UMBRELLA Deliverable D 7.3 “Workshop results on innovative operational tools”

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SEVENTH FRAMEWORK PROGRAMME

THEME [ENERGY.2011.7.3-1]

[Innovative tools for the future coordinated and stable

operation of the pan-European electricity transmission

system]

Project Deliverable

Deliverable D 7.3 “Workshop results on innovative

operational tools”

Project acronym:

UMBRELLA

Project full title:

Toolbox for Common Forecasting, Risk

assessment, and Operational Optimisation

in Grid Security Cooperations of

Transmission System Operators (TSOs)

Grant

agreement

no.:

282775-2

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1 Joint Cooperation between iTesla and UMBRELLA

A description of the joint-collaboration between iTesla and UMBRELLA can be found in deliverable D7.2, which can be downloaded from the website www.e-UMBRELLA .eu. The two projects aligned their starting date and duration to facilitate collaboration. A memorandum of understanding was established and agreed before signing the present Grant Agreements in order to outline the framework of the future detailed work foreseen by the consortiums.

As mentioned in D7.2, the cooperation of the two projects includes the following cornerstones:

 Three common workshops will be organized by iTesla and UMBRELLA :

o Workshop on innovative tools needed for the future and stable system operation (M6) to exchange information about respective project objectives, dissemination, key drivers, results of previous studies (knowledge sharing and information exchange)

o Workshop on intermediate results (M25) (exchange and present information about intermediate results and deliverables)

o Workshop on final results (M46) (exchange and present information about final results).

 A common-use case on which both approaches will be validated.

 A detailed description of necessary information exchange and knowledge sharing was elaborated in deliverable D1.1.“iTesla Cooperation”.

 A common deliverable dealing with common recommendations to ENTSO-E regarding operating rules (for iTesla, Deliverable D8.4 – for UMBRELLA D6.2 - Delivery date M46) will be elaborated.

In the present deliverable, the results of the second common ‘Workshop on intermediate results’, co-organized by UMBRELLA and iTesla projects are summarized. The workshop was hosted at ENTSO-E’s premises on January 14th, 2014 with a total number of some 80 registered participants including experts from industry, academia and regulatory bodies.

This deliverable is structured in the following way: Chapter 1 introduces the framework for joint-collaboration, Chapter 2 presents the organization and structure of common workshop, Chapter 3 presents a summary of the workshop presentations and in Chapter 4 the presentation slides from the UMBRELLA Project are displayed.

All presentations and related documents are available for download at www.e-UMBRELLA.eu , as approved by all presenters.

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2 Organization and structure of common workshop

The common workshop, co-organized by the UMBRELLA and iTesla projects, was held at ENTSO-E’s premises in Brussels on January 14th, 2014. Most of the stakeholders were invited by email. Moreover, the UMBRELLA consortium published a newsletter during the middle of December. This newsletter contained information about the workshop and about the way to subscribe. In this occasion, the subscription and logistic organization of this event was carried out mainly by iTesla.

The agenda of the workshop consisted of the following parts:

10:00 Workshop opening

Welcome speech Dr. Chavdar Ivanov – ENTSO-E

10:15 iTesla Toolbox

 Overview on and state of the iTesla project

 General architecture of the security assessment process

 Definition of security rules taking into account uncertainties and system dynamics

Coffee break (15 minutes)

 Demo of prototype modules

 Validation of dynamic models and use of Modelica models

 Defense plan and restoration

Christian Lemaître Jean-Baptiste Heyberger, Diego Cirio Ioannis Konstantelos, Philippe Duchesne Geoffroy Jamgotchian, Massimo Ferraro Luigi Vanfretti Poul Sørensen, Regina Llopis Rivas

13:00 Lunch

14:00 Umbrella Toolbox

 Overview on and state of the Umbrella project

 Modeling uncertainties relevant for the operation of the European transmission grid

 Optimization algorithms for transmission system operation

Coffee break (15 minutes)

 Risk-based Security Assessment incorporating Forecast Uncertainty and Cascading Events

