下载PDF
Optimizing Energy Consumption in Toyota's European Plants with Weather Data
技术
- 传感器 - 环境传感器
- 传感器 - 温度传感器
适用行业
- 汽车
- 可再生能源
适用功能
- 设施管理
- 销售与市场营销
用例
- 连续排放监测系统
服务
- 系统集成
- 培训
挑战
丰田是一家领先的汽车公司,致力于减少碳足迹并保护环境。作为“丰田 2050 年环境挑战”的一部分,该公司的目标是减少二氧化碳排放、保护水资源、促进回收和保护生物多样性。重点关注领域之一是其欧洲工厂的运营部门,该公司的目标是消除二氧化碳排放并降低能源成本。挑战在于管理这些工厂的能源消耗,这些工厂的能源消耗直接受到外部温度、湿度和风等天气条件的影响。这些因素都会影响设施内的环境温度,必须保持环境温度稳定才能使设备正常运行。此外,随着工厂转向可再生能源,它们的供应能力对天气变化变得敏感。因此,准确的天气预报对于能源系统的有效规划至关重要。
关于客户
丰田汽车欧洲公司(TME)是丰田汽车公司的欧洲运营子公司,总部位于比利时布鲁塞尔。它负责监督丰田在欧洲和西亚的业务,包括土耳其、俄罗斯、以色列、哈萨克斯坦和高加索地区。丰田于 20 世纪 60 年代首次登陆欧洲,此后将其业务扩展到欧洲大陆的每个角落。其业务包括制造工厂、物流中心、销售和营销业务、研发设施、培训和设计中心、世界一流的赛车运动业务以及数千家当地零售商。
解决方案
为了应对这一挑战,丰田与天气数据提供商 Meteomatics 合作。经过成功的试用期后,Meteomatics 成为丰田唯一的天气数据提供商。该公司的 API 无缝集成到丰田的系统中,可以实时访问所有欧洲设施的准确天气数据。这使得数据收集过程更加方便和高效,使丰田能够更快地工作并做出更精确的决策。通过访问历史数据,丰田可以对未来进行估计,作为设定设施能耗目标、改进现有系统以及确定要采用的最佳技术类型的基准。这使得丰田工程师能够优化他们的目标规划并量化潜在的能源减少和经济效益。
运营影响
数量效益
相关案例.
Case Study
Remote Monitoring & Predictive Maintenance App for a Solar Energy System
The maintenance & tracking of various modules was an overhead for the customer due to the huge labor costs involved. Being an advanced solar solutions provider, they wanted to ensure early detection of issues and provide the best-in-class customer experience. Hence they wanted to automate the whole process.
Case Study
Vestas: Turning Climate into Capital with Big Data
Making wind a reliable source of energy depends greatly on the placement of the wind turbines used to produce electricity. Turbulence is a significant factor as it strains turbine components, making them more likely to fail. Vestas wanted to pinpoint the optimal location for wind turbines to maximize power generation and reduce energy costs.
Case Study
Siemens Wind Power
Wind provides clean, renewable energy. The core concept is simple: wind turbines spin blades to generate power. However, today's systems are anything but simple. Modern wind turbines have blades that sweep a 120 meter circle, cost more than 1 million dollars and generate multiple megawatts of power. Each turbine may include up to 1,000 sensors and actuators – integrating strain gages, bearing monitors and power conditioning technology. The turbine can control blade speed and power generation by altering the blade pitch and power extraction. Controlling the turbine is a sophisticated job requiring many cooperating processors closing high-speed loops and implementing intelligent monitoring and optimization algorithms. But the real challenge is integrating these turbines so that they work together. A wind farm may include hundreds of turbines. They are often installed in difficult-to-access locations at sea. The farm must implement a fundamentally and truly distributed control system. Like all power systems, the goal of the farm is to match generation to load. A farm with hundreds of turbines must optimize that load by balancing the loading and generation across a wide geography. Wind, of course, is dynamic. Almost every picture of a wind farm shows a calm sea and a setting sun. But things get challenging when a storm goes through the wind farm. In a storm, the control system must decide how to take energy out of gusts to generate constant power. It must intelligently balance load across many turbines. And a critical consideration is the loading and potential damage to a half-billion-dollar installed asset. This is no environment for a slow or undependable control system. Reliability and performance are crucial.
Case Study
Remote Monitoring and Control for a Windmill Generator
As concerns over global warming continue to grow, green technologies are becoming increasingly popular. Wind turbine companies provide an excellent alternative to burning fossil fuels by harnessing kinetic energy from the wind and converting it into electricity. A typical wind farm may include over 80 wind turbines so efficient and reliable networks to manage and control these installations are imperative. Each wind turbine includes a generator and a variety of serial components such as a water cooler, high voltage transformer, ultrasonic wind sensors, yaw gear, blade bearing, pitch cylinder, and hub controller. All of these components are controlled by a PLC and communicate with the ground host. Due to the total integration of these devices into an Ethernet network, one of our customers in the wind turbine industry needed a serial-to-Ethernet solution that can operate reliably for years without interruption.
Case Study
Integral Plant Maintenance
Mercedes-Benz and his partner GAZ chose Siemens to be its maintenance partner at a new engine plant in Yaroslavl, Russia. The new plant offers a capacity to manufacture diesel engines for the Russian market, for locally produced Sprinter Classic. In addition to engines for the local market, the Yaroslavl plant will also produce spare parts. Mercedes-Benz Russia and his partner needed a service partner in order to ensure the operation of these lines in a maintenance partnership arrangement. The challenges included coordinating the entire maintenance management operation, in particular inspections, corrective and predictive maintenance activities, and the optimizing spare parts management. Siemens developed a customized maintenance solution that includes all electronic and mechanical maintenance activities (Integral Plant Maintenance).