Sustainable Power Supply Research Articles

Optimal operation of lithium-ion batteries in microgrids using a semidefinite thermal model

The growing adoption of microgrids necessitates efficient management of electrical energy storage units to ensure reliable and sustainable power supply. This paper investigates a thermal management system (TMS) for maintaining the longevity of large-scale batteries. To streamline the thermal modeling of batteries, the McCormick relaxation method is employed to linearize a nonlinear and interdependent heat generation model. The thermal model of the battery follows a nonlinear behavior where the generated heat makes the battery system temperature soar, thereby affecting the thermal performance of the battery. To showcase the efficacy of the proposed approach, four distinct case scenarios are studied, highlighting the critical importance of batteries within microgrid operations. A comparative analysis is conducted between linear and nonlinear models for TMS performance. A quantitative assessment based on simulation results demonstrates the precision of the linearized model, particularly in a multitemporal optimal power flow and day-ahead scheduling of microgrids incorporating energy storage units. Controlling the battery temperature within a permissible range (from 15 °C to 40 °C) is achieved by using a heating, ventilation, and air conditioning (HVAC) system. The paper explores the economic implications of energy storage units in microgrids by extracting and comparing daily operational costs with and without battery integration. The findings reveal that the inclusion of energy storage units yields substantial economic benefits, with potential profit margins of approximately 20 % during typical working days and 60 % on weekends.

A heat-triggered triboelectric nanogenerator for self-powered wireless fire alarm

Power supply is playing an increasingly important role in the rapidly developing era of the Internet of Things. Achieving a sustainable and clean power supply for electronic devices is an urgent and challenging task. In this study, we present a heat-triggered triboelectric nanogenerator (TENG) and develop a self-powered fire alarm system to achieve an early warning without an external power supply. A TENG comprises a gear system that can utilize the elastic potential energy of a spring. A wax block was used as a heat trigger. When melted at high temperatures, the TENG will be triggered to work and generate considerable electric energy. Within a single operation cycle of approximately 6 s, a 22 μF capacitor can be charged up to 3.7 V. Such electrical energy is sufficient to drive a wireless transmission module through an automatic switching circuit. Overall, this study provides a feasible approach for a self-powered wireless warning system in power-shortage areas.

Numerical study on self-power supply of large marine monitoring buoys: Wave-excited vibration energy harvesting and harvester optimization

With the diversification of marine monitoring buoy functions, limited onboard batteries have been unable to meet the energy demand of multifarious carrying sensors. Finding a self-sustained power supply for marine monitoring buoys is an urgent problem, while wave energy is an ideal and promising option to address that problem. In this study, two wave-excited vibration energy harvesters (WVEHs) are proposed, which can be installed inside large buoys to provide a sustainable power supply. A full-coupled wave-to-wire model is developed to investigate the influence of blocks’ mass, geometric size of buoys, mooring system and WVEH’s quantity on the electric power performance of harvesters in realistic sea states. Parametric studies based on the Taguchi method imply that the sea state and the WVEH’s quantity have a significant effect on the device’s electric power performance. Numerical results indicate that the optimized two harvesters can produce a mean electric power of 777.50 W and 747.43 W, respectively, under a sea state with a peak wave period of 7 s and a significant wave height of 1.6 m. A high wave-to-wire efficiency of 2.60% is obtained for a specific system parameter combination. Furthermore, more electric power generation can be achieved by installing multiple harvesting units.

A health monitoring system based on flexible triboelectric sensors for intelligence medical internet of things and its applications in virtual reality

