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Pilot Case 1:
Shopping Center
Prof. Luca Ferrarini
Eng. Giancarlo Mantovani
Politecnico di Milano, Italy
Outline
• Pilot case overview
• Pilot case approach
• Part 1: in-simulation
• Part 2: in-field
• Conclusions
Outline
• Pilot case overview
• Pilot case approach
• Part 1: in-simulation
• Part 2: in-field
• Conclusions
Pilot case objectives
• Pilot case 1 has the following main objectives:
– To deploy CASSANDRA software package to the spec...
Pilot site: Campo dei Fiori mall
Type: Shopping center
Location: GAVIRATE (Italy)
Technical data:
• 5-floor building
• 30 ...
Pilot site: Campo dei Fiori mall
• It is an existing shopping center
• Equipped with the local power systems:
– Cooling sy...
Building envelope
• Large central compartment
with lifts and escalators
• Heated swimming pool (with
thermal recovery syst...
Building plans
• Cooling towers
• Heat exchangers (e.g.: district
heating)
• Local refrigeration units and
boilers
• …
Building plans
Outline
• Pilot case overview
• Pilot case approach
• Part 1: in-simulation
• Part 2: in-field
• Conclusions
Pilot case approach
• Part 1: in-simulation
– Thermal and electrical modeling of the building-plants system
– Study in sim...
Pilot case approach – in-simulation
Building modeling
• Building envelope model
• Building plants model
• Control-oriented...
Pilot case approach – in-simulation
Energy control
• Application of different energy
control policies
• Local optimization...
Pilot case approach – in-simulation
Demand-response
• Energy price negotiation with the
grid
• Constraints definition for ...
Pilot case approach – in-simulation
Grid
Demand-response
• Energy price negotiation with the
grid
• Constraints definition...
Pilot case approach – in-field
• Implementation of a behavioral feedback program
– Informing shop-owners about their elect...
Outline
• Pilot case overview
• Pilot case approach
• Part 1: in-simulation
• Part 2: in-field
• Conclusions
In-simulation: building models
• Thermal model from UNI regulations:
– Applies models and formulas from UNI/TS 13790 for b...
In-simulation: zoned thermal model
• Features:
– Finite-volume
dynamic model
– Short-period
simulation
– More complex and
...
In-simulation: zoned thermal model
• January 2012 (t[s],Ti[°C])
simulatedactual
In-simulation: zoned thermal model
• August 2012 (t[s],Ti[°C])
simulatedactual
In-simulation: single-volume model
• Models commercial building average temperature
• Scalable modeling methodology (diffe...
In-simulation: control strategies
• IDEA: use control strategies for decreasing temperature stratification:
(+) More comfo...
In-simulation: control strategies results
• Single-PI, comparison with current practice:
– Cannot control thermal stratifi...
In-simulation: demand-response
• Test consumption and comfort changes when the building
operates under demand-response pro...
In-simulation: demand-response
Demand limiting
Demand cannot exceed
a certain level
Demand shedding
A temporary
consumptio...
In-simulation: integration with CASSANDRA
• Developed models are implemented in an external simulator and
are available fo...
Outline
• Pilot case overview
• Pilot case approach
• Part 1: in-simulation
• Part 2: in-field
• Conclusions
In-field: current situation
• Current situation on feedback:
– Building: network analyzers
– Retail shops: monthly total e...
In-field: program target
• Provide building managers with energy KPIs → improved feedback
• Provide shop ownners with real...
In-field: main steps
• Program design:
– Participants: retail shops (11) and building managers
– Feedback information: tot...
In-field: web-app interface
In-field: web-app interface
In-field: web-app interface
In-field: monetary incentives
• Retail shops participants involvement is improved by monetary
incentives
• Criteria:
– Ene...
Outline
• Pilot case overview
• Pilot case approach
• Part 1: in-simulation
• Part 2: in-field
• Conclusions
Conclusions
• Pilot case is designed to test CASSANDRA platform capabilities
considering both the building and the shops
•...
Thank you for your attention!
