Improve System Efficiency Research Articles

Mini Review of Thermoelectric and their Potential Applications as Coolant in Electric Vehicles to Improve System Efficiency

Mini Review of Thermoelectric and their Potential Applications as Coolant in Electric Vehicles to Improve System Efficiency

Environmental impact of passenger car tire supply chain in Thailand using the life cycle assessment method

Although the tire industry contributes to Thailand's economy, every phase throughout its supply chain has the potential to harm the environment. A comprehensive understanding of all potential environmental impacts and a comparison study are effective approaches to the mitigation of such harm. This research applied a life cycle assessment (LCA) to analyze the detrimental effects of the Thai automotive tire supply chain, starting from rubber plantations, tire production and utilization stage until end-of-life tire handling. Two types of waste tire management technologies, namely, pyrolysis and reclaimed rubber, were compared to identify the optimal disposal option. The results found that both management technologies have negative values for almost every category as a result of the avoided impact from valuable products. The only exception is water consumption in pyrolysis. Global warming, terrestrial ecotoxicity, and fossil resource scarcity are significant benefits if end-of-life tires are recycled. When considered throughout the supply chain, reclaimed rubber yielded a superior negative value for the total score of terrestrial ecotoxicity and water usage. This demonstrates the advantage of reclaiming worn-out tires to replace traditional synthetic rubber, as opposed to pyrolysis, where the cumulative value remains positive. The uncompensated impact came from the higher impact of tire manufacturing and the use of tires. The use of gasoline and greenhouse emissions produced the most effects during the usage phase, while electricity consumption was the major contributor to tire manufacturing and waste tire disposal. As a result, waste tire management technology to recover valuable materials and power system efficiency improvement were suggested, along with research and development of a new tire model for diminishing gasoline consumption and air pollution. These strategies could mitigate the environmental impact and eventually enhance the sustainability of the tire supply chain.

태양광열-공기열원 하이브리드 히트펌프 축열조 온도 및 에너지 사용량 예측모델 개발

Purpose: This study aims to develop a predictive model for optimal control of a hybrid heat pump system using artificial neural network(ANN). The developed prediction model predicts the temperature of the heat storage tank and system energy consumption, and through this, it aims to improve system efficiency. Method: the target building was modeled using TRNSYS 18 simulation program, and data for 1 month for each heating and cooling were acquired to build a dataset for training and performance evaluating of the predictive model. Prediction models consists of three temperature prediction models and two energy consumption prediction models according to the heat sources used during the heating and cooling period. Result: All prediction models for the heating and cooling period showed satisfying performance in accordance to the accuracy criteria presented by ASHRAE. In addition, as a result of analyzing the error between the predicted value and the actual value, the stability of the prediction model demonstrated very low error value. In the future, the prediction model developed through this study will be applied to the optimal control algorithm to conduct demonstrative experiments.

Power Management Control of an Autonomous Photovoltaic/Wind Turbine/Battery System

The study presents an optimal control approach for managing a hybrid Photovoltaic/Wind Turbine/Battery system in an isolated area. The system includes multiple energy sources connected to a DC bus through DC/DC converters for maximum power point tracking. The proposed hybrid MPPT approach (HMPPT) manages the energy production from different sources, while the power flow method is used to balance the load and renewable power. The study shows that integrating the HMPPT algorithm and power flow approach results in improved system performance, including increased power generation and reduced stress on the batteries. The study also proposes an accurate sizing method to further improve system efficiency. The study demonstrates the effectiveness of the proposed approach by presenting results for twelve different days with varying weather conditions. The results show that the proposed approach effectively manages the energy production and load, resulting in optimal system performance. This study provides valuable insights into the optimal control of hybrid renewable energy systems, and highlights the importance of considering different energy sources and optimal sizing for maximizing system efficiency.

Impact of Integration of FO Membranes into a Granular Biomass AnMBR for Water Reuse