 Toolbox Requirements based on TSO Demands and Testing Environment

Dr. Wulf A. Engl, Helmut Paeschke,

Dr.ir. Laura Ramírez-Elizondo Raik Becker,

Prof. Christoph Weber Jonas Eickmann, Tobias van Leeuwen

Thilo Krause, Frauke Oldewurtel, Line Roald

Peter Gilsdorf, Dr. Simon Krahl, Michael Rogge, Oliver Scheufeld

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The opening was carried out by Dr. Chavdar Ivanov, Research and Development Senior Advisor of ENTSO-E. He introduced the ENTSO-E R&D Roadmap and the R&D Implementation Plan. Furthermore, he referred to the importance of the work and deliverables of both the iTesla and the UMBRELLA projects.

The morning session was focused on the iTesla toolbox. Several researchers of the project gave detailed presentations of their progress. In Chapter 3, a summary of these presentations is provided. On the other hand, the afternoon session was dedicated to the Umbrella toolbox. The respective researchers provided comprehensive presentations about the progress of the different work packages. In both cases, the sessions started with an overview of the respective project. This allowed the stakeholders and new participants to obtain a general idea about the main research focus and the main goals.

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3 Summary of the workshop presentations

3.1 Morning Session: iTesla

3.1.1 Overview

The main objective of the iTesla project is to develop a toolbox that will be needed by

Transmission System Operators to operate the European power system in the years to come. Particularly the iTesla toolbox will provide operators with tools to assess the security

of power system situations from 2 days ahead to real time. As part of the project, validation of the toolbox with different European grids in various situations will be performed.

The three main challenges to be tackled in the project are the following:

 To model the increasing amount of uncertainties in the decision process  To take into account system dynamics in the security assessment  To model preventive actions and take them in the decision process 3.1.2 General Architecture of the Security Assessment Process

In this presentation the proposed architecture to target uncertainties, dynamics and action recommendation was explained. First, the existing architecture was shown and later this architecture was upgraded with dynamic simulations, the inclusion of uncertainties and with the addition of a filtering process. The proposed final architecture is presented in Figure 3:

Figure 3 Proposed Final Architecture

New online security assessment

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3.1.3 Definition of Security Rules Taking into Account Uncertainties and System Dynamics

This presentation started by introducing the offline security rules. Later, the sampling process to be used within the iTesla architecture was explained. It was indicated that uncertainties expand the possible operating point state‐space.

The presentation gave particular attention to historical data. The presenters argued that historical data contain information on what the TSO should anticipate in the near future. In their approach, all resulting operating points are analysed using dynamic simulation tools. Furthermore, steady‐state and dynamic indices have been developed to classify pre‐fault state‐space with respect to post‐fault performance.

Finally, it was stated that machine learning enables to ‘compress’ information of 100,000s dynamic simulations into robust security rules.

3.1.4 Demo of Prototype Modules

In this presentation the data manager, the computation manager and the workflow manager were explained by means of diagrams. For example, the diagram of the workflow manager is depicted in Figure 4:

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3.1.5 Validation of Dynamic Models and Use of Modelica Models

This presentation contained information about how to make and use models of the Modelica software and about how to perform model validation. Different validation levels were identified: component level, cluster level and system level. One of the representative slides corresponds to a diagram containing the offline validation of dynamic models. This diagram is depicted in Figure 5:

Figure 5 Offline Validation of Dynamic Models

3.1.6 Defense Plan and Restoration

This presentation focused on the development of a workplan for defense and restoration. With regard to the defense plan, the speakers referred to the following aspects:

 Detection of weak points in existing plans  Use of renewable generation plants  Pan‐European coordination

 Use of PMUs

 Use of distributed energy resources

With respect to restoration, the aspects that were considered are:

 Coordinated restoration (AIA)

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3.2 Afternoon Session: UMBRELLA

3.2.1 Overview

The main objective of the UMBRELLA project is to develop an innovative toolbox to support the decentralised grid security approach of TSOs. This toolbox shall include:

 the simulation of uncertainties due to market activities and renewables on different time scales

 the optimisation of corrective actions in reaction to simulated risks on different time scales according to total costs and transmission capacities

 the development of risk based assessment concepts for anticipated system states with and without corrective actions.

