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Project CONCEPT CON ne C ting District E nergy and P ower Systems in - - PowerPoint PPT Presentation

Sep 13, 2023 458 likes •782 views

Project CONCEPT CON ne C ting District E nergy and P ower Systems in Future Singaporean New T owns Sebastian Troitzsch, Sreepathi Bhargava Krishna - 13 March 2019 What is CONCEPT? CONCEPT stands for: Connecting District Energy and Power

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CONneCting District Energy and Power Systems in Future Singaporean New Towns

Sebastian Troitzsch, Sreepathi Bhargava Krishna - 13 March 2019

Project CONCEPT

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What is CONCEPT?

  • CONCEPT stands for:

− Connecting District Energy and Power Systems in Future Singaporean New Towns

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What is CONCEPT?

  • CONCEPT stands for:

− Connecting District Energy and Power Systems in Future Singaporean New Towns

  • Goals:
  • 1. Integrate planning and operation of electric and

thermal systems on a district scale

Status Quo:

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Electric Grid Thermal System

Planning goal: Peak load satisfaction Planning goal: Demand satisfaction Operation goal: Stay within safe

  • peration limits

Operation goal:

  • Max. comfort,
  • Min. cost

No Framework or Tools for Interaction

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SLIDE 4

What is CONCEPT?

  • CONCEPT stands for:

− Connecting District Energy and Power Systems in Future Singaporean New Towns

  • Goals:
  • 1. Integrate planning and operation of electric and

thermal systems on a district scale

Proposal:

5

Electric Grid Thermal System

Planning goal: Peak load satisfaction Planning goal: Demand satisfaction Operation goal: Stay within safe

  • peration limits

Operation goal:

  • Max. comfort,
  • Min. cost

CONCEPT

Integrated planning Price-based dispatch

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SLIDE 5

What is CONCEPT?

  • CONCEPT stands for:

− Connecting District Energy and Power Systems in Future Singaporean New Towns

  • Goals:
  • 1. Integrate planning and operation of electric and

thermal systems on a district scale

  • 2. Consider flexible resources in the planning phase of

New Town districts

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Flexible resources Building A/C systems without storage Building with thermal storage Vehicle-to-grid (V2G) District cooling & thermal storage Combined heat and power plant

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SLIDE 6

What is CONCEPT?

  • CONCEPT stands for:

− Connecting District Energy and Power Systems in Future Singaporean New Towns

  • Goals:
  • 1. Integrate planning and operation of electric and

thermal systems on a district scale

  • 2. Consider flexible resources in the planning phase of

New Town districts

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Today: Fixed loads Future: Flexible loads

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SLIDE 7

What is CONCEPT?

  • CONCEPT stands for:

− Connecting District Energy and Power Systems in Future Singaporean New Towns

  • Goals:
  • 1. Integrate planning and operation of electric and

thermal systems on a district scale

  • 2. Consider flexible resources in the planning phase of

New Town districts

  • 3. Creating a computational framework integrated in

City Energy Analyst (CEA)

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+

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SLIDE 8

What is CONCEPT?

CONCEPT is set up as 13-month pilot project between the Singapore-ETH Centre (SEC) and TUMCREATE under the “Intra-CREATE Seed Collaboration Grant” of the National Research Foundation (NRF)

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Who is CONCEPT?

Sebastian Troitzsch Researcher (TUMCREATE) Sreepathi B. Krishna Researcher (SEC) Sarmad Hanif Co-PI (TUMCREATE) Jimeno A. Fonseca PI (SEC)

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Arno Schlueter Adviser (SEC) Tobias Massier Adviser (TUMCREATE)

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Methodology

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Electric grid planning Output: electric grid layout Thermal grid & supply system planning Output: thermal grid layout, supply system config.

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SLIDE 11

Methodology

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Electric grid planning Output: electric grid layout Thermal grid & supply system planning Output: thermal grid layout, supply system config.

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Methodology: Electric Grid Planning

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Electric grid planning considering flexible resource operation Numerical optimization (linear program) Flexible resource models (linear models) Building A/C systems without storage Building with thermal storage Vehicle-to-grid (V2G) District cooling & thermal storage Combined heat and power plant

Minimize: Investment costs for the electric lines, substation + Operation costs for flexible resources Constraints: Capacity limit

  • f the electric grid

& Comfort constraints for flexible resources

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SLIDE 13

Methodology: Electric Grid Planning

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Electric grid planning considering flexible resource operation Numerical optimization (linear program)

Minimize: Investment costs for the electric lines, substation + Operation costs for flexible resources Constraints: Capacity limit

  • f the electric grid

& Comfort constraints for flexible resources

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SLIDE 14

Methodology: Electric Grid Planning

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Electric grid planning considering flexible resource operation Numerical optimization (linear program)

Minimize: Investment costs for the electric lines, substation + Operation costs for flexible resources Constraints: Capacity limit

  • f the electric grid

& Comfort constraints for flexible resources

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SLIDE 15

Methodology

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Electric grid planning Output: electric grid layout Thermal grid & supply system planning Output: thermal grid layout, supply system config.