The granular sludge based anaerobic membrane bioreactor (G-AnMBR) has gained emphasis in the last decade by combining AnMBR advantages (high quality permeate and biogas production towards energy positive treatment) and benefits of granular biomass (boosted biological activity and reduced membrane fouling). With the aim to further reduce energy costs, produce higher quality effluent for water reuse applications and improve system efficiency, a forward osmosis (FO) system was integrated into a 17 L G-AnMBR pilot. Plate and frame microfiltration modules were step by step replaced by submerged FO ones, synthetic wastewater was used as feed (chemical oxygen demand (COD) content 500 mg/L), with hydraulic retention time of 10 h and operated at 25 °C. The system was fed with granular biomass and after the acclimation period, operated neither with gas sparging nor relaxation at around 5 L.m-2.h-1 permeation flux during at least 10 days for each tested configuration. Process stability, impact of salinity on biomass, the produced water quality and organic matter removal efficiency were assessed and compared for the system working with 100% microfiltration (MF), 70% MF/30% FO, 50% MF/50% FO and 10% MF/90% FO, respectively. Increasing the FO share in the reactor led to salinity increase and to enhanced fouling propensity probably due to salinity shock on the active biomass, releasing extracellular polymeric substances (EPS) in the mixed liquor. However, above 90% COD degradation was observed for all configurations with a remaining COD content below 50 mg/L and below the detection limit for MF and FO permeates, respectively. FO membranes also proved to be less prone to fouling in comparison with MF ones. Complete salt mass balance demonstrated that major salinity increase in the reactor was due to reverse salt passage from the draw solution but also that salts from the feed solution could migrate to the draw solution. While FO membranes allow for full rejection and very high permeate purity, operation of G-AnMBR with FO membranes only is not recommended since MF presence acts as a purge and allows for reactor salinity stabilization.

Efficiency analysis of a novel reversible solid oxide cell system with the secondary utilization of the stack off-gas: A model-based study

Systems with reversible solid oxide cells (rSOCs) can potentially overcome the spatio-temporal mismatch between intermittent generation from renewables and continuous electricity demand by operating bi-directionally. Achieving high energy conversion efficiency is one of the critical design objectives for a typical rSOC system. However, only a few papers discuss the effect of parameters and system processes on efficiency, and thermal management designs considering gas flow rates of the fuel and air loops are not yet seen. This work presents a novel rSOC-based system that employs a heat recovery unit for absorbing thermal energy as parasitic power gain and a water-gas heat exchanger instead of the electric evaporator to utilize the stack off-gas secondarily. Modeling and efficiency analysis of such a system is performed using a physically finite element method-based rSOC stack model coupled with extra auxiliary component models. Results indicate that efficiencies of 92%, 71.1%, and 62.4% can be achieved at 1,023 K and 1.23 bar in electrolysis, discharge, and the round-trip, respectively. The parasitic gain can significantly improve system efficiency and output performance and reduce the power loss in regulating the temperature uniformity of the stack with increased airflow. The outcomes can serve as guidelines for the thermal management design of real rSOC systems and control strategies optimization.

Dynamic scheduling with uncertain job types

Uncertain job types can arise as a result of predictive or diagnostic inaccuracy in healthcare or repair service systems and unknown preferences in matching service systems. In this paper, we study systems with multiple types of jobs, in which type information is imperfect and will be updated dynamically. Each job has a prior probability of belonging to a certain type which may be predicted by data, models, or experts. A job can only be processed by the right machine, and a job assigned to the wrong machine must be rescheduled. More information is learned from the mismatch, and job type probabilities are updated. The question is how to dynamically schedule all jobs so that they can be processed in a timely fashion. We use a novel coupling and inductive method to conduct optimality analysis. We obtain the near-optimal policy regarding completion time, named the less-uncertainty-first policy, when there are two types of jobs; the insights it yields are used to develop heuristic algorithms for more general cases. We also consider other objectives, including the number of mismatches and the total amount of time jobs spend in the system. In our numerical study, we examine the performance of the proposed heuristics when there are more than two types of jobs under two learning schemes: dedicated learning and exclusive learning. In the extension, we also analyze an online version of the problem in which jobs arrive sequentially to the system and must be assigned immediately and irrevocably without any knowledge of future jobs. We analyze the competitive ratios of different scheduling policies and find similar insights. It is essential that managers dynamically schedule services by leveraging predictive information and knowledge learned from mismatches. Our proposed less-uncertainty-first policy, which accounts for system dynamics to avoid mismatches and resource idling, can be used to improve system efficiency in various contexts.

Design and thermodynamic analysis of solid oxide fuel cells–internal combustion engine combined cycle system based on Two-Stage waste heat preheating and EGR

The integrated solid oxide fuel cell (SOFC)-internal combustion engine (ICE) hybrid system has attracted more and more attention due to its advantages of high efficiency and good response ability. Combined with waste heat recovery (WHR) strategy, the system energy conversion efficiency can be further improved. In this study, a new integrated hybrid power system consisting of SOFC and pilot diesel micro-ignition natural gas engine, with WHR strategy was designed and analyzed. Firstly, the mathematical modeling of each component was established and compared with the experimental results to ensure the reliability of the simulation results. Moreover, the effects of key operating parameters and natural gas mixing with an appropriate amount of hydrogen on improving system efficiency and exergy efficiency were also explored. The results showed that the efficiency of the combined system was higher than each component and improved with the increase in the power distribution ratio of the SOFC and ICE, while descended with the decrease of fuel utilization of the SOFC. Anode exhaust of SOFC had a similar effect on the engine as exhaust gas recirculation, which can significantly reduce NOx emissions. In addition, when the SOFC and ICE had equal power distribution with fuel utilization of 0.7, with adding a 25% hydrogen volume ratio, the exergy efficiency and thermal efficiency of the system increased by 6.01% and 5.8% respectively.