Moreover, the projects aims at demonstrating the enhancement of existing and running procedures by utilisation of the developed toolbox and providing a scientifically sound basis to support common TSO decisions.

3.2.2 Modelling uncertainties relevant for the operation of the European transmission grid

This presentation focused on the second work package of the UMBRELLA project. This work package aims at developing a set of methods to describe the key developments influencing the future state of the European electricity grid. This is done through the accomplishment of five tasks, as depicted below. Each of the tasks was described during the presentation.

Figure 5 Separation and Re-aggregation of Uncertainties

At the end of the presentation, the following next steps were presented:

 Finalizing solar power uncertainty for D and CZ

 Finalizing wind power uncertainty for D, PL, NL and AT  Finalizing power plant outages for all participants  Finalizing load uncertainty for all participants  Make test interface for following tasks  Aggregating all uncertainties

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3.2.3 Optimization algorithms for transmission system operation

This presentation focused on Work Package 3. The objective of this work package is to develop an expert system that is capable of assisting the transmission system operators during the congestion management process. The presentation started by introducing the main challenges, followed by the preliminary results and the outlook. Figure 6 shows an overview of the optimization methods:

The main conclusions are enumerated below:

 The developed algorithms promise to be capable of providing valuable input to system operators by suggesting appropriate and secure remedial measures  All required optimization steps can be carried out in day ahead time horizon and

even assist the operators in real-time

 Further work will enable the consideration of uncertainties in the operational planning processes

Figure 6 Overview of the optimization mehtods

o Step 1: Optimization algorithms supporting operational planning process o Step 2: Short term optimization methods for realtime grid operation o Step 3: Optimized uncertainty accounting in operational planning

Results Input data

Grid topology Uncertainty

Dispatch incl. RES

Congestions Available remedial measures Optimal combination of remedial measures

State of the art Step 1 Step 2 Step 3 Enhanced Optimal Power

Flow Uncertainty

Intra Day Congestion Forecast (Real time restrictions)

Day ahead Congestion Forecast

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3.2.4 Risk-based Security Assessment incorporation Forecast Uncertainty and Cascading events

In this presentation, the method for risk-based security assessment that is followed in the UMBRELLA project was described. The method includes ways to assess how cascading events, different market design/cooperation rules between TSOs and state-of-the-art technological measures as e.g. FACTS (Flexible Alternating Current Transmission Systems) and PSTs (Phase-shifting Transformers) may influence the overall system risk. The diagram below provides an overview of the method:

Figure 7 Overview of the Risk-based security assessment method

At the end of the presentation, the following key messages were given:

 System security has a cost!

o Increased uncertainty due to RES in-feeds and short-term trading leads to higher cost

 Risk-based methods for system security o Utilize additional information o Account for RES uncertainty

o Account for available flexibility (PSTs, remedial actions) o Account for cascading events

o Provide a quantitative assessment of system security level  Better trade-off between operation cost and system risk!

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3.2.5 Toolbox Requirements based on TSO Demands and Testing Environment

This was the last section of the workshop. It comprised two work packages. The overview scheme and the key messages or each work package are included below.

Work Package 5

Figure 8 Overview of Work Package 5

The key messages were:

 Distinction between functional and data requirements o Different functionalities require specific input data

 Data provision and exchange between functionalities (i.e. WPs) is major challenge and key success factor

o Intensive communication and meetings with forecasting, optimization and risk-based-assessment set up

 Specification of data characteristics (format, granularity etc.) to be provided o Research work still in progress

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Work Package 6

Figure 9 Overview of Work Package 6

The key messages were:

 Demonstrating and testing is still in an early stage

 Even in this early stage further European harmonization seems preferable, especially regarding data definitions, data formats and data handling.

Acknowledgement

The UMBRELLA consortium would like to thank ENTSO-E for hosting the workshop and the organizational work as well iTesla for the very good cooperation.

