiquing. It is found to be even more confusing in case of critiquing failures: when the system returns no matching items in response to user critiques. To this end, it would seem important to combine a critiquing-based conversational system with a personalized recommendation component to capture implicit user preferences and thus reduce the user’s burden of providing explicit critiques. To examine the impact of such personalization on critiquing, this article reports on a user study with 228 participants to understand user critiquing behavior for two different recommendation algorithms: (i) non-personalized , that recommends any item consistent with the user critiques; and (ii) personalized , which leverages a user’s past preferences on top of user critiques. In the study, we ask users to find a restaurant that they think is the most suitable to a given scenario by critiquing the recommended restaurants at each round of the conversation on the dimensions of price, cuisine, category, and distance. We observe that the non-personalized recommender leads to more critiquing interactions, more severe critiquing failures, overall more time for users to express their preferences, and longer dialogs to find their item of interest. We also observe that non-personalized users were less satisfied with the system’s performance. They find its recommendations less relevant, more unexpected, and somewhat equally diverse and surprising than those of personalized ones. The results of our user study highlight an imperative for further research on the integration of the two complementary components of personalization and critiquing to achieve the best overall user experience in future critiquing-based conversational recommender systems.

Caching Historical Embeddings in Conversational Search

Rapid response, namely, low latency, is fundamental in search applications; it is particularly so in interactive search sessions, such as those encountered in conversational settings. An observation with a potential to reduce latency asserts that conversational queries exhibit a temporal locality in the lists of documents retrieved. Motivated by this observation, we propose and evaluate a client-side document embedding cache, improving the responsiveness of conversational search systems. By leveraging state-of-the-art dense retrieval models to abstract document and query semantics, we cache the embeddings of documents retrieved for a topic introduced in the conversation, as they are likely relevant to successive queries. Our document embedding cache implements an efficient metric index, answering nearest-neighbor similarity queries by estimating the approximate result sets returned. We demonstrate the efficiency achieved using our cache via reproducible experiments based on Text Retrieval Conference Conversational Assistant Track datasets, achieving a hit rate of up to 75% without degrading answer quality. Our achieved high cache hit rates significantly improve the responsiveness of conversational systems while likewise reducing the number of queries managed on the search back-end.

Experimental investigation of adaptive multi-generalized integrator-based controller for electronically interfaced hybrid microgrid system

This research work explores the conceptualization and evaluation of a hybrid microgrid that taps into the potential of solar photovoltaic systems, wind energy conversion systems, and battery energy storage systems. In practice, nonlinear loads pose power quality issues that significantly impact the performance of hybrid microgrids. To tackle these challenges, an adaptive multi-generalized integrator (MGI) filter is proposed. This filter extracts the fundamental signal from the distorted utility grid voltages. It features a pre-filter with a DC-off set rejection loop, effectively minimizing the DC-offsets from the distorted grid voltages. This facilitates the distribution of active power generated by the hybrid microgrid's sources while simultaneously addressing various power quality problems. In addition, a dynamic power management control approach enhances grid resilience by operating the hybrid microgrid in grid-connected and islanding modes. It provides uninterrupted and high-quality power supply to consumers during grid outages. The performance of this filter is comprehensively assessed through numerical simulations in MATLAB®/Simulink® environment. A real-time laboratory prototype is developed with WAVECT® WUC300 FPGA controller, demonstrating the practical application of the proposed filter. It ensures the minimum DC-offsets of 0.02V, fast convergence, and minimum oscillations. The grid synchronization and power quality index of the grid currents simultaneously achieve a THD of 2.82 %, complying with the IEEE-1547 and IEEE-519 standards. Importantly, the proposed adaptive-MGI filter outperforms the conventional SOGI and LMF filters in terms of nonlinear load tracking capabilities, with a response speed of less than 200μs, thereby highlighting its practical relevance and importance.

