EMA-ESG Partnership

EMA, in collaboration with Enterprise Singapore (ESG), launched a Joint Grant Call for proposals from industry partners to develop and test-bed innovative solutions in solar energy and demand-side management. This Joint Grant Call seeks to help companies build capabilities and innovative solutions relevant to national and industry needs, and potentially transfer technologies from laboratories into the market place. 

Five projects, with focus areas ranging from ESS cooling technology to AI-enabled energy management tools, were awarded. 

No Title  Description Project Team
Problem Statement A - Mitigating Solar Intermittency to Enable Solar Integration
1 Battery Module Enclosure Integrated with Liquid/Air Cooling System To reduce the risk of fire hazards and optimise operational lifespan, energy storage systems require an effective thermal management system to ensure proper heat dissipation during operation and prevent large temperature differences between cells. There are two types of cooling system - air cooling and liquid cooling. 

This project will develop a novel hybrid liquid-air cooling technique for energy storage systems to achieve an optimum operating environment vis-a-vis the conventional off-the-shelf system, especially under conditions of extreme charging and discharging. This will help to improve the overall efficiency of the energy storage system. 
Principal Investigator:
Kelvin Lim, Durapower Technology (Singapore) Pte Ltd

Co-Investigator(s):
- Energeia Labs
2 Mitigating Solar Intermittency by Energy Storage and Demand-Side Management With higher solar photovoltaic (PV) penetration, our power system operator will require a more flexible energy system to address solar intermittency induced by varying weather conditions such as cloud cover. 

The project will develop an artificial intelligence (AI)-enabled management and trading platform equipped with real-time optimisation and forecasting models to dynamically manage and control distributed energy resources such as standby generators across different locations to manage the solar intermittency.
Principal Investigator:
Laurence Kwan, Sunseap Leasing Pte Ltd

Co-Investigator(s):
- Nanyang Technology University (NTU)
- EverComm Singapore
- National Renewable Energy Laboratory (USA)
- University of Saskatchewan (Canada)
3 Pre-emptive and Self-adaptive Control for PV Cluster Intermittency Mitigation  Forecasting PV intermittency in Singapore is challenging due to the complexities of tropical weather. 

The project aims to tackle the PV intermittency prediction and mitigation at the source. The project will develop a pre-emptive control measure by using existing PV installation as geo-spatial sensors at a local cluster level and a multi-functional energy storage system controller to manage solar intermittency. This will remove the need for large-scale sensor deployments currently required for PV intermittency mitigation purposes. 
Principal Investigator:
Lim Ming Chiat, Genplus Pte Ltd

Co-Investigator(s):
- Experimental Power Grid Centre (NTU)

Collaborator(s):
- Narada Asia Pacific Pte Ltd
Problem Statement B - Reducing Energy Consumption through Demand-Side Management
4 Real-time Virtual Audits for Demand-Side Management (RTVA-DSM) This project will develop a demand-side management tool to manage demand reduction in buildings by ingesting real-time data from multiple sources (e.g. load shift) for accurate and automated predictions. The tool is expected to improve the accuracy of the prediction of building performance by over 20% from convention predictions Principal Investigator:
Nilesh Y. Jadhav, Qi Square Pte Ltd

Co-Investigator(s):
- NTU

Collaborator(s):
- Integrated Environmental Solutions Ltd
5 An AI-based Automated Demand-Side Management Solution for Optimal Energy Management of Commercial and Industry Scale Systems The project will develop an AI-based automated demand-side management technique for real-time optimal energy management particularly for commercial and industrial applications. This solution is a plug and play product which can optimise and provide up to 30% of energy cost savings per deployment site. Principal Investigator:
Dr. Jayantika Soni, Resync Technologies Pte Ltd

Co-Investigator(s):
- National University of Singapore



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