Wonder Heat Supply 供热云平台 by Wuxi Hundun Energy Technology Co., Ltd. is a highly esteemed winner of the very prestigious 2023 A' Design Award 铜奖 in 信息技术设计 Competition Category.
铜信息技术· 2023
Wonder Heat Supply 供热云平台
by Wuxi Hundun Energy Technology Co., Ltd.
Client: Wuxi Hundun Energy Technology Co., Ltd.
A' Design Award 铜奖 Winner in 信息技术 Category
Verified Award Winner
Verify Award Status for #142452The Design
About Wonder Heat Supply 供热云平台
「Wonder供热」是一款面向城市供热与暖通企业开发的智慧供热云平台。该平台融合物联网、数字孪生技术与智能算法，基于大数据与管网分布构建热网模型，自动预测并调控热需求，使能源按各区域的实际需求进行分配共享。系统支持非定制化硬件，并可根据不同的设备配置自适应调整显示内容。
The Recognition
About the A' Design Award 铜奖
Wonder Heat Supply 供热云平台是 A' Design Award 铜奖得主，这是授予以创造力、独创性和敏锐见长的杰出设计的极具声望的认可。铜奖得主是技艺娴熟、创意惊人的作品，印证了其设计师丰富的经验、想象力与机智。预计Wonder Heat Supply 供热云平台将成为一件备受推崇、令人钦佩且被珍爱的物品，兼具显著的专业性与创新性。这件赢得 A' Design Award 铜奖的设计融入艺术、科学、设计和技术领域的最佳实践，并因注重细节而出类拔萃。Wonder Heat Supply 供热云平台出色地满足需求，触动渴望，迷住情感，并吸引好奇心。
Behind the Design
Press Kit
Credits, team members and technical details provided by the designer.
- Unique Properties
- This is a standardized smart heat supply cloud platform designed on the basis of IoT, digital twin, and intelligent algorithms, which is specially designed for city HVAC companies. Being a self-aware, self-analyzing, self-regulating and breathing heating system, it can establish a heat supply network model grounded on big data and pipeline networks distribution to predict and regulate the heat supply of cities.
- Tags
- Heat supply cloud platform for city, Heat supply load simulation, Self awareness, Self regulation, Digital twin
- Production Technology
- It adopts clear policy instruction, simple visual language and full function setting, and designs visual data analysis system and a UI interface designed for managers, facilitating the access of users, remote regulation and dispatching. The system reduces the parameter requirements for hardware devices and adopts non customized configuration, lowering the hardware threshold for access and self adjusting the screen effect and display content based on different hardware configurations of users.
- Design Challenge
- A key issue in the research is how to give AI the ability of self-analysis and self-control to energy parameters. With algorithmic strategy of the energy model, digital twin and actual operation data, the design team gives AI the ability to self-adjust parameters and optimize energy efficiency. The optimal solution for heat network management saves energy by 10-15 percent, thus reducing carbon emissions. It helps generate more economic and socially environmental benefits of enterprises.
- Research
- City complexes contain more functional areas of buildings. Compared with the HVAC systems of other single buildings, city HVAC systems need to allocate energy properly based on the actual demand of each area. The traditional mode of manual management and coordination has gradually become unsuitable. Thus, it has become the preferred solution of the design team with the help of AI, IOT and digital twin for collaborative and accurate control.
- Inspiration
- As one of the most energy-consuming systems in the daily lives of residents, problems such as uneven energy distribution and low energy utilization can be found in city HVAC systems, while the platform is designed to solve the above problems. Through the combination of IoT, digital twin and intelligent algorithm, the design team has given AI a new model of self-awareness, self-analysis and self-regulation of unmanned control, thus helping city HVAC systems to save energy and reduce emissions.
- Project Duration
- The product was developed in Wuxi, Jiangsu Province in March 2022 and also launched here in August 2022
- Operation Flow
- With the simplification of operation of system levels, users can freely switch between different animation styles and seasonal scenes based on their preferences, making it user-friendly, 10 industry professionals can use it smoothly when tested for the first time, without training and teaching. Its built-in simulation and load prediction functions can obtain real-time data such as weather and geographic location from the meteorological system and geographic space for real-time display.
- Team Members
- Jun Xu, Jue Wang, Lan Zhu and Guiying Fu
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