A Reliability Model for Integrated Energy System Considering Multi-energy Correlation

An integrated energy system (IES) is a regional energy system incorporating distributed multi-energy systems to serve various energy demands such as electricity, heating, cooling, and gas. The reliability analysis plays a key role in guaranteeing the safety and adequacy of an IES. This paper aims to build a capacity reliability model of an IES. The multi-energy correlation in the IES can generate the dependent capacity outage states, which is the distinguished reliability feature of an IES from a generation system. To address this issue, this paper presents a novel analytical method to model the dependent multi-energy capacity outage states and their joint outage probabilities of an IES for its reliability assessment. To model the dependent multi-energy capacity outage states, a new multi-dimensional matrix method is presented in the capacity outage probability table (COPT) model of the generation system. Furthermore, a customized multi-dimensional discrete convolution algorithm is proposed to compute the reliability model, and the adequacy indices are calculated in an accurate and efficient way. Case studies demonstrate the correctness and efficiency of the proposed method. The capacity value of multi-energy conversion facilities is also quantified by the proposed method.

Multifactor-influenced Reliability-constrained Reserve Expansion of Integrated Electricity-gas Systems Considering Failure Propagation

With the increasing interactions between natural gas systems(NGS)and power systems,component failures in one system may propagate to the other one,threatening reliable operation of the whole system.Due to neglect of such cross-sectorial failure propagation in integrated electricity-gas systems(IEGSs),traditional economy-oriented reserve expansion models may lead to unreasonable planning results.In order to address this,an innovative reserve expansion model is proposed to determine the allocation of energy production components through the harmonization between costs and reliability.First,novel multifactor-influenced reliability indices are defined con-sidering synthetic effects of multiple uncertainties,including failure propagation,load uncertainties and generation failures.In reliability index formulation,contribution of failure propagation on system reliability is analytically expressed.To avoid high computational complexity,the fuzzy set theory is combined with conventional methods,e.g.,Monte-Carlo simulation technique to reduce numerous contingency states.Sampled contingency states are aggregated into several clusters represented by a fuzzy number.To effectively solve the planning model,a decomposition approach is introduced and applied to decompose the original problem into a master problem and two correlated reliability sub-problems.Numerical studies show the proposed model can plan reasonable reserves to guarantee reliability levels of IEGSs considering failure propagation.

Reliability Assessment for Integrated Power-gas Systems Considering Renewable Energy Uncertainty and Cascading Effects

Integrated power-gas systems(IPGSs)make the power system and natural gas system(NGS)as a whole,and strengthen interdependence between the two systems.Due to bidirectional energy conversion in IPGS,a disturbance may turn into a catastrophic outage.Meanwhile,increasing proportion of renewable energy brings challenges to reliability of IPGS.Moreover,partial failure or degradation of system performance leads IPGS operate at multiple performance levels.Therefore,this paper proposes a reliability assessment model of IPGSs which represents multiple performance of components and considers cascading effects,as well as renewable energy uncertainty.First,a framework of IPGS reliability assessment is proposed:multistate models for main elements in the IPGS are represented.Especially a gas-power-generation calculation operator and a power-to-gas calculation operator are utilized to bi-directionally convert a multi-state model between NGS and power systems.Furthermore,nodal reliability indices for IPGS are given to display impacts of cascading effects and renewable energy uncertainty on reliabilities of IPGSs.Numerical results on IPGS test system demonstrate the proposed methods.

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.

计及元件故障率时变特性的综合能源系统运行可靠性高效评估方法

为提高运行可靠性评估效率,进而支撑系统运行风险防控,基于模型-数据混合驱动的思想提出了一种计及元件故障率时变特性的综合能源系统运行可靠性高效评估方法。构建了基于复杂网络理论的支路脆弱度因子指标,提出系统关键元件的筛选方法。建立系统可靠性指标关于关键元件可靠性参数的解析模型,通过引入辅助变量建立线性优化模型求取解析模型系数。通过最小二乘支持向量机(LSSVM)回归模型获得运行可靠性解析模型与负荷水平的映射关系,实现负荷变化时系统运行可靠性的快速更新。通过算例测试验证了所提方法的计算效率和精度。

综合能源网络建模与运维技术研究综述

在当前多种异质能源耦合程度不断加深,清洁能源高比例渗透的背景下,综合能源网络耦合电、气、热、冷等多种能源类型,实现不同能源网络之间的协调规划与互济调控,被认为是促进可再生能源消纳和提高能源利用效率的重要手段之一。首先从综合能源网络的特性分析开始,对其多能流差异特性、天然气网络的管存特性、热力网络的热延迟特性进行重点分析;其次在综合能源网络建模方面,分别介绍3种建模方法:机理分析建模法、数据驱动建模法、统一能路建模法;在综合能源网络状态估计方面,梳理综合能源网络状态估计发展历程以及状态估计主要方法,并对综合能源网络运行可靠性评估的国内外研究现状进行阐述。最后对综合能源网络建模方法与状态估计两方面进行展望,可以为该方向的科研人员提供参考。

