Improve System Energy Efficiency Research Articles

Investigation of Sliding Mode Control in the Nonlinear Modeling of Cordless Jigsaws

The aim of this paper was to reduce the current spikes in battery-powered saw motors by designing and implementing a sliding mode model-following adaptive controller. The proposed controller reduces overcurrent consumption, improves system energy efficiency, and effectively maximizes battery runtime, especially under high-load conditions. By applying nonlinear compensation techniques, the controller can ensure smooth motor operation, reduce mechanical stress, and prolong tool life. The results showed that this control strategy is particularly suitable for hand tools, where a long battery life is essential for efficient operation.

Performance Analysis of Parallel Free-Space Optical/Radio Frequency Transmissions in Satellite–Aerial–Ground Integrated Network with Power Allocation

Satellite–aerial–ground integrated networks (SAGINs) combined with hybrid free-space optical (FSO) and radio frequency (RF) transmissions have shown great potential in improving service throughput and reliability. The coverage mismatch and rate limitation of traditional hybrid FSO/RF design have restricted its development. In this paper, we investigate the performance of parallel FSO/RF transmissions in SAGIN, taking into account the effect of weather conditions and the quality of service (QoS) of ground users. A three-hop relay system is proposed, where the FSO and RF links jointly provide services to ground users in remote areas. Specifically, considering the limited transmit power of the relay node, we have studied the optimal power allocation between parallel FSO and RF links to further improve system energy efficiency. The performance of the proposed system is evaluated in terms of capacity outage probability, weighted average bit-error rate (BER), and energy efficiency. Moreover, asymptotic capacity outage probability is also derived to obtain more engineering insights. Finally, numerical results show that the energy efficiency of the proposed parallel scheme improves by 30.9% compared to only the FSO scheme at a total transmit power of 15 dBW.

Dynamic simulation of wind-powered alkaline water electrolysis system for hydrogen production

Alkaline water electrolysis (AWE) is a mature and cost-effective technology, especially suited for large-scale deployment, yet faces challenges in adapting to the dynamic nature of renewable energy sources. Evaluating AWE's adaptability to fluctuating renewable energy inputs is crucial. This study introduces a dynamic model to assess the influence of wind energy on a 250 kW industrial-scale AWE system for hydrogen production. This paper pioneers the utilization of Aspen Plus Dynamics for dynamic modeling, offering a comprehensive approach that incorporates all vital components and controllers of the balance of plant, such as gas-liquid separator, heat exchangers, deionized water supply, pumps, and the cooling loop. This methodology allows comprehensive simulation at the system level, revealing the real dynamic characteristics of the system under fluctuating wind energy conditions. Due to the absence of a dedicated module for AWE in Aspen Plus Dynamics, an integrated dynamic operation unit for the electrolyzer is constructed using Aspen Custom Modeler. The study analyzes the dynamic characteristics of the AWE system, specifically focusing on temperature, voltage, and liquid level. The study compares two temperature control strategies, before-stack and after-stack, with the refined after-stack method effectively addressing over-temperature issues and improving system energy efficiency by 1.44%.

Stability analysis and multi-objective optimization of methanol steam reforming for on-line hydrogen production

The potential solution to hydrogen storage and transportation challenges is provided by liquid fuel-based on-line hydrogen production. An online hydrogen production device has been constructed and the stable output of hydrogen at 6.8 bar under dynamic conditions of 6–13 Nm3/h has been achieved. To achieve optimal economic and thermodynamic performances, the mathematical models for mass, energy, and techno-economics are constructed based on field test data. The Non-Dominated Sorting Genetic Algorithm is employed to update temperature splitting points between multi-stage heat exchangers, targeting multi-objective optimization of heat exchange area, system energy efficiency, and annual average cost. Pareto optimal solutions indicate that such optimization can improve system energy efficiency by 0.03%–3.76% and decrease the hydrogen production cost from 0.004 $/kg to 0.599 $/kg. This work demonstrates the feasibility and effectiveness of multi-objective optimization for online hydrogen production system design and offers important guidance for decision-making in heat exchange network schemes.

