Transcript Innoweek_On_RES_Dialeksi_Kantar_2.ppt

Óbuda University
Power System Department
Energy consumptions of public sector,
Energy audits and the
Intelligent network
Dr. Péter Kádár
Óbuda University, Power System Department, Hungary
[email protected]
Draft
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Óbuda University
Power System Department
Curve analysis
Audits
Energy management
Intelligent networks and customers
Energy consumption, audits and the intelligent network - Patra, 2012
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Focus on the public consumption
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Óbuda University
Power System Department
Residential area
Flats
Housing estates
Hospital
Library
Local government office
School
Caretaking home for old people
Kindergarten
Industrial buildings
Office towers
Agricultural buildings
Energy consumption, audits and the intelligent network - Patra, 2012
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The energy
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Óbuda University
Power System Department
Electricity
Gas
Remote heating
Water
Canalisation
Telecom
Everything that „come from the utility”
(and the bill comes)
Energy consumption, audits and the intelligent network - Patra, 2012
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The sources of the data for further analysis
Óbuda University
Power System Department
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Yearly invoices
Monthly invoices
Daily meter reading
Automatic meter data for every 15 min
Rough estimation based on nominal power
consumption and watch
• Measurement, etc.
Energy consumption, audits and the intelligent network - Patra, 2012
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Daily load curve of a primary school
Óbuda University
Power System Department
Energy consumption, audits and the intelligent network - Patra, 2012
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Daily load curve of a water well
Energy consumption, audits and the intelligent network - Patra, 2012
Óbuda University
Power System Department
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Aggregated load curve of 7 water pump in a week
Óbuda University
Power System Department
Energy consumption, audits and the intelligent network - Patra, 2012
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High school, building I. a March week
Óbuda University
Power System Department
Energy consumption, audits and the intelligent network - Patra, 2012
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High school building II., a March week
Óbuda University
Power System Department
Energy consumption, audits and the intelligent network - Patra, 2012
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Grammar school, a February week
Óbuda University
Power System Department
Energy consumption, audits and the intelligent network - Patra, 2012
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Grammar school, January weeks
Energy consumption, audits and the intelligent network - Patra, 2012
Óbuda University
Power System Department
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National feast
Energy consumption, audits and the intelligent network - Patra, 2012
Óbuda University
Power System Department
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Monthly electricity consumption of social
institution (11 months)
Óbuda University
Power System Department
9000
8000
7000
6000
Old people's home I.
Old people's home II.
kWh
5000
Homeless hotel
Caretaking center for homeless people I.
4000
Caretaking center for homeless people II.
Temporary family hotel
3000
2000
1000
0
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2
3
4
5
6
7
8
9
10
11
Energy consumption, audits and the intelligent network - Patra, 2012
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Seasonal gas consumption in
social institution (12 months)
Óbuda University
Power System Department
20000
18000
16000
14000
m3
12000
Homeless hotel
10000
Temporary family hotel
Old people's home I.
8000
6000
4000
2000
0
1
2
3
4
5
6
7
8
9
10
11
12
Energy consumption, audits and the intelligent network - Patra, 2012
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Monthly electricity consumption data of
a water utility
Óbuda University
Power System Department
8,000
7,000
6,000
MWh
5,000
4,000
3,000
2,000
1,000
0
1
2
3
4
5
6
7
8
9
Energy consumption, audits and the intelligent network - Patra, 2012
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11
12
16
Daily gas consumption in a year
Óbuda University
Power System Department
200000
180000
160000
140000
120000
100000
80000
60000
40000
20000
0
H
K
Sz
Cs
P
49
45
41
37
33
29
25
21
17
13
9
5
Szo
V
1
Fogyasztás
Naptípusok 2003
Hetek
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Óbuda University
Power System Department
Energy consumption audits
The basic rules of the energy management
Óbuda University
Power System Department
• How can you spare energy?
• How can you use with greater efficiency?
• How can you buy cheaper energy?
