Optimised Demand Side Management for Flexible Operation of Smart Grids

优化需求侧管理，实现智能电网灵活运行

• 批准号: 2854566
• 金额: --
• 依托单位: University of Manchester
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2854566
• 关键词: Optimised; Demand; Side; Management; Flexible

In order to meet our current net-zero carbon targets, the electricity system must accommodate large volumes of intermittent renewable energy sources and new loads (e.g., electrified heating and transports). However, upgrading the capacity of the energy system to accommodate all the aforementioned technologies would be costly.In practice, the full capacity of the energy system is only required during peak conditions,or extreme conditions, e.g., cold days in winter when heating demand is the highest or when a contingency occurs and the system operated with reduced capacity. This is because, the energy system has historically operated in a passive manner (fit-and-forget) because energy demand has been relatively predictable and stable. As this is no longer the case due to the new, sometimes intermittent, technologies being connected to the electricity grid, we need more active approaches to manage our energy systems, such as by deploying demand side management.Demand side management, where customers actively change their energy through the use of devices (e.g., storage) or by changing their behavior (e.g., washing clothes at night), is known to provide attractive options to manage network stress and reduce needs for costly network capacity. However, the use of demand side response can introduce unintended effects on the network as customers payback their energy, e.g., increasing stress during the periods when they charge their storage, do laundry, etc. These payback effects must be properly modelled and assessed when deploying demand side response.The aim of this research project is to provide more accurate means to capture the payback effects, and propose new methods to deploy demand side response. The specific objectives of this project include:- Capturing the characteristics of the different resources used to provide demand side response using models that are compatible with electricity network analysis tools (e.g., ZIP models).- Exploring different optimisation techniques that are suitable for both demand side modelling and electricity network modelling, e.g., multi-stage optimisations where the upper levels are linear.- Producing a relevant optimization model and extending it to consider realistic multi period (rolling horizon) conditions where demand side response deployment is constantly re-optimised as better forecasts are received.- Extend the approach to different electricity network levels, especially to the low voltage level where network imbalances tend to be critical.The outputs of the project are meant to facilitate deployment of demand side response (e.g., by distribution network operators, aggregators, etc.) and facilitate meeting our energy decarbonisation targets in a more cost-effective manner.

为了实现我们当前的净零碳目标，电力系统必须容纳大量间歇性可再生能源和新负载（例如电气化供暖和运输）。然而，升级能源系统的容量以适应所有上述技术的成本高昂。在实践中，只有在高峰工况或极端条件下才需要能源系统的全部容量，例如冬季寒冷的日子，供暖需求最高或发生意外情况而系统以减少的容量运行时。这是因为，由于能源需求相对可预测和稳定，能源系统历来以被动方式（安装即忘记）运行。由于连接到电网的新的、有时是间歇性的技术，情况已不再如此，我们需要更积极的方法来管理我们的能源系统，例如通过部署需求侧管理。众所周知，需求侧管理是客户通过使用设备（例如存储）或改变他们的行为（例如晚上洗衣服）主动改变他们的能源，可以提供有吸引力的选择来管理网络压力并减少对昂贵网络容量的需求。然而，当客户偿还能源时，使用需求侧响应可能会给网络带来意想不到的影响，例如，在充电、洗衣服等期间增加压力。在部署需求侧响应时，必须对这些回报效应进行适当的建模和评估。本研究项目的目的是提供更准确的方法来捕获回报效应，并提出部署需求侧响应的新方法。该项目的具体目标包括： - 使用与电力网络分析工具（例如 ZIP 模型）兼容的模型捕获用于提供需求侧响应的不同资源的特征。 - 探索适用于需求侧建模和电力网络建模的不同优化技术，例如上层是线性的多阶段优化。 - 生成相关的优化模型并将其扩展以考虑实际的多周期（滚动范围） 随着收到更好的预测，不断重新优化需求侧响应部署的条件。 - 将方法扩展到不同的电网级别，特别是网络失衡往往很严重的低压水平。该项目的输出旨在促进需求侧响应的部署（例如，由配电网络运营商、聚合商等），并促进以更具成本效益的方式实现我们的能源脱碳目标。