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DISTRIBUTION STATE ESTIMATION – Wishes and Practical
Possibilities –
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Goran S. Švenda and Vladimir C. Strezoski
Faculty of Technical Sciences, Novi Sad, Serbia
2013 IEEE PES GM – VANCOUVER
2013 IEEE PES General Meeting Vancouver, BC | July 21-25
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POTENTIONAL TOPICS
Beckground:
SE Theory & DSE Models
Comparison of transmission and
distribution network
EMS and DMS SE
System modeling for the
purpose of DSE (elements,
consumption, IT, …)
Possibility of DSE and
problems of its application
Real-Life DSE Integrated in DMS
Comparison of diferent practical solutions
Experience of application of IDSE
in various distribution utilities
Theoretical vs Practical DSE
Direction of further development of DSE
Industrial DSE
Comparison of diferent vendors
Comparison of diferent clients
… etc.
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CONTENTS
Where are we now ?
Industrial Distribution State Estimation
Where are we going ?
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Where are we now ?
WELL-KNOWN
STATEMENTS
FACTS
QUESTIONS
I Part
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remote control: modest
TRANSMISSION SYSTEMS DISTRIBUTION SYSTEMS
redundancy of real-time telem. data :
> 2.0
redundancy of real-time tel. data:
0.2 ÷ 0.3
MODELS, ALGORYTHMS,
... ≠ MODELS, ALGORYTHMS,
...
role:
connects sources and consumer areas
configuration: radial configuration: mashed
role:
supplies group of consumers
remote control: majority of elements
DIFFERENCES BETWEEN SYSTEMS
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well known, modeled in ’70s.
STATE ESTIM. for EMS and DMS
the idea in ’90s
practically realized 20 years ago
provided estimation of quality for:
network state
wrong measurements
network topology
network parameters
practical realization in progress
EMS SE DMS SE ≠
EMS SE DMS SE
provided estimation for:
measurements
topology ???
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DISTRIBUTION STATE ESTIMATION
PROBLEMS
Mathematical Model !? Implementation in Field !?
MODELS, ALGORITHMS, ... ≠ MODELS, ALGORITHMS, ...
EMS SE DMS SE ≠
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STATE ESTIMATION MODELS
EMS SE adjusted to be applied in DN
Highly specialized SE for DN
SE of both transmission and DN
Based on heuristic rules
Based on probabilistic rules
State vector consists of buses voltages
State vector is represented by polar
and by rectangular coordinates
Measurements of P, Q, I and V
phasors are synchronized and
processed simultaneously
Measurements of V are disregarded
or processed individually … etc.
Approches : Techniques / Procedures :
Weighted least squares (WLS)
Decomposition of WLS problem
into a series of separate WLS
problems
Determination of sensitivity zones
Newton method
LaGrange Relaxation
Neural network
Fuzzy logic
Artificial Intelligence
... etc.
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Theoretical papers, applicable for:
There is a small number of papers:
Small test networks, without meshes, services trs, CB, VR, …
Networks with one voltage level and small number of
different consumer types
Short time intervals …
Rely on unacceptably large number of various data:
P, Q, V, I, …(modules and phasors)
SCADA, GPS, PMU, SMI, …
STATE ESTIMATION MODELS
About SE integrated in DMS, applied in real-life
With results of SE application on a real DN
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REQS FOR PRACTICAL REALIZATION
DSE has to be applied in any distribution utility :
completely, partially covered by SCADA systems
very huge, bi-level, weakly-mashed schemes
(un)balance sistem with (un)symmetric state
Real-Time DSE:
DSE must take into account:
all measurements and statuses
local logic, automation, cascade automated CB, VR, …
motors, DG, IPP, Energy Storage, EV Charging, …
load-to-voltage dependences …
enough fast and robust
reliable 24 / 7 / 365
…
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COMPROMISE
Complex methods proposed in the literature
Characteristics and Possibilities of distribution utilities
C O M P R O M I S E !!!
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I part - FACTS
Standard model of DSE and a procedure for its solution have not
been
determined yet.
Integration into DMS and SG concept are negligible.
Practical verification is negligible.
Why ?
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I part - QUESTIONS
Why has industrial-grade DSE product not been established yet
?
Are the developed models practically applicable?
Are DPU ready for their application ?
What do DPU want, and what is offered to them ?
