下载PDF
Accurate Solar Power Forecasts for Stadtwerke Munich: A Case Study
技术
- 应用基础设施与中间件 - 数据交换与集成
- 传感器 - 电表
适用行业
- 电网
- 可再生能源
适用功能
- 物流运输
用例
- 自主运输系统
- 车辆到基础设施 (V2I)
服务
- 系统集成
挑战
Stadtwerke München 是德国最大的能源和基础设施公司之一,在准确预测太阳能发电方面面临着挑战。太阳能和其他可再生能源的生产高度依赖于天气条件,因此很难预测可产生的电量。这种不可预测性给 Stadtwerke München 的日常电力交易业务以及太阳能发电融入电力市场带来了问题。不准确的预测可能会导致成本增加,因为如果公司可以提供的指定电量出现偏差,则必须使用通常以高价购买的平衡能源。此外,准确的电力预测对于可再生能源成功且经济地融入电力市场至关重要,特别是在太阳能和其他可再生能源不断扩张的情况下。
关于客户
Stadtwerke München (SWM) 是德国最大的能源和基础设施公司之一。它们以安全和气候友好的方式为城市提供能源(电力、天然气、区域供暖、区域制冷)和新鲜饮用水。 SWM 还经营 18 个室内和室外游泳池。其交通子公司 MVG 负责地铁、公交车和有轨电车的环境和城市兼容交通以及新的创新交通解决方案。 SWM 正在投资进一步扩大电力、供暖和制冷等可再生能源发电、全国范围内光纤的扩展以及私人交通的电气化。 SWM 与强大的合作伙伴合作,不断开发经过验证的概念并推动创新向前发展。
解决方案
Meteomatics 为 Stadtwerke München 提供了精确的太阳能预测,同时考虑了影响预测准确性的各种因素。这些因素包括高分辨率和精确天气数据的可用性和集成,例如辐射、紫外线指数、云量、温度等。其他考虑的影响因素还有太阳能发电厂的特性,如装机容量、太阳能电池板的倾斜角度、朝向和其他技术规格。通过与发电厂的实时数据进行比较,预测也不断得到改进。经过几个月的市场筛选,Stadtwerke München 决定使用 Meteomatics 的预测,该预测考虑了一流的天气数据、发电厂的技术条件和实际发电量。
运营影响
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
Temperature monitoring for vaccine fridges
Dulas wanted a way to improve the reliability of the cold chain, facilitating maintenance and ensuring fewer vaccines are spoiled. Dulas wanted an M2M solution which would enable them to record and report the temperature inside vaccine refrigerators.
Case Study
Hydro One Leads the Way In Smart Meter Development
In 2010, Ontario’s energy board mandated that time-of-use (TOU) pricing for consumers be available for all consumers on a regulated price plan. To meet this requirement, Hydro One needed to quickly deploy a smart meter and intelligent communications network solution to meet the provincial government’s requirement at a low cost. The network needed to cover Hydro One’s expansive service territory, which has a land mass twice the size of Texas, and its customers live in a mix of urban, rural, and remote areas, some places only accessible by air, rail, boat or snowmobile. Most importantly, the network needed to enable future enterprise-wide business efficiencies, modernization of distribution infrastructure and enhanced customer service. To meet these needs, Hydro One conceptualized an end-to-end solution leveraging open standards and Internet Protocols (IP) at all communication levels. The utility drew upon industry leaders like Trilliant to realize this vision.