1 distribution automation and functionalities for active network … · 2017-04-10 · ideal grid...

ideal grid for all

Distribution automation and functionalities for active network management

Smart Energy Workshop 2015

Konstanz, Germany

Dr. Tech. Anna Kulmala

Tampere University of Technology, Finland

1

ideal grid for all

Content

• IDE4L project overview

• Decentralized automation architecture

• Congestion management

10/04/2017 WWW.IDE4L.EUSLIDE 2

ideal grid for all

Introduction

• Motivation• RES and energy efficiency actions increase the

complexity of network planning and operation

• Existing and new networks and resources should be utilized more efficiently

• Continuity of the electricity supply is important for the modern society and must be guaranteed

• Scope• Planning of active network

• Distribution automation in MV and LV networks

• Active network management utilizing DERs

• Interactions of DSO/TSO and DSO/market actors


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From concept to demonstrations


1. Defining the concepts• Active network (D2.1)

• Automation for active network management (D3.1)

• Aggregator system (D6.1)

2. Developing planning methods and automation functionality

3. Building and running the demonstrations in:• Denmark (Østkraft Holding A/S)

• Italy (A2A Reti Electtriche SpA)

• Spain (Unión Fenosa Distribución, S.A.)

ideal grid for all

Main objectives

• Develop an advanced distribution network automation system enabling utilization of flexibility services of DERs and their aggregators

• Develop advanced functions for monitoring and control of the whole network

• Demonstrate the automation system and selected use cases for active distribution network

• Develop planning tools to design active distribution network and to evaluate costs and benefits of developed concept and technical solutions


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Breakthroughs of IDE4L project

WP2Planning tools for distribution

network management

ANM concept

Target and expansion

planning including ANM

Operational planning including DER uncertainty

WP3 Distribution

network automation architecture

Automation concept

Smart meter as a sensor

Testing Platform for monitoring & control systems

Hierarchical and decentralized automation

WP4 Fault location, isolation and

supply restoration

Decentralized FLISR

IEC 61850 Distribution

Protection System Reconfiguration

Microgridinterconnection

switch

WP5Congestion

management

Decentralized state estimation and state forecast

Tertiary control –Network

reconfiguration

Secondary control – Coordination of voltage controllers

Dynamic tariff

WP6Distribution

networks dynamics

Aggregator concept

Optimal scheduling of flexibility

Transmitting synchro-phasors &

real-time model syntheses

Improved microgridoperation

WP7 Demonstrations


ideal grid for all

Content





ideal grid for all

Decentralized automation

Control center

DMSMonitoring

Control

PSAU

Operator Operator

SSAU

Monitoring

Control

Monitoring

Control

Grid Level

MV level

LV level

PSAU PSAU

SSAU SSAU

1. Cooperation with commercial

aggregator and Electrical market

2. Decision of Grid tariff

3. Collection and harmonization of

measurements at grid level

4. Coordination of PSAUs

5. Coordination of secondary controllers

1. Coordination of FLISR

2. Control of PS IEDs (OLTC,

capacitors)

3. Collection and harmonization

of measurements at MV level

4. Coordination of SSAUs

5. Secondary power control

1. Control of SS IEDs (OLTC,

capacitors, DGs)

2. Collection and harmonization

of measurements at LV level

(smart meters)

3. Secondary power control


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Real-time monitoring and state estimation

• LV grid• EV, PV, HP and demand-response

schemes mainly affect the LV grid

• Monitor the LV grid

• Data management• Data coming from heterogeneous

system

• Incomplete: Some nodes are not monitored; Broken/unreachable device

• Uncertain: Low synchronization accuracy; Measure corrupted

MV & LV State Estimation

• Network Description Update


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Outcomes of IDE4L architecture

1. Integration and participation of DERs in the automation system

2. Extension of monitoring and control functions to the distribution network• Distribution of such functions on several levels

