BHC3能源管理
降低能源部门工厂的设备范围内的能源成本
BHC3能源管理
Reduce whole-facility energy costs for refineries
Reduce Overall Energy Costs and Improve Building Operations
BHC3™能源管理采用机器学习帮助能源企业能够进入其交叉设施能源支出的能力，并优先采取行动，以降低其整体运营成本。该应用程序利用先进的AI和优化算法来模拟建筑运营，检测炼油资产中的异常，预测能源节省机会，并帮助能源管理人员在近实时采取行动。
特征
Streaming energy analysis
Develop high-level and granular insights into energy trends in energy assets using configurable KPIs, benchmarking and time series visualizations.
Peak-demand forecasting
Predict peak loads in energy assets with advanced AI algorithms that use streaming energy data, building data (e.g., lighting sensors, audits, operating schedules) and weather data.
最终用途分类
Conduct granular energy analysis of energy assets with AI-based algorithms that disaggregate consumption to identify constituent end-use loads such as heating, cooling and lighting within the facility.
全建筑优化
Optimize whole-building energy costs, maintain comfort and make effective use of on-site power supply (e.g., solar) using AI-enabled techniques.
异常检测
使用AI算法检测与能源资产相关的操作异常和计费误差。
Operator engagement
Use AI-enabled segmentation, energy analytics, savings recommendations and alerts to spur action that saves energy and improves overall operations of energy assets.
测量和验证
Track and report energy savings of energy assets using machine learning algorithms.
项目分析仪
组装，优先考虑和管理能源资本项目的投资组合，最大限度地提高金融目标。
Virtual building audit
提高AI模型的准确性，通过收集交叉设施行为，操作和建筑特征数据来实现新的分析。
Power purchase analysis
Evaluate real-time power demand, on-site energy supply, utility tariffs and market pricing for actionable insights into cost reduction opportunities.
自助数据科学
Visually create whole-facility analytics and machine learning models. Analyze, explore and derive business insights quickly, all without writing a single line of code.
互操作性
Integrate energy asset data from any enterprise system, third-party source, building system or on-site generation source. Embed insights into existing applications using APIs.
Benefits
Reduce
Reduce energy costs from energy assets by 15 to 30% using predictive analytics to identify high-impact energy saving opportunities and operational improvements.
预报
使用量身定制的机器学习分析预测能源资产中的能源需求，可实现大于80％的准确性。
增加
通过优化建筑和能源基础设施的投资增加资本投资投资（例如，太阳能，智能照明，储能，EV）。
自动化
自动化能源管理，通过流式分析和AI算法预测能源资产负荷以动态优化构建操作。
Improve
通过整合现场电力，预测峰值和中断事件，以及跨建筑物的需求来提高能源资产的可靠性。
Streamline
简化季度/年度审核和财务审计能源资产电力使用的报告。
部署
Rapidly deploy and configure energy solutions using self-service tools for AI, analytics, dashboards and data integrations.
数据源
BHC3能源管理creates a unified federated cloud image of energy asset data from all key sources, including energy data (e.g., meter readings, utility bills), site operational data (e.g., schedules, occupancy), telemetry signals from building systems (e.g., lighting, HVAC), and third-party data (e.g.,building audits, weather).
This unified data set inBHC3™ AI Suiteenables multi-dimensional energy analysis, predictive analytics, building optimization and anomalous performance monitoring across numerous energy asset classes. BHC3 Energy Management processes energy asset data in near real time, performing continuous analyses, generating insights, and delivering recommendations through multi-channel solutions such as mobile alerts, email reports and control signals directly to building equipment.
通过跨越许多能源系统和以级别连续运行的算法综合了解，BHC3能源管理Empowers设施经理能够优化建筑运营，减少公用事业支出并实现可持续发展目标。
Demo
Proven results in weeks, not years
Get insights into BHC3 capabilities, enterprise AI best practices and highest-value use cases.
Understand BHC3™ AI Suite's capabilities, its model-driven architecture and test it against your company's sample data set.
确定一个高影响的业务问题，并与BHC3团队合作，迅速构建解决它的AI应用程序。
规模并将测试的BHC3应用程序部署到生产中。合并用户反馈并优化算法以推动最大的经济价值。