1
Highlights Achievements Control architecture The control centre (master agent) placed in the primary substation Groß Reken gains measurements from all slave agents. Also it is able to send switching commands to switching agents. The master agent features different functionalities which enable supervision, control and decision making: Control and decision module Forecast module Execution module Topology optimization module Post-fault operation module (FDIR) Data storage/SCADA Interface Slave agents are responsible for Measurements Switching Local state evaluation Local forecasting Demonstration of advanced MV-network operation using multi agent system Most of the functionalities are already implemented and being tested The working communication chain is established: - network model - slave agent - master agent Agents are implemented on automation devices RTU560 (r emote t erminal u nit) Ongoing laboratory implementation and testing of the system Hardware-in-the-loop simulation with real automation devices from ABB Quasi real time network representation on a PC system hardware layer Smart Grid applications in PLC* programming language software layer network model MATLAB/Simulink measurements control signals * programmable logic controller control centre State Machine Principle Depending on the measurements and defined voltage/current limits different system states are defined: For every operative state action schemes are developed measured voltage time endangered level 2 endangered level 1 secure switching sequence References [1] Shapovalov A., Spieker C., Rehtanz Ch.: “Network Reduction Algorithm for Smart Grid Applications”, 23rd AUPEC, 2013 Hobart, Australia [2] Taylor, J. W.: “Short-Term Electricity Demand Forecasting Using Double Seasonal Exponential Smoothing”, The Journal of the Operational Research Society, Vol. 54, No. 8 (Aug., 2003), pp. 799-805 [5] Goswami S. K.: “Distribution system planning using branch exchange technique”, IEEE Trans. on PWRS, V01.12, Na.2.718 -723, May 1997 Demo 1

switchingsequence - grid4eu.blob.core.windows.netgrid4eu.blob.core.windows.net/media-prod/14207/... · automation devices –RTU560 (remote terminal unit) Ongoing laboratory implementation

Embed Size (px)

Citation preview

Page 1: switchingsequence - grid4eu.blob.core.windows.netgrid4eu.blob.core.windows.net/media-prod/14207/... · automation devices –RTU560 (remote terminal unit) Ongoing laboratory implementation

Highlights

Achievements

Control architecture

The control centre (master agent) placed in the primary

substation Groß Reken gains measurements from all slave

agents. Also it is able to send switching commands to

switching agents.

The master agent features different functionalities which

enable supervision, control and decision making:

• Control and decision module

• Forecast module

• Execution module

• Topology optimization module

• Post-fault operation module (FDIR)

• Data storage/SCADA Interface

Slave agents are responsible for

• Measurements

• Switching

• Local state evaluation

• Local forecasting

Demonstration of advanced

MV-network operation

using multi agent system

Most of the functionalities are already implemented and

being tested

The working communication

chain is established:

- network model

- slave agent

- master agent

Agents are implemented on

automation devices – RTU560

(remote terminal unit)

Ongoing laboratory implementation and testing of the system

• Hardware-in-the-loop simulation with real automation

devices from ABB

• Quasi real time network representation on a PC system

hardware layer

Smart Grid applications

in PLC* programming language

software layer

network model

MATLAB/Simulink

measurements

control

signals

* programmable logic controller

control

centre

State Machine Principle

Depending on the measurements and defined voltage/current

limits different system states are defined:

For every operative state action schemes are developed

measured voltage

time

endangered level 2

endangered level 1

secure

switching sequence

References[1] Shapovalov A., Spieker C., Rehtanz Ch.: “Network Reduction Algorithm for

Smart Grid Applications”, 23rd AUPEC, 2013 Hobart, Australia

[2] Taylor, J. W.: “Short-Term Electricity Demand Forecasting Using Double

Seasonal Exponential Smoothing”, The Journal of the Operational Research

Society, Vol. 54, No. 8 (Aug., 2003), pp. 799-805

[5] Goswami S. K.: “Distribution system planning using branch exchange

technique”, IEEE Trans. on PWRS, V01.12, Na.2.718 -723, May 1997

Demo 1