Cascade utilization of full spectrum solar energy for achieving simultaneous hydrogen production and all-day thermoelectric conversion

Solar-driven photocatalytic water/seawater splitting holds great potential for green hydrogen production.However,the practical application is hindered by the relatively low conversion efficiency resulting from the inadequate utilization of solar spectrum with significant waste in the form of heat.Moreover,current equipment struggles to maintain all-day operation subjected to the lack of light during nighttime.Herein,a novel hybrid system integrating photothermal catalytic(PTC)reactor,thermoelectric generator(TEG),and phase change materials(PCM)was proposed and designed(named as PTC-TEG-PCM)to address these challenges and enable simultaneous overall seawater splitting and 24-hour power generation.The PTC system effectively maintains in an optimal temperature range to maximize photothermal-assisted photocatalytic hydrogen production.The TEG component recycles the low-grade waste heat for power generation,complementing the shortcoming of photocatalytic conversion and achieving cascade utilization of full-spectrum solar energy.Furthermore,exceptional thermal storage capability of PCM allow for the conversion of released heat into electricity during nighttime,contributing significantly to the overall power output and enabling PTC-TEG-PCM to operate for more than 12 h under the actual condition.Compared to traditional PTC system,the overall energy conversion efficiency of the PTC-TEG-PCM system can be increased by∼500%,while maintaining the solar-to-hydrogen efficiency.The advancement of this novel system demonstrated that recycling waste heat from the PTC system and utilizing heat absorption/release capability of PCM for thermoelectric application are effective strategies to improve solar energy conversion.With flexible parameter designing,PTC-TEG-PCM can be applied in various scenarios,offering high efficiency,stability,and sustainability.

Double-Layer-Optimizing Method of Hybrid Energy Storage Microgrid Based on Improved Grey Wolf Optimization

To reduce the comprehensive costs of the construction and operation of microgrids and to minimize the power fluctuations caused by randomness and intermittency in distributed generation,a double-layer optimizing configuration method of hybrid energy storage microgrid based on improved grey wolf optimization(IGWO)is proposed.Firstly,building a microgrid system containing a wind-solar power station and electric-hydrogen coupling hybrid energy storage system.Secondly,the minimum comprehensive cost of the construction and operation of the microgrid is taken as the outer objective function,and the minimum peak-to-valley of the microgrid’s daily output is taken as the inner objective function.By iterating through the outer and inner layers,the system improves operational stability while achieving economic configuration.Then,using the energy-self-smoothness of the microgrid as the evaluation index,a double-layer optimizing configuration method of the microgrid is constructed.Finally,to improve the disadvantages of grey wolf optimization(GWO),such as slow convergence in the later period and easy falling into local optima,by introducing the convergence factor nonlinear adjustment strategy and Cauchy mutation operator,an IGWO with excellent global performance is proposed.After testing with the typical test functions,the superiority of IGWO is verified.Next,using IGWO to solve the double-layer model.The case analysis shows that compared to GWO and particle swarm optimization(PSO),the IGWO reduced the comprehensive cost by 15.6%and 18.8%,respectively.Therefore,the proposed double-layer optimizationmethod of capacity configuration ofmicrogrid with wind-solar-hybrid energy storage based on IGWO could effectively improve the independence and stability of the microgrid and significantly reduce the comprehensive cost.

Dynamic responses of an energy harvesting system based on piezoelectric and electromagnetic mechanisms under colored noise

Because of the increasing demand for electrical energy,vibration energy harvesters(VEHs)that convert vibratory energy into electrical energy are a promising technology.In order to improve the efficiency of harvesting energy from environmental vibration,here we investigate a hybrid VEH.Unlike previous studies,this article analyzes the stochastic responses of the hybrid piezoelectric and electromagnetic energy harvesting system with viscoelastic material under narrow-band(colored)noise.Firstly,a mass-spring-damping system model coupled with piezoelectric and electromagnetic circuits under fundamental acceleration excitation is established,and analytical solutions to the dimensionless equations are derived.Then,the formula of the amplitude-frequency responses in the deterministic case and the first-order and secondorder steady-state moments of the amplitude in the stochastic case are obtained by using the multi-scales method.The amplitude-frequency analytical solutions are in good agreement with the numerical solutions obtained by the Monte Carlo method.Furthermore,the stochastic bifurcation diagram is plotted for the first-order steady-state moment of the amplitude with respect to the detuning frequency and viscoelastic parameter.Eventually,the influence of system parameters on mean-square electric voltage,mean-square electric current and mean output power is discussed.Results show that the electromechanical coupling coefficients,random excitation and viscoelastic parameter have a positive effect on the output power of the system.