Energy, exergy, economic, and environmental analyses and optimization of a multigeneration system considering high-temperature island environment

Renewable energy based multigeneration systems help satisfy the diverse demand for marine resources exploration in off-grid island area, where the storage of fluctuating renewable energy for continuous power supply becomes necessary. Therefore, this paper proposes a solar-driven multigeneration system for island environment integrated with energy storage and production of electricity, cooling, heating, and freshwater. The system comprises an ejector power subsystem, a multiple-effect distillation subsystem, and a CO2 binary mixture-based compressed gas energy storage subsystem. The system performance from the perspectives of energy, exergy, economics, and environment, as well as the impact on performance of the working fluid and several key system parameters, are investigated in this paper. According to the results, an increase in the mass fraction of organic in the CO2 mixture leads to an improvement in system energy efficiency and exergy density at the cost of lower system power efficiency. Increasing the high-pressure tank pressure enhances system performance except for system power efficiency. Increased low-pressure tank pressure leads to improved system energy efficiency and exergy density, accompanied by lower system power efficiency and exergy efficiency. When the ambient temperature increases from 298 K to 303 K, the system energy efficiency noticeably decreases, whereas an increase in direct normal irradiance improves various system performance indicators. Among several mixtures, CO2/R32 mixture was chosen for further analysis and optimization for its wider operating range with R32 mass fraction and better system performance. The optimal operating point had system energy efficiency, exergy density, and modified levelized cost of energy of 1.281, 22.216 kWh/m3, and 0.131 $/kWh, respectively. The proposed system in this research is proven to be a novel technical solution to meet the diverse energy demands on unique island environments.

Low‐power multibit delta–sigma modulator based on passive and unattenuated summation scheme

AbstractA low‐power multibit delta–sigma modulator (DSM) based on a passive and unattenuated summation scheme is proposed. The summation circuit achieves multiplication of the voltage signal carried on the summation capacitor through a bidirectional sampling technique, thereby compensating for the inherent attenuation caused by passive summation, which eliminates the need for an active operational transconductance amplifier (OTA) to achieve perfect summation. Here, a second‐order DSM based on a 4‐bit first‐order passive noise‐shaping (NS) SAR quantizer is employed to satisfy the SNDR requirements exceeding 100 dB, which validates the reliability of the summation scheme. In addition, a cascoded floating inverter amplifier (FIA) is used as the core OTA to further improve system energy efficiency. Simulation results demonstrate that at a supply voltage of 1.2 V and a bandwidth of 20 kHz, the SNDR reaches 102.62 dB, power consumption is only 148.32 μW, and the Schreier figure‐of‐merit (FoM) of the SNDR is 183.92 dB. The results demonstrate that the proposed DSM has considerable potential for widespread application in the audio domain.

Solar-blind ultraviolet emission-detection monolithic integration of AlGaN multiple-quantum-well diodes via concentric ring-circle configuration

AlGaN multiple-quantum-well diode-based solar-blind ultraviolet emission-detection monolithic integration system shows great application value due to its advantages of multifunctionality, secure communication, and anti-interference ability. To reduce the lateral optical propagation loss and improve the emitting light detection efficiency, we have proposed a concentric ring-circle configuration for the system, where the out-ring light-emitting diode is the emitter at 253 and 267 nm, and the inner-circle detector is the receiver. The out-ring light-emitting diode exhibits about twice the injection current at the same bias and slightly higher light output power at the same current due to better current spreading and sidewall light extraction compared to the conventional square–square configuration. Simultaneously, the concentric inner-circle detector maximizes the collection of the emitted light flux. Under the emission-detection mode for the monolithic integration system, compared to the conventional square–square configuration, the concentric ring-circle design presents an improvement in the ratio of emitter injection current to detector output photocurrent and higher output signal amplitude under the same transmission work mode, demonstrating the improved system energy and coupling efficiency. This design provides a potential approach to achieve low power consumption and high bandwidth in the monolithic integrated optoelectronic chips.