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Questions to answer
Óbuda University
Power System Department
• Ratio of the energy consumption
• Assessment of the present energy purchase
• Assessment of the energy management
person/system
• Is there any anomalies? – benchmarking
• Capability of the loadforecasting
• General status of the technical devices
• Thermal isolation (heating and cooling)
• Recommendation for the control of the
heating/cooling. Shadowing – passive houses
• Alternative, direct energy usage (lighting, heating)
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Methodes of energy audit
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Óbuda University
Power System Department
Walk and look
Talk and hear
Assessment of the building heating/cooling system
Analysis of elecricity and gas consumption
Investigation of the alternative sources
Thermovision
Project plan, etc.
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The way of the electricity
Óbuda University
Power System Department
Current transformers
10/0.4 kV transformer
Meters
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Devices from different ages
10/0.4 kV transformer
Meter box
Óbuda University
Power System Department
0.4 kVmain supply
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Óbuda University
Power System Department
Energy consumption, audits and the intelligent network - Patra, 2012
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Electrical devices
Óbuda University
Power System Department
Aggregator
10/0.4 kV transformer
0.4 kV distribution box
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Metering in Hungary
Energy consumption, audits and the intelligent network - Patra, 2012
Óbuda University
Power System Department
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Metering in Greece
Energy consumption, audits and the intelligent network - Patra, 2012
Óbuda University
Power System Department
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Metering in Greece
Energy consumption, audits and the intelligent network - Patra, 2012
Óbuda University
Power System Department
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Reactive power compensation and distr. boxes
Óbuda University
Power System Department
Energy consumption, audits and the intelligent network - Patra, 2012
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UPS and accumulators
Energy consumption, audits and the intelligent network - Patra, 2012
Óbuda University
Power System Department
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Problems of public energy management
Óbuda University
Power System Department
• Costs occurre later (bill arrives months later
than the real consumption)
• Fixed prices, the consumption can not be
changed
• The public customer is a „ financially secure
customer”
• The technical and financial management is
distributed
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Present deals
Óbuda University
Power System Department
Co-generation – tri-generation
Natural gas -> electricity + heat + cooling
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Gas engines
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Óbuda University
Power System Department
400 pcs in Hungary
600 MW biult in capacity
State support
Co-generation
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Electrical energy management: active
power and the tariffs
Óbuda University
Power System Department
kWh
Csúcson kívül
Csúcs
2004. okt.
2004. szept.
2004. aug.
400000
350000
300000
250000
200000
150000
100000
50000
0
2004. júl.
2004. jún.
2004. máj.
2004. ápr.
2004. márc.
2004. febr.
2004. jan.
2003. dec.
2003. nov.
2003. okt.
2003. szept.
2003. aug.
2003. júl.
2003. jún.
2003. máj.
2003. ápr.
2003. márc.
2003. febr.
2003. jan.
Wattos energia összes
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Electrical energy management: peak power
Óbuda University
Power System Department
Maximal load
<900kW
Peak must be set/controlled by the tariffs
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Electrical energy management: prefixed peaks
Óbuda University
Power System Department
oversizing !
June, July, August, September – lower consumption – higher costs
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Over- and undersizing of the prefixed peak
Óbuda University
Power System Department
Teljesítmény díj és büntetés
810 kW real plan
penalty or overcosts?
1 600 000
1 500 000
Ár (Ft)
1 400 000
Büntetés
1 300 000
Teljesítmény díj
1 200 000
1 100 000
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87
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85
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83
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81
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79
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77
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75
0
1 000 000
Lekötött teljesítmény (kW)
765 kW
900 kW
fixed Energy consumption, audits and the intelligent networkfixed
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Peak management
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Óbuda University
Power System Department
The tariff structure must be known
Strategy: less fixed + some penalties
Lower consumption, lower peaks!
Peak controlling, limiting
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Electrical energy management: reactive power
Óbuda University
Power System Department
Inductive reactive poser can be 25-30 % of the active part.
cos=0,96
condenser
Penalty for the capacitive reactive power!
