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.

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.

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.

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.

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.

MPPT for Hybrid Energy System Using Gradient Approximation and Matlab Simulink Approach

This paper applies new maximum-power-point tracking （MPPT） algorithm to a hybrid renewable energy system that combines both Wind-Turbine Generator （WTG） and Solar Photovoltaic （PV） Module （SPVM）. In this paper, the WTG is a direct-drive system and includes wind turbine, three-phase permanent magnet synchronous generator, three-phase full bridge rectifier, and buck-bust converter, while the SPVM consist of solar PV modules, buck converter, maximum power tracking system for both systems, and load. Several methods are applied to obtain maximum performances, the appropriate and most effective method is called gradient-approximation method for WTG approach, because it enables the generator to operate at variable wind speeds. Furthermore MPPT also is used to optimized the achieved energy generated by solar PV modules.Matlab / Simulink approach is used to simulate, discuss, and optimized the generated power by varying the duty cycle of the converters, and tip speed ratio of the WTG system.

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.

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.

Fuzzy Adaptive Filtering-Based Energy Management for Hybrid Energy Storage System

Regarding the problem of the short driving distance of pure electric vehicles,a battery,super-capacitor,and DC/DC converter are combined to form a hybrid energy storage system(HESS).A fuzzy adaptive filtering-based energy management strategy(FAFBEMS)is proposed to allocate the required power of the vehicle.Firstly,the state of charge(SOC)of the super-capacitor is limited according to the driving/braking mode of the vehicle to ensure that it is in a suitable working state,and fuzzy rules are designed to adaptively adjust the filtering time constant,to realize reasonable power allocation.Then,the positive and negative power are determined,and the average power of driving/braking is calculated so as to limit the power amplitude to protect the battery.To verify the proposed FAFBEMS strategy for HESS,simulations are performed under the UDDS(Urban Dynamometer Driving Schedule)driving cycle.The results show that the FAFBEMS strategy can effectively reduce the current amplitude of the battery,and the final SOC of the battery and super-capacitor is optimized to varying degrees.The energy consumption is 7.8%less than that of the rule-based energy management strategy,10.9%less than that of the fuzzy control energy management strategy,and 13.1%less than that of the filtering-based energy management strategy,which verifies the effectiveness of the FAFBEMS strategy.

Dual Power Allocation Optimization Based on Stackelberg Game in Heterogeneous Network with Hybrid Energy Supplies

In heterogeneous network with hybrid energy supplies including green energy and on-grid energy, it is imperative to increase the utilization of green energy as well as to improve the utilities of users and networks. As the difference of hybrid energy source in stability and economy, thus, this paper focuses on the network with hybrid energy source, and design the utility of each user in the hybrid energy source system from the perspective of stability, economy and environment pollution. A dual power allocation algorithm based on Stackelberg game to maximize the utilities of users and networks is proposed. In addition, an iteration method is proposed which enables all players to reach the Stackelberg equilibrium(SE). Simulation results validate that players can reach the SE and the utilities of users and networks can be maximization, and the green energy can be efficiently used.

Research on the Hybrid Energy Storage based Photovoltaic Piconets and the Isolated Net Running Comprehensive Control System in the Campus Environment

In this paper, we conduct research on the hybrid energy storage based photovoltaic piconets and the isolated net running comprehensive control system in the campus environment. Piconets flexible operation mode and the efficient power supply without perfect stable control. Micro the early stage of network development related to micro network operation concepts are modeled on the control of large power system. Our proposed approach is proven to be effective and feasible through the numerical simulation and theoretical analysis which will be meaningful.

Real-time Energy Management Method for Electric-hydrogen Hybrid Energy Storage Microgrids Based on DP-MPC

With the increasing presence of intermittent energy resources in microgrids,it is difficult to precisely predict the output of renewable resources and their load demand.In order to realize the economical operations of the system,an energy management method based on a model predictive control(MPC)and dynamic programming(DP)algorithm is proposed.This method can reasonably distribute the energy of the battery,fuel cell,electrolyzer and external grid,and maximize the output of the distributed power supply while ensuring the power balance and cost optimization of the system.Based on an ultra-shortterm forecast,the output power of the photovoltaic array and the demand power of the system load are predicted.The offline global optimization of traditional dynamic programming is replaced by the repeated rolling optimization in a limited period of time to obtain power values of each unit in the energy storage system.Compared with the traditional DP,MILP-MPC and the logic based real-time management method,the proposed energy management method is proved to be feasible and effective.

High Na-ion conductivity andmechanical integrity of anion-exchanged polymeric hydrogel electrolytes for flexible sodium ion hybrid energy storage

The polymeric gel electrolytes are attractive owing to their higher ionic conductivities than those of dry polymer electrolytes and lowered water activity for enlarged potential window.However,the ionic conductivity and mechanical strength of the Na-ion conducting polymeric gel electrolytes are limited by below 20 mS cm−1 and 2.2 MPa.Herein,we demonstrate Na-ion conducting and flexible polymeric hydrogel electrolytes of the chemically coupled poly(diallyldimethylammonium chloride)-dextrin-N,N′-methylene-bisacrylamide film immersed in NaClO_(4) solution(ex-DDA-Dex+NaClO_(4))for flexible sodium-ion hybrid capacitors(f-NIHC).In particular,the anion exchange reaction and synergistic interaction of ex-DDA-Dex with the optimum ClO_(4)−enable to greatly improve the ionic conductivity up to 27.63 mS cm−1 at 25◦C and electrochemical stability window up to 2.6 V,whereas the double networking structure leads to achieve both the mechanical strength(7.48 MPa)and softness of hydrogel electrolytes.Therefore,the f-NIHCs with the ex-DDA-Dex+NaClO_(4) achieved high specific and high-rate capacities of 192.04 F g^(−1)at 500 mA g^(−1)and 116.06 F g^(−1)at 10000 mA g^(−1),respectively,delivering a large energy density of 120.03Wh kg^(−1)at 906Wkg^(−1)and long cyclability of 70%over 500 cycles as well as demonstrating functional operation under mechanical stresses.