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4. Luca Ferrarini (POLIMI, Italy) - Pilot Case 1: The Reality of Working with Small Commercial Customers to Improve Energy Management

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4. Luca Ferrarini (POLIMI, Italy) - Pilot Case 1: The Reality of Working with Small Commercial Customers to Improve Energy Management

  1. 1. Pilot Case 1: Shopping Center Prof. Luca Ferrarini Eng. Giancarlo Mantovani Politecnico di Milano, Italy
  2. 2. Outline • Pilot case overview • Pilot case approach • Part 1: in-simulation • Part 2: in-field • Conclusions
  3. 3. Outline • Pilot case overview • Pilot case approach • Part 1: in-simulation • Part 2: in-field • Conclusions
  4. 4. Pilot case objectives • Pilot case 1 has the following main objectives: – To deploy CASSANDRA software package to the specific case, feeding the platform with data coming from a real test scenario. – To evaluate the applicability of demand response and feedback programs in the commercial sector. – To use CASSANDRA as a decision support tool in the pilot case and evaluate the obtained results in order to determine platform effectiveness.
  5. 5. Pilot site: Campo dei Fiori mall Type: Shopping center Location: GAVIRATE (Italy) Technical data: • 5-floor building • 30 retail shops • Large gym and pool at first floor • Bars and restaurant on fifth floor • Park with PV roof cover (602 kWp)
  6. 6. Pilot site: Campo dei Fiori mall • It is an existing shopping center • Equipped with the local power systems: – Cooling system – Heating system – Electrical power station • Fully instrumented with a building automation system for monitoring: – Temperature / humidity – Plants state – Electrical consumptions meters
  7. 7. Building envelope • Large central compartment with lifts and escalators • Heated swimming pool (with thermal recovery systems) • Glass roof (high solar radiation contribution to internal temperature) • Walls above and under ground
  8. 8. Building plans • Cooling towers • Heat exchangers (e.g.: district heating) • Local refrigeration units and boilers • …
  9. 9. Building plans
  10. 10. Outline • Pilot case overview • Pilot case approach • Part 1: in-simulation • Part 2: in-field • Conclusions
  11. 11. Pilot case approach • Part 1: in-simulation – Thermal and electrical modeling of the building-plants system – Study in simulation of the impact of different energy control systems – Testing of various pricing policies on the controlled building • Part 2: in-field – Application of a behavioral program to the commercial building retail shops – Provide consumption reduction by informing shop-owners about their electrical consumptions (feedback program)
  12. 12. Pilot case approach – in-simulation Building modeling • Building envelope model • Building plants model • Control-oriented approach
  13. 13. Pilot case approach – in-simulation Energy control • Application of different energy control policies • Local optimization of the building Building modeling • Building envelope model • Building plants model • Control-oriented approach
  14. 14. Pilot case approach – in-simulation Demand-response • Energy price negotiation with the grid • Constraints definition for Energy Controller Energy control • Application of different energy control policies • Local optimization of the building Building modeling • Building envelope model • Building plants model • Control-oriented approach
  15. 15. Pilot case approach – in-simulation Grid Demand-response • Energy price negotiation with the grid • Constraints definition for Energy Controller Energy control • Application of different energy control policies • Local optimization of the building Building modeling • Building envelope model • Building plants model • Control-oriented approach
  16. 16. Pilot case approach – in-field • Implementation of a behavioral feedback program – Informing shop-owners about their electrical consumption – Use a web-application as channel • Monetary incentives are provided as result of a competition among shops
  17. 17. Outline • Pilot case overview • Pilot case approach • Part 1: in-simulation • Part 2: in-field • Conclusions
  18. 18. In-simulation: building models • Thermal model from UNI regulations: – Applies models and formulas from UNI/TS 13790 for building energy use calculation • Five-floor stratified thermal model: – Takes into account vertical temperature distribution – Built from first principle thermal equations, detailed modeling approach – Models building envelope, thermal plants and external conditions (weather/occupancy) • Single volume thermal model: – Simplified model with an unique temperature for the whole building – Models building envelope, thermal plants and external conditions – Good for behavior prediction
