Q-PLUS Intelligent Building energy management system utilising energy storage

“与英国的住宅市场相比，商业地产中可再生能源系统的采用率较低，这是由于补贴和上网电价的减少，使得投资于该技术在财务上对建筑业主没有吸引力。然而，这种情况需要改变，因为可再生能源预计将在使英国实现至少为1990年水平80%的雄心勃勃的减排目标方面发挥重要作用。其他有助于降低排放的技术是电动汽车和热泵，尽管这两种技术都将进一步增加电力系统的负荷。我们迫切需要创新的解决方案来利用现有的资产，同时将储能资产整合到电力系统中，以确保供应安全，同时为这些资产的所有者提供长期的节省和新的收入来源。该项目是QBOTS Technology Ltd和曼彻斯特大学（UoM）之间的合作项目，将为商业建筑设计和验证一个决策支持能源管理框架，该框架将优化多个性能标准，包括当地可再生能源的自我消耗，储能系统的使用、电网支持服务的提供、负载整形、经济成本和舒适度，以及控制室内空气质量和热环境的标准目标。决策支持框架将使用曼彻斯特大学现有的资产进行验证，以形成一个测试平台（使用高保真度真实的时间数字模拟器（RTDS）系统来模拟适当的保真度可再生系统模型和建筑物电力架构的实时模拟建模的混合，通过将商用240 kW 180 kWh Siemens SieStorage电池储能系统连接到RTDS，与硬件在环一起实现决策-支持框架将在不同的商业建筑运营时间表上进行评估。"

"The adoption of renewable energy systems in commercial properties has been low in comparison to the residential market in the UK, due to reductions in subsidies and feed-in-tariffs which make investing in the technology financially unattractive to building owners. There is however a need for this situation to change as renewable generation sources are anticipated to play a significant role in enabling the UK to meet the ambitious emission reduction target of at least 80% of the 1990 level. Other technologies proposed to help lower emissions are electric vehicles and heat pumps, though both of these will further increase the load on the power system. There is an urgent need for innovative solutions to utilise existing assets while integrating energy storage asset in the power system to ensure security of supply while providing the owners of these assets with long-term savings and new revenue streams.This project, a collaboration between QBOTS Technology Ltd and The University of Manchester (UoM), will design and validate a decision-support energy management framework for commercial buildings that will optimise multiple performance criteria, including self-consumption from local renewable generation sources, usage of energy storage systems, provision of grid support services, load shaping, economic costs and comfort, together with the standard objectives of controlling the indoor air quality and thermal environment. The decision-support framework will be validated using existing assets available at The University of Manchester to form a test platform (a blend of real-time simulation modelling using a high-fidelity Real Time Digital Simulator (RTDS) system to emulate appropriate fidelity renewable system models and the building power architecture, together with hardware-in-the-loop by interfacing a commercial 240 kW 180 kWh Siemens SieStorage battery energy storage system to the RTDS to enable the decision-support framework to be evaluated over a diverse range of commercial building operating schedules."