The Internet of Medical Things (IoMT) is a platform that combines Internet of Things (IoT) technology with medical applications, enabling the realization of precision medicine, intelligent healthcare, and telemedicine in the era of digitalization and intelligence. However, the IoMT faces various challenges, including sustainable power supply, human adaptability of sensors and the intelligence of sensors. In this study, we designed a robust and intelligent IoMT system through the synergistic integration of flexible wearable triboelectric sensors and deep learning-assisted data analytics. We embedded four triboelectric sensors into a wristband to detect and analyze limb movements in patients suffering from Parkinson's Disease (PD). By further integrating deep learning-assisted data analytics, we actualized an intelligent healthcare monitoring system for the surveillance and interaction of PD patients, which includes location/trajectory tracking, heart monitoring and identity recognition. This innovative approach enabled us to accurately capture and scrutinize the subtle movements and fine motor of PD patients, thus providing insightful feedback and comprehensive assessment of the patients’ conditions. This monitoring system is cost-effective, easily fabricated, highly sensitive, and intelligent, consequently underscores the immense potential of human body sensing technology in a Health 4.0 society.

Development of an electromagnetic energy harvester for ultra-low frequency pitch vibration of unmanned marine devices

Pitch vibrations can be commonly observed in unmanned marine devices under wave excitation, but there is relatively little research on harvesting the energy from the pitch vibrations with ultra-low frequency. This work develops a novel built-in electromagnetic energy harvester using rope transmission to provide sustainable power supply for onboard electronics. It has the advantages of low friction and compact structure, which is suitable for installation inside an autonomous underwater vehicle with slender cylindrical shape. Dynamic modeling and linearization approach are employed to analyze its energy harvesting performance theoretically. A scalable prototype is fabricated and tested on a motion platform with six degrees of freedom by simulating periodic pitch vibration. The results show that the prototype can output electrical power with the peak value of 1663 mW and the average value of 315 mW at the excitation frequency of 0.6 Hz. It also has competitive energy extraction efficiency and the maximum value reaches 33.23%. The experimental data are in good agreement with the theoretical data, which verifies the effectiveness of the theoretical model. The developed energy harvester can serve as a potential candidate for powering the electronics on unmanned marine devices.

A STUDY OF PERFORMANCE OF DFIG BASED MICROGRID SUBJECTED TO DISTURBANCES

The integration of wind energy into the electrical grid has become increasingly essential in our pursuit of sustainable and renewable energy sources. The research employs techniques to capture the complex dynamics of DFIG wind turbines, encompassing the rotor, drivetrain, and electrical subsystems. This analysis provides critical information for designing control strategies that enhance the stability and performance of grid-connected wind turbines. Furthermore, the inclusion of a detailed model allows us to investigate the mechanical aspects of the turbine. This holistic approach not only enhances our understanding of the system but also aids in the development of strategies to mitigate disturbance and improve the overall reliability of wind turbines. The findings of this study contribute to the optimization of grid connected DFIG wind turbines, making them more resilient and efficient in harnessing wind energy. As renewable energy sources continue to play a pivotal role in the global energy landscape, a comprehensive understanding of the dynamic behavior of wind turbines is essential for achieving a sustainable and reliable power supply. Key Words: MCDM; AHP; TOPSIS; MOORA; HRES.

Group assessment for the selection of sustainable small-scale power supply projects: A study case from northern Colombia

Sustainability assessment provides essential information to facilitate informed decision-making, enabling the selecting of the best option among various projects. This research paper considers the decision-making problem in the context of marginalised and isolated communities, introducing a groupal model for evaluating the sustainability of small-scale power supply projects. The proposed model incorporates a comprehensive set of five indicators and 25 criteria. The analysis presented in this study prioritises these indicators and criteria, introducing new criteria based on several stakeholders’ participation and offering guidance on measuring the identified criteria. Furthermore, the proposal provides fundamental thresholds for evaluating the projects’ sustainability and proposes a model based on aggregated indicators to assess the available alternatives. It encompasses all stages of the decision-making process, employing multiple indicators to evaluate the sustainability of power supply projects. The effectiveness of the proposed model was validated in a real case study conducted in a marginalised community facing isolation challenges in La Guajira, Colombia. The evaluation showcased the model’s contribution to decision-making processes regarding power supply projects in isolated communities. Finally, the results demonstrated the suitability of this strategy for immediate application, highlighting its potential impact on decision-making for sustainable development within marginalised areas.

