Mitsubishi Heavy Industries Thermal Systems receives the 61st SHASE Award for Distinguished Technologies (Academic paper category) from The Society of Heating, Air-Conditioning and Sanitary Engineers of Japan (SHASE) '

• Awarded based on research results with a view to stabilizing power supply and demand in the future smart grids
• Optimized control with machine learning of both air conditioner’s power consumption and room temperature achieves both comfort by air conditioning and energy saving which are usually in trade-off relationship.

Mitsubishi Heavy Industries Thermal Systems, Ltd. (MHI Thermal Systems), a group company of Mitsubishi Heavy Industries (MHI) Group, received the 61st SHASE Award for Distinguished Technologies (Academic paper category) at the Society of Air-Conditioning and Sanitary Engineers of Japan Award, sponsored by the Society of Heating, Air-Conditioning and Sanitary Engineers of Japan, for its "Response Prediction Neural Network Modeling for Complex Adaptive Control of Building Multi-type Air-conditioning Facilities for Real-Time Pricing - Training method with virtual power command and DNA analysis algorithm -."

Since 1963, for the purpose of promoting the advancement of science and technology, SHASE has been presenting awards every year to excellent papers and achievements in facility engineering technology.

Demand-response-control (Note1) is accelerated to be introduced in the market by Agency for Natural Resources and Energy in Ministry of Economy, Trade and Industry, making the balance of electricity power supply and demand, where renewable energy is getting more supplied. Real-time-pricing (Note2) is focused in one way of demand-response-control and estimated to be popular in the future. Multi-type air-conditioner makes up a large proportion of electricity power consumption in the buildings, and it is featured to have effective demand-response-control.

This winning technology is achieved by the joint research project on smart grid power control engineering with Gifu University and it provides new method to establish both comfort by air conditioning and energy saving which are usually in trade-off relationship, predicting electricity consumption and room temperature by machine learning. The process of implementing optimal air-conditioning control is achieved with Machine to Machine (M2M), remote monitoring device to air-conditioner, using single evaluating function regarding the variation in the price of electricity and the air-conditioning power consumption. This new technology enables automated and effective demand-response-control which is now traditional manual control.

Encouraged by this award, MHI Thermal Systems will continue developing technologies and products focused on the individual consumer, and provide optimal thermal solutions to a range of customer needs. with its comprehensive technological capabilities, derived from synergies between its broad-based air-conditioning and refrigeration operations.

• 1Demand-response-control: Electricity supplier or aggregator controls the supply of electricity and encourage electricity user to change its demand.
• 2Real-time-pricing: Dynamic electricity pricing where electricity charge varies in short time period such as 10-min, reflecting electricity power price in the market.

Air-Conditioner Designing & Engineering Department