Verification of a Modeling Toolkit for the Design of Building Electrical Distribution Systems

DC electrical distribution systems offer many potential advantages over their AC counterparts. They can facilitate easier integration with distributed energy resources, improve system energy efficiency by eliminating AC/DC converters at end-use devices (e.g., laptop chargers), and reduce installation material, time, and cost. However, DC electrical distribution systems present additional design considerations, largely resulting from potentially greater magnitude and variation in cable losses. Modeling and simulation are rarely used to design such systems. However, the greater dependency of DC system energy efficiency on design choices such as distribution voltages, architecture, and integration of PV and BESS suggests that modeling and simulation may be required. Such system performance analysis is currently not a standard practice, in part due to limited availability and validation of capable software tools. This paper characterizes the accuracy of a Modelica-based Building Electrical Efficiency Analysis Model (BEEAM) toolkit, as a precursor for validating its use to perform system performance analysis and inform design decisions. The study builds upon previous verification research by characterizing complete systems comprised of commercially available equipment, and providing a more detailed analysis of simulation results. Five lighting systems with varying electrical distribution architectures were designed using market-available equipment, installed in a laboratory environment, modeled using BEEAM, and simulated using three Modelica integrated development environments (IDEs). Simulated and measured results were compared to characterize toolkit accuracy. Initial results revealed that simulated performance was mostly within ±5% of measured system-level and device-level performance. While simulation results were not found to be dependent on the IDE, some Modelica compiler interoperability issues were identified. Although the BEEAM toolkit showed promise for the targeted use case, further work is needed to determine whether the demonstrated 5% accuracy is sufficient for making real-world design decisions, and for BEEAM to advance from an interesting research tool to one that can impact real-world building projects.

Efficient Power Conversion Using a PV-PCM-TE System Based on a Long Time Delay Phase Change With Concentrating Heat

Based on the characteristics of phase change concentrated heat, this paper proposes a photovoltaic/phase change/thermoelectric (PV-PCM-TE) self-supply system with sidewall integrated TE. In the system, an intelligent control circuit for phase change time is designed to intelligently switch the TE working mode using real-time temperature tracking. Therefore, the phase change time of the phase change material (PCM) is delayed with enhanced heat absorption and storage capacity, resulting in greater suppression of the PV temperature rise. Based on the constant temperature difference during the delayed phase change, more electrical power output can be obtained with integrated multistage thermoelectric generators (TEG) in the sidewall of the PCM container. With the supplementary TEG energy injected into the PV battery, a complete self-powered design is constructed, leading to improved system energy efficiency. Experimental results show that compared with the PV-PCM-TEG system, the PCM phase change time of the proposed system is extended by 15 min, where the peak PV temperature after suppression is only 68.5 °C, which is 8 °C lower than that of the conventional PV-TEG-PCM system. The conversion efficiency of the entire system reached 30.26%, an improvement of 43.15%. The proposed self-powered PV-PCM-TE power conversion system with a long-time delay and high efficiency can operate during both day and night, providing a green scheme for intelligent low-power electrical systems.

Multi-objective optimization of energy-saving measures and operation parameters for a newly retrofitted building in future climate conditions: A case study of an office building in Chengdu

The energy-saving measures and suitable operation parameters will be urgent concerns in future global climate change conditions. However, a critical review revealed that most studies considered upgrading the wall insulation and glazing in the design process or the retrofit stage for existing buildings built before the twenty-first century and neglected improving system energy efficiency and operation of newly retrofitted buildings with higher-performance envelopes in the context of the carbon peak and carbon neutrality. Therefore, a real and newly retrofitted office building in Chengdu was investigated. The effect of indoor cooling and heating temperature setpoints, water supply/return temperature setpoints for the air-conditioning system, night ventilation settings in summer, and renewable energy variables (photovoltaic) are considered in the optimization. The simulation model was validated using the monitored heating and cooling energy consumption. Transient system simulation coupled with jEPlus + an evolutionary algorithm and the non-dominated sorting genetic algorithm were used to explore the optimal solution to reduce carbon emission and energy consumption while ensuring acceptable indoor thermal comfort. The sensitivity analysis showed night ventilation duration and the air change rate had significant effects on carbon emission reduction. The annual carbon emission reduction of the building was 46500–58500 kg from 2030 to 2060 using a photovoltaic panel area of 1000 m2. The indoor temperature setpoint decreased over time due to the increasing outdoor temperature in the future. Moreover, the building energy system showed a better performance when the air source heat pump cooling setpoint was increased from 7 °C to 9 °C. Decreasing the air source heat pump heating setpoint from 45 °C to 42.5 °C for 2030 and 2060, and from 45 °C to 40 °C for 2040 and 2050 were the optimal solutions. The proposed approach provides guidance for operators to optimize energy savings and operation parameters under future climate conditions.