A Study and Implementation of Inductive Power Transfer System Using Hybrid Control Strategy for CC-CV Battery Charging

In this paper, a hybrid control strategy is studied and implemented on an Inductive Power Transfer (IPT) system to simultaneously realize zero-voltage switching (ZVS) and constant current (CC) and constant voltage (CV) battery charging. A steady-state analysis of pulse frequency modulation was conducted, based on the characteristic of voltage gain versus switching frequency, and CC and CV charging modes were promised. The ZVS of the inverter was obtained by satisfying the minimum requirement of full discharge of the junction capacitor on the MOSFETs using a commutation current during the dead-time interval. Two control degrees of freedom are needed to realize the two control targets. This hybrid control strategy adopts a self-oscillating (SO) control to achieve ZVS and phase shift (PS) control and a constant output for the series–series (SS)-compensated IPT system. To validate the hybrid control strategy, a 1.6 kW prototype with 360–440 V input voltage and 250–400 V output voltage was built and the experimental results show that the peak efficiency can reach 96.1%. Compared with the conventional variable frequency (VF) control, the hybrid control method proves that an additional control variable can fulfill the control target in a more flexible manner, which makes the switching frequency close to the resonant frequency during the charging process, minimizing the reactive current in the resonant tank and improving system efficiency.

Capacity control of a cascade multi-purpose heat pump using variable speed compressor

Cascade multi-purpose heat pumps are designed to concurrently meet the hot water (HW) and cooling needs, and the HW and heating demands of buildings. However, the capacity of heat pumps deteriorates as the building load increases. At such conditions, the capacity of the heat pump needs to be enhanced to ensure that its rated value is maintained. This study examines the adoption of a variable speed compressor in the low-stage (LS) of a water source cascade multi-purpose heat pump for capacity control at different outdoor conditions in many operating modes. The study showed that the variable speed compressor is highly reliable for the capacity control of the cascade multi-purpose heat pump in all operating modes at varying outdoor temperature conditions. However, the variable speed compressor to be adopted for the capacity control of the cascade multi-purpose heat pump should have a higher capacity and wider range of compressor speeds to meet the rated capacity of the cascade multi-purpose heat pump at severe outdoor temperature conditions in HW mode and heating-HW mode. Furthermore, the variable speed compressor should be installed in the low stage cycle and hot water cycle to ensure precise capacity control, improved system efficiency and energy savings.

A Resonant DC-Link Inverter and Its Voltage Compensation Strategy

In order to solve the output voltage loss problem caused by the zero-voltage notch of resonant dc-link (RDCL) inverter and improve system efficiency, this article proposes an RDCL inverter and its voltage compensation method. The topology of this auxiliary circuit is simpler, and the resonant current is separated from the load current by parallel auxiliary switch, which reduces the current stress of the main switches. At the same time, the method is based on the conventional sinusoidal pulsewidth modulation (SPWM); this method first calculates the operation time of the auxiliary circuit based on the magnitude of the phase current, second adjusts the position of the triangular carrier according to the calculation results, and finally generates the driving signals for early turn-on and delayed turn-off, which solves the voltage loss problem and improves the voltage utilization, the output voltage is the same as that of the ideal SPWM. The working principle, parameter design conditions, and voltage compensation method are analyzed in detail in the article. Finally, a 5-kW/16 kHz prototype is created with insulated gate bipolar transistor (IGBT) as switching device, which verifies the novel resonant dc-link inverter and its modulation strategy is effective.

Hybrid-Modulation Hysteresis Scheme Based Decoupled Power Control of Grid-Connected Inverter

Most existing power control methods for grid-connected inverter are implemented in synchronous reference frame. In order to achieve soft-switching operation, those methods usually need additional design considerations, which could introduce complex computation. This article presents a control strategy for single-phase grid-connected inverter system with LCL filter that can be used for grid-connected battery/photovoltaic (PV) system, with the target to implement decoupled active and reactive power control capability in stationary frame and achieve soft-switching behavior for higher efficiency. In order to improve system efficiency, a new hybrid-modulation-based hysteresis current scheme is used to achieve soft-switching while improving the inherent zero-crossing distortion issue existing in traditional unipolar hysteresis current control. Multiproportional and resonant compensators are utilized to mitigate output low-frequency distortions further, together with a capacitor current feedback-based active damping design embedded in an inner loop. The proposed controller also demonstrates good robustness and immunity to distorted grid conditions. Simulation and experimental results are presented in this article with essential theoretical analysis to verify the validity of the proposed control strategy.