Characteristics of Bi-2223 HTS Tapes Under Short-Circuit Current Impacts in Hybrid Energy Transmission Pipelines

A hybrid energy transmission pipeline is proposed with the aim of long-distance cooperative transmission of electricity and chemical fuels, which is composed of an inner high-temperature superconducting (HTS) power cable and outer liquefied natural gas (LNG) pipeline. The flowing LNG could maintain the operating temperature of the inner HTS power cable within the range of 85 K-90 K, thus the Bi-2223 superconductors in the HTS power cable produce little Joule loss with the transmission current below the critical current. Owing to the advantages of high power density, low transmission losses and economical manufacturing costs, the hybrid energy transmission pipeline is expected to be widely utilized in the near future. In order to ensure the safety of the HTS power cable and explosive LNG in case of short-circuit faults, this paper tests and analyzes the characteristics of Bi-2223 HTS tapes of the Type HT-CA, Type HT-SS and Type H models under short-circuit current impacts at the LNG cooling temperature (85 K-90 K). An experimental platform is designed and established for the ampacity tests of HTS tapes above LN2 cooling temperature (77 K). The AC over-current impact tests at 85 K-90 K are carried out on each sample of Bi-2223 tapes respectively, and the experimental results are analyzed and compared to evaluate their performances under different operating conditions. The results indicate that the Type HT-CA tape can withstand 50 Hz short-circuit current impact with the amplitude of 1108 A (10 times of critical current Ic ) for 100 ms at 90 K, and its resistance is the smallest of the three tested samples under similar current impacts. Therefore, the Type HT-CA Bi-2223 tape is the optimal superconductor of the HTS power cable in the hybrid energy transmission pipeline.

An overview of application-oriented multifunctional large-scale stationary battery and hydrogen hybrid energy storage system

The imperative to address traditional energy crises and environmental concerns has accelerated the need for energy structure transformation.However,the variable nature of renewable energy poses challenges in meeting complex practical energy requirements.To address this issue,the construction of a multifunctional large-scale stationary energy storage system is considered an effective solution.This paper critically examines the battery and hydrogen hybrid energy storage systems.Both technologies face limitations hindering them from fully meeting future energy storage needs,such as large storage capacity in limited space,frequent storage with rapid response,and continuous storage without loss.Batteries,with their rapid response(<1 s)and high efficiency(>90%),excel in frequent short-duration energy storage.However,limitations such as a self-discharge rate(>1%)and capacity loss(~20%)restrict their use for long-duration energy storage.Hydrogen,as a potential energy carrier,is suitable for large-scale,long-duration energy storage due to its high energy density,steady state,and low loss.Nevertheless,it is less efficient for frequent energy storage due to its low storage efficiency(~50%).Ongoing research suggests that a battery and hydrogen hybrid energy storage system could combine the strengths of both technologies to meet the growing demand for large-scale,long-duration energy storage.To assess their applied potentials,this paper provides a detailed analysis of the research status of both energy storage technologies using proposed key performance indices.Additionally,application-oriented future directions and challenges of the battery and hydrogen hybrid energy storage system are outlined from multiple perspectives,offering guidance for the development of advanced energy storage systems.

Optimal Multi-Timescale Scheduling of Integrated Energy Systems with Hybrid Energy Storage System Based on Lyapunov Optimization

The economic operation of integrated energy system(IES)faces new challenges such as multi-timescale characteristics of heterogeneous energy sources,and cooperative operation of hybrid energy storage system(HESS).To this end,this paper investigates the multi-timescale rolling opti-mization problem for IES integrated with HESS.Firstly,the architecture of IES with HESS is established,a comparative analysis is conducted to evaluate the advantages of the HESS over a single energy storage system(SESS)in stabilizing power fluctuations.Secondly,the dayahead and real-time scheduling cost functions of IES are established,the day-ahead scheduling mainly depends on operation costs of the components in IES,the real-time optimal scheduling adopts the Lya-punov optimization method to schedule the battery and hydrogen energy storage in each time slot,so as to minimize the real-time average scheduling operation cost,and the problem of day-ahead and real-time scheduling error,which caused by the uncertainty of the energy storage is solved by online optimization.Finally,the proposed model is verified to reduce the scheduling operation cost and the dispatching error by performing an arithmetic example analysis of the IES in Shanghai,which provides a reference for the safe and stable operation of the IES.

Dynamic Task Offloading for Mobile Edge Computing with Hybrid Energy Supply

Mobile edge computing(MEC),as a new distributed computing model,satisfies the low energy consumption and low latency requirements of computation-intensive services.The task offloading of MEC has become an important research hotspot,as it solves the problems of insufficient computing capability and battery capacity of Internet of things(IoT)devices.This study investigates task offloading scheduling in a dynamic MEC system.By integrating energy harvesting technology into IoT devices,we propose a hybrid energy supply model.We jointly optimize local computing,offloading duration,and edge computing decisions to minimize system cost.On the basis of stochastic optimization theory,we design an online dynamic task offloading algorithm for MEC with a hybrid energy supply called DTOME.DTOME can make task offloading decisions by weighing system cost and queue stability.We quote dynamic programming theory to obtain the optimal task offloading strategy.Simulation results verify the effectiveness of DTOME,and show that DTOME entails lower system cost than two baseline task offloading strategies.