A power plant for integrated waste energy recovery from liquid air energy storage and liquefied natural gas

Liquefied natural gas(LNG)is regarded as one of the cleanest fossil fuel and has experienced significant developments in recent years.The liquefaction process of natural gas is energy-intensive,while the regasification of LNG gives out a huge amount of waste energy since plenty of high grade cold energy(-160℃)from LNG is released to sea water directly in most cases,and also sometimes LNG is burned for regasification.On the other hand,liquid air energy storage(LAES)is an emerging energy storage technology for applications such as peak load shifting of power grids,which generates 30%-40%of compression heat(-200℃).Such heat could lead to energy waste if not recovered and used.The recovery of the compression heat is technically feasible but requires additional capital investment,which may not always be economically attractive.Therefore,we propose a power plant for recovering the waste cryogenic energy from LNG regasification and compression heat from the LAES.The challenge for such a power plant is the wide working temperature range between the low-temperature exergy source(-160℃)and heat source(-200℃).Nitrogen and argon are proposed as the working fluids to address the challenge.Thermodynamic analyses are carried out and the results show that the power plant could achieve a thermal efficiency of 27%and 19%and an exergy efficiency of 40%and 28%for nitrogen and argon,respectively.Here,with the nitrogen as working fluid undergoes a complete Brayton Cycle,while the argon based power plant goes through a combined Brayton and Rankine Cycle.Besides,the economic analysis shows that the payback period of this proposed system is only 2.2 years,utilizing the excess heat from a 5 MW/40 MWh LAES system.The findings suggest that the waste energy based power plant could be co-located with the LNG terminal and LAES plant,providing additional power output and reducing energy waste.

Real-time Risk-averse Dispatch of an Integrated Electricity and Natural Gas System via Condi-tional Value-at-risk-based Lookup-table Ap-proximate Dynamic Programming

The real-time risk-averse dispatch problem of an integrated electricity and natural gas system(IEGS)is studied in this paper.It is formulated as a real-time conditional value-at-risk(CVaR)-based risk-averse dis-patch model in the Markov decision process framework.Because of its stochasticity,nonconvexity and nonlinearity,the model is difficult to analyze by traditional algorithms in an acceptable time.To address this non-deterministic polynomial-hard problem,a CVaR-based lookup-table approximate dynamic programming(CVaR-ADP)algo-rithm is proposed,and the risk-averse dispatch problem is decoupled into a series of tractable subproblems.The line pack is used as the state variable to describe the impact of one period’s decision on the future.This facilitates the reduction of load shedding and wind power curtailment.Through the proposed method,real-time decisions can be made according to the current information,while the value functions can be used to overview the whole opti-mization horizon to balance the current cost and future risk loss.Numerical simulations indicate that the pro-posed method can effectively measure and control the risk costs in extreme scenarios.Moreover,the decisions can be made within 10 s,which meets the requirement of the real-time dispatch of an IEGS.Index Terms—Integrated electricity and natural gas system,approximate dynamic programming,real-time dispatch,risk-averse,conditional value-at-risk.

The second fusion of laser and aerospace-an inspiration for high energy lasers

Since the first laser was invented,the pursuit of high-energy lasers(HELs)has always been enthusiastic.The first revolution of HELs was pushed by the fusion of laser and aerospace in the 1960s,with the chemical rocket engines giving fresh impetus to the birth of gas flow and chemical lasers,which finally turned megawatt lasers from dream into reality.Nowadays,the development of HELs has entered the age of electricity as well as the rocket engines.The properties of current electric rocket engines are highly consistent with HELs’goals,including electrical driving,effective heat dissipation,little medium consumption and extremely light weight and size,which inspired a second fusion of laser and aerospace and motivated the exploration for potential HELs.As an exploratory attempt,a new configuration of diode pumped metastable rare gas laser was demonstrated,with the gain generator resembling an electric rocket-engine for improved power scaling ability.

Analysis and Economic Evaluation of Hourly Operation Strategy Based on MSW Classification and LNG Multi-Generation System