Research on Source Load Interaction Mode Supporting New Power System

The construction of a new power system will face challenges such as a high proportion of new energy consumption and a sustainable and reliable power supply. It is urgent to fully tap the potential of demand-side regulation, make up for the shortage of flexible regulation resources of the source side caused by a high proportion of new energy connected to the grid, and promote the transformation of power system operation to the mode of “source load interaction.” One of the effective ways to solve the above problem is to introduce a Hierarchical Load Response Center (HLRC) and establish a load regulation market, effectively promoting user participation in load regulation through market-oriented means. In this paper, the operation framework of “Dispatching Center + Trading Center + Hierarchical Load Response Center” is proposed to support the interaction of source and load under the new power system and the coordination and cooperation relationship of LRC in the operation of the load control market is analyzed. Based on this, the source load interaction mode led by HLRC is analyzed, and the source load interaction modes in the primary and secondary markets are proposed, respectively.

MANAGEMENT METHOD OF ELECTRICITY GENERATION SYSTEM USING WIRELESS TECHNOLOGIES

The subject of the study is the method of control and monitoring of the electricity generation system. The goal of the work is to investigate and develop a method for controlling the electricity generation system using wireless technologies. Relevance. The issues of energy efficiency and the use of alternative energy sources are relevant and important in modern conditions. In particular, solar energy is one of the most perspective areas in solving these problems. It is necessary to have the ability to monitor and control the generation process for optimal use of solar energy. The developed method should control the power generation system using wireless technologies and have flexible modes of operation. The development of the method of effective search for the point of maximum power and the power generation system in general is one of the most important tasks of the work. The object of the study is the process of control and monitoring of the electricity generation system. Research methods. Solar panel operation methods at maximum power: PWM (Pulse Width Modulation) and MPPT (Maximum Power Point Tracking). Results. The management method for the electricity generation system using wireless technologies is proposed in this work. A solar panel and a generator were chosen for electricity generation. The control of generation and system operation is based on the work of a microcontroller, which, in turn, transmits current data and the ability to control the system to a mobile application via a Wi-Fi module. This method can be used in a "Smart Home" system and other systems aimed at sustainable energy supply for consumers. Conclusion. The developed management method of the electricity generation system is planned to be used in systems of sustainable power supply for consumers. The method can be improved by integrating with other wireless technologies and adding other objects of electricity generation in the future.

A Review on Neural Network Based Models for Short Term Solar Irradiance Forecasting

The accuracy of solar energy forecasting is critical for power system planning, management, and operation in the global electric energy grid. Therefore, it is crucial to ensure a constant and sustainable power supply to consumers. However, existing statistical and machine learning algorithms are not reliable for forecasting due to the sporadic nature of solar energy data. Several factors influence the performance of solar irradiance, such as forecasting horizon, weather classification, and performance evaluation metrics. Therefore, we provide a review paper on deep learning-based solar irradiance forecasting models. These models include Long Short-Term Memory (LTSM), Gated Recurrent Unit (GRU), Recurrent Neural Network (RNN), Convolutional Neural Network (CNN), Generative Adversarial Networks (GAN), Attention Mechanism (AM), and other existing hybrid models. Based on our analysis, deep learning models perform better than conventional models in solar forecasting applications, especially in combination with some techniques that enhance the extraction of features. Furthermore, the use of data augmentation techniques to improve deep learning performance is useful, especially for deep networks. Thus, this paper is expected to provide a baseline analysis for future researchers to select the most appropriate approaches for photovoltaic power forecasting, wind power forecasting, and electricity consumption forecasting in the medium term and long term.

