Improving decision-making through holistic power grid network modeling（通过整体电网网络建模优化决策制定）¶

Industry Sector: Utilities

Business Function: Operations

At a European utility company, Foundry was used to create a rich data asset, which drives other use cases downstream, including:

Outage response and root cause analysis
Reporting on Assets and KPIs at different granularities
Outage review and validation for regulatory reporting

Challenge¶

A utility's asset management team is responsible for maintaining grid stability and reducing outage time. This has important regulatory requirements (for example, Germany requires utilities to have a System Average Interruption Duration Index (SAIDI) score of less than 12 minutes per customer) as well as being crucial for their ability to renew their concession contracts to provide power.

Given siloed geographical asset and grid systems, this utility lacked a comprehensive, updated picture of grid state, protracting outage response, and root cause analysis.

Solution¶

The company’s various datasources tracking the state of their grid and geographic information were integrated into an ontology in Foundry, which in turn is used in a wide variety of operational workflows to better manage their assets.

Improving Decision Making Through Holistic Power Grid Network Modelling

Stakeholders and user groups¶

Asset Management
Asset Management Data Team
Individual business functions for different parts of the Grid
Data source owners

Impact¶

The Grid Digital Twin was implemented from tens of thousands of coordinates, electrical grid, cables, circuits, and relationships. Foundry’s data integration capabilities and interoperability mean that, in addition to unlocking the new asset management workflows, Foundry’s integration with their PSI control system drives rich data back into existing operational systems.
This version of the ontology took approximately 12 months to be implemented, but has been subsequently converted to a library and can be deployed in weeks.

How it’s made¶

Power grid asset data from PSI control systems and geographic (GIS) data were first unified via transforms to make sure they matched and writeback was enabled for both. Using this unified data asset, the objects were created in Object Explorer.

The network topology serves as the foundation of several use cases, such as the outage localization app (implemented in Slate), which provided a new method of determining the most likely location of the cause of an outage (e.g., where a tree fell on some cables).

The Network Grid Topology is modeled as Ontology objects and views representing the different network elements. Visualizations are done using Object Explorer Maps, Quiver Charts, and other common Object Explorer widgets.

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中文翻译¶

通过整体电网网络建模优化决策制定¶

行业领域：公用事业

业务职能：运营

某欧洲公用事业公司利用 Foundry 构建了丰富的数据资产，进而驱动下游多个用例，包括：

故障响应与根因分析
不同粒度下的资产与关键绩效指标（KPI）报告
面向监管报告的故障审查与验证

挑战¶

公用事业公司的资产管理团队负责维护电网稳定性并缩短故障时间。这不仅关乎其续签供电特许经营合同的能力，还涉及重要的监管要求（例如，德国要求公用事业公司的系统平均中断持续时间指数（SAIDI）评分低于每位客户 12 分钟）。

由于地理资产与电网系统相互孤立，该公司缺乏全面且更新的电网状态视图，导致故障响应和根因分析周期延长。

解决方案¶

该公司将追踪电网状态和地理信息的多源数据整合到 Foundry 的本体（Ontology）中，进而广泛应用于各类运营工作流，以更好地管理资产。

通过整体电网网络建模优化决策制定

利益相关者与用户群体¶

资产管理团队
资产管理数据团队
电网各环节的独立业务职能部门
数据源所有者

影响¶

电网数字孪生（Grid Digital Twin）基于数万个坐标、电网线路、电缆、电路及其关系构建而成。Foundry 的数据集成能力与互操作性意味着，除了解锁新的资产管理工作流外，其与 PSI 控制系统的集成还能将丰富数据回传至现有运营系统。
该版本的本体实施耗时约 12 个月，但后续已转化为库（library），可在数周内完成部署。

实现方式¶

首先通过转换（transforms）统一来自 PSI 控制系统的电网资产数据和地理信息系统（GIS）数据，确保数据匹配，并为两者启用写回（writeback）功能。基于这一统一数据资产，在 Object Explorer 中创建了对象。

网络拓扑（network topology）是多个用例的基础，例如故障定位应用（基于 Slate 实现），该应用提供了一种新方法来确定故障原因最可能的位置（例如，树木倒在电缆上的位置）。

电网拓扑被建模为 Ontology 对象和视图，以表示不同的网络元素。可视化通过 Object Explorer 地图、Quiver 图表及其他常用 Object Explorer 组件实现。

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