Performance evaluation of fuel cell based on a DC-DC boost converter through optimized MPPT controller

The current electric vehicle domain is increasingly focused on fuel cell technologies due to its flexibility, steady supply of power, low atmospheric pollution, increased startups, and rapid responses. Fuel cells exhibit nonlinear power versus current characteristics, making it challenging to extract maximum peak power from the fuel stack. To address this, this work introduces an adaptive Coati Optimization algorithm combined with a Tilt-integral-derivative (TID) controller (TID-ACOA) to find the maximum power point (MPP) of the fuel stack systems, ensuring maximum power extraction. The proposed MPPT controller is compared with other MPPT controller, including PI, TID, and TID-COA. Comprehensive evaluations are conducted on tracking current, voltage, maximum power extraction, MPPT controller efficiency, converter voltage settling time, and oscillations. The fuel stack’s low output voltages are enhanced using a boost DC-DC converter, and the entire fuel stack-fed boost converter systems is modeled using MATLAB/Simulink. Simulation result show that the TID-ACOA MPPT controller achieves higher MPP tracking efficiency compared to conventional controllers.

Comparative study of improved control strategies for DFIG in wind energy conversion systems: A dSpace real-time implementation approach

This research paper focuses on the comparison of two distinct strategies for direct power control (DPC) of a doubly fed induction generator (DFIG) in wind energy conversion systems (WECSs). The study places particular emphasis on algorithms based on low-pass filters for the estimation of stator and rotor flux, which have demonstrated good performance characteristics. Detailed theoretical analysis and implementation procedures of the proposed methods are presented. To evaluate and compare the performance of the control strategies, MATLAB/Simulink software is utilized for comprehensive analysis. The obtained results, both quantitative and qualitative, from this comparative analysis are expected to be of great interest to researchers engaged in the field of DFIG-based WECSs. Furthermore, real-time validation is conducted to demonstrate the effectiveness of the proposed control strategy, specifically focusing on the DPC approach based on stator flux estimation. A dSpace 1104 real-time card is employed and tested with a wind turbine emulator. The experimental results obtained through this validation process provide evidence of the efficiency and validity of the proposed control strategy. Overall, this research contributes to the advancement of DPC strategies for DFIG-based WECS by comparing and evaluating different control methods, providing in-depth theoretical analysis, and validating the proposed approach through real-time experimentation. The findings affirm the efficiency and effectiveness of the proposed control strategy, further establishing its value in practical applications.

Wind Speed Modeling under Quasi‐Linear Autoregressive Neural Network Model for Prediction of Production Power

Accurate wind speed modeling is beneficial for the design of wind energy conversion systems. Models of wind speed are used to assess the adequacy and dependability of a power supply. However, precise wind speed modeling is challenging due to the sporadic availability of wind speed. In this note, we propose a wind speed model with an autoregressive (AR) structure. A hybrid model is developed under linear and nonlinear parts based on a quasi‐linear autoregressive exogenous neural network (Q‐ARX‐NN). The model's structure is composed of a regression vector and its coefficients. The coefficients are divided into linear and nonlinear coefficients. A set of linear coefficients is identified under the algorithm of least square error (LSE), and a set of nonlinear coefficients is modeled by using a neural network to refine the residual error of the nonlinear part. Some artificial neural network (ANN) models can be set as nonlinear part sub‐models to sharpen the model's accuracy. The proposed model is tested for wind speed modeling to estimate wind energy production. Various nonlinear parts of the sub‐model are tested, such as neural networks, radial basis function networks, and ANN networks. Moreover, we evaluate the effects of the order of the model by varying hidden and output nodes, which can be summarized as the number of coefficients of the regression vector. Using specific wind turbine performance data, prediction models estimate production power. © 2024 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC.

A Recyclable Energy Storage Wood Composite with Photothermal Conversion Properties for Regulating Building Temperature

AbstractAddressing the challenges of energy storage liquid leakage and long‐term stability in energy storage is crucial for achieving sustainable energy efficiency. In this study, polymethyl methacrylate (PMMA) is innovatively employed as an encapsulation film on the surface of the wood‐based phase change material, resulting in a recyclable wood‐based composite energy storage material (PPW). A novel energy storage liquid (PCMs) composed of lauric acid (LA), capric acid (CA), and polyethylene glycol (PEG) is immersed in the pretreated porous wood frame through vacuum impregnation. The PCMs imparted a phase change temperature of 21.0 °C, which is close to human comfort levels, and a high energy storage efficiency of 31.6 J g−1 to the PPW. Additionally, the PCMs provided the PPW with a photothermal conversion efficiency of 29.3%. Even after 200 freeze‐thaw cycles, the energy storage properties of the PPW remained nearly unchanged. Therefore, utilizing PMMA as an effective encapsulation material is a viable approach to prevent leakage of the phase change solution and enhance the recyclability of the PPW. Furthermore, the transparency of PMMA preserves the natural appearance of the wood, thereby broadening the application potential of PPW in residential buildings, thermal energy storage, and solar thermal conversion systems.