A community scale hybrid renewable energy system for sustainable power supply during load shedding

Load shedding is an operating condition in which the electrical grid is temporarily disconnected from the load. The objective is to minimize the gap between available generation capacity and load demand while maintaining an equitable supply for all consumers. Load shedding is a prominent problem for many developing countries. To address this issue, this paper explores the potential of a hybrid energy system (HES) to provide uninterrupted power supply at the distribution feeder despite load shedding from electrical grid. The proposed HES in this work combines photovoltaic (PV) array, battery storage system (BSS) and diesel generator (DG). The HES is equipped with energy management scheme (EMS) that ensures continuous power supply, improves energy efficiency, and minimizes the electricity cost. To accomplish these tasks, the EMS operates the system in one of three modes: grid mode, renewable energy source mode and the diesel generator mode. Besides, the proposed methodology allows injecting surplus PV energy into the grid, thus maximizing PV utilization and improving power system’s reliability. The results of this study will assist policymakers to determine the prospect of renewable based hybrid system to supply sustainable power and eliminate the energy problems in the power deficit countries.

ПРИСТРОЇ ТА СИСТЕМИ РОЗПОДІЛЕНОЇ ГЕНЕРАЦІЇ

Abstract. The article is devoted to the analysis of the features of various distributed generation systems from the point of view of their inclusion in a single distributed energy system. It is shown that the need to switch to distributed generation is associated with the need to create reliable power supply systems that can maintain their performance in the event of partial or complete destruction of any part of such a system. The devices of solar, wind and hydropower, as well as the possibility of using small modular nuclear reactors as devices for distributed generation are analyzed. It is shown that the most promising for application are environmentally friendly solar cells. Wind generation and small hydropower plants can also be used to create sustainable and reliable power supply systems. Small modular reactors can be used to power large cities and industrial consumers. The analysis of economic and energy parameters of various devices of distributed generation is carried out. It is concluded that the elements of a distributed generation system can be not only individual devices, but also systems of such devices at the level of a territorial region. Keywords: distributed generation; electrical system; solar energy; solar power plants, wind energy; modular nuclear reactors; intelligent networks.

ПРИСТРОЇ ТА СИСТЕМИ РОЗПОДІЛЕНОЇ ГЕНЕРАЦІЇ

Abstract. The article is devoted to the analysis of the features of various distributed generation systems from the point of view of their inclusion in a single distributed energy system. It is shown that the need to switch to distributed generation is associated with the need to create reliable power supply systems that can maintain their performance in the event of partial or complete destruction of any part of such a system. The devices of solar, wind and hydropower, as well as the possibility of using small modular nuclear reactors as devices for distributed generation are analyzed. It is shown that the most promising for application are environmentally friendly solar cells. Wind generation and small hydropower plants can also be used to create sustainable and reliable power supply systems. Small modular reactors can be used to power large cities and industrial consumers. The analysis of economic and energy parameters of various devices of distributed generation is carried out. It is concluded that the elements of a distributed generation system can be not only individual devices, but also systems of such devices at the level of a territorial region. Keywords: distributed generation; electrical system; solar energy; solar power plants, wind energy; modular nuclear reactors; intelligent networks.

Toward self-powered integrated smart packaging system − Desiccant-based triboelectric nanogenerators

Smart packaging plays a crucial role in safeguarding products, monitoring their quality, and ensuring supply chain efficiency during distribution and transportation. However, the extensive use of sensors in smart packaging systems requires a sustainable power supply for long-term monitoring. Unfortunately, portable batteries may not meet the needs for next-generation smart packaging as they have a limited lifetime, are heavy, and may cause environmental pollution after use. To address this issue, we propose a self-powered integrated smart packaging system driven by a novel desiccant-based triboelectric nanogenerator (D-TENG). The D-TENG is designed using a contact-separation mode and includes a paperboard-based honeycomb frame, two PTFE/Cu triboelectric layers, and desiccants stored in the honeycomb holes as the freestanding triboelectric material. We systematically investigate the significant parameters affecting the energy harvesting performance of the D-TENG, including the type of desiccants, frame height, number of honeycomb holes, frequency and amplitude of external excitation, and device orientation with the vibration direction. Furthermore, we demonstrate a self-powered integrated smart packaging system based on the D-TENGs that harvests vibration energy to power sensors integrated into the package. This research provides a practical strategy to continuously monitor the status and quality of packaged products throughout the supply chain for an extended period, reducing food waste and ensuring a complete record of logistics history in vaccine delivery.