• Hierarchy, modularity, scalability

3. Wide applicability in European context


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Content





ideal grid for all 10/04/2017 WWW.IDE4L.EUSLIDE 12

Congestion management

+ HP

+ EVHV/MV MV/LV

MV feeder LV feeder

Voltage

1 pu

Permissible

voltage

variation

Allowable

range of

substation

voltage

Minimum load, substation voltage at its highest value

Maximum load, substation voltage at its lowest value

Transformer

tapping boost

Transformer

voltage drop

LV feeder

voltage drop

MV feeder

voltage drop

Voltage drop margin

Voltage rise

margin

• Mitigate voltage rise and prevent overloading of feeders and transformers

• Optimize network state

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Control hierarchy of congestion management• Secondary control

• Mitigates congestions and optimizes the network state

• Operates through changing the set points of primary controllers

• No connection to the market place. Only direct control - predefined contracts, grid code requirements and DSO’s resources

• Real time control based on present state estimation results

• Located at primary and secondary substations

• Tertiary control• Network reconfiguration based on forecasts

• Flexibility services from Commercial Aggregator

• No direct control of DER. DER activated through the market place

• Control decisions based on state forecasts for a longer time interval

• Located at the control center


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ideal grid for all

Set points

Structure of secondary controlReal time control

• Medium voltage power control algorithm (PSAU.PC) optimizes the MV network operation and low voltage power control algorithm (SSAU.PC) the LV network operation

• Block OLTC’s of Transformers (PSAU.BOT) generates block signals for PCs and transformer OLTCs to prevent hunting phenomena

Offline control

• Cost parameters of the real time functions are determined by an offline control algorithm


PSAU.BOT PSAU.PC

MV.IED

Set points

SSAU.PC

LV.IED

Block signal

Block

signal

MV.IED

LV.IED

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Real time secondary control• Objective function

f(x,ud,uc) = ClossesPlosses + (Ccur Pcur) + (CDRPDR) + Ctap ntap + (CVdiff |Vi,r-Vi|)

• Inequality constraints

Vlower ≤ Vi ≤ Vupper Feeder voltage limits

Iij ≤ Iijmax Branch current limits

Pactiveimin ≤ Pactivei ≤ Pactiveimax Limits for active power of controllable resources

Qactiveimin ≤ Qactivei ≤ Qactiveimax Limits for reactive power of controllable resources

mmin ≤ m ≤ mmax Limits for transformer tap ratio

• Load flow equations are nonlinear equality constraints

• Sequential quadratic programming (SQP) algorithm is used


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Secondary control increases hosting capacity remarkably

3 MW wind turbine in weak 20 kV network

Distance to primary substation 22 km

Results based on stochastic MV network analysis


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Example simulation

Feeder 2Feeder 1

G

G

G

Substation (Ss)

Gen 1Gen 2

Gen 3

1

23

4

5

6

78

9

10 11

12

13

14

15

1617

18

19

20

2122

23

24 2526

27

28

29

30 31

32

33

34

35

36

37

38 39

4041

42

434445

Time

[s]

Pset1

[pu]

Pset2

[pu]

Pset3

[pu]

0 0.1 0.1 0.1

20 1.0 0.1 0.1

50 1.0 1.0 0.1

80 1.0 1.0 1.0

130 0.1 1.0 1.0

160 0.1 0.1 1.0

190 0.1 0.1 0.1

Simulation sequence


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0 20 40 60 80 100 120 140 160 180 200 220 2401

1.02

1.04

1.06

1.08

1.1

1.12

1.14

1.16

[pu

]

t [s]

Feeder 1

Substation

and feeder 2

Node voltages without secondary control

Unacceptable!


ideal grid for all

0 20 40 60 80 100 120 140 160 180 200 220 240

0.95

1

1.05

1.1

[pu]

Vmax

Vmin

0 20 40 60 80 100 120 140 160 180 200 220 2400.95

1

1.05

[pu]

Vss Vref

0 20 40 60 80 100 120 140 160 180 200 220 240

-0.4

-0.2

0

[MV

Ar]

Qref1

Qref2

Qref3

0 20 40 60 80 100 120 140 160 180 200 220 240

-0.4

-0.2

0

0.2

t [s]

[MW

]

Pcvc1 Pcvc2 Pcvc3

Secondary control in operation Feeder voltage

limits

AVC relay

deadband


ideal grid for all

THANK YOU

FURTHER INFORMATION: WWW.IDE4L.EU


1 distribution automation and functionalities for active network … · 2017-04-10 · ideal grid...

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