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Walking – looking – listening
Energy consumption, audits and the intelligent network - Patra, 2012
Óbuda University
Power System Department
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Ratio analysis
Óbuda University
Power System Department
Beépített teljesítmény
arányok
Built in power
10%
Hőtechnika
Világítás
18%
Pékség
52%
Irodák
Mall
8%
Egyéb
4%
8%
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Measurement analysis
Óbuda University
Power System Department
Havi negyedórás átlagértékek
Average daily loads
2200
Január
Február
2000
Március
Április
1800
Május
Június
1600
Július
Augusztus
1400
Szeptember
Október
1200
November
December
0:
15
1:
45
3:
15
4:
45
6:
15
7:
45
9:
15
10
:4
5
12
:1
5
13
:4
5
15
:1
5
16
:4
5
18
:1
5
19
:4
5
21
:1
5
22
:4
5
1000
Idő
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Measuring
Energy consumption, audits and the intelligent network - Patra, 2012
Óbuda University
Power System Department
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The relation of the electrical and heating energy
Óbuda University
Power System Department
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Heating – cooling system
Cooling with absorber machines
Seasonality
Building technology
Drives (air, lifts)
Cogeneration
Air conditioners
Electric heating
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Ratio of heating and cooling in a mall
Óbuda University
Power System Department
Energy consumption, audits and the intelligent network - Patra, 2012
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Gas consumption
Óbuda University
Power System Department
Havi gázfogyasztás
180 000
160 000
140 000
m3
120 000
100 000
80 000
60 000
40 000
20 000
0
I.
II.
III.
IV.
V.
VI.
VII
VIII
IX.
X.
XI.
XII.
Hónap
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Thermovision
Energy consumption, audits and the intelligent network - Patra, 2012
Óbuda University
Power System Department
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General recommendations for better
energy management
Óbuda University
Power System Department
Lowering costs:
• Cheaper energy purchase
• Decrease of consumption
• Decrease of losses
How?
• Energetics audit
• Investment
• Change the present practice!
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Energy management in the organisation
Óbuda University
Power System Department
• Personal competences
– Clearing the responsibilities
– Clearing the motivation
– Support for the work
– Responsibility
• Technical conditions
– Energy measurements
– Central control system
– Actors in the system (switches, controllers)
• Financing (short term ROI)
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Recommendations:
Óbuda University
Power System Department
• Building an energy management system
• Building of energy manager team
• Environment and sustainability consciousness
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Specific recommendations - electricity
Óbuda University
Power System Department
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Appropriate feeding point
Better load forecast
Better purchasing agreements
Peak control (e.g. with meters Actaris SL7000)
On-line SCADA control
Reactive compensation
Renovation of old devices, nets
Phase balancing
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Specific recommendations - heat
Óbuda University
Power System Department
• Measurements
• Independent measurement of the heating energy
and the hot water(‘s energy)
• Better isolation
• Temperature control
• Optimisation, etc.
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What about the renewables?
Óbuda University
Power System Department
• Small scale application, only on economy basis
• Wind – not really
• PV? – only if you combine with architectural
solutions, e.g. shadowing
• Geothermal – if the tempreature is high enogugh,
combined with heat pump
• Solar collector? – yes! Even try to use it for air
conditioning
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Shadowing by PV cells at University of
Cantabria, Santander, Spain
Óbuda University
Power System Department
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The process of energy management
Óbuda University
Power System Department
Planned
schedule
Continuous
control
Measurements
Settling
Influences / actions / control
Technology
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Energy magement system
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Óbuda University
Power System Department
„SCADA”
Data acqiosition, visualisation, reporting, statistics
Support for cost planning
Forecast
Portfolio management
Risk management
Control
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Continuous control of the usages
Energy consumption, audits and the intelligent network - Patra, 2012
Óbuda University
Power System Department
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Energy management functions
Óbuda University
Power System Department
• limit investigation
• optimisation
•cost allocation
•settling
Energy consumption, audits and the intelligent network - Patra, 2012
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Building control system
Energy consumption, audits and the intelligent network - Patra, 2012
Óbuda University
Power System Department
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Óbuda University
Power System Department
Intelligent network?