Integrated energy system operation considering building thermal inertia and hydrogen storage systems

(1) An IES operation optimization system considering building thermal inertia and hydrogen energy storage systems is formed. (2) A hybrid particle swarm optimization-cuckoo search based on the beetle antennae search strategy (BPSO-CS) is proposed.

Energy-Aware Relay Optimization and Power Allocation in Multiple Unmanned Aerial Vehicles Aided Satellite-Aerial-Terrestrial Networks

With the explosive growth of various connected devices and the supported services, the satellite-aerial-terrestrial network (SATN) can fulfill the requirements of the increasing data traffic with enlarged coverage and enhanced capacity. In particular, utilizing multiple unmanned aerial vehicles (UAVs) as relays in the SATN holds great promise for bringing lots of benefits in terms of high flexibility and high reliability. However, due to the limited power of UAVs and the long distance of the aerial-satellite links, how to improve system energy efficiency (EE) is still a challenging issue since existing works mainly paid their attentions to resource while neglecting relay strategy optimization among multiple UAVs. Toward this end, in this article we explore the problem of system EE maximization through jointly optimizing relay selection and power allocation as well as UAV deployment. An iterative algorithm is presented as our solution via alternately leveraging coordinate ascent and Lagrangian dual decomposition methods. Extensive simulation results demonstrate that our devised optimization strategy can significantly improve system EE and obtain the optimal relay selection and power allocation decisions.

Optimal Task Offloading and Resource Allocation for C-NOMA Heterogeneous Air-Ground Integrated Power Internet of Things Networks

By combining information communication technology with power grid, the smart grid-oriented Power Internet of Things (PIoT) has become a critical technology to guarantee the safe and reliable power grid operation and improve system energy efficiency. Nevertheless, PIoT devices have only limited communication and computing resources since they are mostly deployed in remote areas that may be out of service coverage of existing terrestrial 5G networks. To overcome the resource limitation, we leverage Air-Ground Integrated C-NOMA Heterogeneous PIoT Networks (PAGIC HetNets), and study the core challenges in PAGIC HetNets. As PIoT devices are normally powered by battery, we aim at minimizing the energy consumption of PIoT devices and thoroughly investigate the problem of task offloading and resource allocation with minimal energy consumption. This problem belongs to a mixed integer nonlinear programming (MINLP) with extra difficulty that the long-term queuing delay and short-term constraints are coupled. To tackle the difficulty, we use Lyapunov optimization to transform this hard problem into three subproblems. The first subproblem is task splitting and local computing resource assignment at the PAGIC user side, which we solve with the Lagrangian multiplier method. The second subproblem is queue-aware channel reusing, and matching theory is adopted to solve it. The third subproblem is optimizing the aerial server resource allocation, for which we propose a greedy-based solution. Numerical simulations demonstrate that our approach can obtain excellent performance in terms of energy consumption, spectrum efficiency, task backlog, and queuing delay with lower complexity compared with several benchmark methods.

Geometry effect of phase change material container on waste heat recovery enhancement

Waste heat recovery from industrial exhaust gases is a key method to reduce fuel consumption and improve system energy efficiency. Phase change materials (PCMs) are one of the major media in the waste heat storing and recovering processes. The PCM container geometry is a crucial design factor but attracts less attention for its effect on the PCM melting and heat storage operation. This study simulates the melting behaviour and heat storage performance in the PCM storage containers with the same cross area but different configurations with the rectangular shape and ones with concave folded sidewalls and protruding folded sidewalls. The geometry variation on PCM containers influences both the contact area with the hot airflow and natural convection in the melting phase of PCMs. The three-dimensional transient modelling indicates that the natural convection currents enhance the PCM melting and thermal storage rates. The PCM container design angle, α, shows a remarkable impact on the natural convection strength, PCM melting time, and energy storage rate. The protruding-shaped container with α at 133.8∘ presents the least melting time of 4,645 s, reducing 24.9% of the melting time in comparison to the rectangular chamber as the baseline with α= 90 ∘. The study can inspire the design of PCM storage geometries with efficient waste heat recovery in the industrial applications.

