SS03: AI:MPC for Optimisation of HVACR Systems with Hybrid Energy Sources including Renewables

Distributed energy use in buildings is becoming increasingly common with options such as solar (both PV and thermal systems) trigeneration systems to meet building energy needs. Commercial buildings have in the past utilised chilled water storage and the building thermal mass as storage to avoid electricity peak demand charges. Future building HVAC systems will have a combination of storage systems (electrical and thermal), energy sources (electricity, gas, solar PV, solar thermal) and various chillers (electrical and thermal) to optimally meet building energy needs.

This session will outline an artificial intelligence-supported model predictive controller (AI-MPC) framework. AI-MPC uses a high-level model to generate predictions of system load and resources to minimise operation costs. AI methods will be applied to continuously learn and update the system models based on feedback from measurements and to generate predictions and define optimal trajectories.

The AI-MPC will focus on addressing the following two challenges existing in the framework;

1.  Reliable and efficient estimation of future status is required for multiple factors in the system, e.g., temperature and energy demand.

2.  Joint optimization of the whole system. Building HVAC energy usage consists of various subsystems that, from an energy delivery perspective, can be classified as air side and water side. These subsystems share commonalities and dynamically interact with each other however the most efficient performance of each subsystem may not necessarily lead to optimum performance of the overall system.

A working solution for the project is due for delivery by June 2021.

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Chirayu Shah, General Manager, Conserve It

Chirayu Shah is the General Manager at Conserve It with over 16 years of experience in the automation and controls industry. He started his career in India in 2002, working on special purpose projects with multiple government organisations in various fields of research. Shah has considerable experience in technical product and application development, product distribution & support and business development in #SmartBuildings, edge to cloud IoT solutions, building automation and analytics industries.

 

 

 

 

 


Michael Berger, R&D Engineering Manager, Conserve It

As the R&D Engineering Manager at Conserve It, Berger leads the R&D efforts to develop innovative chiller plant optimisation, predictive maintenance and advanced controls solutions. Having graduated with a Master of Engineering in France and with experiences in a leading research centre and in environmentally sustainable design consultancy in Singapore prior to joining Conserve It in 2014, he draws on years of experience in the fields of energy efficiency, chiller plant optimisation and energy modelling.

 

 

 

 

Note: The seminar program may be subject to change. If you have registered for this seminar any topic, presenter, timetable or price changes will be communicated as soon as possible prior to the event.