Cascading Failure Propagation Simulation in Integrated Electricity and Natural Gas Systems

The sharp increase in the total installed capacity of natural gas generators has intensified the dynamic interaction between the electricity and natural gas systems,which could induce cascading failure propagation across the two systems that deserves intensive research.Considering the distinct time response behaviors of the two systems,this paper discusses an integrated simulation approach to simulate the cascading failure propagation process of integrated electricity and natural gas systems(IEGSs).On one hand,considering instantaneous re-distribution of power flows after the occurrence of disturbance or failure,the steady-state AC power flow model is employed.On the other hand,gas transmission dynamics are represented by dynamic model to capture the details of its transition process.The interactions between the two systems,intensified by energy coupling components(such as gas-fired generator and electricity-driven gas compressor)as well as the switching among the operation modes of compressors during the cascading failure propagation process,are studied.An IEGS composed of the IEEE 30-bus electricity system and a 14-node 15-pipeline gas system is established to illustrate the effectiveness of the proposed simulation approach,in which two energy sub-systems are coupled by compressor and gas-fired generator.Numerical results clearly demonstrate that heterogeneous interactions between electricity and gas systems would trigger the cascading failure propagation between the two coupling systems.

Stochastic Dynamic Economic Dispatch of Wind-integrated Electricity and Natural Gas Systems Considering Security Risk Constraints

As the proportion of wind power generation increases in power systems,it is necessary to develop new ways for wind power accommodation and improve the existing power dispatch model.The power-to-gas technology,which offers a new approach to accommodate surplus wind power,is an excellent way to solve the former.Hence,this paper proposes to involve power-to-gas technology in the integrated electricity and natural gas systems(IEGSs).To solve the latter,on one hand,a new indicator,the scale factor of wind power integration,is introduced into the wind power stochastic model to better describe the uncertainty of grid-connected wind power;on the other hand,for quantizing and minimizing the impact of the uncertainties of wind power and system loads on system security,security risk constraints are established for the IEGS by the conditional value-at-risk method.By considering these two aspects,an MILP formulation of a security-risk based stochastic dynamic economic dispatch model for an IEGS is established,and GUROBI obtained from GAMS is used for the solution.Case studies are conducted on an IEGS consisting of a modified IEEE 39-bus system and the Belgium 20-node natural gas system to examine the effectiveness of the proposed dispatch model.

Resilience of gas interchangeability in hydrogen-blended integrated electricity and gas systems:A transient approach with dynamic gas composition tracking

Green hydrogen can be produced by consuming surplus renewable generations.It can be injected into the natural gas networks,accelerating the decarbonization of energy systems.However,with the fluctuation of renewable energies,the gas composition in the gas network may change dramatically as the hydrogen injection fluctuates.The gas interchangeability may be adversely affected.To investigate the ability to defend the fluctuated hydrogen injection,this paper proposes a gas interchangeability resilience evaluation method for hydrogen-blended integrated electricity and gas systems(H-IEGS).First,gas interchangeability resilience is defined by proposing several novel metrics.Then,A two-stage gas interchangeability management scheme is proposed to accommodate the hydrogen injections.The steady-state optimal electricity and hydrogen-gas energy flow technique is performed first to obtain the desired operating state of the H-IEGS.Then,the dynamic gas composition tracking is implemented to calculate the real-time traveling of hydrogen contents in the gas network,and evaluate the time-varying gas interchangeability metrics.Moreover,to improve the computation efficiency,a self-adaptive linearization technique is proposed and embedded in the solution process of discretized partial derivative equations.Finally,an IEEE 24 bus reliability test system and Belgium natural gas system are used to validate the proposed method.

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.

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.

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.

