Design and control of grid-responsive communities

拟议的研究计划旨在通过开发综合方法来支持建筑设计的转型，以优化具有现场可再生能源发电的电网响应型、节能社区的设计和运营。电网响应能力是指综合社区能源系统（ICES）和社区内建筑物适应电力需求以减少峰值负载或最大限度地利用可再生能源的能力，从而在智能电网中发挥积极作用。该赠款申请侧重于两个主要目标：1）先进的综合社区能源系统建模； 2）电网响应型社区的设计和运营策略。 1）建模 电网响应社区包括基于新型 HVAC 组件的复杂混合 ICES，这对现有仿真工具提出了重大挑战。需要不同的模型：在线（实时）预测控制需要非常适合在线参数识别的计算高效模型，而详细设计模型应基于物理原理和/或测量的性能数据。两个子项目将解决组合这些模型要求的挑战。实验室设施和来自真实系统的数据将用于通知和验证模型，这些模型将在适当的设计、控制策略开发和在线控制工具中实施。 2）设计与运营策略 使用基本控制规则优化能源系统设计，然后优化给定设计的控制策略的传统方法无法利用能源效率、弹性和电网响应性等不同目标之间的协同作用。将开发一种综合方法，使用最合适的建模分辨率来优化建筑物和综合能源系统的设计和运行。该项目将提供基于模型的预测控制策略，能够考虑实时数据以及天气、居住者行为和能源价格的预测。我们的工作表明，这无法通过对现有方法的渐进式改进来实现，并且将开发一种新颖的方法并将其集成到设计优化过程中。 预期影响 这些研究项目将在以前成功的合作项目的基础上与业界密切合作进行。他们还将通过让受过培训的总部人员参与与大学和工业界的多学科合作，努力弥合建筑师和工程师之间的学科鸿沟。这将使加拿大受益，因为它可以推进和转让实现下一代高性能综合社区能源系统所需的知识，并培训能够在多学科背景下贡献专业知识的总部。

The proposed research program aims at supporting the transformation of building design by developing integrated methodologies to optimize the design and operation of grid-responsive, energy efficient communities with on-site renewable energy generation. Grid responsiveness is the ability of Integrated Community Energy Systems (ICES) and of the buildings within a community to adapt their power demand to reduce peak loads or maximize the use of renewable energy, thereby playing an active role in a smart electric grid. This grant application focuses on two main objectives: 1) modeling of advanced Integrated Community Energy Systems; and 2) design and operation strategies for grid-responsive communities. 1) Modeling Grid-responsive communities include complex, hybrid ICES based on novel HVAC components, which poses significant challenges to existing simulation tools. Different models are required: online (real-time) predictive control requires computationally efficient models well suited to online parameter identification, while detailed design models should be based on physical principles and/or measured performance data. Two sub-projects will address the challenge of combining these model requirements. Laboratory facilities and data from real systems will be used to inform and validate the models which will be implemented in the appropriate tools for design, development of control strategies, and online control. 2) Design and operation strategies The conventional approach of optimizing energy system design using basic control rules and then optimizing control strategies for a given design cannot leverage synergies between different objectives such as energy efficiency, resilience, and grid-responsiveness. An integrated methodology will be developed to optimize the design and operation of buildings and integrated energy systems, using the most appropriate modeling resolution. The project will deliver model-based predictive control strategies capable of taking into account real-time data and forecasts for the weather, occupant behavior and energy prices. Our work has shown that this cannot be achieved through incremental improvements to existing methods, and a novel approach will be developed and integrated within the design optimization process. Anticipated impact The research projects will be performed in close collaboration with industry, building on previous successful collaborative projects. They will also strive to bridge the disciplinary divide between architects and engineers by involving the trained HQP in multidisciplinary collaborations with university and industry. This will benefit Canada by advancing and transferring the knowledge required to enable the next generation of high performance integrated community energy systems and by training HQP capable of contributing their expertise in a multidisciplinary context.