Smart Multi-Energy System SMES

Transcription

1 Smart Multi-Energy System SMES Roch Drozdowski-Strehl Dr Sanjay C Kuttan -Program Director Energy Smart & Research Innovation d-erian@ntu.edu.sg Energy Research NTU (ERI@N) 1 CleanTech Loop, #06-04 CleanTech One, Singapore Phone: (65) / 2468 Fax: (65)

2 Multi-use-multi-energy estates present opportunities for further optimisation Gas Network Electricity Distribution System District Cooling/Heating Renewable Energy Storage Mixed use Estates Problem Statement and Opportunity Conventional gas and electricity systems are decoupled resulting low optimisation, under utilisation of assets, energy losses and over design District cooling/heating systems can provide greater efficiency within the district but are also decoupled from other energy systems Increased distributed renewable energy systems coupled with energy storage whilst addressing intermittency challenges have limited controllability and can result in network instability Opportunity to deliver energy efficiency, cost savings, better utilisation of assets with greater system level optimisation and resilience enabled by smart grid functionalities in an intelligent system

3 Estate and facility management system have limited capability to generate insights for effective operational decision making Key challenges Big data not smart data coupled with operational insights Monitoring of assets performance with limited optimisation Asset level optimisation not estate or facility level optimisation Reactive to failures not pro-active to limit impact of failures Act as a consumer and not partner in system level resilience

4 SMES provides operational insights through algorithms to drive energy efficiency, cost reduction and system resiliency SMES Software platform 1 2 Interoperable open architecture & scalable software platform 4 SMES software platform serves as a central command center enabling smart grid functionalities across two key management systems

5 SMES s in house developed software solution key features to help operators of facility and estate management Supply side management Turbine power generation + WHR Solar PV generation Wind power generation Thermal storage Electrical storage Other distributed energy resources Supply Demand Data driven Insights System load forecasting System supply forecasting Asset failure prediction Benchmarking (top/flop) System economic dispatch Curtailable load availability Demand side management Industrial load Building load Air conditioning Heating Lighting Occupancy Storage systems Thermal Electrical Building grid (AC/DC) Grid resilience and market monetisation Demand response program Interruptible load program

6 System of system level optimization using a bottoms up strategy moving from the equipment to the building to the estate Equipment & operations level Building level Estate level Engineers Building managers Energy managers Continuous monitoring / alarm limits / health status Prioritization of notifications Building base energy load analysis, supply management and optimization Energy usage benchmarking Energy efficiency projects planning and monitoring Energy Optimisation

7 SMES s project will demonstrate the benefits of an integrated system. Smart Grid ibms CleanTech Three(CT3) Local Energy Generation Solar Panel (PV) Gas Turbine Electrical Storage Thermal Storage Smart AC/DC Grid 7 Connection Energy Market DC Grid SMES Command Center Smart Multi-Energy Management System (heat, thermal, gas) optimization / Software Energy Market, D-R, MPC Data Analytics, Interoperability Load Forecast, Weather Demand Side Management DC Energy Grid Existing Power Grid EMIS: -10 to -15% Total energy savings: -30 to -50% DER: -5 to -10% DR/ToU: -5 to -10% Multi-energy: -5 to -10%

8 For further information please contact: Energy Research NTU (ERI@N) Executive Director ERI@N 1 CleanTech Loop, #06 04 CleanTech One, Singapore D ERIAN@ntu.edu.sg Phone: (65) / 2468 Fax: (65)