Proton-Coupled Electron Transfer in Photoelectrochemical Alcohol Oxidation Enhanced by Nickel-based Cocatalysts.

Using biomass oxidation reactions instead of water oxidation reactions is optimal for accomplishing biomass conversion and effective hydrogen generation. Here, we report that Fe2O3 photoanodes with a NiOOH cocatalyst exhibit excellent performance for photoelectrochemical oxidation of 5-hydroxymethylfurfural (HMF) to 2,5-furandicarboxylic acid (FDCA). The conversion efficiency for HMF reaches 98.5%, while the selectivity for FDCA is 94.2%. We revealed that HMF is oxidized through a spontaneous proton-coupled electron transfer (PCET) process with the high-valent phase of the Ni-based catalyst. The dangling oxygen and bridging oxygen of the high-valent phase species serve as proton-accepting sites. Furthermore, we pointed out that the deprotonated bond dissociation free energy difference between the catalysts and alcohols is the thermodynamic trigger for the PCET process. This study provides a reasonable explanation for the alcohol oxidation reaction, which is beneficial for designing biomass conversion systems.

Insight into the Rate-Determining Step in Photocatalytic Z-Scheme Overall Water Splitting by Employing A Series of Perovskite RTaON2 (R = Pr, Nd, Sm, and Gd) as Model Photocatalysts.

Photocatalysis is an intricate process that involves a multitude of physical and chemical factors operating across diverse temporal and spatial scales. Identifying the dominant factors that influence photocatalyst performance is one of the central challenges in the field. Here, we synthesized a series of perovskite RTaON2 semiconductors with different A-site rare earth atoms (R = Pr, Nd, Sm, and Gd) as model photocatalysts to discuss the influence of the A-site modulation on their local structures as well as both physical and chemical properties and to get insight into the rate-determining step in photocatalytic Z-scheme overall water splitting (OWS). It is interesting to find that, with a decreasing ionic radius of the A-site cations, the RTaON2 compounds exhibit continuous blue shift of light absorption and a concomitant reduction in the lifetime of photogenerated carriers, revealing a significant influence of A-site atoms on the light absorption and charge separation processes. On the other hand, the A-site atomic substitution was revealed to significantly modulate the valence band positions as well as surface oxidation kinetics. By employing the Pt-modified RTaON2 as H2-evolving photocatalysts, the activity of photocatalytic Z-scheme OWS for hydrogen production on them is found to be determined by its surface oxidation process instead of light absorption or charge separation. Our results give the first experimental demonstration of the rate-determining step during the photocatalytic Z-scheme OWS processes, as should be instructive for the design and development of other efficient solar-to-chemical energy conversion systems.

Optimal Design and Analysis of High-Frequency Isolation Transformer for Switched-Mode Power Converters

High-frequency (HF) transformers have gained great interest in recent years due to the advent of powerful soft magnetic materials with low core loss in semiconductor power switches. Also, the optimal design of the HF transformer is a significant issue for high-performance energy conversion systems. In this paper, a 40W 50/12.5/25 V universal input and two output discontinuous-conduction mode (DCM) flyback transformer is designed by using mathematical calculations and analyzed via 3D ANSYS/Maxwell simulation including electromagnetic and loss analysis. It is shown that the simulation results accounting for hysteresis losses, eddy current losses, copper losses, and magnetic flux density determine the accuracy of the mathematical model calculation. Analyzes are performed at 100 kHz frequency levels. Results obtained will include core magnetic flux density, core/copper losses, leakage/magnetizing inductances, windings parasitic capacitances, input/output voltage, current values, and all design parameters. Finally, the proposed HF transformer's overall efficiency is calculated and presented. Significantly, the HF transformer achieves 97.8% efficiency thanks to the transformer's core and coil selection, B-H and B-P characteristics, one-to-one dimension design, and mesh operation. The dynamic and mathematical results of the designed transformer demonstrate the design and efficiency success

New design of robust controller based on fuzzy 12 linguistic variables for wind power conversion system

New design of robust controller based on fuzzy 12 linguistic variables for wind power conversion system