In this study,a model of combined cooling,heating and power system with municipal solid waste(MSW)and liquefied natural gas(LNG)as energy sources was proposed and developed based on the energy demand of a large community,andMSW was classified and utilized.The systemoperated by determining power by heating load,and measures were taken to reduce operating costs by purchasing and selling LNG,natural gas(NG),cooling,heating,and power.Based on this system model,three operation strategies were proposed based on whether MSW was classified and the length of kitchen waste fermentation time,and each strategy was simulated hourly throughout the year.The results showed that the strategy of MSW classified and centralized fermentation of kitchen waste in summer(i.e.,strategy 3)required the least total amount of LNG for the whole year,which was 47701.77 t.In terms of total annual cost expenditure,strategy 3 had the best overall economy,with the lowest total annual expenditure of 2.7730×108 RMB at LNG and NG unit prices of 4 and 4.2 RMB/kg,respectively.The lower heating value of biogas produced by fermentation of kitchen waste from MSW being classified was higher than that of MSW before being classified,so the average annual thermal economy of the operating strategy of MSW being classified was better than that of MSW not being classified.Among the strategies in which MSW was classified and utilized,strategy 3 could better meet the load demand of users in the corresponding season,and thus this strategy had better thermal economy than the strategy of year-round fermentation of kitchen waste(i.e.,strategy 2).The hourly analysis data showed that the net electrical efficiency of the system varies in the same trend as the cooling,heating and power loads in all seasons,while the relationship between the energy utilization efficiency and load varied from season to season.This study can provide guidance for the practical application of MSW being classified in the system.

Enhancing Renewable Energy Integration:A Gaussian-Bare-Bones Levy Cheetah Optimization Approach to Optimal Power Flow in Electrical Networks

In the contemporary era,the global expansion of electrical grids is propelled by various renewable energy sources(RESs).Efficient integration of stochastic RESs and optimal power flow(OPF)management are critical for network optimization.This study introduces an innovative solution,the Gaussian Bare-Bones Levy Cheetah Optimizer(GBBLCO),addressing OPF challenges in power generation systems with stochastic RESs.The primary objective is to minimize the total operating costs of RESs,considering four functions:overall operating costs,voltage deviation management,emissions reduction,voltage stability index(VSI)and power loss mitigation.Additionally,a carbon tax is included in the objective function to reduce carbon emissions.Thorough scrutiny,using modified IEEE 30-bus and IEEE 118-bus systems,validates GBBLCO’s superior performance in achieving optimal solutions.Simulation results demonstrate GBBLCO’s efficacy in six optimization scenarios:total cost with valve point effects,total cost with emission and carbon tax,total cost with prohibited operating zones,active power loss optimization,voltage deviation optimization and enhancing voltage stability index(VSI).GBBLCO outperforms conventional techniques in each scenario,showcasing rapid convergence and superior solution quality.Notably,GBBLCO navigates complexities introduced by valve point effects,adapts to environmental constraints,optimizes costs while considering prohibited operating zones,minimizes active power losses,and optimizes voltage deviation by enhancing the voltage stability index(VSI)effectively.This research significantly contributes to advancing OPF,emphasizing GBBLCO’s improved global search capabilities and ability to address challenges related to local minima.GBBLCO emerges as a versatile and robust optimization tool for diverse challenges in power systems,offering a promising solution for the evolving needs of renewable energy-integrated power grids.

Optimal Scheduling for Flexible Regional Integrated Energy Systemwith Soft Open Point

The Regional Integrated Energy System(RIES)has brought new modes of development,utilization,conversion,storage of energy.The introduction of Soft Open Point(SOP)and the application of Power to Gas(P2G)technology will greatly deepen the coupling of the electricity-gas integrated energy system,improve the flexibility and safety of the operation of the power system,and bring a deal of benefits to the power system.On this background,an optimal dispatch model of RIES combined cold,heat,gas and electricity with SOP is proposed.Firstly,RIES architecture with SOP and P2G is designed and its mathematical model also is built.Secondly,on the basis of considering the optimal scheduling of combined cold,heat,gas and electricity,the optimal scheduling model for RIES was established.After that,the original model is transformed into a mixed-integer second-order cone programming model by using linearization and second-order cone relaxation techniques,and the CPLEX solver is invoked to solve the optimization problem.Finally,the modified IEEE 33-bus systemis used to analyze the benefits of SOP,P2G technology and lithium bromide absorption chillers in reducing systemnetwork loss and cost,as well as improving the system’s ability to absorb wind and solar and operating safety.

Reliability Assessment of Integrated Electricity and Natural Gas Transmission Systems in Presence of Power-to-gas and Combined Heat and Power Technologies

Assessing the reliability of integrated electricity and gas systems has become an important issue due to the strong dependence of these energy networks through the power-to-gas(P2G)and combined heat and power(CHP)technologies.The current work,initially,presents a detailed energy flow model for the integrated power and natural gas system in light of the P2G and CHP technologies.Considering the simultaneous load flow of networks,a contingency analysis procedure is proposed,and reliability is assessed through sequential Monte Carlo simulations.The current study examines the effect of independent and dependent operation of energy networks on the reliability of the systems.In particular,the effect of employing both P2G and CHP technologies on reliability criteria is evaluated.In addition,a series of sensitivity analysis are performed on the size and site of these technologies to investigate their effects on system reliability.The proposed method is implemented on an integrated IEEE 24-bus electrical power system and 20-node Belgian natural gas system.The simulation procedure certifies the proposed method for reliability assessment is practical and applicable.In addition,the results prove connection between energy networks through P2G and CHP technologies can improve reliability of networks if the site and size of technologies are properly determined.