Experimental and simulation study of a hydraulic piezoelectric energy harvester under different connection modes

Pressure pulsation from water hydraulic system exhibits great potential in vibration energy harvesting. Herein a novel hydraulic piezoelectric energy harvester is proposed, which exhibits excellent insulation and sealing performance. The effect of connection modes such as single output, series and parallel connection, on the energy harvesting performance is investigated at different parameters by the experiment. The theoretical analysis and simulation study are employed to explain the energy harvesting process. The results show that the transient voltage exhibits alternating characteristics, and it has the same period with the transient pressure. The piezoelectric disk closer to the liquid inlet has greater energy harvesting ability. The voltage increases as the static pressure rises and the main influence factor is pulsation amplitude rather than static pressure. Moreover, the root mean square voltage of series connection is highest, and it increases with the increasing resistance, but the average power first increases and then decreases. The parallel connection mode has higher average power and lower optimal resistance. The average power and power density can respectively reach 394 μW and 1.34 mW/cm3 under 3 MPa and 20 KΩ. This paper can provide methods for the sustainable power supply of sensors in water hydraulic system.

Flexible Self-Powered Friction Piezoelectric Sensor Based on Structured PVDF-Based Composite Nanofiber Membranes.

With the rapid development of the economy and technology, intelligent wearable devices have gradually entered public life. Flexible sensors, as the main component of wearable devices, have been widely concerned. However, traditional flexible sensors need an external power supply, lacking flexibility and sustainable power supply. In this study, structured poly(vinylidene fluoride) (PVDF)-based composite nanofiber membranes doped with different mass fractions of MXene and zinc oxide (ZnO) were prepared by electrospinning and were then assembled to flexible self-powered friction piezoelectric sensors. The addition of MXene and ZnO endowed PVDF nanofiber membranes with better piezoelectric properties. The structured PVDF/MXene-PVDF/ZnO (PM/PZ) nanofiber membranes with a double-layer structure, interpenetrating structure, or core-shell structure could further enhance the piezoelectric properties of PVDF-based nanofiber membranes through the synergistic effects of filler doping and structural design. In particular, the output voltage of the self-powered friction piezoelectric sensor made of a core-shell PM/PZ nanofiber membrane showed a good linear relationship with the applied pressure and could produce a good piezoelectric response to the bending deformation caused by human motion.

Predictive Control of a Wind Turbine Based on Neural Network-Based Wind Speed Estimation

Predictive control is an advanced control technique that performs well in various application domains. In this work, linearised control design models are first derived in state-space form from the full nonlinear model of the 5 MW Supergen (Sustainable Power Generation and Supply) exemplar wind turbine. Feedback model predictive controllers (FB-MPCs) and feedforward model predictive controllers (FF-MPCs) are subsequently designed based on these linearised models. A neural network (NN)-based wind speed estimation method is then employed to obtain the accurate wind estimation required for designing a FF-MPC. This method uses a LiDAR to be shared between multiple wind turbines in a cluster, i.e., one turbine is mounted with a LiDAR, and each of the remaining turbines from the cluster is provided with a NN-based estimator, which replaces the LiDAR, making the approach more economically viable. The resulting controllers are tested by application to the full nonlinear model (based on which the linearised models are derived). Moreover, the mismatch between the control design model and the simulation model (model–plant mismatch) allows the robustness of the controllers’ design to be tested. Simulations are carried out at varying wind speeds to evaluate the robustness of the controllers by applying them to a full nonlinear 5 MW Matlab/SIMULINK model of the same exemplar Supergen wind turbine. Improved torque/speed plane tracking is achieved with a FF-MPC compared to a FB-MPC. Simulation results further demonstrate that the control performance is enhanced in both the time and frequency domains without increasing the wind turbine’s control activity; that is, the controller’s gain crossover frequency (or bandwidth) remains within the acceptable range, which is about 1 rad/s.