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4 UMBRELLA Workshop presentations

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Overview on and state of the Umbrella project 1 Brussels, 14/01/14

Innovative Tools for the Future Coordinated Operation of the

Pan-European Electricity Transmission System

Overview on and state of the Umbrella project

Helmut Paeschke, Dr. Wulf Engl TenneT TSO GmbH

Laura Ramirez - Elizondo Delft University of Technology

2nd iTesla/Umbrella Open Workshop, Brussels, 14-01-2014

Overview on and state of the Umbrella

project

I. Project Objectives

II. Project Participants

III. Project Structure

IV. Present situation and Challenges

V. Dissemination and Website

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◦

Develop an innovative toolbox to support the decentralised grid

security approach of TSOs. This toolbox shall include

 simulation of uncertainties due to market activities and

renewables on different time scales

 optimisation of corrective actions in reaction to simulated risks

on different time scales according to total costs and

transmission capacities.

 development of risk based assessment concepts for anticipated

system states with and without corrective actions

◦

Demonstrate the enhancement of existing and running procedures

by utilisation of the developed toolbox

◦

Provide a scientifically sound basis to support common TSO

decisions.

Main Objectives of UMBRELLA

Overview on and state of the Umbrella

project

I. Project Objectives

II. Project Participants

III. Project Structure

IV. Present situation and Challenges

V. Dissemination and Website

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Project Participants

Participant legal name Country Organisation

TenneT TSO GmbH (Coordinator) Germany TSO

Amprion GmbH Germany TSO

ČEPS, a.s. Czech Republic TSO

Elektro-Slovenija, d.o.o Slovenia TSO

TransnetBW Germany TSO

PSE Operator S.A. Poland TSO

swissgrid ag Switzerland TSO

TenneT TSO B.V. Netherlands TSO

Austrian Power Grid AG Austria TSO Delft University of Technology Netherlands University

ETH Zurich Switzerland University

Graz University of Technology Austria University

RWTH Aachen Germany University

University Duisburg-Essen Germany University

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Overview on and state of the Umbrella

project

I. Project Objectives

II. Project Participants

III. Project Structure

IV. Present situation and Challenges

V. Dissemination and Website

VI. Publications

Project structure

Risk‐based Assessment Optimization

Forecasting Synthesis and

Prototyping

PM Project Management (WP1)

PMB

Project

Management

Board

WP2

WP3

WP4

WP5

General project organisation: Common structure from the working to the steering level

Demonstration and Testing

WP6

Dissemination

WP7

Project Consortium

U Duisburg‐Essen RWTH Aachen ETH Zurich Amprion TransnetBW TU Delft

TenneT TSO Germany

PMT Project Management Team

(PM, WG-Leaders)

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Overview on and state of the Umbrella

project

I. Project Objectives

II. Project Participants

III. Project Structure

IV. Present situation and Challenges

V. Dissemination and Website

VI. Publications

Present Situation

o

In the mainland Europe synchronous area substantial difference

between

- actual physical flows and

- the market exchanges

Problems due to “loop” flows already today

o

Analysis of the 2015 time horizon identified

o

Increasing power transits due to market activities

o

Higher power flows from large wind power installations

(Germany) directed to remote load centres than

- previous national studies had anticipated

- existing planned reinforcements can accommodate

o

Increasing “loop” flows through Poland and the Czech Republic

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Operational challenges in Central Europe

Challenges concerning system operation with a significant contribution from RES relate to: • Coordination of the operation of flow controlling devices across Europe and

• of system arrangements to adjust power flows in the event of faults and other events. • Development and use of dynamic equipment ratings reflecting ambient conditions, loading

and conductor temperatures.

•Shared intelligence on developing generation and load conditions (including wind forecasts). •Suitable monitoring and control facilities.

• Procedures for using enhanced operational measures to achieve maximum benefit across each region.

◦

Increasing uncertainties due to

- growing share of electricity generation from intermittent RES

- as well as increasing market-based cross border flows

◦

Enhanced grid capability and grid flexibility

◦

New possibilities in network operation due to

- new planned interconnections including new technologies (AC, DC),

- devices for power flow control and FACTS for system services

◦

Better system coordination and cooperation by using common tools

Further developments of common grid security tools are therefore one

of the major challenges European TSOs will face in the mid-term.

