Solutions for Sustainable Development
of the Smartgrids
Prof. Davor Škrlec, IEEE Member
University of Zagreb
Faculty of Electrical Engineering and Computing
IEEE Greece Section & NTUA, Dec 13 2012
FER Map
Skyscraper
Main
entrance
43308 m2
FER in numbers
Undergraduate students
~ 4300
Postgraduate students
~ 450
Freshmen each year
~ 650
Graduating students each year
~ 550
Graduated since 1956 (Dipl.Ing.) ~ 16000
Graduated since 1956 (M.Sc.)
~ 2100
Graduated since 1956 (Ph.D.)
~ 630
Bachelors Degree
• Duration: 3 years, 180 ECTS
• Bachelor level (3 years)
 Electrical engineering and information technology
 Computing
Masters degree
• Duration: 2 years, 120 ECTS
• Electrical engineering and information technology
•
•
•
•
•
Control engineering
Electrical power engineering
Electronic and computer engineering
Electronics
Electrical engineering systems and technology
• Information and communication technology
• Information processing
• Telecommunications and informatics
• Wireless technologies
More info …
• Progress Report and more information
available on:
http://www.fer.unizg.hr/en
Sustainable development of the Smartgrids
My interest is in the future because I am
going to spend the rest of my life there.
Charles F. Kettering (1876 - 1958)
(engineer, scientist, inventor)
What we need ?
 EU technology platform - general policy (SGGA;SET Plan)
 industry initiative (EEI;EEGI;EURELETRIC)
 network operators (EEGI;ENTSO-E;EDSO4SG)
 demonstration projects (FP7;Smartgrids ERANet)
 technical solutions
 costs/benefits
 business models
 standards and regulation (ACER;CENELEC;IEC)
 customers
 market
Solution No. 1
Distribution Network Optimization-CADDiN
CIRED 2011 poster session – paper 1252 – session 5
CADDiN


Computer Aided Design of Distribution Network
Data preparation in CADDiN Map Module


AutoCAD MAP Add-on
Connection cost assignment
o
o
o
o

Optimization




Existing cable
Ex-line route
Corridor
Custom cost
Evolutionary algorithm
Adjusted VRP algorithm
Various output topologies
Results

Visualization and simple analysis
in CADDiN Map Module
Feeder
Support point
Consumption
station
Cable
Backup cable
Distribution Network Optimization-CADDiN
(results in Google Earth)
OGULIN SUPPLY AREA


Consumption concentrated in urban area
Two big radial areas – low consumption

Approximated with single consumption
point
Connection cost

Existing cable (Blue on picture)

Ex-line route


Existing overhead lines (Red on picture)
Corridors determined by Urban Planning
(Orange on picture)

Corridors


All roads
User defined (by experience)
Solution layout – Closed loop (ring)
Solution No. 2
Input data - BAU
13
Input data - BAU (2)
Result of data integration - BAU
• several months later...
Summary of BAU
• building the network for calculation
– long term job (months)
– data quality/accuracy
• distributed and non-uniform data update
• local organizational units have more accurate data
– all resources-consuming job of checking network
topology and data after initial network building
• waste of time (money)
– after some time network model is uncompatible
with real network
Network data in GIS
 network data in GIS
– updated and accurate
– spatial character
– network model for calculations in minutes not in
months
 DeGIS (customize application in SmallWorld)
Network data in DeGIS
Transfer of data to NEPLAN
• Transfer from DeGIS
– all objects “after and on the same voltage level” of
selected object
– all object “after” selected object
• possibility to stop tracing on switching elements
depending on switch status
• transfer of simplified geometry
– start/end point of line
– full data model is not necessary for calculation purposes
Network data in NEPLAN
Network data in NEPLAN (2)
Network data in DeGIS
Network data in DeGIS (2)
Representation in NEPLAN
Network data in DeGIS(3)
Representation in NEPLAN
Representation in NEPLAN
NEPLAN to DeGIS
• network data and calculations results - simple
return to DeGIS
– IT WORKS !
Further improvements
• calculations within DeGIS
+ NEPLAN as external application
+ unnecessary export/import of data
+ instantenously visible calculations results
+ user-friendly application
+ and more ...
Solution No. 3
Power Quality Monitoring in
Distribution Network
 21 distribution regions
 100 supply points 110 kV
 300 TS 35/10 kV
 20 000 TS 10/0,4 kV
 2 300 000 customers
 most of 110 kV supply points are equipped with power quality analyzing units, but
only some of them are connected to the related control centre
 since every region develops according its own policy, there was no unified approach
what kind of measuring, control or protection equipment is used in distribution TS
 most of TS are equipped with PLCs, DMM, numeric relays or bay controllers with
communication ability, but none of them is yet used for PQ data acquisition
Optimization of Existing Resources
SCHEDULED TASKS:
 detailed analysis of the entire monitoring equipment installed in
distribution networks in Croatia
 defining monitoring and measurement capabilities of the installed
equipment
 determining communication links to distribution centers
 defining common warehouse for PQ monitoring data
 defining final solution
PQ Data Sources
SCADA systems
 data are collected in control centre from
remote station computers using WAN
 PQ data are preprocessed and exported in
appropriate file format
IED - Intelligent Electronic Devices




numeric relays
bay controllers,
DMM - digital multimeters
power analyzers
 data are collected in local PQ-IPC using
local process bus (MODBUS)
 PQ data are preprocessed and exported in
appropriate file format
PQ Data Sources cont.
AMR systems
 data are collected in control center using PSTN,
GSM/GPRS or Ethernet network
 PQ data are preprocessed and exported in
appropriate file format
 meters of new generation can acquire PQ relevant
data, but this feature is useful only if high-speed
communication is available (WAN)
PQ MONITORS
«. »
 new generation of IED specially provided for PQ data
acquisition ^ local data processing
 processed data can be directly transferred to the
related control centre
PQ Data Acqusition Concept
(TS 35/20/10 kV)
Control centre
PLC, PAC
numeric relay, bay controller
AMR
DMM, network analyzer PQ-MONITOR numeric revenue meter
Low voltage network/Households
TS 10/0,4 kV
PQ monitoring device
 simple and inexpensive device capable to measure all the
required PQ parameters
PQube - power monitor
Power Quality monitoring:
Voltage dips, swells, and interruptions Waveforms and RMS
graphs Over-frequency and under-frequency events 1microsecond high-frequency impulse detection THD, TDD, and
time-triggered snapshots Voltage and current unbalance. RMS
Flicker - Pinst, PST, PLT
Detailed event recording, plus daily, weekly, monthly trend
Energy monitoring:
Watts, VA, VAR's, true Power Factor, Watt-hours, VA-hour
Peaks: single-cycle peak, 1-minute, and 15-minute averac Daily,
weekly, monthly trends. Load duration curves
No software required:
Spreadsheets: CSV files; events, trends, statistics. Pictures:
Event and trend/statistics graphs in GIF format PQDIF: the
IEEE's standard for power quality data files. Text, XML, and
HTML summaries
Easy data retrieval:
Ethernet:
Built-in web server - retrieve meters, files, graphs FTP
server for easy file transfer Modbus-TCP
Thank you for your attention
Contact:
Email: davor.skrlec@fer.hr
HTTP: www.fer.unizg.hr/davor.skrlec
Skype: davor318456