Robust optimization for improving resilience of integrated energy systems with electricity and natural gas infrastructures

The integration of natural gas in electricity network requires a more reliable operating plan for increasing uncertainties in the whole system. In this paper, a threestage robust optimization model is proposed for resilient operation of energy system which integrates electricity and natural gas transmission networks with the objective of minimizing load curtailments caused by attacks. Nonconvex constrains are linearized in order to formulate the dual problem of optimal energy flow. Then, the proposed three-stage problem can be reformulated into a two-stage mixed integer linear program(MILP) and solved by Benders decomposition algorithm. Numerical studies on IEEE30-bus power system with 7-node natural gas network and IEEE 118-bus power system with 14-node natural gas network validate the feasibility of the proposed model for improving resilience of integrated energy system. Energy storage facilities are also considered for the resiliency analysis.

Optimal Operation of Integrated Energy Systems Subject to Coupled Demand Constraints of Electricity and Natural Gas

This paper proposes a hybrid multi-objective optimization and game-theoretic approach(HMOGTA)to achieve the optimal operation of integrated energy systems(IESs)consisting of electricity and natural gas(E&G)utility networks,multiple distributed energy stations(DESs),and multiple energy users(EUs).The HMOGTA aims to solve the coordinated operation strategy of the electricity and natural gas networks considering the demand characteristics of DESs and EUs.In the HMOGTA,a hierarchical Stackelberg game model is developed for generating equilibrium strategies of DESs and EUs in each district energy network(DEN).Based on the game results,we obtain the coupling demand constraints of electricity and natural gas(CDCENs)which reflect the relationship between the amounts and prices of electricity and cooling(E&C)that DESs purchase from utility networks.Furthermore,the minimization of conflicting costs of E&G networks considering the CDCENs are solved by a multi-objective optimization method.A case study is conducted on a test IES composed of a 20-node natural gas network,a modified IEEE 30-bus system,and 3 DENs,which verifies the effectiveness of the proposed HMOGTA to realize fair treatment for all participants in the IES.

Symplectic-energy-first integrators of discrete mechanico-electrical dynamical systems

A discrete total variation calculus with variable time steps is presented for mechanico-electrical systems where there exist non-potential and dissipative forces. By using this discrete variation calculus, the symplectic-energy-first integrators for mechanico-electrical systems are derived. To do this, the time step adaptation is employed. The discrete variational principle and the Euler-Lagrange equation are derived for the systems. By using this discrete algorithm it is shown that mechanico-electrical systems are not symplectic and their energies are not conserved unless they are Lagrange mechanico-electrical systems. A practical example is presented to illustrate these results.

Optimal Energy Reserve Scheduling in Integrated Electricity and Gas Systems Considering Reliability Requirements

With the growing interdependence between the electricity system and the natural gas system,the operation uncertainties in either subsystem,such as wind fluctuations or component failures,could have a magnified impact on the reliability of the whole system due to energy interactions.A joint reserve scheduling model considering the cross-sectorial impacts of operation uncertainties is essential but still insufficient to guarantee the reliable operation of the integrated electricity and natural gas system(IEGS).Therefore,this paper proposes a day-ahead security-constrained unit commitment(SCUC)model for the IEGS to schedule the operation and reserve simultaneously considering reliability requirements.Firstly,the multi-state models for generating units and gas wells are established.Based on the multi-state models,the expected unserved energy cost(EUEC)and the expected wind curtailment cost(EWC)criteria are proposed based on probabilistic methods considering wind fluctuation and random failures of components in IEGS.Furthermore,the EUEC and EWC criteria are incorporated into the day-ahead SCUC model,which is nonconvex and mathematically reformulated into a solvable mixed-integer second-order cone programming(MISOCP)problem.The proposed model is validated using an IEEE 30-bus system and Belgium 20-node natural gas system.Numerical results demonstrate that the proposed model can effectively schedule the energy reserve to guarantee the reliable operation of the IEGS considering the multiple uncertainties in different subsystems and the cross-sectorial failure propagation.