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Optimal thermal grid planning (Genetic algorithm)

Methodology: Thermal Grid and Supply System Planning

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Supply system config. Electric grid layout Generate graph model of thermal network Supply system sizing Cost calculation for thermal network & supply system Optimal electric grid planning Thermal grid layout Updated thermal demand

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Optimal thermal grid planning (Genetic algorithm)

Methodology: Thermal Grid and Supply System Planning

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Electric grid layout Generate graph model of thermal network Optimal electric grid planning Thermal grid layout Updated thermal demand Supply system sizing Cost calculation for thermal network & supply system Supply system config.

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Optimal thermal grid planning (Genetic algorithm)

Methodology: Thermal Grid and Supply System Planning

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Electric grid layout Generate graph model of thermal network Optimal electric grid planning Thermal grid layout Updated thermal demand Supply system sizing Cost calculation for thermal network & supply system Supply system config.

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Case Study: New Town – Tanjong Pagar Water Front

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Case Study: New Town – Tanjong Pagar Water Front

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MIXed-use GFA = 374, 237 sqm FAR = 4.62 People = 34,513 Buildings = 10

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Case Study: Scenarios

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Fixed loads Flexible loads Fixed loads Flexible loads Fixed loads Flexible loads Fixed loads Flexible loads

Residential

  • ccupancy

Office

  • ccupancy

Retail

  • ccupancy

Mixed use

  • ccupancy
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Results

  • 1. Cost distribution for fixed building loads
  • 2. Cost implications of integrated planning and operation (Fixed vs. Flexible building loads)
  • 3. Energy implications of integrated planning and operation (Fixed vs. Flexible building loads)
  • 4. Occupancy type dependency of costs (Mixed, Office, Residential & Retail)

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Electricity costs, 88.6% 0.6% 8.8% 1.1% 0.9% 11.4%

Annualized costs [SGD]*

Electricity costs Investment (electric lines) Investment (substation & transformers) Investment (compression chiller) Investment (cooling tower & pumps)

Results: Cost Distribution (Fixed Building Loads)

24 *(Preliminary results)

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10 20 30 40 50 60 70 80 90 100 Fixed building loads Flexible building loads

Peak load [MW]*

4.8 5 5.2 5.4 5.6 5.8 6 6.2 6.4 6.6 Fixed building loads Flexible building loads Millions

Annualized costs [SGD]*

Electricity costs Investment costs

Results: Cost implications (Fixed vs. Flexible building loads)

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+ 0.2 %

  • 28.9 %

Total:

  • 2.7 %
  • 20.7 %

*(Preliminary results)

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10,000 20,000 30,000 40,000 50,000 60,000 70,000 Fixed building loads Flexible building loads

Annualized electricity consumption [MWh]*

Hot water Appliances Space cooling

Results: Energy Implications (Fixed vs . Flexible Building Loads)

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Total: + 0.2 %

*(Preliminary results)

10 20 30 40 50 60 70 80 90 100 Fixed building loads Flexible building loads

Peak load [MW]*

  • 20.7 %
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Results: Occupancy Type Dependency

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Mixed

  • ccupancy

Office

  • ccupancy

Residential

  • ccupancy

Retail

  • ccupancy

Annualized Total Costs

  • 2.7 %
  • 3.8 %
  • 2.6 %
  • 2.1 %

Investment Costs

  • 28 %
  • 31 %
  • 21 %
  • 19 %
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Results: Occupancy Type Dependency

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  • 10.00

20.00 30.00 40.00 50.00 00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00

Office electricity demand [W/sqm]

Fixed building loads Flexible building loads

  • 10.00

20.00 30.00 40.00 50.00 00:00 03:00 06:00 09:00 12:00 15:00 18:00 21:00

Retail electricity demand [W/sqm]

Fixed building loads Flexible building loads

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Conclusions

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  • 1. The impact of flexible resources on the district energy system planning is tested by using flexible

building models at a pilot scale.

  • 2. A detailed computational framework for generating district energy systems for neighbourhoods with

flexible buildings has been developed and presented

  • 3. Flexible building loads could decrease the investment cost (- 28 %)* of the energy systems by

decreasing the peak load. This comes at the cost of increased electricity consumption (+ 0.2 %)*.

  • 4. Of all occupancy types, offices allow for the biggest decrease in investment costs (- 31 %)*.

*(Preliminary results)

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What about Implementation & Operation?

  • Electric grid operation:

− Distribution grid market, with a bid and clearing structure similar to the transmission level

  • Building operation:

− Model predictive control (MPC) for air-condition system control − Allows for consideration of dynamic electricity prices − MPC is actively being distributed by start-ups ( e.g. Meteoviva ) & trialed by BMS providers ( e.g. Siemens )

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  • Build. Operator

Building

  • Elec. Grid Operator

Price Schedule Demand Bid

Model Predictive Control

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What is the Future of CONCEPT?

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Size Extension Feedback

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SLIDE 31

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Electric Grid Thermal System Planning goal: Peak load satisfaction Planning goal: Demand satisfaction Operation goal: Stay within safe

  • peration limits

Operation goal:

  • Max. comfort,
  • Min. cost

Project CONCEPT

Integrated planning Price-based dispatch