A Review of Seasonal Hydrogen Storage Multi-Energy Systems Based on Temporal and Spatial Characteristics

The temporal and spatial characteristics of seasonal hydrogen storage will play a very important role in the coupling of multi-energy systems.This essay believes that there are several key issues worth noting in the seasonal hydrogen storage coupled multi-energy system,namely,hydrogen storage methods,coupling models,and benefit evaluation.Through research,this article innovatively divides seasonal hydrogen storage into two types:space transfer hydrogen storage technology and time transfer physical property conversion hydrogen storage technology.Then sort out the two most typical seasonal hydrogen storage multi-energy system application scenarios and their hydrogen storage unit models.Finally,it is shown that hydrogen storage methods should be selected according to different periods of time and regions,and the benefits should be evaluated before they can be used in practice.This review study is applicable to the process of coupling seasonal hydrogen storage in multi-energy systems.Hydrogen energy is used as an intermediate energy link for the selection,evaluation and modeling of the optimal selection and rational utilization.

Optimal Dispatch for Flexible Uncertainty Sets in Multi-energy Systems: An IGDT Based Two-stage Decision Framework

The operational stability and economy of multi-energy systems(MES)are threatened by various uncertainties,such as variable renewable energy power,energy demands,and weather conditions.Most of the existing methods for the dispatch decisions of MES are based on the prescribed probability distribution or uncertainty sets of random variables,which have many disadvantages,such as potential infeasibility and over-conservatism.In this paper,we propose a novel dispatch model for MES that integrates dispatch decision making,uncertainty set selection,and operational cost control into a unified framework.First,the deterministic dispatch model of MES is introduced,in which the physical characteristics of district heating systems and buildings are fully considered.Then,a novel decision framework that combines the two-stage dispatch strategy and info-gap decision theory(IGDT)is proposed for MES,where the uncertainty set is flexible and can be optimized based on the operational cost budget.Finally,a revised algorithm,based on the column-and-constraint generation method,is proposed for the model.Case studies are performed on MES that includes a 33-bus distribution system and a heating network modified from a real 51-node network located in Jinlin Province,China.The results verify the effectiveness of the proposed method.

Strategic potential of multi-energy system towards carbon neutrality:A forward-looking overview

Carbon neutrality is an ambitious goal that has been promulgated to be achieved on or before 2060.However,most of the current energy policies focus more on carbon emission reduction,efficiency and high penetration of renewable energy.Thus,this paper presented a review strategy towards carbon neutrality by presenting the concept of a multi-energy system(MES)in terms of its technologies,configuration,modelling and feasibility as zero-emission equipment.The paper addressed some prominent challenges associated with zero-carbon multi-energy systems(ZCMES).Various proven solutions in the extant studies that have been affirmed to alleviate some of these challenges were presented.In the end,we identified and summarised the current research gaps,and the future directions to ensure the feasibility of ZCMES as a primary strategy towards the actualization of carbon neutrality.Hence,this review work serves as a reference for revising the current energy policies to incorporate a carbon neutrality framework.

Object-oriented Modeling for Planning and Control of Multi-energy Systems

Multi-energy systems(MES)involving networks of different energy carriers can support the balancing of fluctuating renewable generation by co-ordinated joint operation.In this paper,an object-oriented modeling methodology for planning and operations control of MES based on nodal analysis is proposed.The framework provides the modularity to simulate scenarios with varying network configurations.Based on object-oriented programming,classes are formed with regard to common attributes of the network elements.The instances of classes represent physical network elements,such as buses,lines,and power conversion units.The models of the individual network elements involve adjustable and flexible parameters.This is especially advantageous for scenarios with operatingpoint-dependent efficiencies.The overall framework makes use of a uniform description of the model parameters across the diverse energy carriers.Thus,the methodology is particularly suited for the analysis of MES.The applicability of the modeling framework is demonstrated by two use cases involving a technology campus in Berlin.