Integrated coordination scheduling framework of electricity-natural gas systems considering electricity transmission N—1 contingencies and gas dynamics

This paper discusses a security-constrained integrated coordination scheduling framework for an integrated electricity-natural gas system(IEGS),in which both tight interdependence between electricity and natural gas transmission networks and their distinct dynamic characteristics at different timescales are fully considered.The proposed framework includes two linear programming models.The first one focuses on hour-based steady-state coordinated economic scheduling on power outputs of electricity generators and mass flow rates of natural gas sources while considering electricity transmission N-1 contingencies.Using the steady-state mass flow rate solutions of gas sources as the initial value,the second one studies second-based slow gas dynamics and optimizes pressures of gas sources to ensure that inlet gas pressure of gas-fired generator is within the required pressure range at any time between two consecutive steady-state scheduling.The proposed framework is validated via an IEGS consisting of an IEEE 24-bus electricity network and a15-node 14-pipeline natural gas network coupled by gasfired generators.Numerical results illustrate the effectiveness of the proposed framework in coordinating electricity and natural gas systems as well as achieving economic and reliable operation of IEGS.

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.

Integrated operational planning of hydrothermal power and natural gas systems with large scale storages

The growing installation of natural gas fired power plants has increased the integration of natural gas and electricity sectors. This has driven the need investigate the interactions among them and to optimize energy resources management from a centralized planning perspective. Thus, a combined modeling of the reservoirs involved in electric power and gas systems and their locations on both networks are essential features to be considered in the operational planning of energy resources.This paper presents a modeling and optimization approach to the operational planning of electric power and natural gas systems, taking into account different energy storage facilities, such as water reservoirs, natural gas storages and line packs of pipelines. The proposed model takes advantage of captures both energy systems synergy and their associated networks. This approach identifies the interactions between the energy storage facilities and their economic impact over their optimal scheduling. The results show the benefits of an integrated operational planning of electric power and natural gas systems, the close interdependency between the energy resources stored in both systems, and the effects of a combined scheduling.

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.

考虑季节性储氢的电-气-氢混联综合能源系统优化调度

新能源电力系统的季节性电量不平衡,为电网长短期协同调度带来挑战。为此,该文以电-气-氢多能耦合为载体,提出一种考虑季节性储氢的综合能源系统长短期协同优化调度模型。首先,基于时间序列分解和场景聚类方法获取丰能季和枯能季的典型场景;然后,基于电网直流潮流模型和掺氢天然气准动态流量/能量模型,构建电-气-氢混联综合能源系统运行模型;针对混氢-天然气高维非凸非线性方程,提出基于逐次二阶锥松弛的凸能流模型,实现了综合能源系统协同优化模型的高效精准求解;最后,通过算例分析验证所提模型的经济性和求解方法的可行性,并剖析了季节性储氢下的电-气-氢多能耦合情况。仿真结果显示,相比传统电-气耦合系统,所提模型的运行成本降低了6.43%。

Coordinated optimal dispatch and market equilibrium of integrated electric power and natural gas networks with P2G embedded

As power to gas(P2 G) technology gradually matures, the coupling between electricity networks and natural gas networks should ideally evolve synergistically.With the intent of characterizing market behaviors of integrated electric power and natural gas networks(IPGNs)with P2 G facilities, this paper establishes a steady-state model of P2 G and constructs optimal dispatch models of an electricity network and a natural gas network separately. In addition, a concept of slack energy flow(SEF) is proposed as a tool for coordinated optimal dispatch between the two networks. To study how the market pricing mechanism affects coordinated optimal dispatch in an IPGN, a market equilibrium-solving model for an IPGN is constructed according to game theory, with a solution based on the Nikaido-Isoda function. Case studies are conducted on a joint model that combines the modified IEEE 118-node electricity network and the Belgian 20-node gas network.The results show that if the game between an electric power company and a natural gas company reaches market equilibrium, not only can both companies maximize their profits, but also the coordinated operation of the coupling units, i.e., gas turbines and P2 G facilities, will contribute more to renewable energy utilization and carbon emission reduction.