Intelligent customer?
Future trends
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Intelligence in the power system – customer level
Óbuda University
Power System Department
hair
drier,
TV
set,
radio,
telecommunication
devices,
modems, lighting, iron, microwave
oven, coffee machine, computers,
cooking plate
spontaneous loads (based on
individual needs)
washing machine, tumble drier,
refrigerator,
cooler,
air
conditioners, electric bread baking
machine and the heat pump
Can be delayed, controlled
Electric heating devices
Existing ripple control (HKV /
RKV)
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Seeking for low level DSM sources
Óbuda University
Power System Department
Is there DSM potential in the households?
The methodes:
• Monitoring of the household consumption
• Creating an aggregated schedule
• Identification of ripple control part
• Proposal for the better ripple control schedule
• Identification of the controllable part
• Proposal for new schedule
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„Stopwatch measurement” - Flat 1.
Óbuda University
Power System Department
•Forrás: hallgatói projekt mérés Kun Viktor vezetésével
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„Stopwatch measurement” - Flat 2.
Óbuda University
Power System Department
•Forrás: hallgatói projekt mérés Kun Viktor vezetésével
Energy consumption, audits and the intelligent network - Patra, 2012
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„Stopwatch measurement” - Flat 3.
Óbuda University
Power System Department
•Forrás: hallgatói projekt mérés Kun Viktor vezetésével
Energy consumption, audits and the intelligent network - Patra, 2012
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„Stopwatch measurement” - Flat 4.
Óbuda University
Power System Department
•Forrás: hallgatói projekt mérés Kun Viktor vezetésével
Energy consumption, audits and the intelligent network - Patra, 2012
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Analysis of customers’ behaviour
Óbuda University
Power System Department
Some remarks:
• Four flats was checked
• The actual load is replaced by the nominal load
• 5 min time blocks
• Weekday was measured
• Smoothing function was applied
• The load of the 4 flats was extended on 40 flats
• At the reschedule of the ripple control we calculated the
same amount of the consumption
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Further development
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Óbuda University
Power System Department
Measuring at more flats
Detailed ratio analysis
Raising the density of the meaasurements
Identifying day-types
Individual measurements
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40 households, present ripple control
Óbuda University
Power System Department
23:45
22:10
20:35
19:00
17:25
15:50
14:15
12:40
11:05
9:30
7:55
6:20
4:45
3:10
1:35
40000
35000
30000
25000
20000
15000
10000
5000
0
0:00
P (W)
40 db, különböző típusú háztartás
összfogyasztása (kék), illetve ebből a
HKVezérelt fogyasztás (bordó)
óra:perc
Energy consumption, audits and the intelligent network - Patra, 2012
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40 households, rescheduled ripple control
Óbuda University
Power System Department
22:30
21:00
19:30
18:00
16:30
15:00
13:30
12:00
10:30
9:00
7:30
6:00
4:30
3:00
1:30
35000
30000
25000
20000
15000
10000
5000
0
0:00
P(W)
Az összfogysztás alakulása a HKV (bordó) -2 és
+3 órával történő eltolásakor
óra:perc
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40 households, reschedule potential
Óbuda University
Power System Department
23:00
21:05
19:10
17:15
15:20
13:25
11:30
9:35
7:40
5:45
3:50
1:55
40000
35000
30000
25000
20000
15000
10000
5000
0
0:00
P(W)
Az összfogyasztás befolyásolható (bordó) és
nem befolyásolható része (kék) 40 lakásnál
óra:perc
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40 households, after the reschedule of 50 %
Óbuda University
Power System Department
Az összfogyasztás alakulása a kapcsolható rész
50% -nak (bordó) 6 órával való késleltesekor
30000
25000
15000
10000
5000
22:30
21:00
19:30
18:00
16:30
15:00
13:30
12:00
10:30
9:00
7:30
6:00
4:30
3:00
1:30
0
0:00
P(W)
20000
óra:perc
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Foundings
Óbuda University
Power System Department
• The greater parts of the consumers’ appliances can be
involved into the DSM
• This is only qualitative measurements
• The adaptive reschedule can be performed by differenf
optimisation methodes
This is the low level intelligence in the network
Energy consumption, audits and the intelligent network - Patra, 2012
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The need for the DSM
Óbuda University
Power System Department
• Decreasing the peak / increasing the valley load
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Further data sources
Óbuda University
Power System Department
• Measurements from the utility meters
• Special high density metering
• Metering based of social behaviours, statistics, etc.