Operation Cost Optimization Method of Regional Integrated Energy System in Electricity Market Environment Considering Uncertainty

In the electricity market environment,the regional integrated energy system(RIES)can reduce the total operation cost by participating in electricity market transactions.However,the RIES will face the risk of load and electricity price uncertainties,which may make its operation cost higher than expected.This paper proposes a method to optimize the operation cost of the RIES in the electricity market environment considering uncertainty.Firstly,based on the operation cost structure of the RIES in the electricity market environment,the energy flow relationship of the RIES is analyzed,and the operation cost model of the RIES is built.Then,the electricity purchase costs of the RIES in the medium-and long-term electricity markets,the spot electricity market,and the retail electricity market are analyzed.Finally,considering the risk of load and electricity price uncertainties,the operation cost optimization model of the RIES is established based on conditional value-at-risk.Then it is solved to obtain the operation cost optimization strategy of the RIES.Verification results show that the proposed operation cost optimization method can reduce the operation cost of high electricity price scenario by optimizing the energy purchase and distribution strategy,constrain the risk of load and electricity price uncertainties,and help balance the risks and benefits.

Optimal Scheduling of Electrical Energy Systems Using a Fluid Dynamic Analogy

The electricity-gas transformation problem and related intrinsic mechanisms are considered.First,existing schemes for the optimization of electricity-gas integrated energy systems are analyzed through consideration of the relevant literature,and an Electricity Hub(EH)for electricity-gas coupling is proposed.Then,the distribution mechanism in the circuit of the considered electricity-gas integrated system is analyzed.Afterward,a mathematical model for the natural gas pipeline is elaborated according to the power relationship,a node power flow calculation method,and security requirements.Next,the coupling relationship between them is implemented,and dedicated simulations are carried out.Through experimental data,it is found that after 79 data iterations,the optimization results of power generation and gas purchase cost in the new system converge to$54,936 in total,which is consistent with the data obtained by an existing centralized optimization scheme.However,the new proposed optimization scheme is found to be more flexible and convenient.

Gas Valorization in the Republic of Congo: Production of Electricity from National Gas Reserves

The environmental impact of greenhouse gases based on natural gas flaring influences the rate of gas recovery around the world. In the Republic of Congo, the natural gas reserve in 2019 is estimated at 90 billion cubic meters (BCM). In this study, from the Congolese gas reserve we used five gas turbines with a capacity of 150 MW each;these five turbines consume 1.69 billion cubic meters (BCM)/year for the power of 273.750 MW and consumption of 6.57 billion kilowatt-hours. The results of this study revealed that an investment capital of 192,305,137 euros was required with a net profit of 9,581,250 euros at an annual rate of return of 4.98% with an investment payback period of approximately 20 years. This will allow the Congolese government to accomplish its policy of valuing gas and developing the country;the electricity produced by the National Petroleum Company of Congo (SNPC) will be sold to the Electrical Energy of Congo (E2C) at 0.06 euro/kWh.

Improving the Global Energy Industry by Integrating Macro-Technologies:Challenges and Opportunities for Corporations

Emerging energy technologies and market evolution of some energy products, particularly natural gas, can converge to produce a new global scenario closer to the objectives of Sustainable Development, with a smooth transition that would avoid social and economic upheavals and could open a new cycle of growth and wealth. The first steps of unconventional gas production have induced stabilization in the gas spot price that should be continued to guarantee stable prices in the long term. Another line of development that should start a second phase of consolidation and cost reduction is the field of Renewable Energies. Besides research and technology advancements, a new financial deal could substitute for subsidies and feed-in tariffs. Last but not least, electric vehicles and other emerging technologies from the demand side will also have a main role in this quest to re-structure the Energy sector, where a new hierarchy of energy goods and energy applications will appear, and a better integral use of energy will take place. A main consequence of that will be a significant reduction of CO2 emissions, and a cheaper cost of energy, although fiscal policies could swallow this advantage. In this transition, which would likely last thirty years or so, energy corporations will have to face challenges and opportunities to consolidate their working and value-adding status.

Modeling and Simulation of Hydrogen Energy Storage System for Power-to-gas and Gas-to-power Systems