Toward Intelligent and Efficient 6G Networks: JCSC Enabled On-Purpose Machine Communications

Driven by the vision of "intelligent connection of everything" towards 6G, the collective intelligence of networked machines can be fully exploited to improve system efficiency by shifting the paradigm of wireless communication design from naive maximalist approaches to intelligent value-based approaches. In this article, we propose an on-purpose machine communication framework enabled by joint communication, sensing and computation (JCSC) technology, which employs machine semantics as the interactive information flow. Naturally, there are potential technical barriers to be solved before the widespread adoption of on-purpose communications, including the conception of machine purpose, fast and concise networking strategy and semantics-aware information exchange mechanism during the process of task-oriented cooperation. Hence, we discuss enabling technologies complemented by a range of open challenges. Simulation result shows that the proposed framework can significantly reduce networking overhead and improve communication efficiency.

Construction and concentrating performance of a critically truncated compound parabolic concentrator without light escape

Conventional solar CPC (Compound Parabolic Concentrator, CPC) has a limited collection of solar radiation at the end of the concentrating surface, which is not conducive to its wide application. In the present research, a solar CT-CPC (Critically Truncated CPC, CT-CPC) without light escape is proposed and constructed for the vacuum tube absorber, and discusses its optical properties, which provides a choice for improving or reforming the existing CPC system. Based on the edge ray principle, the geometric model of the CT-CPC is designed by the dichotomy method, and the concentrating performance of the CT-CPC is verified by the adjustable laser experiment. The study found that the average optical efficiency of CT-CPC reaches 47.84% and is 7.2% higher than the traditional S-CPC (Standard CPC, S-CPC) without light escape at the same aperture, and the energy flux distribution on the absorber surface is also more uniform, which is beneficial to improving system efficiency. The effective working hours of CT-CPC is higher than the S-CPC in the whole year, and the average effective working hours is 8.8 h and 5.7 h, respectively. The total annual radiation collection of CT-CPC is 3397 MJ/m2, which is 11.2% higher than the S-CPC. Furthermore, the economic analysis shows that solar CT-CPC has significant advantages and more friendly engineering application potential.

MODI: A Structured Development Process of Mode-Based Control Algorithms in the Early Design Stage of Building Energy Systems

The growing share of renewable energy sources in building energy systems leads to more complex energy conversion and distribution systems. The current process of developing appropriate control functions for energy systems is insufficient and consequently error-prone. Regarding this problem, a new method is expected to systematically develop appropriate control functions for buildings and reduce design errors in this process. This paper introduces the MODI method, aiming at a structured development process of mode-based control algorithms to reduce errors in the early design stages of buildings. A complete framework and a standardized application process of the MODI method will be established to systematically design mode-based control algorithms described through signal-interpreted Petri nets. Furthermore, we performed a simulation-assisted evaluation approach to test and improve the performance of the control algorithms generated by MODI. In a case study, we applied MODI to develop a mode-based control strategy for an energy system containing heating and cooling supply networks. The desired control strategy was tested and tuned in a simulation phase. Compared to a reference control, the mode-based control algorithm shows an improvement in system efficiency by 4% in winter and 8% during the transitional season phase.

An Improved Energy Management Strategy of Diesel-Electric Hybrid Propulsion System Based on FNN-DP Strategy

Diesel-electric hybrid propulsion system (HPS) is widely applied for shunting locomotive due to the characteristics of flexible configuration, economic and environmental protection in the world. Energy management strategy (EMS) is an important design factor of HPS that can optimize the energy distribution of each power sources, improve system efficiency, and reduce fuel consumption. In this paper, the model of HPS for shunting locomotive and system operating profile are firstly carried out. Then the EMS consist of the conventional rule-based (RB) strategy rule, and a fuzzy neural network base on dynamic programming (FNN-DP) strategy are studied. Finally, the simulations were carried out with these EMSs in the system model at full operating conditions to derive the fuel consumption. The conclusion is that the theoretical optimal solution of DP provides reference and guidance for the fuzzy neural network strategy to improve the rules, and the fuel consumption of the FNN-DP strategy is 10.2% lower than the conventional RB strategy.