Energy consumption, audits and the intelligent network - Patra, 2012
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Traditional load curve analysis
Energy consumption, audits and the intelligent network - Patra, 2012
Óbuda University
Power System Department
76
Óbuda University
Power System Department
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Óbuda University
Power System Department
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Remote measurement with special recorder
Óbuda University
Power System Department
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Óbuda University
Power System Department
Peak hours
Deep valley hours
Energy consumption, audits and the intelligent network - Patra, 2012
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Óbuda University
Power System Department
Electric water
heating
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Óbuda University
Power System Department
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Óbuda University
Power System Department
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Reschedule
Óbuda University
Power System Department
hh:mm
23:00
21:05
19:10
17:15
15:20
13:25
11:30
9:35
7:40
The total load after 6 hours delay of the 50% of
controllable load
30000
25000
20000
P(W)
15000
10000
5000
hh:mm
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22:30
21:00
19:30
18:00
16:30
15:00
13:30
12:00
10:30
9:00
7:30
6:00
4:30
3:00
1:30
0
0:00
5:45
3:50
1:55
40000
35000
30000
25000
20000
15000
10000
5000
0
0:00
P(W)
The controllable (brown) and non controllable
part (blue) of residential area load
Functions of the intelligent VGRID elements
Óbuda University
Power System Department
Intelligent loadi
Schedule center
•Monitoring of
generation capabilities
•Load forecast
•Monitoring of load
demand
•Connection with
the schedule centre
•Local load control
•Global load forecast
•Generation optimisation
Intelligent
generatorn
•Cost dependency
Intelligent storagex
•Load control
•Monitoring of
possible generation
capacity
•Logging, evaluation
•Storage/generation
capability
•Cost calculation
•Connection with the
system operator
•Local store control
•Generation control
•Connection with the
schedule centre
•Scheduling
•Connection with
the schedule centre
•Cost calculation
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Radial IP connections of the VGRID elements
Óbuda University
Power System Department
High level control
(TSO)
Intelligent storagex
Intelligent loadg
Schedule center
Intelligent generatoro
Intelligent loadi
Intelligent loadj
Intelligent loadk
Intelligent loadh
Intelligent generatorq
Intelligent storagey
Intelligent generatorm
Intelligent generatorp
Intelligent loadj
Measurement and
86
control unit
Energy consumption, audits and the intelligent network - Patra, 2012
Local power surveillance
Óbuda University
Power System Department
households
generators
loads
Utility
trader
Energy controller
Energy consumption, audits and the intelligent network - Patra, 2012
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Communication possibilities
Óbuda University
Power System Department
• Inside the flat
–
–
–
–
–
–
LAN (ethernet)
WiFi
Bluetooth
EIB (instabus)
ZIGbee
Other field buses (profibus, mobus), stb.
• Between the household and the utility
–
–
–
–
SMS
GPRS
Internet
PLC (Power Line Carrier), etc.
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Conclusion
Óbuda University
Power System Department
The basic rules of the Energy management:
• How can you spare energy?
• How can you use with greater efficiency?
• How can you buy cheaper energy?
The customer behaviour can be adjusted (DR, DSM)
• The local intelligence can find a lot of DSM resources
• The new IT systems makes it possible
• The network contains intelligent solution on different
levels
• The technical solution is possible
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Óbuda University
Power System Department
Thanks for the attention!
Energy consumption, audits and the intelligent network - Patra, 2012
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