Combined hybrid energy storage system and transmission grid model for peak shaving based on time series operation simulation

This study proposes a combined hybrid energy storage system(HESS) and transmission grid(TG) model, and a corresponding time series operation simulation(TSOS) model is established to relieve the peak-shaving pressure of power systems under the integration of renewable energy. First, a linear model for the optimal operation of the HESS is established, which considers the different power-efficiency characteristics of the pumped storage system, electrochemical storage system, and a new type of liquid compressed air energy storage. Second, a TSOS simulation model for peak shaving is built to maximize the power entering the grid from the wind farms and HESS. Based on the proposed model, this study considers the transmission capacity of a TG. By adding the power-flow constraints of the TG, a TSOS-based HESS and TG combination model for peak shaving is established. Finally, the improved IEEE-39 and IEEE-118 bus systems were considered as examples to verify the effectiveness and feasibility of the proposed model.

Maximum Power Extraction Control Algorithm for Hybrid Renewable Energy System

In this research,a modified fractional order proportional integral derivate(FOPID)control method is proposed for the photovoltaic(PV)and thermoelectric generator(TEG)combined hybrid renewable energy system.The faster tracking and steady-state output are aimed at the suggested maximum power point tracking(MPPT)control technique.The derivative order number(μ)value in the improved FOPID(also known as PIλDμ)control structure will be dynamically updated utilizing the value of change in PV array voltage output.During the transient,the value ofμis changeable;it’s one at the start and after reaching the maximum power point(MPP),allowing for strong tracking characteristics.TEG will use the freely available waste thermal energy created surrounding the PVarray for additional power generation,increasing the system’s energy conversion efficiency.A high-gain DC-DC converter circuit is included in the system to maintain a high amplitude DC input voltage to the inverter circuit.The proposed approach’s performance was investigated using an extensive MATLAB software simulation and validated by comparing findings with the perturbation and observation(P&O)type MPPT control method.The study results demonstrate that the FOPID controller-based MPPT control outperforms the P&O method in harvesting the maximum power achievable from the PV-TEG hybrid source.There is also a better control action and a faster response.

Solar cell-based hybrid energy harvesters towards sustainability

Energy harvesting plays a crucial role in modern society.In the past years,solar energy,owing to its renewable,green,and infinite attributes,has attracted increasing attention across a broad range of applications from small-scale wearable electronics to large-scale energy powering.However,the utility of solar cells in providing a stable power supply for vari-ous electrical appliances in practical applications is restricted by weather conditions.To address this issue,researchers have made many efforts to integrate solar cells with other types of energy harvesters,thus developing hybrid energy har-vesters(HEHs),which can harvest energy from the ambient environment via different working mechanisms.In this re-view,four categories of energy harvesters including solar cells,triboelectric nanogenerators(TENGs),piezoelectric nanogenerators(PENGs),and thermoelectric generators(TEGs)are introduced.In addition,we systematically summar-ize the recent progress in solar cell-based hybrid energy harvesters(SCHEHs)with a focus on their structure designs and the corresponding applications.Three hybridization designs through unique combinations of TENG,PENG,and TEG with solar cells are elaborated in detail.Finally,the main challenges and perspectives for the future development of SCHEHs are discussed.

Hybrid Energy Systems and the Logic of Their Service-Dominant Implementation: Screening the Pathway to Improve Results

The transition of the global economy to a low-carbon development path has led to dramatic changes in the organization and functioning of energy markets around the world,where hybrid energy systems(HESs)are one of the decisive active agents.At the same time,a number of problems facing the modern HESs are primarily due to the stochastic nature of the renewable energy they use,require further profound changes not only in the technologies they use and how they manage them,necessary to meet the needs of end consumers and interact with the unified energy system,but also to preserve the ability of the environment to self-heal.In order to make the process of changes more efficient and eco-deep,the article proposes to use and discusses the approach based on service dominant(SD)logic,which opens up new opportunities for solving the problems of HESs.First of all through:the implementation of closer service interaction with other participants in the energy markets,as well as with the environment;a systemically organized process of transforming the“product”economic activity of HESs into a service-dominant one;developing the generalized and engineering models for solving the problems of optimizing the technical and economic indicators of HESs,operation in steady-state and transient modes.The calculations confirm the effectiveness of the proposed approach and its ability to reduce the average daily costs for the system as a whole by 14.7%compared to the costs with a uniform distribution of power between the modules.