考虑天然气动态的综合能源系统运行可靠性分析

在电气综合能源系统运行可靠性分析中,传统数值算法在求解天然气动态时计算量庞大,难以在运行的时间尺度内有效完成动态分析。提出了一种新的方法,基于神经网络结合多尺度膨胀卷积和注意力机制,替代传统数值算法。首先利用卷积神经网络(convolutional neural network,CNN)进行特征提取,结合长短期记忆网络(long short-term memory,LSTM)捕捉时间序列特征,并通过多尺度膨胀卷积扩展感受野以及引入注意力机制提升对关键状态变化的敏感度。然后通过序列到序列的学习过程,模型能够准确捕捉相邻时间步之间的复杂映射关系,构建气网动态代理模型。最后,将气网动态代理模型与电力系统潮流模型相结合,并利用蒙特卡洛法和多态模型完成了电气综合能源系统运行可靠性的全面分析。在配网级电-气综合能源系统的实际测试中,验证结果表明,所提出的CNN-LSTM组合模型不仅能够准确模拟气网动态的复杂特性,且显著提高了计算效率,满足了大规模综合能源系统运行可靠性评估的要求。

电-气互联系统仿射能流交替递归计算方法

在源荷不确定性日益显著的背景下,不确定性能流计算对电-气互联系统能源优化调度具有重要意义。针对天然气网络仿射能流算法面临的仿射数矩阵求逆运算复杂、难以适用环网等问题,该文提出一种天然气网络全纯嵌入仿射能流方法。在此基础上,根据耦合设备处的能量流动对电、气子系统能流方程进行重构,构建全纯嵌入的电-气仿射多能流模型。为降低多能流计算的初值依赖性、提升多能流计算效率,提出一种仿射能流交替递归计算方法,将电网空载状态的状态量初值作为多能流计算起始点,基于各仿射型状态量的幂级数系数递推关系,以交替进行的方式逐阶递归计算电网、气网和耦合设备的仿射型状态量幂级数系数,求解电-气互联系统的能流分布区间。仿真结果验证了所提方法在算法保守性、收敛性和计算效率等方面的优势。

电-气互联系统预测-校正型仿射能流算法

综合能源系统能流耦合渐趋紧密,与此同时可再生能源和负荷需求的强不确定性对系统能流分析提出了挑战。因此,提出一种电-气互联系统(IEGS)仿射型区间能流算法,在仿射能流计算结果中保留噪声元特征,通过噪声元系数分析各独立不确定因素对系统状态变量的影响程度。建立电、气子系统仿射模型及能流方程。提出基于域收缩思想的IEGS预测-校正型仿射能流算法,根据灵敏度对状态量的解域进行保守的预测,并构建优化模型对解域进行压缩校正。同时,采用多能流分布式迭代方法进行求解,其无须考虑复杂耦合网络中的多能流计算顺序。最后通过仿真验证了所提方法在保守性、计算效率方面的优势,并量化分析了不确定因素对系统状态量的影响。

考虑氢混燃机动态混氢特性的电-气互联系统优化调度

电–气互联系统是综合能源系统的重要组成部分,燃气机组是其中关键的能源耦合元件,而随着能源系统低碳化转型,燃气机组掺氢燃烧发电的技术应运而生。传统氢混燃机相关研究大多只考虑固定掺氢比运行的情况,并未考虑机组动态调整掺氢比运行的影响。传统电–气互联系统优化调度相关研究主要面向运行经济性,而对计及氢混燃机的能量与备用统一出清鲜有研究。为此,该文提出了一种考虑氢混燃机动态混氢比的电–气互联系统优化调度方法,基于动态混氢特性建立氢混燃机精细化模型,并通过电解水制氢技术为氢混燃机提供氢气来源,配置储氢罐和储气罐作为联合体为系统提供备用;采用二项式松弛方法对氢混燃机耗气流量方程进行线性转化,将原有非凸非线性模型转化为混合整数线性规划模型求解;最后通过仿真验证所提方法的有效性,分析不同场景下系统运行状态,实现了“风电–电解水制氢–氢混燃机”模式下风电消纳潜力的深度挖掘。

Bi-Level Bidding and Multi-Energy Retail Packages for Integrated Energy Service Providers Considering Multi-Energy Demand Elasticity