综合能源系统运行可靠性评估综述及展望

研究综合能源系统的运行可靠性评估对规避综合能源系统的短期风险、保障其安全稳定运行具有重要价值。考虑系统运行状态、实时运行环境等因素的影响,分析综合能源系统在当前状态下未来短期内的可靠性水平,通过给出实时的运行可靠性指标为系统的运行调度提供决策支持。首先介绍综合能源系统的发展背景及意义、运行可靠性评估的概念及必要性;然后从运行可靠性评估建模、模型驱动以及数据驱动的运行可靠性评估方法3个方面,对国内外研究现状进行梳理,并分析归纳当前综合能源系统运行可靠性评估研究所面临的亟需解决的问题;最后针对问题,提出模型-数据混合驱动的综合能源系统运行可靠性评估思路,并对未来的研究方向进行展望。

基于LSSVM的电-气区域综合能源系统短期可靠性评估

电-气区域综合能源系统电、气相互影响,一方面使得模型驱动的单一能源系统可靠性评估方法不再适用;另一方面由于天然气的引入,导致其短期可靠性评估计算开销大。为综合解决这两个问题,提出用机理模型结果训练最小二乘支持向量机(LSSVM),由LSSVM在线评估短期可靠性的方法。首先,建立元件可靠性模型,提出基于系统等效节点模型的故障后果分析方法。在此基础上,构建基于蒙特卡洛模拟的模型驱动短期可靠性评估方法,获得训练样本。然后,构建LSSVM回归模型,通过离线训练,得到系统状态与短期可靠性指标间映射的LSSVM模型,实现系统短期可靠性实时评估。最后,电-气区域综合能源算例系统测试验证了所提方法的准确性和快速性。

基于改进协同演化算法的综合能源系统经济性与可靠性优化规划

随着多能流耦合程度的加深以及能源利用需求的多样化,综合能源系统(IES)对规划方案的经济性与 可靠性提出了更高的要求。然而,经济性与可靠性之间存在相互制约的复杂关系,导致二者难以实现协调优 化。为此,提出了一种基于改进协同演化算法的 IES经济性与可靠性优化规划方法。在多场景经济性评估 模型和基于马尔科夫链蒙特卡洛法的供能可靠性评估模型的基础上构建 IES多目标优化规划模型;基于正 交试验法计算决策变量对系统经济性与可靠性的影响因子,并建立经济性和可靠性演化子种群,进而提出一 种基于改进协同演化算法的模型优化方法;结合某地区的实际数据开展算例仿真分析,仿真结果表明所提模 型可以协调提升 IES规划方案的经济性与可靠性。

综合能源系统运行可靠性评估评述Ⅰ:模型驱动法

综合能源系统运行可靠性更加关注系统在实时运行条件下的时变可靠性。对综合能源系统进行运行可靠性评估,不仅能实时反映系统运行状态,还能在考虑多重运行不确定性因素的前提下对未来短时段内的系统运行风险进行预测。综合能源系统涉及多个能源环节,存在不同供能子系统间的耦合问题,影响运行可靠性的因素极为复杂多样。为了规避短期运行风险,提升系统的安全性与可靠性,综合能源系统运行可靠性的建模及评估工作具有重要意义。该文首先对基于模型驱动的综合能源系统设备运行可靠性建模的研究现状进行阐述与总结;然后,从系统状态生成与选取、系统状态分析与评估、可靠性指标建立与计算三方面详细介绍了模型驱动的综合能源系统运行可靠性评估的研究现状;最后,系统归纳了现有研究存在的不足,以便后续研究进行参考和改进。

综合能源系统运行可靠性评估评述Ⅱ:数据驱动法与模型-数据混合驱动法

对综合能源系统进行运行可靠性评估,不仅能实现系统运行状态的实时感知,而且能对系统的短期运行风险进行合理预测。利用数据驱动的人工智能技术解决能源领域问题是当下的研究热点。该文首先基于数据驱动法对考虑时变性与供需不确定性的综合能源系统设备运行可靠性建模方法进行阐述和总结,并归纳出在设备运行可靠性建模方面现有研究存在的不足;其次,详细总结数据驱动及模型-数据混合驱动两种运行可靠性评估方法的原理、研究现状和目前研究存在的局限性;最后,针对现有研究存在的问题,对综合能源系统运行可靠性评估研究进行总结与展望并提出人工智能背景下模型-数据混合驱动的运行可靠性建模及评估总体思路。

