Kognitwin Grid - Utilities

**Overview**
As the energy system is facing an influx of intermittent, distributed and renewable energy and a sharp increase in electrification the complexity of planning and operating the energy system increases. These changes are causing challenges related to power quality and grid stability, more demanding customers with low-cost expectations, and new competitors with innovative solutions.

A digital twin solution will support the increasing complexity and enable new business models. Kognitwin Grid is a digital twin of the distribution power grid. It is a SaaS solution accessible from the browser or through API. It uses asset documentation from the Network Information System (NIS) and models it in a map displaying all components from lines and cables to transformers, generators, and end-users.

The simulation engine forecasts load and production down to meter level and performs a load flow analysis of the entire grid. The main output from the load flow is bottleneck detection and voltage quality. In addition, the solution can include live and planned switch status to reflect the grid topology and identify disconnected areas correctly. This provides an always-on status of the power grid with possibilities to look into the past, present, and future.

The simulation engine collects, adapts, and contextualizes data from different sources and systems to make them available for new applications and use cases.

**Use cases**
- **Increased Grid Utilization** - Optimized performance and improved power quality
- **Optimized Investments** - Postponement and optimization of grid investments
- **Improved Reliability** - Holistic risk evalutaion and efficient fault management
- **Democratized Data** - Increased data-driven decision support across business areas

**Product details**
This dataset provides information on substations, usage points, and static generators based on CIM-compliant XML files. It includes geographic locations, equipment details, and operational attributes essential for power system analysis and grid management.

**Dataset**
- **mod8_cimfile1.xml**: Substations with geographic locations and associated usage points
- **mod8_cimfile6_SG.xml**: Static generators and their attributes

**Sample Fields**
- **Substations**: mRID, name, location, PSRType
- **Usage Points**: mRID, annualConsumption, objectNumber, shortName, LoadGroup
- **Locations**: mRID, CoordinateSystem, mainAddress
- **Terminals**: mRID, sequenceNumber, ConductingEquipment, ConnectivityNode

**Additional Insights**
Product: [Kognitwin Grid](https://www.kongsbergdigital.com/industrial-work-surface/kognitwin-grid)
Youtube: [Kognitwin Grid - Digital Twin for Utitities](https://www.youtube.com/watch?v=SrJC3wxXEWs)

**概述**
随着能源系统迎来间歇性分布式可再生能源的大量接入，以及电气化水平的大幅提升，能源系统规划与运行的复杂度显著提升。这些变化带来了诸多挑战：包括电能质量与电网稳定性相关问题、对成本敏感且要求更高的用户群体，以及携创新解决方案入局的新型市场竞争者。

数字孪生（digital twin）解决方案可应对日益增长的系统复杂度，并催生新型商业模式。Kognitwin Grid是一款配电网数字孪生系统，属于可通过浏览器或应用程序编程接口（API）访问的软件即服务（Software as a Service, SaaS）解决方案。该系统依托网络信息系统（NIS）中的资产文档，在地图中对电网全组件进行建模，覆盖线路、电缆、变压器、发电机及终端用户等所有设备。

其仿真引擎可实现电表级别的负荷与发电量预测，并对整个电网进行潮流分析。潮流分析的核心输出结果包括瓶颈检测与电压质量评估。此外，该系统可接入实时与计划中的开关状态数据，以精准反映电网拓扑结构并正确识别断电区域。由此，系统可实时掌握电网运行状态，支持回溯历史、分析现状及预判未来。

该仿真引擎可采集、适配并关联来自不同来源与系统的数据，为新型应用与业务场景提供数据支撑。

**用例场景**
- **提升电网利用率** - 优化运行性能，改善电能质量
- **优化投资决策** - 延迟电网投资规划并优化投资方案
- **提升供电可靠性** - 开展全面风险评估，实现高效故障管理
- **数据普惠化** - 为各业务领域提供增强型数据驱动决策支持

**产品详情**
本数据集基于符合公共信息模型（Common Information Model, CIM）标准的可扩展标记语言（Extensible Markup Language, XML）文件，提供变电站、用电点及静态发电机的相关信息。数据集包含地理位置、设备细节与运行属性等电网分析与管理所需的核心要素。

**数据集**
- **mod8_cimfile1.xml**：包含地理位置与关联用电点的变电站数据
- **mod8_cimfile6_SG.xml**：静态发电机及其属性数据

**样本字段**
- **变电站**：mRID、名称、地理位置、电力系统资源类型（PSRType）
- **用电点**：mRID、年用电量、对象编号、简称、负荷组（LoadGroup）
- **地理位置**：mRID、坐标系（CoordinateSystem）、主要地址
- **端子**：mRID、序号、导电设备（ConductingEquipment）、连接节点（ConnectivityNode）

**附加洞察**
产品：[Kognitwin Grid](https://www.kongsbergdigital.com/industrial-work-surface/kognitwin-grid)
YouTube：[Kognitwin Grid——面向公用事业的数字孪生系统](https://www.youtube.com/watch?v=SrJC3wxXEWs)