技术
- 分析与建模 - 机器学习
- 传感器 - 电表
适用行业
- 建筑物
- 零售
用例
- 楼宇自动化与控制
- 减废预测
服务
- 系统集成
关于客户
Salling Group 是丹麦零售巨头,在丹麦拥有 700 多家超市和大卖场。该公司致力于减少碳足迹,并制定了雄心勃勃的气候计划,其中包括对可再生能源的大量投资。然而,不断上涨的能源价格需要立即采取行动。 Salling Group 需要一种解决方案来帮助其优化建筑运营并降低能源消耗和成本,而无需大量的前期投资。该公司还希望有一种解决方案能够深入了解能源消耗,并提出节省资金和减少二氧化碳排放的方法。
挑战
丹麦零售巨头 Salling Group 面临着降低能源消耗和成本的挑战。该公司制定了雄心勃勃的气候计划,其中包括未来几年在热泵和太阳能等设备上投资约 3.3 亿欧元。然而,不断上涨的能源价格需要立即采取行动。最显着的收益可以通过优化建筑运营来实现,这项任务需要一种无需任何大量前期投资即可立即实施的解决方案。该解决方案还需要适用于所有主要建筑业主,并能够使用可用的能源消耗数据。
解决方案
Salling Group 向丹麦软件公司 Ento 寻求解决方案。 Ento 的人工智能平台使用来自公用事业公司电表的消耗数据,如果安装了智能电表,大多数公司都可以访问该数据源。该人工智能平台能够从丹麦 Salling Group 的 700 多家超市和大卖场获取数据,并根据最大可能的节省对每栋建筑的所有可能的节能进行排名。该人工智能平台深入了解能源消耗,并建议 Salling Group 的能源管理者在哪些方面既可以节省资金,又可以减少二氧化碳排放。该平台还使用天气和商店营业时间等公开数据源来了解影响个别建筑物消费的因素。它能够自动识别运行状况不佳的建筑物并记录节能情况。
运营影响
数量效益
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