What is Industrial DSE ???
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Industrial Distribution State Estimation
DSE – BASIC
STRUCTURE
PROBLEMS
IMPLEMENTATION
II Part
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DISTRIBUTION STATE ESTIMATION
Sensitivity zones (defined by measurements locations)
Topology and Incidence matrices
Fictitious measurements (Preestimation)
Eqs of balance of P and Q of zones
Classic Constrained Optimization Problem & Load Flow
Determine the state of DN which is optimally tuned with:
original measurements and topology
DLPs of shunts
ULTCTs operation
values estimated in supply network
resources for active and reactive powers control operation
Based on :
DSE formulation :
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D M S
INDUSTRIAL DSE
DSE
HISTORY
DN
PARAMETERS &
TOPOLOGY MEASURE
DATA
MATHEMATICAL
MODEL A
CT
UA
L
DN
MO
DE
L
PREEST.
STATE LF
PREEST.
LOAD
NTLF / LPT
DN
STRUCTURE
STATUSES LOCAL
LOGIC TRIGGERS
DMS
POWER
APPLICATION
UI
REAL TIME
INIT
IAL
DN
MO
DE
L TA
GIS (Bulder) EMS SCADA SMI/MDM WIS
ICCP WiMax
WEATHER
DATA
DMS
HISTORY
MDM
HISTORY
WIS
HISTORY
EMS
HISTORY
SCADA
HISTORY
CALCULATION
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INDUSTRIAL DSE
D M S
DSE
HISTORY
DN PARAMETERS &
TOPOLOGY MEASURE
DATA
MATHEMAT.
MODEL A
CT
UA
L
DN
MO
DE
L
PREEST.
STATE LF
PREEST.
LOAD
NTLF / LPT
DN
STRUCTURE
STATUSES LOCAL
LOGIC TRIGGERS
DMS
POWER
APPLICATION
UI
REAL TIME
INIT
IAL
DN
MO
DE
L TA
GIS (Bulder) EMS SCADA SMI/MDM WIS
ICCP WiMax
WEATHER
DATA
DMS
HISTORY
MDM
HISTORY
WIS
HISTORY
EMS
HISTORY
SCADA
HISTORY
CALCULATION
- DATA
- MATH. MODEL
- ARHITECTURE
- INTEGRATIONS
- SERVERS
- SERVICES
- ENVIROMENT
- TRIGGERING
- COMINICATIONS
- LOCAL LOGIC
- CLOSED LOOP
- SINHRONIZATION:
DIF. VENDORS
DIF. CONTROL DEVICES
DIF. COMMAND EXECUT.
DIF. DATA COLLECTION
- TIME & MONEY
CONSUMING
- MAINTENANCE
- NEW RESOURCES
- VERIFICATION
PROBLEMS:
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Where are we going … ?
SMART GRID ERA
NEW CHALLENGE FOR DN
…
…
III Part
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WHERE ARE WE (GOING) ?
We are in Smart Grid era :
DG, IPP, SMI, Energy Storage Systems, …
The large-scale deployment of Smart Meters …
From being in an under-determined to over-derermined state
DN is being developed from totally passive to active DN
Where are we going :
Direct Load Control
Full automatization DMS in Closed Loop
DMS self-learning
Model self-correction
Smart City (Smart House, Electic car, … ) …
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INSTEAD OF CONCLUSION
Mathematical model is just one of problems (a smaller one)
DSE needs Investments in distribution (metering
infrastructure)
Realization of IDSE is very expensive and time consuming
process
IDSE cannot be realized on one computer (server)
IDSE cannot be done by one man or small group of engineers (this
work
includes participation of many well organized various
experts)
BUT
What have we learned by imeplementation of SE in the field ?
IDSE can be realized in Real-Life !
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INDUSTRIAL DSE – RESULTS
80
100
120
140
160
180
200
220
240 I [A]
measure. estim. first app.
Distribution SS current on 0.4 kV side
Friday Saturday Sanday
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Distribution SS voltage on 0.4 kV
Friday Saturday Sanday 395
400
405
410
415
420
425
430
435 V [V]
measure. estim. first app.
INDUSTRIAL DSE – RESULTS
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Thank you …
SLIDE 27 2013 IEEE PES GM – VANCOUVER
Goran S. Švenda
[email protected]