By collecting and organizing historical data and typical model characteristics,hydrogen energy storage system(HESS)-based power-to-gas(P2G)and gas-to-power systems are developed using Simulink.The energy transfer mechanisms and numerical modeling methods of the proposed systems are studied in detail.The proposed integrated HESS model covers the following system components:alkaline electrolyzer(AE),highpressure hydrogen storage tank with compressor(CM&H_(2) tank),and proton-exchange membrane fuel cell(PEMFC)stack.The unit models in the HESS are established based on typical U-I curves and equivalent circuit models,which are used to analyze the operating characteristics and charging/discharging behaviors of a typical AE,an ideal CM&H_(2) tank,and a PEMFC stack.The validities of these models are simulated and verified in the MicroGrid system,which is equipped with a wind power generation system,a photovoltaic power generation system,and an auxiliary battery energy storage system(BESS)unit.Simulation results in MATLAB/Simulink show that electrolyzer stack,fuel cell stack and system integration model can operate in different cases.By testing the simulation results of the HESS under different working conditions,the hydrogen production flow,stack voltage,state of charge(SOC)of the BESS,state of hydrogen pressure(SOHP)of the HESS,and HESS energy flow paths are analyzed.The simulation results are consistent with expectations,showing that the integrated HESS model can effectively absorb wind and photovoltaic power.As the wind and photovoltaic power generations increase,the HESS current increases,thereby increasing the amount of hydrogen production to absorb the surplus power.The results show that the HESS responds faster than the traditional BESS in the microgrid,providing a solid theoretical foundation for later wind-photovoltaic-HESS-BESS integration.

基于虚拟储能的综合能源系统用能协调控制策略

多能互补综合能源系统(Integrated Energy System,IES)是提高分布式新能源渗透率和增强终端能源消费灵活性的重要手段,针对现有技术在多能系统对外能量特性建模和多系统交互策略方面研究的不足,文章提出了一种基于虚拟储能的综合能源系统用能协调控制方法,基于多代理技术构建楼宇-代理商-配网三层能量交互架构,以描述系统对外特性的虚拟储能模型为交互接口,量化分析管控多楼宇和并网储能、微燃机等多能分布式资源的代理商的虚拟储能。在此基础上,按照系统空间范围扩大递进分析,构建基于多代理的综合能源系统用能协调控制策略,该策略能够根据决策目标最大化利用以配电网为核心的楼宇、园区等各层级综合能源系统的资源,尽可能实现自治运行。

基于深度强化学习的电-气区域综合能源系统安全校正控制决策方法

电–气区域综合能源系统电、气相互耦合与影响,使得其安全校正控制难度大且对快速性要求高,为此,提出一种基于深度确定性策略梯度(deepdeterministicpolicy gradient,DDPG)算法的安全校正控制决策方法。首先,进行系统多能流与变量分析,建立安全校正控制的目标与约束条件。然后,构建基于DDPG的安全校正控制模型,设计目标奖励和各种约束条件奖励,提出结合基于综合灵敏度的安全校正知识经验设计目标奖励函数,使调整具有方向性,且目标奖励考虑能量枢纽(energy hub,EH)的经济效益及其可再生能源消纳;通过智能体离线训练,使其能够在线做出实时最优的安全校正控制策略,预先产生专家经验数据集存放于经验回放池,提高训练速度和收敛性。最后,通过含EH电–气区域综合能源系统仿真算例验证了所提方法的有效性。

电动汽车与清洁能源融合发展技术研究与展望

以光电、风电为代表的清洁能源发电技术可为电动汽车提供清洁的电力供给,减少全生命周期碳排放,助力交通领域“双碳”战略目标的实现,因此近年来得到迅猛发展。为了推动交能融合技术的应用,明确相关研究中的关键问题,该文综述了国内外学者过去10年在电动汽车与清洁能源融合技术方面的研究进展。首先,介绍了二者融合发展的必要性与现实意义;其次,将已有研究成果分为公路环境与城市道路环境两类,分别从电网、充电站、车辆3个层面归纳了当前电动汽车与清洁能源融合技术的研究成果;最后,考虑到清洁能源发电以及电动汽车充电存在较强的随机波动,对未来发展提出了加强公共领域交能融合发展、构建多种互补型清洁能源发电策略、建立“源—网—荷—储”集成优化技术、强化分布式微电网能源自洽调度、加强无线光伏充电公路运营管理等建议。

含垃圾能源化处理及电动汽车负载的区域综合能源系统协调优化

传统能源系统互相独立、欠缺联动,容易导致能量的浪费,并且能源结构也难以优化。区域综合能源系统具备多能互补、高效利用的优点,是提高能源利用效率和环保性的重要改进技术。为了利用垃圾蕴含的能量和电动汽车负载端的能源消纳,文中建立一个考虑垃圾焚烧和电动汽车负载的区域综合能源系统模型,利用模型进行系统的优化调度研究。论文分析了系统内的多能源能量流通关系,而后对系统内的各种能源转换设备及电动汽车进行分析,引入垃圾能源化处理,将热能转化为电能,并利用电动汽车进行电能消纳的模式,得出区域综合能源系统的能源效益最大化的模型。通过python进行算例分析,结果表明,含垃圾处理和电动汽车参与的区域综合能源系统既能提高能源的利用效率,又能带来更优的经济效益。