支持AMI的基于云的开放自动化需求响应协议

Lida Safarzadeh, M. Khorasani, M. Moghaddam
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摘要

随着客户数量的增加和可再生能源进入智能电网,维持供需平衡已成为一项挑战。智能电网中最重要的问题之一是有效管理能源传输和分配网络的需求,特别是在电网中。最近的研究主要是试图模拟客户的使用模式,以尽量减少用电,特别是在用电高峰时段。由于需求响应方案是降低高峰需求和平衡供需的主要解决方案之一,因此需求响应是当今业界和学术界的热门话题之一。另一方面,需求响应程序客户数量的增加凸显了这些程序过程自动化的重要性。近年来,OpenADR作为实现响应程序自动化的国际标准被引入。在本文中,我们在实验室环境中实现了OpenADR,需求响应服务器部署在私有云中。该实现支持用所有电气设备信息注册客户端的能力,还支持自动读取每个设备和与智能电表相关的数据。目标是将先进的计量基础设施与需求响应程序相结合,以降低部署成本和服务集成。我们通过OpenADR将客户成本、最小和最大使用量、社会平均使用量等有用的信息发送给客户,使他们有动力改变自己的使用模式。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A cloud-based open automated demand response protocol with AMI support
With the increasing number of clients and emerging of renewable energies to the smart grids, maintaining a balance between supply and demand has become a challenge. One of the most important issues in smart grids is the efficient management of demand for energy transfer and distribution networks, especially in electrical grids. The recent studies mostly try to model the clients' usage patterns to use less electricity preferably, particularly during high usage hours. Nowadays demand response is one of the hottest topics in industry and academia as the demand response programs is one of the main solutions in lowering the peak demand and balancing the supply and demand. On the other hand, increasing in the number of clients in demand response programs highlights the importance of process automation of these programs. In recent years OpenADR has been introduced as the international standard for implementation response programs automation. In this paper, we implemented OpenADR in a lab environment, and the demand response server has been deployed in the private cloud. This implementation supports the ability to register clients with all the electrical device information and also automatic reading for each device and the data related to the smart meter. The goal was to combine the advanced metering infrastructures with demand response programs to reduce deployment costs and integration of services. We send useful information like clients cost, minimum and maximum usage and the average usage in the society to the clients through OpenADR to make motivations for them to reform their usage pattern.
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