Hybrid Power Bank Deployment Model for Energy Supply Coverage Optimization in Industrial Wireless Sensor Network

Energy supply is one of the most critical challenges of wireless sensor networks(WSNs)and industrial wireless sensor networks(IWSNs).While research on coverage optimization problem(COP)centers on the network’s monitoring coverage,this research focuses on the power banks’energy supply coverage.The study of 2-D and 3-D spaces is typical in IWSN,with the realistic environment being more complex with obstacles(i.e.,machines).A 3-D surface is the field of interest(FOI)in this work with the established hybrid power bank deployment model for the energy supply COP optimization of IWSN.The hybrid power bank deployment model is highly adaptive and flexible for new or existing plants already using the IWSN system.The model improves the power supply to a more considerable extent with the least number of power bank deployments.The main innovation in this work is the utilization of a more practical surface model with obstacles and training while improving the convergence speed and quality of the heuristic algorithm.An overall probabilistic coverage rate analysis of every point on the FOI is provided,not limiting the scope to target points or areas.Bresenham’s algorithm is extended from 2-D to 3-D surface to enhance the probabilistic covering model for coverage measurement.A dynamic search strategy(DSS)is proposed to modify the artificial bee colony(ABC)and balance the exploration and exploitation ability for better convergence toward eliminating NP-hard deployment problems.Further,the cellular automata(CA)is utilized to enhance the convergence speed.The case study based on two typical FOI in the IWSN shows that the CA scheme effectively speeds up the optimization process.Comparative experiments are conducted on four benchmark functions to validate the effectiveness of the proposed method.The experimental results show that the proposed algorithm outperforms the ABC and gbest-guided ABC(GABC)algorithms.The results show that the proposed energy coverage optimization method based on the hybrid power bank deployment model generates more accurate results than the results obtained by similar algorithms(i.e.,ABC,GABC).The proposed model is,therefore,effective and efficient for optimization in the IWSN.

A Hybrid Biofuel and Triboelectric Nanogenerator for Bioenergy Harvesting

Various types of energy exist everywhere around us,and these energies can be harvested from multiple sources to power micro-/nanoelectronic system and even personal electronic products.In this work,we proposed a hybrid energy-harvesting system(HEHS)for potential in vivo applications.The HEHS consisted of a triboelectric nanogenerator and a glucose fuel cell for simultaneously harvesting biomechanical energy and biochemical energy in simulated body fluid.These two energy-harvesting units can work individually as a single power source or work simultaneously as an integrated system.This design strengthened the flexibility of harvesting multiple energies and enhanced corresponding electric output.Compared with any individual device,the integrated HEHS outputs a superimposed current and has a faster charging rate.Using the harvested energy,HEHS can power a calculator or a green light-emitting diode pattern.Considering the widely existed biomechanical energy and glucose molecules in the body,the developed HEHS can be a promising candidate for building in vivo self-powered healthcare monitoring system.

Recent progress and application on seismic isolation energy dissipation and control for structures in China

China is a country where 100% of the territory is located in a seismic zone. Most of the strong earthquakes are over prediction. Most fatalities are caused by structural collapse. Earthquakes not only cause severe damage to structures, but can also damage non-structural elements on and inside of facilities. This can halt city life, and disrupt hospitals, airports, bridges, power plants, and other infrastructure. Designers need to use new techniques to protect structures and facilities inside. Isolation, energy dissipation and, control systems are more and more widely used in recent years in China. Currently, there are nearly 6,500 structures with isolation and about 3,000 structures with passive energy dissipation or hybrid control in China. The mitigation techniques are applied to structures like residential buildings, large or complex structures, bridges, underwater tunnels, historical or cultural relic sites, and industrial facilities, and are used for retrofitting of existed structures. This paper introduces design rules and some new and innovative devices for seismic isolation, energy dissipation and hybrid control for civil and industrial structures. This paper also discusses the development trends for seismic resistance, seismic isolation, passive and active control techniques for the future in China and in the world.