Coping with these challenging system security research issues the

toolbox to be developed will enable TSOs to ensure secure grid

operation also in future electricity networks with high penetration of

intermittent renewables.

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Make Use of Hybrid Grid Solutions

… new transmission for new energy

sources …

o

Development of the German

transmission grid for the further

integration of renewables

o

Corridors for the efficient transport of

generated energy from turbines to

consumers

o

Intermediate grid enforcement

measures

o

Sustainable and secure long term grid

solutions for more grid flexibility

(AC/DC systems)

Example Germany…

Thank you very much for your attention!

www.e-umbrella.eu

This research work has been carried out within the scope of the project UMBRELLA, supported under the 7th Framework Programme of the European Union, grant agreement 282775.

Questions?

Comments?

Helmut Paeschke Operational Planning and Regional Coordination TenneT TSO GmbH Rosswachtstr. 40 85221 Dachau Telefon: +49 (8131) 3323 ‐ 2902 Telefax: +49 (8131) 3323 ‐ 2503 mailto: helmut.paeschke@tennet.eu www.tennet.eu Dr. Wulf A. Engl Interim and project management Engineering consultant Engl‐Energie Thingstr. 24 D‐82041 Oberhaching Telefon: +49 (89) 905470 ‐ 90 Telefax: +49 (89) 905470 ‐ 88 mailto: info@engl‐energie.de wulf.engl@tennet.eu www.engl‐energie.de

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Brussels, 21/10/13 15

Overview on and state of the Umbrella

project

I. Project Objectives

II. Project Participants

III. Project Structure

IV. Present situation and Challenges

V. Dissemination and Website

VI. Publications

Brussels, 21/10/13 16

Main Objective

o

The main objective is to ensure that this project and its results are

brought to the attention of those parties for which this project and its

results are of interest.

Dr. Laura Ramírez‐Elizondo Assistant Professor Electrical Sustainable Energy Department Delft University of Technology Mekelweg 4, NL‐2628 CD Delft Phone: +31 (1) 5278 1848 Telefax: +31 (1) 5278 1182 Mobile: +31 (6) 5097 4304 mailto: L.M.RamirezElizondo@tudelft.nl www.tudelft.nl

Contact

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Brussels, 21/10/13 17

Kick-off Meeting

o

Kick-off Meeting was held in Cologne in February 2012.

UMBRELLA Kick-off Meeting

Brussels, 21/10/13 18

Project Website

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Brussels, 21/10/13 19

Project Logo

o

The design concepts for the logo were the following:

o

The shining star in the centre: a source of energy and

electricity

o

The pentagonal star: references the stars in the European

Union logo and the European collaboration in the

UMBRELLA project.

o

Coloured arrows which point to the centre of the star from

all directions: the stakeholders involved

o

The total sum of the logo: an UMBRELLA viewed from the

top.

o

A European (Swiss) font was used for the typography:

Helvetica Neue 75 Bold and Helvetica Neue 55 Roman.

Brussels, 21/10/13 20

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Brussels, 21/10/13 21

Overview on and state of the Umbrella

project

I. Project Objectives

II. Project Participants

III. Project Structure

IV. Present situation and Challenges

V. Dissemination and Website

VI. Contacts and Publications

Brussels, 21/10/13 22

Publications (1)

[1]

UMBRELLA WP2, "Deliverable 2.1 ‐ Report on uncertainty modeling,"

http://www.e

‐umbrella.eu/documents, 2013.

[2]

R. Becker and C. Weber, "Using Time‐Adaptive Probabilistic Forecasts for Grid

Management

‐ Challenges and Opportunities," in 31st USAEE/IAEE North

American

Conference, Austin, Texas, USA, 06.11.2012.

[3]

R. Becker and C. Weber, "Probabilistic Wind Power Forecasting in Transmission

Grids

‐ Making use of Spatial Correlation," in WIPFOR: 2nd Workshop on Industry

&

Practices for Forecasting, Paris, France, 06.06.2013.