Federated double DQN based multi-energy microgrid energy management strategy considering carbon emissions

Multi-energy microgrids(MEMG)play an important role in promoting carbon neutrality and achieving sustainable development.This study investigates an effective energy management strategy(EMS)for MEMG.First,an energy management system model that allows for intra-microgrid energy conversion is developed,and the corresponding Markov decision process(MDP)problem is formulated.Subsequently,an improved double deep Q network(iDDQN)algorithm is proposed to enhance the exploration ability by modifying the calculation of the Q value,and a prioritized experience replay(PER)is introduced into the iDDQN to improve the training speed and effectiveness.Finally,taking advantage of the federated learning(FL)and iDDQN algorithms,a federated iDDQN is proposed to design an MEMG energy management strategy to enable each microgrid to share its experiences in the form of local neural network(NN)parameters with the federation layer,thus ensuring the privacy and security of data.The simulation results validate the superior performance of the proposed energy management strategy in minimizing the economic costs of the MEMG while reducing CO_2 emissions and protecting data privacy.

Optimal dispatch approach for rural multi-energy supply systems considering virtual energy storage

In response to the underutilization of energy and insufficient flexible operation capability of rural energy supply systems in China,this study proposes an optimal dispatch approach for a rural multi-energy supply system(RMESS)considering virtual energy storage(VES).First,to enable the flexible utilization of rural biomass resources and the thermal inertia of residential building envelopes,this study constructed VES-I and VES-II models that describe electrical-thermal and electrical-gas coupling from an electrical viewpoint.Subsequently,an RMESS model encompassing these two types of VES was formulated.This model delineates the intricate interplay of multi-energy components within the RMESS framework and facilitates the precise assessment of the adjustable potential for optimizing RMESS operations.Based on the above models,a day-ahead optimal dispatch model for an RMESS considering a VES is proposed to achieve optimal economic performance while ensuring efficient energy allocation.Comparative simulations validated the effectiveness of the VES modeling and the day-ahead optimal dispatch approach for the RMESS.

Multi-energy synergistic optimization in steelmaking process based on energy hub concept

The production process of iron and steel is accompanied by a large amount of energy production and consumption. Optimal scheduling and utilization of these energies within energy systems are crucial to realize a reduction in the cost, energy use, and CO_2 emissions.However, it is difficult to model and schedule energy usage within steel works because different types of energy and devices are involved. The energy hub(EH), as a universal modeling frame, is widely used in multi-energy systems to improve its efficiency, flexibility, and reliability.This paper proposed an efficient multi-layer model based on the EH concept, which is designed to systematically model the energy system and schedule energy within steelworks to meet the energy demand. Besides, to simulate the actual working conditions of the energy devices, the method of fitting the curve is used to describe the efficiency of the energy devices. Moreover, to evaluate the applicability of the proposed model, a case study is conducted to minimize both the economic operation cost and CO_2 emissions. The optimal results demonstrated that the model is suitable for energy systems within steel works. Further, the economic operation cost decreased by 3.41%, and CO_2 emissions decreased by approximately 3.67%.

Optimization of Distributed Integrated Multi-energy System Considering Industrial Process Based on Energy Hub

As a typical scenario of distributed integrated multi-energy system(DIMS),industrial park contains complex production constraints and strong associations between industrial productions and energy demands.The industrial production process(IPP)consists of controllable subtasks and strict timing constraints.Taking IPP as a control variable of optimal scheduling,it is an available approach that models the IPP as material flow into an extension energy hub(EH)to achieve the optimization of industrial park.In this paper,considering the coupling between the production process and energy demands,a model of IPP is proposed by dividing the process into different adjustable steps,including continuous subtask,discrete subtask,and storage subtask.Then,a transport model of material flow is used to describe the IPP in an industrial park DIMS.Based on the concept of EH,a universal extension EH model is proposed considering the coupling among electricity,heat,cooling,and material.Furthermore,an optimal scheduling method for industrial park DIMS is proposed to improve the energy efficiency and operation economy.Finally,a case study of a typical battery factory is shown to illustrate the proposed method.The simulation results demonstrate that such a method reduces the operation cost and accurately reflects the operation state of the industrial factory.

