advancements in distributed power flow control · load! line overload ∆p ref ∆p ref p meas p...

Prof. Dr.-Ing. Christian Rehtanz | Champéry, 08.02.2019

Advancements in Distributed Power

Flow Control

2nd FEPSET Champéry 2019


Agenda

• Chapter 1 – ENSURE

• Overview & Concept

• Test system and scenario setup

• Exemplary simulation results

• Violation of network restrictions

• Chapter 2 – IDEAL

• Motivation

• Agent based power flow control

• Laboratory setup



CROSS VOLTAGE LEVEL POWER FLOW

CONTROL

Chapter 1 | ENSURE



Control

Center

Transmission

Grid (TG)

Sub-

Transmission

Grid (STG)

Distribution

Grid (DG)

Sub-Transmission Grid

Control System (STG-CS)

Flexible

Load

! Line Overload

∆Pref

∆Pref

Pmeas

Pmeas

PP

P

P

P

P

∆Pref

∆Pref

!

50 Hz

f

Pref

Pref

Psched

∆Pref

Psched

∆Pref

Psched

•Shut-down of the conventional power plants

• Increase of volatile and distributed generation

Pmeas

•New strategies for system control are necessary

•Possible approach: Control power flowsbetween several voltage levels

•The STG-CS uses DERs connected to the STG and subordinated DG-CSs as actuators

•The DG-CSs uses DERs connected to the DG as actuators

Distribution Grid

Control System (DG-CS)

Conventional

Power Plant

Measurement

Setpoints (transfer rate in

the range of seconds)

Schedules (transfer

rate e.g 15 min)

Frequency

Deviation

Distributed Energy

Resources (DERs)

ENSURE | Overview & Concept



ENSURE | Test system and scenario setup

PL

• Dynamic simulations in Matlab-

Simulink to proof concept

• The System is in initial state at

t=0s

• In DG2 the load increases by

10 MW at t=1s

• Case I: DG2 is able to compensate

the change of load independently

• Case II: In DG2 is not enough

flexibility available to compensate the

loadstep independently

Feeder 1 of the CIGRE MV benchmark network

HV-CSSTG-CS

DG-CS

1

DG-CS

3

DG-CS

2

PFlex DG1

PFlex STG

PFlex DG2 + Loadstep

PFlex DG3

13 MW 13 MW

13 MW

10 MW

4 MW 4 MW

4 MW

7 MW



ENSURE | Exemplary simulation results – Case I

PL



ENSURE | Exemplary simulation results – Case II

PL



STG-CS

ENSURE | Violation of network restrictions

• The CS is blocked when

network restrictions are violated.

• The CS restarts operation when

problems are solved.

• How could congestions in future

electrical power supply system

be solved?

!Line Overload

DG-CS

1

DG-CS

3

DG-CS

2



Chapter 2 | IDEALAGENT BASED CURATIVE CONGESTION

MANAGEMENT



IDEAL | Motivation

• Curative congestion management:

• Operating lines closer to their capacity limit

• Enabling higher utilization of available transmission capacity

• Use of distributed power flow controllers and flexible infeed from active distribution networks

• Agent based approach:

• Distributed control algorithm

• Autonomous determination of countermeasures

• Support of control center staff

• Validation in laboratory setup:

• Testing interconnection between control center, communication system and power flow controller

• Implementation using commercially available products and industry standards



Qflex

PflexQflex

Pflex

Control

Center

Control

Center

Sub-

Transmission

Grid (STG)

Distribution

Grid (DG)

G

G

Distributed Power

Flow Controller

Smart Telecontrol

Unit in STGState Inform

Message

State Inform Message &

Negotiation of Actions

Measurements

& Setpoints

Information Flow & Decision MakingHardware Components

Flexible

Load

G Flexible

Generator

Agent

DPFC

Setpoint

G

G

!

!Line

Overload

Smart Telecontrol

Unit in DG



IDEAL | MAS information flow

State Inform Message:

- Contains:

- line loading,

- Impedance

- connected nodes

• Information is exchanged

periodically between

agents

• Distribution limited to

relevant agents

Current system state is

known for relevant area to

all agents

Qflex

PflexQflex

Pflex

G

G

Information

exchange

Monitoring and

Decision Making

Decision and

Control Action



IDEAL | MAS decision making

Qflex

PflexQflex

Pflex

G

G

Information

exchange

Monitoring and

Decision Making

Decision and

Control Action

!