Energy Efficiency Optimization for SWIPT-Enabled IoT Network with Energy Cooperation.

As an advanced technology, simultaneous wireless information and power transfer (SWIPT), combined with the internet of things (IoT) devices, can effectively extend the online cycle of the terminal. To cope with the fluctuation of energy harvesting by the hybrid access points (H-AP), the energy cooperation base station is introduced to realize the sharing of renewable energy. In this paper, we study the SWIPT-enabled IoT networks with cooperation. Our goal is to maximize the energy efficiency of the system, and at the same time, we need to meet the energy harvesting constraints, user quality of service (QoS) constraints and transmission power constraints. We jointly solve the power allocation, time switching and energy cooperation problems. Because this problem is a nonlinear programming problem, it is difficult to solve directly, so we use the alternating variable method, the iterative algorithm is used to solve the power allocation and time switching problem, and the matching algorithm is used to solve the energy cooperation problem. Simulation results show that the proposed algorithm has obvious advantages in energy efficiency performance compared with the comparison algorithm. At the same time, it is also proved that the introduction of energy cooperation technology can effectively reduce system energy consumption and improve system energy efficiency.

A two-stage energy management for heat-electricity integrated energy system considering dynamic pricing of Stackelberg game and operation strategy optimization

Considering the flexibility and adjustability value of integrated energy system (IES) with flexible energy units and multivariate adjustable load in urban energy market, this paper proposes a two-stage energy management method of heat-electricity integrated energy system (HE-IES) considering dynamic pricing of Stackelberg game and operation strategy optimization. Firstly, a general comprehensive energy efficiency considering the exergy properties of electric and thermal energy is established, on this basis, this paper put forward a two-stage energy management framework considering interactive relationship between energy service provider (ESP) and users. Secondly, a two-stage energy management model is established to improve the energy efficiency and operation economy of the system, which includes the multi-objective optimization model of day-ahead scheduling and Stackelberg game dynamic pricing model of real-time energy management based on the source-load interaction optimization for hybrid energy. Finally, in order to illustrate the effectiveness of the proposed energy management method in improving system energy efficiency and operation strategy, a typical HE-IES consisting of 6 users and 1 ESP is chosen to simulation. The simulation results demonstrate that the proposed approach can not only enhance renewable energy utilization and reduce the cost of both ESP and users, but helpful to promote the benign interaction between energy equipment and load in IES, which could improve the energy efficiency of system operation.

Measurements to Quantify the Effect of a Reduced Flow Rate on the Performance of a Tilting Pad Journal Bearing With Flooded Ends

Abstract Operation of tilting pad journal bearings (TPJBs) with a reduced flow decreases pumping costs and oil sump storage. A low supplied oil flow improves system energy efficiency by reducing drag power losses, albeit the temperature rise in both the bearing pads and the lubricating oil become a concern. This paper presents measurements of the static and dynamic load performance of a flooded ends TPJB lubricated with an ISO VG 46 oil supplied at 60 °C, and with a flow rate ranging from 150% to just ∼5% of a nominal supply condition. The flow range covers both over-flooded and starved flow conditions. The test bearing is a four-pad, 102 mm diameter, center pivot, with single orifice feeds, and configured with end seals to flood the bearing housing. The experiments include operation at two shaft speeds = 6 krpm and 12 krpm (= 64 m/s surface speed) and under three specific loads = 0.345 MPa, 1.03 MPa, and 2.07 MPa applied in between pads (LBP). The measurements show the bearing drag power loss decreases by nearly 20% when the flow rate drops to 50% of nominal. However, halving the flow produces a raise in pad subsurface temperatures, ∼7 °C for operation at 12 krpm. Flow reduction below 50% does result in even more substantial power savings; however, it also produces too hot pad temperatures that approach 130 °C, a known limit for Babbitt material safe operation. The bearing static eccentricity (e) and direct stiffnesses Kxx < Kyy (load direction) do not show a significant dependency on the supplied flow, either above or below the nominal condition. A minor stiffness hardening does occur for very low flow conditions, 5% or so of nominal. Damping coefficients (Cxx ∼ Cyy) decrease by ∼30% as the flow rate decreases from 150% to just a few % of the nominal flow. The experimental results are first to quantify the operation of a TPJB supplied with minute amounts of lubricant flow. A test with a very low flow rate at ∼2% of nominal and under a light load produced the emergence of a broadband subsynchronous vibration (SSV) frequency, albeit with a very small amplitude.