A review of Danish integrated multi-energy system flexibility options for high wind power penetration

The current status of wind power and the energy infrastructure in Denmark is reviewed in this paper.The reasons for why Denmark is a world leader in wind power are outlined.The Danish government is aiming to achieve 100%renewable energy generation by 2050.A major challenge is balancing load and generation.In addition,the current and future solutions of enhancing wind power penetration through optimal use of cross-energy sector flexibility,so-called indirect electric energy storage options,are investigated.A conclusion is drawn with a summary of experiences and lessons learned in Denmark related to wind power development.

Two-stage capacity optimization approach of multi-energy system considering its optimal operation

With the depletion of fossil fuel and climate change,multi-energy systems have attracted widespread attention in buildings.Multi-energy systems,fuelled by renewable energy,including solar and biomass energy,are gain-ing increasing adoption in commercial buildings.Most of previous capacity design approaches are formulated based upon conventional operating schedules,which result in inappropriate design capacities and ineffective operating schedules of the multi-energy system.Therefore,a two-stage capacity optimization approach is pro-posed for the multi-energy system with its optimal operating schedule taken into consideration.To demonstrate the effectiveness of the proposed capacity optimization approach,it is tested on a renewable energy fuelled multi-energy system in a commercial building.The primary energy devices of the multi-energy system consist of biomass gasification-based power generation unit,heat recovery unit,heat exchanger,absorption chiller,elec-tric chiller,biomass boiler,building integrated photovoltaic and photovoltaic thermal hybrid solar collector.The variable efficiency owing to weather condition and part-load operation is also considered.Genetic algorithm is adopted to determine the optimal design capacity and operating capacity of energy devices for the first-stage and second-stage optimization,respectively.The two optimization stages are interrelated;thus,the optimal design and operation of the multi-energy system can be obtained simultaneously and effectively.With the adoption of the proposed novel capacity optimization approach,there is a 14%reduction of year-round biomass consumption compared to one with the conventional capacity design approach.

The Static Stability Region of an Integrated Electricity-Gas System Considering Voltage and Gas Pressure

In an integrated electricity-gas system(IEGS),load fluctuations affect not only the voltage in the power system but also the gas pressure in the natural gas system.The static voltage stability region(SVSR)method is a tool for analyzing the overall static voltage stability in a power system.However,in an IEGS,the SVSR boundary may be overly optimistic because the gas pressure may collapse before the voltage collapses.Thus,the SVSR method cannot be directly applied to an IEGS.In this paper,the concept of the SVSR is extended to the IEGS-static stability region(SSR)while considering voltage and gas pressure.First,criteria for static gas pressure stability in a natural gas system are proposed,based on the static voltage stability criteria in a power system.Then,the IEGS-SSR is defined as a set of active power injections that satisfies multi-energy flow(MEF)equations and static voltage and gas pressure stability constraints in the active power injection space of natural gas-fired generator units(NGUs).To determine the IEGSSSR,a continuation MEF(CMEF)method is employed to trace the boundary point in one specific NGU scheduling direction.A multidimensional hyperplane sampling method is also proposed to sample the NGU scheduling directions evenly.The obtained boundary points are further used to form the IEGSSSR in three-dimensional(3D)space via a Delaunay triangulation hypersurface fitting method.Finally,the numerical results of typical case studies are presented to demonstrate that the proposed method can effectively form the IEGS-SSR,providing a tool for IEGS online monitoring and dispatching.

Simulation and Analysis of Cascading Faults in Integrated Heat and Electricity Systems Considering Degradation Characteristics

Cascading faults have been identified as the primary cause of multiple power outages in recent years.With the emergence of integrated energy systems(IES),the conventional approach to analyzing power grid cascading faults is no longer appropriate.A cascading fault analysis method considering multi-energy coupling characteristics is of vital importance.In this study,an innovative analysis method for cascading faults in integrated heat and electricity systems(IHES)is proposed.It considers the degradation characteristics of transmission and energy supply com-ponents in the system to address the impact of component aging on cascading faults.Firstly,degradation models for the current carrying capacity of transmission lines,the water carrying capacity and insulation performance of thermal pipelines,as well as the performance of energy supply equipment during aging,are developed.Secondly,a simulation process for cascading faults in the IHES is proposed.It utilizes an overload-dominated development model to predict the propagation path of cascading faults while also considering network islanding,electric-heating rescheduling,and load shedding.The propagation of cascading faults is reflected in the form of fault chains.Finally,the results of cascading faults under different aging levels are analyzed through numerical examples,thereby verifying the effectiveness and rationality of the proposed model and method.

