Integrated multi-vector smart energy systems at building, campus and neighbourhood scales

该项目的总体目标是创建一个基于证据的框架，以评估在城市环境中整合大学校园智能能源系统的潜力。伦敦大学学院布卢姆斯伯里校区将被用作参考系统。它位于伦敦市中心，是现有大学网络共享基础设施并不断与城市区域系统互动的典型例子。因此，它可以作为一个模型，可以展示整个生态系统适应智能校园与智能能源系统的复杂性和好处。具体而言，该项目将着手确定：i.在英国或欧盟范围内的大学水平上应用能源效率措施所产生的潜在能源需求减少的规模；2。大学校园系统可主要在智慧校园的背景下使用或调整；将根据建筑能源性能指令（EPBD）的智能准备指标（SRI）和“脱碳能源系统中的智能建筑，为欧洲公民提供真正利益的10项原则”报告，探索关系，提出隔离系统和基础设施的连接。其目的将是加强大学的典型学习活动、用户体验和管理活动，并促进与大学邻近活动和用户的协同作用，使两者都受益；3。整合低碳能源技术和信息通信技术解决方案的必要措施，从单一部门转向多向量智能能源系统，以提供低碳能源和智慧校园——包括能效措施、可再生能源整合、能源和热储存、需求灵活性；四、如何形成一个框架，作为大学校园评价的通用路线图；v.如何将建议的框架应用于参考UCL校园系统，以创建一个反馈循环，以重新评估框架并提出对框架方法的潜在更改；vi.对校园和社区的经济、社会和伦理影响，以支持采用该框架的商业案例；7。向利益相关者和决策者传播成果。将进行快速系统的文献综述，以确定和评估现有框架，基准方法（例如显示能源证书）和系统建模工具对伦敦大学学院校园参考系统的适用性。除此之外，还将根据选定的分析方法整理一份所需数据和资料的登记册。将确定可用的数据、能源报告工具、物业管理参与和确定与伦敦大学学院有关的先前研究。为了简化整个过程，将创建一个适当的数据管理计划。UCL的建筑存量将基于之前的研究结果和现有的校园模型进行建模，旨在评估校园的智能准备和整合智能能源网络的潜力。根据评估结果，提出智能能源系统集成的相关适应措施。然后将使用能源系统模型对拟议的措施进行测试，旨在测试和量化采用这些措施的影响。模拟结果将为制定框架增加证据基础。一个高质量的项目将为大学校园智能能源系统的评估和集成提供一个新的框架。这些最终可以成为推动整个商业建筑领域和城市规模创新的领跑者。

The overarching aim of this project is to create an evidence based framework for evaluating the potential for integrating Smart Energy Systems at University Campus level within an urban environment. The UCL Bloomsbury campus will be used as a reference system. Its location, within the heart of London, is a characteristic example of an existing University network sharing infrastructure and continuously interacting with an urban district system. Thus, it can be used as a model that can demonstrate the intricacies and benefits of the adaptation to a smart campus with smart energy systems for the entire ecosystem. Specifically, the project will set out to identify: i. The scale of potential energy demand reduction derived from applying energy efficiency measures at a UK or EU wide university level; ii. University campus systems that can be primarily utilised or adapted in the context of the Smart Campus; relationships will be explored to propose connections of segregated systems and infrastructure by integrating intelligence based on the Energy Performance of Buildings Directive (EPBD) Smart Readiness Indicator (SRI) for buildings and the 'Smart buildings in a decarbonised energy system, 10 Principles to Deliver Real Benefits for Europe's Citizens' report by the Buildings Performance Institute Europe (BPIE). The aim will be to enhance typically occurring university learning activities, user experience and management activities as well as to promote synergies with the university's neighbouring activities and users to the benefit of both; iii. The required measures to integrate low-carbon energy technologies and ICT solutions to move from a single-sector to multi-vector smart energy systems for the delivery of low-carbon energy and a smart campus - including energy efficiency measures, renewable energy integration, energy and thermal storage, demand flexibility; iv. How the above can form a framework that can be used as a universal roadmap for the evaluation of university campuses; v. How applying the proposed framework to the reference UCL campus system can create a feedback loop to re-evaluate the framework and propose potential changes to the framework's methodology; vi. The economic, social and ethical impacts at campus and neighbourhood scale to support the business case for the uptake of the framework; vii. Dissemination of outcomes to stakeholders and decision and policy makers.A rapid systematic literature review will be conducted to identify and evaluate the applicability of existing frameworks, benchmarking methodologies (e.g. Display Energy Certificates) and system modelling tools to the reference system of the UCL campus. Alongside this, a register of the required data and information will be collated based on the selected methods of analysis. Available data will be identified, energy reporting tools, estates management engagement and identification of related previous studies concerning the UCL. To streamline the whole process an appropriate data management plan will be created.The UCL building stock will be modelled based on the previous findings and existing campus models aiming to evaluate the campus's smart readiness and potential to integrate smart energy networks. Based on the outcomes of this evaluation, the relevant adaptation measures will be proposed for the integration of smart energy systems.The proposed measures will be then tested using energy systems modelling aiming to test and quantify the impacts of the adoption of such measures. Modelling outcomes will add to the evidence base for the development of the framework.A high-quality project will deliver a novel framework for the evaluation and integration of smart energy systems to university campuses. These can ultimately act as the frontrunner in driving innovation in the whole commercial building sector and the city scale.