An improved input variable selection method of the data-driven model for building heating load prediction

In building energy conservation, HVAC systems have great potential, and load prediction plays an important role in optimizing system control and improving system energy efficiency. Therefore, improving the accuracy of load prediction is of great significance. This paper aims to improve the prediction accuracy of the data-driven model of load prediction through optimizing the input variable selection. Factors such as outdoor temperature, wind speed, solar radiation, indoor temperature and user behavior have different mechanisms of action to influence the heating load, and there exists difference among the influence degree of each factor on the heating load at each moment. Therefore, the optimal input variable used by the heating load prediction models at different moments will be different. Based on this, this paper proposes to establish an input variable selection method based on hourly correlation analysis. Taking an office building as the case building, this paper uses the back propagation neural network (BPNN) model and the support vector regression (SVR) model to compare the selection methods of hourly correlation analysis and non-hourly correlation analysis. The results show that the influence degree of solar radiation intensity and the historical load at the moment of 24 h ahead on the load at each moment have great difference. Compared with non-hourly correlation analysis, hourly correlation analysis can reduce the root mean square error (RMSE) of the prediction results of the BPNN model and the SVR model by an average of 10.4% and 12.9%, respectively, and increase the coefficient of determination (R2) by an average of 11.7% and 7.9%, respectively, while all the calculation time is about 0.4 s. This shows that the heating load prediction method based on hourly correlation analysis can improve the prediction accuracy of model while keeping the prediction rate unchanged.

RIS-Enhanced WPCNs: Joint Radio Resource Allocation and Passive Beamforming Optimization

Wireless-powered communication and reconfigurable intelligent surface (RIS) can complement each other for increasing energy utilization and spectrum efficiency by reconfiguring the surrounding radio environment, however, which has not been sufficiently studied by the existing works. In this paper, we propose a joint radio resource and passive beamforming optimization scheme for a downlink RIS-assisted wireless-powered communication network with a harvest-then-transmit protocol to improve system energy efficiency (EE). In the considered model, the single-antenna wireless devices (WDs) harvest wireless energy from a multi-antenna dedicated power station (PS) through the RIS in the downlink and transmit their independent information to a single-antenna receiver in the uplink by a time-division-multiple-access mode. Our goal is to maximize the total EE of all WDs. To make full use of the beamforming gain provided by both the PS and the RIS, we jointly optimize the active beamforming of the PS and the passive beamforming of the RIS. To deal with the challenging non-convex optimization problem with multiple coupled variables, we first consider fixing the passive beamforming, and converting the remaining radio resource allocation problem into an equivalent convex problem which is solved by using Lagrange dual theory. Then, we fix the optimized resource allocation parameters and optimize the passive beamforming of the RIS by using a semidefinite programming method. Simulation results demonstrate that the proposed algorithm achieves higher EE compared to the conventional schemes.

Collision-free and low delay MAC protocol based on multi-level quorum system in underwater wireless sensor networks

Underwater wireless sensor network (UWSN) is a typical application of wireless network in underwater environment, which mainly uses acoustic communication at present. However, due to the characteristics of high bit error rate, very limited bandwidth and high transmission delay, the data transmission collision of underwater communication is very serious. In order to reduce transmission collision and improve network performance, we propose a collision-free time slot scheduling MAC protocol based on multi-level quorum system for high loaded UWSNs. The proposed protocol can allocate different time slots for nodes in the same collision area, while realize space reuse for nodes in different collision areas. Considering the unbalanced data transmission of each node, a multi-level quorum system algorithm is constructed for fairness, which can allocate time slots on demand according to the data transmission amount of each node. In order to ensure reliable transmission of data, a light weight retransmission mechanism is designed to reduce the impact of long delay on channel duty cycle. Simulation results prove that the proposed MAC protocol can effectively avoid transmission collision, reduce transmission delay, improve system energy efficiency, and have good adaptability for different network topologies.