Modeling and Utilization of Biomass-to-syngas for Industrial Multi-energy Systems

Excessive consumption of fossil fuels in the industry sector has caused hij»h operating costs and severe environmental pollution,advocating a cost-effective and sustainable substitute for fossil fuels.I'his paper proposes an enhanced utilization mechanism of biomass-to-syngas(B2S)to provide various types of steam flows in industrial multi-energy systems(MESs).In this mechanism,the available generations from renewable energy sources(RESs)can be harvested to assist in the biomass gasification in a B2S gasifier for enhancing the syngas yield and its calorific value.A thermodynamic interaction model for B2S is formulated to capture gasification temperature dynamics under high-temperature steam injections and optimally control the thermochemical behaviors of biomass drying,pyrolysis,and gasification.A B2S based energy hub framework with its multienergy coupling matrix is formulated for mapping the input hiomass-wind-solar energy into electricity,syngas,and various types of’steam carriers to satisfy industrial energy cieniands.A hierarchical multi-timeframe dispatch scheme is developed for the energy-efficient conversion and utilization of multi-energy carriers to minimize the system operation costs.Comparative studies are implemented to demonstrate the superior performance of the proposed methodology on system operational economy and sustainability.

Optimal operation of cold–heat–electricity multi-energy collaborative system based on price demand response

In a multi-energy collaboration system, cooling, heating, electricity, and other energy components are coupled to complement each other. Through multi-energy coordination and cooperation, they can significantly improve their individual operating efficiency and overall economic benefits. Demand response, as a multi-energy supply and demand balance method, can further improve system flexibility and economy. Therefore, a multi-energy cooperative system optimization model has been proposed, which is driven by price-based demand response to determine the impact of power-demand response on the optimal operating mode of a multi-energy cooperative system. The main components of the multi-energy collaborative system have been analyzed. The multi-energy coupling characteristics have been identified based on the energy hub model. Using market elasticity as a basis, a price-based demand response model has been built. The model has been optimized to minimize daily operating cost of the multi-energy collaborative system. Using data from an actual situation, the model has been verified, and we have shown that the adoption of price-based demand response measures can significantly improve the economy of multi-energy collaborative systems.

Day-ahead Risk-constrained Stochastic Scheduling of Multi-energy System

As an increasing penetration of renewable energy sources can potentially impact voltage profile and compromise system security,the security continues to be the most critical concern in power system operations.A risk-constrained stochastic scheduling model is proposed to leverage the latent scheduling capacity of a multi-energy system to seek an economic operation solution while maintaining system operation risk level against uncertain renewable generation.Overvoltage risk constraints,as compared to the straightforward voltage boundary limits,are incorporated into the stochastic scheduling model to guarantee the operation security and economics.Linearized AC power flow model is applied to enable overvoltage risk assessment within the coordinated scheduling model.The proposed stochastic scheduling model is tackled via the improved progressive hedging approach with an enhanced relax-round-polish process,which overcomes the convergence issues of the traditional progressive hedging in handling nonconvex stochastic scheduling model with binary variables on both stages.Numerical simulation results of IEEE 30-bus system and IEEE 118-bus system illustrate the efficacy of the proposed model in ensuring voltage security and improving economic operation of systems.

A Summary of the Main Contents and Existing Problems in the Study of Multi-Energy Coupling in Energy Internet

Multi-energy flow (MEF) coupling is one of the key features of the energy Internet and integrated energy systems that are different from smart grids. With the increasing coupling of heterogeneous energy flow, the system characteristics of coupling are becoming more and more obvious and more complicated. The modeling, analysis and control methods of traditional single flow systems have not been applied directly. Therefore, it is necessary to study the modeling of multi-energy flow coupling, the power flow analysis, optimization and control method of heterogeneous energy flow, which plays the role of multi-energy flow synergy to avoid the adverse effects of coupling. This paper summarizes the current research situation of energy Internet at home and abroad from the aspects of modeling of multi-energy flow, power flow calculation and optimal dispatching, and analyzes the existing problems in the research of these aspects.

