A novel design for Data Processing Framework of Park-level Power System with Data Mesh concept

Jin Li, Shixia Cai, Lei Wang, Mingyang Li, Jiamao Li, Hui Tu
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引用次数: 1

Abstract

Building a new-type power system with renewable energy is the key to achieving the target of carbon peak and carbon neutrality, which has been the consensus of the clean, low-carbon, and safe energy transition. The construction of a new-type power system at the industrial park level is the first demonstration of the coordinated optimization and intelligent control of power sources, grid, load, and energy storage to make overall planning to achieve diversified development. To sustain the ‘balance, security, diversity, and low cost’ construction goals of the new-type power system at the park level, the power grid dispatching and control system is transformed to the direction of intelligence and automation, which is reflected in the rapid emergence and construction of complex systems such as digital twin, simulation, reinforcement learning, model training and prediction, and intelligent decision-making of the EMS (Energy Manage System). This brings more complex data sharing, interaction, construction, and other technical requirements than ever before. At the same time, along with the simultaneous construction of new power systems such as micro-grids, virtual power plants, and distributed photovoltaic systems, it has exacerbated the problems of data divergence from business, low data utilization, and centralized architecture brought by the data lakes and data warehouses under the previous monolithic architecture, leading to the data model hard to deploy to meet the demand for efficient collection, interaction, and sharing of scattered and heterogeneous data under the new generation energy structure and greatly increases the work pressure of the data team, making the data team a bottleneck for business applications. Therefore, this paper proposes a novel design scheme of data processing framework with the data mesh concept, supports the federal computing and analysis engine by building a distributed metadata center, changes the previous centralized data modeling method through data service and productization, realizes data sharing and interaction between complex multi-systems by defining service invocation and encapsulation technology means, improves data utilization, and better supports the automation, rationalization, and balanced construction of the intelligent dispatch system to meet the challenges and requirements brought by the new-type park-level power system.
基于数据网格的电网数据处理框架设计
建设新型可再生能源电力系统是实现碳峰值和碳中和目标的关键,是清洁、低碳、安全能源转型的共识。产业园级新型电力系统建设,首次展示了电源、电网、负荷、储能协同优化和智能控制,统筹兼顾,实现多元化发展。为坚持园区级新型电力系统“平衡、安全、多样、低成本”的建设目标,电网调度控制系统向智能化、自动化方向转型,体现在数字孪生、仿真、强化学习、模型训练与预测、EMS (Energy management system)智能决策等复杂系统的快速出现和建设。这带来了比以往更复杂的数据共享、交互、构建和其他技术需求。同时,随着微电网、虚拟电厂、分布式光伏等新型电力系统的同步建设,加剧了以往单片架构下的数据湖、数据仓库带来的数据偏离业务、数据利用率低、架构集中化等问题,导致数据模型难以部署,难以满足高效采集、交互、而新一代能源结构下分散、异构的数据共享,大大增加了数据团队的工作压力,使数据团队成为业务应用的瓶颈。为此,本文提出了一种基于数据网格概念的数据处理框架设计方案,通过构建分布式元数据中心来支持联邦计算和分析引擎,通过数据服务和产品化改变以往集中式的数据建模方法,通过定义服务调用和封装技术手段实现复杂多系统之间的数据共享和交互,提高数据利用率,更好地支持自动化。合理、均衡地建设智能调度系统,迎接新型园区级电力系统带来的挑战和要求。
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