[4]

M. Schoeneberger, P. Schäfer, O. Scheufeld, S. Krahl and A. Moser, "Forecast of

vertical

reactive loads considering the influence of renewable energy sources

using

artificial neural networks," in Submitted to PSCC, Wroclaw, Poland, 2014.

[5]

UMBRELLA WP3, "Deliverable 3.1 ‐ Report on deterministic algorithms for EOPF,"

http://www.e

‐umbrella.eu/documents, 2013.

[6]

K. Vandyshev, D. Gijswijt and K. Aardal, "Topology Optimization Methods in

Electric

Power Systems," in EURO2013: 26th European Conference on Operational

Research,

Rome, Italy, 1‐4 July, 2013.

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Brussels, 21/10/13 23

Publications (2)

[7]

J. Eickmann, C. Pasch, N. Rotering and A. Moser, "Including Reasoning in

Congestion

Management Expert Systems," in submitted to CIGRE conference,

Brussels,

Belgium, 2014.

[8]

UMBRELLA WP4, "Deliverable 4.1 ‐ Risk‐based Assessment Concepts for System

Security

– State‐of‐the‐art review and concept extensions," http://www.e‐

umbrella.eu/documents,

2012.

[9]

L. Roald, F. Oldewurtel, T. Krause and G. Andersson, "Analytical reformulation of

security

constrained optimal power flow with probabilistic constraints," in IEEE

PowerTech,

Grenoble, France, 2013.

[10]

UMBRELLA WP4, "Deliverable 4.2 ‐ Risk assessment methods," http://www.e‐

umbrella.eu/documents,

2013.

[11]

Vrakopoulou, M. and et al., "A Unified Analysis of Security‐Constrained OPF

Formulations

Considering Uncertainty, Risk, and Controllability in Single and

Multi

‐area Systems," in IREP Conference, Crete, Greece, 2013.

Brussels, 21/10/13 24

Publications (3)

[12]

L. Roald, M. Vrakopoulou and F. Oldewurtel, "Risk‐Constrained Optimal Power

Flow

with Probabilistic Guarantees," in submitted to PSCC, Wroclaw, Poland,

2014.

[13]

L. Roald, B. Li, F. Oldewurtel, T. Krause and G. Andersson, "An optimal power flow

(OPF)

formulation including risk of cascading events," in submitted to XIII SEPOPE,

Foz du

Iguazu, Brazil, 2014.

[14]

M. d. Jong, G. Papaefthymiou, D. Lahaye, C. Vuik and L. v. d. Sluis, "Impact of

correlated

infeeds on risk‐based power system security assessment," in

submitted

to PSCC, Wroclaw, Poland, 2014.

[15]

K. Köck and H. S. J. Renner, "Probabilistic Cascading Event Risk Management," in

submitted

to PSCC, Wroclaw, Poland, 2014.

[16]

UMBRELLA WP7, "Deliverable 7.1 ‐ Website, basic communication plan and

dissemination

strategy," 2012.

[17]

UMBRELLA WP7, "Deliverable 7.2 ‐ Workshop results on innovative operational

tools,"

2012.

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Brussels, 21/10/13 25

Publications (4)

[18]

K. Maslo, "Power system dynamics modelling," in 10th International conference

control

of power systems, Tatranské Matliare Slovak Republic, May 2012.

[19]

Liu, Z. et al., "Challenges Experiences and Possible Solutions in Transmission

System

Operation with Large Wind Integration," in 11th International Workshop

on

Large‐Scale Integration of Wind Power into Power Systems, Lisbon, Portugal,

November

2012.

[20]

Liu, Z. et al., "Innovative operational security tools for the development of a

stable

pan‐European grid," in Cigré Canada, Montreal, Canada, September 2012.

[21]

UMBRELLA WP7, "Deliverable 7.3: Open Workshop on intermediate results

together

with iTesla," 2014.