Design of the Multi-Energy Complementary Distributed Energy System for Towns

The multi-energy complementary distributed energy system (MCDES) covers a variety of energy forms, involves complex operation modes, and contains a wealth of control equipment and coupling links. It can realize the complementary and efficient use of different types of energy, which is the basic component of the physical layer of the Energy Internet. In this paper, aiming at the demand of the energy application for towns, a distributed energy system based on multi-energy complementary is constructed. Firstly, the supply condition of the distributed energy for the demonstration project is analyzed, and the architecture of the multi-energy complementary distributed energy system is established. Then the regulation strategy of the multi-energy complementary distributed energy system is proposed. Finally, an overall system scheme for the multi-energy complementary distributed energy system suitable for towns is developed, which provides a solid foundation for the development and promotion of the multi-energy complementary distributed energy system.

Multi-Energy Gamma-Ray Attenuations for Non-Destructive Detection of Hazardous Materials

We present a non-destructive method (NDM) to identify minute quantities of high atomic number (Z) elements in containers such as passenger baggage, goods carrying transport trucks, and environmental samples. This method relies on the fact that photon attenuation varies with its energy and properties of the absorbing medium. Low-energy gamma-ray intensity loss is sensitive to the atomic number of the absorbing medium, while that of higher-energies vary with the density of the medium. To verify the usefulness of this feature for NDM, we carried out simultaneous measurements of intensities of multiple gamma rays of energies 81 to 1408 keV emitted by sources 133Ba (half-life = 10.55 y) and 152Eu (half-life = 13.52 y). By this arrangement, we could detect minute quantities of lead and copper in a bulk medium from energy dependent gamma-ray attenuations. It seems that this method will offer a reliable, low-cost, low-maintenance alternative to X-ray or accelerator-based techniques for the NDM of high-Z materials such as mercury, lead, uranium, and transuranic elements etc.

Bi-level Multi-leader Multi-follower Stackelberg Game Model for Multi-energy Retail Package Optimization

In the competitive energy market,energy retailers are facing the uncertainties of both energy price and demand,which requires them to formulate reasonable energy purchasing and selling strategies for improving their competitiveness in this market.Particularly,the attractive multi-energy retail packages are the key for retailers to increase their benefit.Therefore,combined with incentive means and price signals,five types of multi-energy retail packages such as peak-valley time-of-use(TOU)price package and day-night bundled price package are designed in this paper for retailers.The iterative interactions between retailers and end-users are modeled using a bi-level model of stochastic optimization based on multi-leader multi-follower(MLMF)Stackelberg game,in which retailers are leaders and end-users are followers.Retailers make decisions to maximize the profit considering the conditional value at risk(CVaR)while end-users optimize the satisfaction of both energy comfort and economy.Besides,a distributed algorithm is proposed to obtain the Nash equilibrium of above MLMF Stackelberg game model while the particle swarm optimization(PSO)algorithm and CPLEX solver are applied to solve the optimization model for each participant(retailer or end-user).Numeral results show that the designed retail packages can increase the overall profit of retailers,and the overall satisfaction of industrial users is the highest while that of residential users is the lowest after game interaction.

石化行业控制室承爆风险评估方法研究

针对传统的气体爆炸风险评估方法的不足之处,提出采用一种基于CFD技术的气体爆炸风险评估方法,对某煤气化厂区氢气爆炸对控制室造成的风险进行模拟计算与预测分析。并把研究结果与传统的TNT当量法、Multi-Energy方法预测结果进行比较。结果表明,该方法能考虑到密集管道与复杂装置布局、气云大小等因素对爆炸超压的影响,且能用于超压波的近场预测,以及确定空间不同位置处的爆炸超压,更适用于石化行业控制室的承爆风险评估。