How to effectively use the multi-energy demand elasticity of users to bid in the multi-energy market and formulate multi-energy retail packages is an urgent problem which needs to be solved by integrated energy service providers(IESPs)to attract more users and reduce operating costs.This paper presents a unified clearing of electricity and natural gas based on a bi-level bidding and multi-energy retail price formulation method for IESPs considering multi-energy demand elasticity.First,we propose an operating structure of IESPs in the wholesale and retail energy markets.The multi-energy demand elasticity model of retail-side users and a retail price model for electricity,gas,heat and cooling are established.Secondly,a bi-level bidding model for IESPs considering multi-energy demand elasticity is established to provide IESPs with wholesale-side bidding decisions and retail-side energy retail price decisions.Finally,an example is given to verify the proposed method.The results show that the method improves the total social welfare of the electricity and natural gas markets by 7.99%and the profit of IESPs by 1.40%.It can reduce the variance of the electricity,gas,and cooling load curves,especially the reduction of the variance of the electricity load curve can which reach 79.90%.It can be seen that the research in this paper has a positive effect on repairing the limitations of integrated energy trading research and improving the economics of the operation of IESPs.

Active-reactive power scheduling of integrated electricity-gas network with multi-microgrids

Advances in natural gas-fired technologies have deepened the coupling between electricity and gas networks,promoting the development of the integrated electricity-gas network(IEGN)and strengthening the interaction between the active-reactive power flow in the power distribution network(PDN)and the natural gas flow in the gas distribution network(GDN).This paper proposes a day-ahead active-reactive power scheduling model for the IEGN with multi-microgrids(MMGs)to minimize the total operating cost.Through the tight coupling relationship between the subsystems of the IEGN,the potentialities of the IEGN with MMGs toward multi-energy cooperative interaction is optimized.Important component models are elaborated in the PDN,GDN,and coupled MMGs.Besides,motivated by the non-negligible impact of the reactive power,optimal inverter dispatch(OID)is considered to optimize the active and reactive power capabilities of the inverters of distributed generators.Further,a second-order cone(SOC)relaxation technology is utilized to transform the proposed active-reactive power scheduling model into a convex optimization problem that the commercial solver can directly solve.A test system consisting of an IEEE-33 test system and a 7-node natural gas network is adopted to verify the effectiveness of the proposed scheduling method.The results show that the proposed scheduling method can effectively reduce the power losses of the PDN in the IEGN by 9.86%,increase the flexibility of the joint operation of the subsystems of the IEGN,reduce the total operation costs by $32.20,and effectively enhance the operation economy of the IEGN.

电–气混联综合能源系统概率能量流分析

由电力系统(electric power systems,EPS)、天然气系统(natural-gas systems,NGS)之间的耦合与互联构成的综合能源系统(integrated energy systems,IES),对于构建经济、环保、高效的能源系统至关重要。同时,由于IES中大量的不确定因素,有必要将不确定建模技术应用于IES分析。该文将广泛应用于EPS的概率潮流的概念推广到IES的概率能量流分析中,计及了EPS、NGS之间3方面的耦合:1)燃气轮机组;2)电力驱动加压站;3)能源集线器。在IES稳态能量流的基础上,考虑了电、气、热负荷以及风电场出力的不确定性,并采用蒙特卡罗模拟法求解IES概率能量流。算例分析表明,NGS(或EPS)中不确定性因素会对EPS(或NGS)的概率能量流产生影响;同时NGS能量流方程线性化精度明显低于EPS。

考虑氢能-天然气混合储能的电-气综合能源微网日前经济调度优化

在可再生能源渗透率的快速增长背景下,构建电-气综合能源系统具有重要的经济和环保意义。传统电-气综合能源系统模型对电转气（power to gas,P2G）过程处理过于简化,且环保效益考虑不充分。在电-气综合能源系统中,提出带有中间缓冲环节的P2G实现系统—氢能-天然气混合储能系统（hydrogen-gas energy storage system,HGESS）,将P2G过程细分为电转氢和电转天然气,并分别与燃料电池和微型燃气机形成高效型和能量型两阶段电-气-电的能量闭环流动圈。然后将HGESS与微网结合,提出计及P2G过程能量转换损失和环境成本的日前经济调度优化模型。算法中分别采用分段线性化和二阶锥松弛方法,对电网潮流和天然气网络潮流非线性边界做线性化处理。最后在算例中采用高、低风电并网渗透率两种场景,结果证明所提HGESS在高、低渗透率下的电-气综合能源系统都具很好的经济性和环保性,具有广阔的应用前景。