Modelling aggregate demand-side flexibility in distribution networks with electrified heat and transport

该项目旨在模拟需求方的灵活性，来自大量的住宅和中小型商业最终用户在分配网络（DN）的聚合。通过该项目开发的算法将通过评估灵活负荷的时变容量来促进DN的更灵活的操作，以响应目前由配电系统运营商（DSO）采购的灵活服务，即：维持，安全，动态和恢复。聚合灵活性将被描述为可用容量的数量及其持续时间，作为聚合具有不同操作模式、开始时间、最大延迟时间等的各个负载的结果，由最终用户的日常行为驱动，并受其舒适度的约束。这种灵活性概况与实践中已经使用的较大灵活资源的情况相对应（例如，分布式发电机或储能）将为中小型最终用户提供多种灵活的服务。这将导致DN作为一个整体的灵活性增加。此外，利用住宅和商业用户的灵活性潜力将产生重大的精神影响，因为这些用户在电力使用和全球温室气体排放中占很大比例。该项目的调查结果可以进一步补充智能电表数据，以制定针对住宅和商业用户的费率和激励措施，通过减少需求响应方案效率和结果的不确定性，支持更加协调的采购灵活性。灵活性建模问题不仅对于报告需求方的减少灾害风险潜力（通常是集合者的作用）很重要，而且对于更有把握地估计减少灾害风险方案、费率设计和灵活性评估的结果也很重要，这些都与直销组织高度相关。该项目为DSO带来的主要好处之一是在投资激励措施和基础设施时支持决策，从而允许对灵活负载进行网络范围的控制。

This project aims to model demand-side flexibility coming from aggregation of a largenumber of residential and small and medium-size commercial end-users in the distribution network (DN). Thealgorithms developed through this project will facilitate more flexible operation of the DN by assessing the timevarying capacity available from flexible loads, in response to flexible services currently procured by thedistribution system operator (DSO), namely: Sustain, Secure, Dynamic and Restore. The aggregate flexibility willbe described as the amount of available capacity and its duration, as a result of aggregating individual loads withdifferent operating modes, start times, maximum deferral times, etc., driven by the end-users' daily behaviourand constrained by their comfort. Such flexibility profiling, corresponding to that of larger flexible resourcesalready employed in practice (e.g., distributed generators or storage), will make provision of multiple flexibleservices accessible to small and medium-size end-users. This will result in increased flexibility of the DN as awhole. Furthermore, harnessing flexibility potential of residential and commercial users would have significantenvironmental implications, as these contribute to a large share to both, electrical usage and global greenhousegas emissions. The findings of the project could be further complemented with smart meter data to developtariffs and incentives for residential and commercial users, supporting more coordinated procurement offlexibility by reducing uncertainty of efficiency and outcome of the demand response (DR) programmes.The main beneficiaries of the research would be DSOs, aggregators and other DR responsible parties at the DNlevel. The question of flexibility modelling is not only important for reporting DR potential at the demand side(commonly, an aggregator's role), but also for more confident estimation of the outcome of DR programmes, tariff design and flexibility assessment, which are highly relevant to DSOs. One of the main benefits for DSOsbrought by this project would be in supporting decision making when investing into incentives and infrastructureallowing network-wide control of flexible loads.