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4.2 Modeling uncertainties relevant for the operation of the European

transmission grid

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Innovative Tools for the Future Coordinated Operation of the Pan-European Electricity Transmission System

Modeling uncertainties relevant for the

operation of the European transmission grid

Klaus Köck (TUG), Raik Becker (UDE), Christoph Weber (UDE)

2nd iTesla/Umbrella Open Workshop, Brussels, 14-01-2014

Modeling uncertainties relevant for the operation of the European transmission grid 2 Brussels, 14/01/14

Modeling

uncertainties relevant for the

operation

of the European transmission grid

I. Overview

II. Feed

‐ins from renewable energy sources

III. Load

uncertainty

IV. Intraday trading

V. Power

plant outages

VI. Combination

of uncertainties and provision of overall system

states

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OVERVIEW

Considered

uncertainties in the Umbrella project

1. Feed

‐ins from renewable energy sources

–

Status

quo: only strongly aggregated point predictions

2. Load

–

Status

quo: only point predictions in DACF

3. Intraday

trading

–

Status

quo: no forecasts so far

4. Power

plant outages

–

Status

quo: forecast improvement desirable

Main

objective

 Developing a set of methods describing the

key

developments/uncertainties influencing the future state of

the

electricity grid

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Main

challenge

• Most

of the mentioned processes are more or less easy to predict individually

• However,

TSOs have limited information on the detail of these processes, but can

only

observe an aggregation of them

 Collection and use of data becomes difficult

Separation

and re‐aggregation of uncertainties

Task

1

Wind and solar power

Task

2

Short‐term trading

Task

3

Load and power plant outages Distribution of nodal in‐feeds and load

Task

4

Deriving forecast distributions for the system state

Task

5

Forecast of critical system states

Must

be

regarded

separately

from

the

vertical

grid

load

Market

interaction

has

to be

considered

Input

for

load

flow

calculations

Early

anticipation

of

critical

system

states

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FEED

‐INS FROM RENEWABLE

ENERGY

SOURCES

Feed

‐ins from renewable energy sources

Objective

• Identify

appropriate possibilities for describing these uncertainties in a

way

that grid operators may make use of the information most efficiently

Methodical

key aspects

• Estimation

of forecast uncertainty

– Conditional probability density function (cpdf) of the forecast error

conditional

on the deterministic forecast

– Different estimation for each grid node and look‐ahead time using non‐

parametric

approaches (Nadaraya‐Watson estimator)

• Modelling of spatial interdependences

– Gaussian copula models

• Simulation

of forecast uncertainty

– cpdf + point forecast + copula  Monte‐Carlo‐Simulation

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Feed

‐ins from renewable energy sources

Periodical

estimation

Daily

operation

Historic

point

measurements

Historic

point

forecasts

Assignment

to grid nodes

Estimate

conditional

probability

density

function

using

CKDE

Estimate

copula

in order

to

model

spatial

inter‐

dependences

Daily

point

forecast

Monte

‐Carlo‐

Simulation

Simulated

distributions

for

each grid

node

In‐ or output Interfaces Methods

Assignment

to grid nodes

LOAD

UNCERTAINTY

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Load

uncertainty

Objective

• Identification

of suitable descriptions of the associated uncertainties in view of

providing

a consistent overall system state description

Methodology

• Identification of

pure load nodes (underlying generation is negligible)

• Estimation

of the uncertainty using a parametric approach

• Application

to other nodes

• Simulation

of the forecast error distributions using Gaussian copulas

Data

• Load

data from the DACF and SN files

Current

status

• Load:

completed

, , , , , , Modeling uncertainties relevant for the operation of the European transmission grid 12 Brussels, 14/01/14

Load

uncertainty

Exemplary

results for one TSO

Source: Deliverable D2.1 “Report on uncertainty modeling”

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INTRADAY

TRADING

Integrating

uncertainty in short‐term trading

Objective

• Detailed

analysis of intraday renominations and a subsequent proposal for

statistical

description

Methodology

• Prediction

of changes in power in‐feed at grid node level by using a merit‐

order

model

Data

• DACF

in order to derive power plant schedules

• Fuel

prices

• Uncertainties

of RES, load and power plant outages

Current

status

• Implementations

in MATLAB completed, results from wind and solar

power

uncertainty modelling are required for final evaluation

(37)