!

Detection of line overload

Call for proposalResponsible Agent calls foravailable flexibility:- Flexibility of underlying grids- Available PFC flexibility



IDEAL | MAS decision making

Qflex

PflexQflex

Pflex

G

G

Information

exchange

Monitoring and

Decision Making

Decision and

Control Action

!

!

Line overload present

Choosing flexibility accordingly:- PFC flexibility before flexible

loads and generation- Highest sensitivity on

overloaded line first- No additional overloads are

created- DC sensitivities calculated

using information from State Inform Messages2nd FEPSET Champéry 2019


IDEAL | MAS executing control actionOption 1: Propose control action to control center (semi-autonomous)

Qflex

PflexQflex

Pflex

G

G

Information

exchange

Monitoring and

Decision Making

Decision and

Control Action

- Send proposal to controlcenter

- Assessment of proposal bycontrol center staff

- Activation of flexibility bycontrol center



IDEAL | MAS executing control actionOption 2: Autonomous execution of control actions

Qflex

PflexQflex

Pflex

G

G

Information

exchange

Monitoring and

Decision Making

Decision and

Control Action

- Activation of control actionby agent

- Send information ofperformed control action to control center



IDEAL | Simulation setup: New England Test System

• Power Flow Controller installed

on line TL0415

• Active Distribution Network at

Node 5 and 15

• Line outage on TL0506 causes

overload on TL 0414

• Overload resolved by

countermeasures determined

by MAS

• Use of power flow controllers

and flexibilty from active

distribution networks

25

2

1

39

9

8

7

6

5

4

3

18

26

29

28

L05

L08

L07

L39

11

10

13

12

14

15 19

20

16

17

2427

2322

21

G

G08

G

G10

G

G01

G

G02

L03

L04

L25

L18

L26

G

G09

L29

L28

G

G03

L15

L20 G

G05

G

G04

G

G06

L21

L23 G

G07

L16

L12

L27

TL0414PFC

ADNADN

Qflex

Pflex

Qflex

Pflex



IDEAL | Exemplary Simulation resultsOutage of line TL0506 at t=5s

0

20

40

60

80

100

120

140

0 5 10 15 20

Lo

ad

ing

(%)

Time (s)

Loading of line TL0414

-120

-100

-80

-60

-40

-20

0

20

0 5 10 15 20

ΔP

(M

W)

Time (s)

ADN Flexibility

0

20

40

60

80

100

0 5 10 15 20

Lo

ad

ing

(%)

Time (s)

Loading of line TL0405

-100

-80

-60

-40

-20

0

20

0 5 10 15 20S

et

Po

int(

-)

Time (s)

Power Flow Controller

No Control MAS



IDEAL | Laboratory Setup: Real-time simulation and Power

hardware-in-the-loop

19

Real-time digital simulator OPAL RT

eMegasim simulation software

IEC 104 measurement transmission

Analog signal output

Power amplifiers

200 kVA

AC, DC operation

Voltage & Current mode

Internal measurement system (4 µs minimum delay)

Real-time Simulator 200 kVA Power Amplifiers

Busbar Cabinet SFP Communication SYSLaboratory2nd FEPSET Champéry 2019


IDEAL | Laboratory Testbed

Control CenterPSI Control

Real-Time Simulator

Power Amplifier

Impedance ControllersSmart Wires Powerline Guardian

Control actions and measurements

Grid Model and MAS

PSI STUs (Agents)

Control actions and measurements

Simulated Elements

Hardware Elements

IEC 60870-5-104 Communication

Non-Standardized Communication Protocol

Conntroller Set Points



Conclusion and Outlook

Accomplishments:

• Distributed generation can be controlled to follow scheduled power flows at

interconnection points

• Multiagent Sytems can be implemented to use power flow controllers and flexible load and

generation for corrective congestion management

Next steps:

• Integration of agent based congestion management and control of distributed generation

Increased autonomous grid operation relieves grid operators and enables high shares of

renewable energies

• Consider real world and market conditions!


advancements in distributed power flow control · load! line overload ∆p ref ∆p ref p meas p...

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