Design and Optimization of a Hybrid Energy System for Decentralized Heating

The performances of a hybrid energy system for decentralized heating are investigated.The proposed energy system consists of a solar collector,an air-source heat pump,a gas-fired boiler and a hot water tank.A mathematical model is developed to predict the operating characteristics of the system.The simulation results are compared with experimental data.Such a comparison indicates that the model accuracy is sufficient.The influence of the flat plate solar collector area on the economic and energy efficiency of such system is also evaluated through numerical simulations.Finally,this system is optimized using the method of orthogonal design.The results clearly demonstrate that the solar-heat pump-gas combined system is more convenient and efficient than the simple gas system and the heat pump-gas combined system,whereas it is less convenient but more efficient than the solarassisted gas system.

Energy storage for black start services:A review

With the increasing deployment of renewable energy-based power generation plants,the power system is becoming increasingly vulnerable due to the intermittent nature of renewable energy,and a blackout can be the worst scenario.The current auxiliary generators must be upgraded to energy sources with substantially high power and storage capacity,a short response time,good profitability,and minimal environmental concern.Difficulties in the power restoration of renewable energy generators should also be addressed.The different energy storage methods can store and release electrical/thermal/mechanical energy and provide flexibility and stability to the power system.Herein,a review of the use of energy storage methods for black start services is provided,for which little has been discussed in the literature.First,the challenges that impede a stable,environmentally friendly,and cost-effective energy storage-based black start are identified.The energy storagebased black start service may lack supply resilience.Second,the typical energy storage-based black start service,including explanations on its steps and configurations,is introduced.Black start services with different energy storage technologies,including electrochemical,thermal,and electromechanical resources,are compared.Results suggest that hybridization of energy storage technologies should be developed,which mitigates the disadvantages of individual energy storage methods,considering the deployment of energy storage-based black start services.

Research on Distributed Cooperative Control Strategy of Microgrid Hybrid Energy Storage Based on Adaptive Event Triggering

Distributed collaborative control strategies for microgrids often use periodic time to trigger communication,which is likely to enhance the burden of communication and increase the frequency of controller updates,leading to greater waste of communication resources.In response to this problem,a distributed cooperative control strategy triggered by an adaptive event is proposed.By introducing an adaptive event triggering mechanism in the distributed controller,the triggering parameters are dynamically adjusted so that the distributed controller can communicate only at a certain time,the communication pressure is reduced,and the DC bus voltage deviation is effectively reduced,at the same time,the accuracy of power distribution is improved.The MATLAB/Simulink modeling and simulation results prove the correctness and effectiveness of the proposed control strategy.

DEVELOPMENT OF THE ENERGY MANAGEMENT STRATEGY FOR PARALLEL HYBRID ELECTRIC URBAN BUSES

A novel parallel hybrid electrical urban bus （PHEUB） configuration consisting of an extra one-way clutch and an automatic mechanical transmission （AMT） is taken as the study subject. An energy management strategy combining a logic threshold approach and an instantaneous optimization algorithm is proposed for the investigated PHEUB. The objective of the energy management strategy is to achieve acceptable vehicle performance and drivability requirements while simultaneously maximizing the engine fuel consumption and maintaining the battery state of charge in its operation range at all times. Under the environment of Matlab/Simulink, a computer simulation model for the PHEUB is constructed by using the model building method combining theoretical analysis and bench test data. Simulation and experiment results for China Typical Bus Driving Schedule at Urban District （CTBDS_UD） are obtained, and the results indicate that the proposed control strategy not only controls the hybrid system efficiently but also improves the fuel economy significantly.

Sparse identification method of extracting hybrid energy harvesting system from observed data

Hybrid energy harvesters under external excitation have complex dynamical behavior and the superiority of promoting energy harvesting efficiency.Sometimes,it is difficult to model the governing equations of the hybrid energy harvesting system precisely,especially under external excitation.Accompanied with machine learning,data-driven methods play an important role in discovering the governing equations from massive datasets.Recently,there are many studies of datadriven models done in aspect of ordinary differential equations and stochastic differential equations(SDEs).However,few studies discover the governing equations for the hybrid energy harvesting system under harmonic excitation and Gaussian white noise(GWN).Thus,in this paper,a data-driven approach,with least square and sparse constraint,is devised to discover the governing equations of the systems from observed data.Firstly,the algorithm processing and pseudo code are given.Then,the effectiveness and accuracy of the method are verified by taking two examples with harmonic excitation and GWN,respectively.For harmonic excitation,all coefficients of the system can be simultaneously learned.For GWN,we approximate the drift term and diffusion term by using the Kramers-Moyal formulas,and separately learn the coefficients of the drift term and diffusion term.Cross-validation(CV)and mean-square error(MSE)are utilized to obtain the optimal number of iterations.Finally,the comparisons between true values and learned values are depicted to demonstrate that the approach is well utilized to obtain the governing equations for the hybrid energy harvester under harmonic excitation and GWN.