Performance enhancement of the wavy cylinder-based piezoelectric wind energy harvester with different wave-shaped attachments

The vortex-induced vibration (VIV)-based piezoelectric wind energy harvester (PWEH) has a small working bandwidth and poor wind energy harvesting performance. In order to improve the output power of the PWEH and achieve sustainable power supply for microelectronic products, this study proposes a novel wavy cylinder-based PWEH with two wavy attachment rods attached to the surface of the wavy cylinder, the mathematical model of PWEH is developed. The flow-induced vibration (FIV) response mechanism and the energy harvesting characteristics of the wavy cylinder-based PWEH are numerically explored. The wavy cylinder with wavy-shaped attachments produces a three-dimensional shear layer that can increase the wavy cylinder’s aeroelastic instability range and realize the synergistic effects of VIV and galloping, which increases the wave cylinder’s vibrational amplitude and lowers the galloping critical wind speed. Compared with the typical VIV-PWEH, the novel wind energy harvester can work outside the VIV lock-in range, and its output power and voltage rise as wind speed does. The wavy attachment rods with triangular cross section have greater advantages than other rods, its output power is 6.13 mW at a wind speed of 5.7 m/s and load resistance of 100 KΩ, compared with the circular cylinder PWEH, the average power increases by approximately 166%. The study’s findings can theoretically promote the enhancement of PWEH’s energy harvesting efficiency.

Universal Energy Solution for Triboelectric Sensors Toward the 5G Era and Internet of Things.

The launching of 5G technology provides excellent opportunity for the prosperous development of Internet of Things (IoT) devices and intelligent wireless sensor nodes. However, deploying of tremendous wireless sensor nodes network presents a great challenge to sustainable power supply and self-powered active sensing. Triboelectric nanogenerator (TENG) has shown great capability for powering wireless sensors and work as self-powered sensors since its discovery in 2012. Nevertheless, its inherent property of large internal impedance and pulsed "high-voltage and low-current" output characteristic seriously limit its direct application as stable power supply. Herein, a generic triboelectric sensor module (TSM) is developed toward managing the high output of TENG into signals that can be directly utilized by commercial electronics. Finally, an IoT-based smart switching system is realized by integrating the TSM with a typical vertical contact-separation mode TENG and microcontroller, which is able to monitor the real-time appliance status and location information. Such design of a universal energy solution for triboelectric sensors is applicable for managing and normalizing the wide output range generated from various working modes of TENGs and suitable for facile integration with IoT platform, representing a significant step toward scaling up TENG applications in future smart sensing.

A sandwich-like flexible nanofiber device boosts moisture induced electricity generation for power supply and multiple sensing applications

Moisture-electricity generators (MEGs) are emerging as an attractive sustainable power supply due to their clean energy harvesting and conversion. However, there still remain some challenges in the development of high-performance and practical MEGs. Herein, we develop a novel sulfonate-polyaniline-bifunctionalized lignin (SAlignin), which can be incorporated into additive polyacrylonitrile for engineering electrospun nanofiber membrane (BioMem) to improve moisture power generation. To achieve maximal electric conversion efficiency, a flexible sandwich-like MEG (fMEG) consisting of an outer bilayer electrode of carbonized BioMem and an inner hygroscopic layer of as-spun BioMem is constructed. The unique structures and compositions endow fMEG with optimal ion diffusion, streaming tendency and surface potential for moisture electric generation. Importantly, phase-field simulation reveals that the interpenetrating network of SAlignin and polyacrylonitrile has good moisture absorption capacity and electricity generation, thereby boosting electric outputs. We identify that fMEG exhibits SAlignin-dose dependent increase in power conversion efficiency, and can generate a stable voltage of 0.28 V and current of 125 nA/cm2. In addition, electric output can be further improved by assembling multiple fMEG units in series or parallel, which is sufficient to power up electronic devices. More excitingly, fMEG can sensitively detect humid wind, and especially harvest the energy from human breath for respiration monitoring. Particularly, fMEG exhibits the potential of real-time monitoring of different human motions, including finger movements, sound waves and neck pulses. Therefore, our study provides new insights for advancing MEGs and related applications.