考虑电-气-热-交通相互依存的城市能源系统韧性评估与提升方法

Resilience Assessment and Enhancement Methods for Urban Energy System Considering Electricity-Gas-Heat-Transport Interdependency

能源转型背景下,城市能源系统得到了快速发展。当高影响、低概率的极端事件发生时,城市能源系统可能因为各子系统间的相互依存关系而承受更大风险。针对此问题,该文提出考虑电-气-热-交通相互依存的城市能源系统韧性评估与提升方法。首先,针对极端事件的发生全过程,提出包含整体性和针对性两个角度的多维韧性评估指标;然后,建立电、气、热、交通各子系统及耦合元件的模型;进而,为实现系统韧性的提升,提出采用发电车紧急供电、维修人员调度、拓扑重构等措施,以及考虑建筑物热惯性的协同优化模型;最后,在一个92节点的电-气-热-交通融合系统中进行算例分析。结果表明,所提的韧性评估指标能全面地反映系统在各个阶段的性能;所提的韧性提升方法可以协调各子系统间的措施与设备,实现系统性能的维持与恢复。

With the rapid changes in the global environment,high-impact and low-probability(HILP)events,represented by natural disasters,have attracted widespread attention.In the face of HILP events,the urban energy system(UES)may suffer more significant losses due to the complex interdependencies between the energy subsystems.Due to the geographical location of the access nodes of the coupling elements,the effects of extreme events on the subsystems may not be simultaneous or of equal severity.As a result,there may be"time differences"and"spatial differences"in the impact of extreme events between subsystems.With this characteristic,the interdependence of the subsystems in the UES can have a“positive”and“negative”impact on system performance.On the one hand,the effects of inadequate power supply propagate through the coupling elements to the other subsystems,resulting in a degradation of their performance.The degradation of the performance of each subsystem will in turn lead to a further undersupply of the urban distribution network through the coupling elements,exacerbating the deterioration of the UES performance.On the other hand,when one form of energy supply is lost,other forms of energy can be substituted and complemented by energy conversion equipment,supporting the performance of the UES.To address this issue,this paper proposes a resilience assessment and enhancement method for UESs that considers the interdependence of electricity-gas-heat-transport.Firstly,the multidimensional resilience assessment metrics that include both holistic and targeted perspectives are proposed for the whole process of extreme events.Then,the models of electricity,gas,heat and transport subsystems and coupling elements are established.The resilience assessment assesses the resilience of the UES in 2 areas and 7 dimensions.It includes both an overall grasp of UES resilience(performance maintenance,resistance,responsiveness,resilience)and a targeted assessment of system performance of particular concern(island connectivity,number of islands covered by power supply,critical load maintenance time).In terms of resilience enhancement,this paper aims to minimise the sum of weighted electrical,gas and thermal load losses and develop a system-level co-optimisation model.The resilience enhancement of the UES is achieved using power generator scheduling,maintenance staff scheduling,topology reconfiguration,and building thermal inertia.Due to the reliance on the traffic network in the resilience enhancement measures taken,the transport network subsystem is considered in this paper to establish a model for mobile emergency generators routing and repair crews dispatching.Finally,case studies are analysed in a 92-node integrated electricity-gas-heat-transport system.The following conclusions can be drawn from the simulation analysis:(1)A comprehensive study of UES resilience assessment and enhancement can consider the correlation between each resilience enhancement measure and each resilience assessment metric,which is conducive to decision-makers to avoid risks better and take advantage of multi-energy integration to achieve system resilience enhancement.(2)The proposed resilience assessment index assesses the system performance at different stages from two perspectives:holistic and targeted.The multidimensional resilience assessment metrics provide a comprehensive picture of system performance in terms of its characteristics and topological features,allowing more targeted solutions and countermeasures to be developed.(3)The proposed resilience enhancement method achieves effective coordination and synergistic optimisation of various subsystems and measures;enhances the resilience of the UES to extreme events;improves the coverage of energy supply;and facilitates the rapid recovery of the UES after HILP events.