Wonder Heat Supply 熱供給クラウドプラットフォーム by Wuxi Hundun Energy Technology Co., Ltd. is a highly esteemed winner of the very prestigious 2023 A' Design Award 銅賞 in 情報技術デザイン Competition Category.
銅情報技術· 2023
Wonder Heat Supply 熱供給クラウドプラットフォーム
by Wuxi Hundun Energy Technology Co., Ltd.
Client: Wuxi Hundun Energy Technology Co., Ltd.
A' Design Award 銅賞 Winner in 情報技術 Category
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- Verified Award Winner
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The Design
About Wonder Heat Supply 熱供給クラウドプラットフォーム
Wonder Heat Supplyは、都市の熱供給・空調事業者向けに開発されたスマート熱供給クラウドプラットフォームです。本プラットフォームはIoT、デジタルツイン技術、インテリジェントアルゴリズムを組み合わせ、ビッグデータと配管ネットワークの分布から熱供給ネットワークモデルを構築します。熱需要を予測し自動的に調整することで、各エリアの実際の需要に応じてエネルギーを分配・共有します。本システムは非カスタマイズのハードウェアにも対応し、機器構成の違いに応じて表示内容を最適化します。
The Recognition
About the A' Design Award 銅賞
Wonder Heat Supply 熱供給クラウドプラットフォームは、創造性、独創性、鋭い洞察力で際立つ傑出したデザインに授与される、高い権威をもつ評価である A' Design Award 銅賞の受賞作品です。銅賞の受賞作品は、十分に巧みで印象的なほど創造的な工芸品であり、デザイナーの豊富な経験、想像力、機知を裏づけています。Wonder Heat Supply 熱供給クラウドプラットフォームは、高く評価され、称賛され、愛される品であり、顕著にプロフェッショナルで革新的であることが期待されます。この A' Design Award 銅賞を受賞したデザインは、芸術・科学・デザイン・技術のベストプラクティスを取り入れており、細部への配慮に優れています。Wonder Heat Supply 熱供給クラウドプラットフォームは、ニーズを見事に満たし、欲求に触れ、感情を魅了し、好奇心を引きつけます。
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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