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 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.

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)

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

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

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 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)

Pilot case approach – in-simulation

Building modeling

• Building envelope model

• Building plants model

• Control-oriented approach

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

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

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

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

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 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

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…)

In-simulation: zoned thermal model

• January 2012 (t[s],Ti[°C])

sim

ula

ted

actu

al

In-simulation: zoned thermal model

• August 2012 (t[s],Ti[°C])

sim

ula

ted

actu

al

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 Tem

pera

ture

[oC

]

Time [s]

Single-volume

Zoned model

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)

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)

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

In-simulation: demand-response

Demand limitingDemand cannot exceed

a certain level

Demand sheddingA temporary consumption reduction is performed in critical periods

Demand shiftingDemand is anticipated/delayed in time

Energy efficiencyDefinitive intervention to reduce overall consumption

Asse

ts f

or

co

nsu

mption

red

uctio

n

Asse

ts f

or

de

ma

nd s

ha

pin

g

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

modelCASSANDRA

platform

Model parameters

Power consumption

Temperatures

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 expenses report

BUILDING

1217,64 kW

SHOP SHOP SHOP

SHOP SHOP SHOP

SHOP

SHOP

Bill Bill Bill Bill

Bill Bill Bill Bill

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

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

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:

– 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

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

• 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

Thank you for your attention!

Questions?