能源互联网背景下的置信容量评估研究综述与展望

置信容量定义为等可靠性前提下可再生能源系统可以替代的常规机组的容量,置信容量是衡量供能系统对系统供能充裕性贡献的重要指标。随着我国能源互联网的发展,电—气综合能源系统的规模逐步扩大,考虑能源互联网背景下的置信容量将成为未来配电网规划中电力平衡的重要指标。综述了能源互联网背景下的置信容量的定义和主要计算方法,展望了未来有待进一步研究的方向。

基于综合能源的区域用能可靠性评估研究

综合能源系统的区域用能可靠性评估是保障其安全可靠运行的重要基础。文章提出了一种基于马尔可夫模型多组件的综合能源可靠性评估方法。针对综合能源系统出现大量组件问题,建立基于马尔可夫模型综合能源供能子系统随机状态模型,对RBTS-Bus2系统模型进行可靠性评估,计算其可靠性指标。根据该评估方法,可以确定光伏、风力、储能、冷热电联供和市电、用户的负载等在综合能源系统中需求比重。案例分析结果表明,综合能源供应体系能有效提升系统的可靠性,但也存在边界效应问题,有待进一步研究解决。

考虑天然气管网多状态模型的电–气综合能源系统可靠性评估

现有针对电–气综合能源系统可靠性评估中天然气管道状态的研究多是基于管道的两状态模型,而实际的天然气管网受到扰动后可能的不正常运行状态有泄漏、穿孔、破裂,此时仍能运行一段较长时间,因此两状态模型并不完全适用于管道故障建模分析。此外,基于能流分析求解系统供能可靠性计算量大,计算效率较低。由于Petri网模型能直观地表达系统拓扑结构,并清晰地描述元件状态之间的动态转移过程,在基于流网络的Petri网模型推理计算中避免了直接计算系统能流,提高计算效率。为此,利用随机Petri网理论建立了一种统一的物理网络模型,对电–气综合能源系统开展供能可靠性评估。首先,构建管线故障的多状态随机Petri网模型,求解与之同构的马尔科夫状态转移矩阵并进行随机抽样;其次,考虑电、气传输速度的差异,构建网络的随机Petri网模型,依据推理计算规则,并考虑基于能量传递关系的容量约束、管道容量缩减曲线等,得到系统可靠性指标。最后,以两个互联的电力系统与天然气系统作为算例进行仿真分析,验证模型和方法的有效性。

计及多重热惯性特征的区域综合能源系统可靠性评估

为提高区域综合能源系统可靠性评估的精度与效率,并从可靠性角度分析多能互补机理并量化对可靠性影响,该文提出一种考虑多能互补与多重热惯性的区域综合能源系统序贯模拟可靠性评估方法。首先,构建热电联产机组典型结构,分析热电联产机组正常运行、降电供热、降额供电及系统停运等运行状态,基于马尔科夫链建立热电联产机组的四状态可靠性模型;然后,分析热源起动惯性、热网传输惯性及建筑热惯性对系统可靠性的影响,基于差异化能流建模思想提出稳态的运行优化模型与考虑多重热惯性的动态最优切负荷模型,分别以运行经济性和等效失负荷量为目标建立优化模型;最后,计及用户舒适度特性对热网失负荷指标进行修正,采用序贯蒙特卡洛模拟实现对区域综合能源系统的可靠性评估。仿真验证了该方法的有效性,并深入分析了热电联产机组四状态可靠性模型、多能互补及热惯性对系统可靠性的影响,通过对比其他算法,以及采用更大系统验证所提方法的有效性,为系统规划设计提供参考。

计及柔性电负荷的综合能源系统规划

柔性电负荷能提高综合能源系统的能源利用效率,减少因弃风造成的资源浪费.为此,提出计及柔性电负荷的综合能源系统规划模型,分析柔性电负荷对综合能源系统的影响.算例分析结果表明:该模型能降低运行成本、提升系统的风电消纳能力.因此,该模型能提高综合能源系统的经济性和可靠性.

考虑综合需求响应混合不确定性的综合能源系统优化调度策略

综合需求响应(integrated demand response,IDR)是挖掘综合能源系统(integrated energy system,IES)负荷侧调节潜力的主要手段。然而,IDR用户的用能行为具有随机性、模糊性相耦合的混合不确定性特征,由此产生的IDR不确定性不仅会给调度策略的制定带来挑战,而且会对系统的可靠性产生影响,甚至可能引起负荷断供。针对上述问题,首先提出了基于改进PMV-PPD(predicted mean vote-predicted percentage of dissatisfied)指标的用户参与意愿评估模型;其次,基于云模型理论,建立了考虑混合不确定性的价格型IDR模型;在此基础上,综合考虑各类能源响应量边界和价格弹性系数等因素的不确定性,提出了IES优化调度策略。算例结果表明所提的IES优化调度策略可以更好地应对IDR不确定性带来的负荷波动,有效提升系统可靠性。