The Possibility of Using Superconducting Magnetic Energy Storage/Battery Hybrid Energy Storage Systems Instead of Generators as Backup Power Sources for Electric Aircraft

The annual growth rate of aircraft passengers is estimated to be 6.5%, and the CO2 emissions from current large-scale aviation transportation technology will continue to rise dramatically. Both NASA and ACARE have set goals to enhance efficiency and reduce the fuel burn, pollution, and noise levels of commercial aircraft. However, such radical improvements require radical solutions. With the current traditional aircraft designs based on gas turbines or piston engines, these goals are infeasible. Small-scale aircraft have successfully proven emission reductions using energy storage systems, such as Alice aircraft. This paper involves an investigation of the possibility of using superconducting magnetic energy storage (SMES)/battery hybrid energy storage systems (HESSs) instead of generators as backup power sources to improve system efficiency and reduce emissions. Two different power system architectures of electric aircraft (EA) were compared in terms of reliability and stability in a one-generator failure scenario. As weight is crucial in EA designs, the weights of the two systems were compared, including the generators and energy storage systems. The two EA systems were built in Simulink/MATLAB to compare their reliability and stability. With the currently available technologies, based on the energy density of 250 Wh/kg for lithium-ion batteries and a power density of 8.8 kW/kg for generators, the use of the generators as backup sources proved more efficient than the use of HESS. The break-even point was observed at 750 Wh/kg for battery energy density. Any value more than the 750 Wh/kg energy density makes HESS lighter and more efficient than generators.

Design and Implementation of Embedded Controller-Based Energy Storage and Management System for Remote Telecom

The source of energy extracted in renewable form has turned out to be a primary mainstream energy source, especially in the telecom sectors. Rapid growth of renewable sources has led to telecom operators concentrating more on designing the system with appropriate energy storage elements, providing control facilities, improving system efficiency and verifying uninterrupted power supplies. Therefore, this paper gives a novel approach of utilizing embedded control in energy generation consisting of a solar-wind hybrid energy system placed in isolated areas. For the purpose of integration of wind, together with the solar energy sources, into an increasingly efficient system, a single Cuk-Luo integrated DC-DC converter has been put forward. The proposed system has been modeled using MATLAB/Simulink and verified under various combinations of solar-wind energy sources without compromising the required power. In order to verify the proposed Cuk-Luo integrated converter with the energy management controller system, a prototype hardware is implemented and tested.

Power Quality Monitoring and Feedback Control for Hybrid Renewal Energy System using Meta Heuristic Optimization Technique

Solar and wind energy are becoming more popular. Hybrid Renewable Energy System (HRES) is a fast-growing power industry segment. Power quality (PQ) issues have increased as renewable energy has increased in the electricity supply. This study will help electrical engineers identify power quality (PQ) disruptions from hybrid renewable power sources like solar and wind. The investigation will predict powergeneration-induced PQ problems. A self-contained Hybrid Renewable Energy System (HRES) is the project’s main goal. We will collect and analyses energy system data using Grey Wolf Optimization to improve mitigation and reduce PQ interruptions. The suggested technique analyses live data from several sources and historical data in many formats. To prevent problems, the hardware’s controllers will receive the data. Algorithms and designers will improve system efficiency and design ability. The monitoring system will predict PQ disturbances caused by electricity generation from different energy sources. The suggested device labels PQ disturbances by impact.

A mechanism to ensure identity-based anonymity and authentication for IoT infrastructure using cryptography

The spread of the Internet of Things (IoT) has caused a variety of devices to communicate with one another, producing enormous volumes of data and nurturing a linked ecosystem. However, the privacy of users, the integrity of the data, and secure authentication are seriously jeopardised by this link. In this context, we suggest a unique technique that makes use of identity-based anonymity and cryptographic authentication in IoT infrastructure in order to solve these problems.In order to facilitate safe communications between IoT devices, users, and service providers, our proposed mechanism creates a third-party authenticated protocol. This anonymity protection reduces the danger of unauthorised tracking and data exploitation by securing user names and usage patterns from possible attackers.The proposed system ensures the integrity and confidentiality of data transmitted between IoT devices and service providers by utilising sophisticated encryption algorithms. Additionally, it simplifies the authentication procedure, improving system efficiency overall without sacrificing security. The proposed technique into practise and assessed it using real-world IoT infrastructure scenarios, showcasing how well it protects user privacy and ensures safe communication. The findings show that the mechanism has a low computing cost and can withstand a range of security threats, making it a viable option for identity-based anonymity and authentication in IoT networks. Our approach makes a significant contribution to protecting user data and encouraging trustworthy interactions in IoT infrastructure as the IoT environment continues to grow.