Band Edge Emission Improvement by Energy Transfer in HybridⅢ-Nitride/Organic Semiconductor Nanostructure

GaN nanorods are fabricated using inductively coupled plasma etching with Ni nano-island masks. The poly [2- methoxy-5-（2-ethyl）hexoxy-l,4-phenylenevinylene] （MEH-PPV）/GaN-nanorod hybrid structure is fabricated by depositing the MEH-PPV film on the GaN nanorods by using the spin-coating process. In the hybrid structure, the spatial separation is minimized to achieve high-emciency non-radiative resonant energy transfer. Optical properties of a novel device consisting of MEH-PPV/GaN-nanorod hybrid structure is studied by analyzing photoluminescenee （PL） spectra. Compared with the pure GaN nanorods, the PL intensity of the band edge emission of GaN in the MEH-PPV/GaN-nanorods is enhanced as much as three times, and the intensity of the yellow band is suppressed slightly. The obtained results are analyzed by energy transfer between the GaN nanorods and the MEH-PPV. An energy transfer model is proposed to explain the phenomenon.

Nonequilibrium reservoir engineering of a biased coherent conductor for hybrid energy transport in nanojunctions

We show that a current-carrying coherent electron conductor can be treated as an effective bosonic energy reservoir involving different types of electron–hole pair excitations.For weak electron–boson coupling,hybrid energy transport between nonequilibrium electrons and bosons can be described by a Landauer-like formula.This allows for unified account of a variety of heat transport problems in hybrid electron–boson systems.As applications,we study the non-reciprocal heat transport between electrons and bosons,thermoelectric current from a cold-spot,and electronic cooling of the bosons.Our unified framework provides an intuitive way of understanding hybrid energy transport between electrons and bosons in their weak coupling limit.It opens the way of nonequilibrium reservoir engineering for efficient energy control between different quasi-particles at the nanoscale.

New developments in the multiscale hybrid energy density computational method

Further developments in the hybrid multiscale energy density method are proposed on the basis of our previous papers. The key points are as follows. （i） The theoretical method for the determination of the weight parameter in the energy coupling equation of transition region in multiscale model is given via constructing underdetermined equations. （ii） By applying the developed mathematical method, the weight parameters have been given and used to treat some problems in homogeneous charge density systems, which ,＇ire directly related with multiscale science. （iii） A theoretical algorithm has also been presented for treating non-homogeneous systems of charge density. The key to the theoretical computational methods is the decomposition of the electrostatic energy in the total energy of density functional theory for probing the spanning characteristic at atomic scale, layer by layer, by which the choice of chemical elements and the defect complex effect can be understood deeply. （iv） The＇numerical computational program and design have also been presented.

Hybrid Renewable Energy Source Combined Dynamic Voltage Restorer for Power Quality Improvement

In this paper,the hybrid photovoltaic-thermoelectric generator(PVTEG)combined dynamic voltage restorer(DVR)system is proposed for the power quality disturbances compensation in a single-phase distribution system.The stable and precise level of input voltage is essential for the smooth and trouble-free operation of the electrically sensitive loads which are connected at the utility side to avoid system malfunctions.In this context,the hybrid PV-TEG energy module combined DVR system is proposed in this paper.With the support of the hybrid energy module,the DVR will perform the power quality disturbances compensation effectively with needed voltage and/or power.In the proposed system,the PV and TEG energy sources are connected electrically in series to produce adequate voltage for the DVR operation and the fractional factor-based variable incremental conduction(FFVINC)maximum power point tracking(MPPT)control algorithm is employed to extract the possible maximum power from the PV array.The intelligent fuzzy logic controller(FLC)is chosen for implementing the MPPT control algorithm.The half-bridge voltage source inverter(VSI)circuit and in-phase voltage compensation technique are used in the DVR for better power quality disturbances compensation.The performance and usefulness of the proposed DVR system are investigated by an extensive simulation study with four different modes of operation,the study results are confirmed that the proposed system promptly identifies the power quality disturbances for compensation.Moreover,the investigation proved that the combined PV and TEG energy module can provide better energy efficiency in converting solar irradiation into electricity.