  19. 19. In-simulation: zoned thermal model • Features: – Finite-volume dynamic model – Short-period simulation – More complex and detailed – Considers building use and occupancy • Physical entities modeled: – Envelope (walls, glass roof, furniture, etc…) – Plants (fan-coils, air-handling units, refrigeration units/heat pumps, heat transfer in the water circuits, etc…)
  20. 20. In-simulation: zoned thermal model • January 2012 (t[s],Ti[°C]) simulatedactual
  21. 21. In-simulation: zoned thermal model • August 2012 (t[s],Ti[°C]) simulatedactual
  22. 22. In-simulation: single-volume model • Models commercial building average temperature • Scalable modeling methodology (different building can be modeled only with parameters re-tuning) • Useful for consumption prediction in a short-term/medium-term E ≅ 0.2 oC Temperature[oC] Time [s] Single-volume Zoned model
  23. 23. In-simulation: control strategies • IDEA: use control strategies for decreasing temperature stratification: (+) More comfort with.. (-) Less energy consumption • Possible control variables: – Temperatures and mass flows – Equipment switch on-off signals • Considered techniques: – Hysteresis (current practice, does not control supply water temperature) – Single-PI regulator (controls average temperature) – Five-PI (controls temperature in each floor) – MPC (optimizes building-plants overall system, work in progress)
  24. 24. In-simulation: control strategies results • Single-PI, comparison with current practice: – Cannot control thermal stratification (comfort not improved) – -7% energy consumption • Five-PI, comparison with current practice: – -25% temperature stratification (comfort improved) – -5% energy consumption (less savings with respect to single-PI)
  25. 25. In-simulation: demand-response • Test consumption and comfort changes when the building operates under demand-response programs • Pricing schemas applied: – TOU (Time Of Use pricing) – CPP (Critical Peak Pricing) – RTP (Real Time pricing) • Demand response assets and strategies: – Thermal inertia – Load shaping: – Demand limiting – Demand shedding – Demand shifting
  26. 26. In-simulation: demand-response Demand limiting Demand cannot exceed a certain level Demand shedding A temporary consumption reduction is performed in critical periods Demand shifting Demand is anticipated/delayed in time Energy efficiency Definitive intervention to reduce overall consumption Assetsforconsumptionreduction Assetsfordemandshaping
  27. 27. In-simulation: integration with CASSANDRA • Developed models are implemented in an external simulator and are available for CASSANDRA as a web-service • A standardized interface for data exchange was designed • In this way, models can be parameterized inside the platform and run on an external server MODEL SERVER web-server DATA EXCHANGE INTERFACE Java Thermal model CASSANDRA platform Model parameters Power consumption Temperatures
  28. 28. Outline • Pilot case overview • Pilot case approach • Part 1: in-simulation • Part 2: in-field • Conclusions
  29. 29. In-field: current situation • Current situation on feedback: – Building: network analyzers – Retail shops: monthly total expenses report BUILDING 1217,64 kW SHOP SHOP SHOP SHOP SHOP SHOP SHOP SHOP Bill Bill Bill Bill Bill Bill Bill Bill
  30. 30. In-field: program target • Provide building managers with energy KPIs → improved feedback • Provide shop ownners with real-time information on electrical consumptions (web application channel) BUILDING 1217,64 kW SHOP 7,41 kW KPIs SHOP 6,70 kW KPIs SHOP SHOP SHOP SHOP Bill Bill Bill Bill KPIs SHOP 30,12 kW KPIs SHOP 5,23 kW KPIs
  31. 31. In-field: main steps • Program design: – Participants: retail shops (11) and building managers – Feedback information: total electrical consumptions and energy KPI – Feedback channel: web application • Information campaign with shop-owners: – Visits and potentialities explaination – Flyer design – Promotion on Politecnico web-site • Program deployment: – Web-application coding – Application release
  32. 32. In-field: web-app interface
  33. 33. In-field: web-app interface
  34. 34. In-field: web-app interface
  35. 35. In-field: monetary incentives • Retail shops participants involvement is improved by monetary incentives • Criteria: – Energy saving with respect to own consumption in pre-program period – Energy saving with respect to the other shops (with similar consumption profiles) – Program involvement (access to website pages) • Total amount: – About 2500€ – Distributed in two periods
  36. 36. Outline • Pilot case overview • Pilot case approach • Part 1: in-simulation • Part 2: in-field • Conclusions
  37. 37. Conclusions • Pilot case is designed to test CASSANDRA platform capabilities considering both the building and the shops • Both thermal and electrical consumptions are considered • Building use and comfort principles are taken into account • Both in-simulation and in-field activites are carried out • Almost unique behavioral program in the commercial sector
  38. 38. Thank you for your attention! Questions?

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