Range

of future short‐term trading

Price Quantity E(PWind) Demand Price by expected wind in‐feeds

Input

, , … ,

Output

Δ

Uncertainty of wind power etc. Change in power production at each grid node and, thus, change of trades as well as power flows Source: Deliverable D2.1 “Report on uncertainty modeling”

Analyzed

uncertainties

can

be used to anticipate

intraday

trades

POWER

PLANT OUTAGES

(38)

Power

plant outages

Modelled

as Semi‐Markov‐Process

• TTF:

time to fail

• TTR:

time to repair

• Av:

unit is available

• Unav:

unit is unavailable

• =1/MTTF

• µ=1/MTTR

Probability

distribution of TTF and TTR

TTR

(initial state: unit is unavailable)

• Weibull distribution

• µ=scale

factor: MTTR

• k=shape

factor: k>1 (bell‐shaped)

TTF

(initial state: unit is available)

• Exponential

distribution (k=1)

• µ=distribution

parameter: MTTF

Example: MTTR=70h, MTTF=1738.2h, P_av=0.9612, P_unav=0.0387

(39)

COMBINATION

OF UNCERTAINTIES AND

PROVISION

OF OVERALL SYSTEM STATES

Deriving

forecast distributions for the system state/

Forecast

of Critical System States

Load

flow Calculations

Load

flow Calculations

Load

flow Calculations

Load

flow Calculations

Distributions

of load and RES infeed

Incorporation

of specifics, in particular related to

intraday

trading

Load

flow Calculations

Identification

of critical system states

P and Q (load) • Pump storages • International intraday trades • …

Monte

‐Carlo‐Simulation

Distributions

of intraday trades

P and Q (load+injection) Source: Deliverable D2.1 “Report on uncertainty modelling”

(40)

Final

framework

Power

plant

DB

RES

point

forecast

Grid topology + aggregated load and infeed

Grid

node

in

te

rf

ace

Prototype

DB on distribution parameters

Monte

‐Carlo‐simulation of Uncertainty

Algorithms

of distribution

generation

In

‐ or output

Interfaces

Methods

steps

• Finalizing solar power uncertainty for D and CZ

• Finalizing wind power uncertainty for D, PL, NL

and

AT

• Finalizing power plant outages for all participants

• Finalizing load uncertainty for all participants

• Make test interface for following tasks

• Aggregating all uncertainties

• Refinement

(41)

(42)

(43)

Brussels, 14/01/14 Optimization algorithms for transmission system operation 1

Innovative Tools for the Future Coordinated Operation of the

Pan-European Electricity Transmission System

Optimization algorithms for transmission system operation

2nd iTesla/Umbrella Open Workshop, Brussels, 14-01-2014

Jonas Eickmann, Tobias van Leeuwen

Institute for Power Systems and Power Economics, RWTH Aachen University

Brussels, 14/01/14 _{Optimization algorithms for transmission system operation} 2

Agenda

I. Background and overview

II. Challenges

III. Preliminary results

IV. Outlook

(44)

o

Growing complexity and importance of transmission system operation



Development of expert system to provide optimized guidance

Optimization for operational planning

Optimization algorithms

Network model including load/feed‐in Network related remedials Redispatch potential © SD 2013 © SD 2013 © SD 2013 Network use cases 0:30 0:30 2:302:30 4:304:30 6:306:30 8:308:30 10:3010:3012:3012:3014:3014:3016:3016:3018:3018:3020:3020:3022:3022:30 0:300:30 D D D+ 1 D+ 1 Contingency simulation Estimation of relevant contingencies Results Contingency list

Outage A Branch i: , Node j: , Θ Outage B Branch k: , Outage …

Optimization of transmission system operation

Possible switching states Continuous optimization Topology optimization Network use cases 0:30 2:30 4:30 6:30 8:30 10:3012:3014:3016:3018:3020:3022:30 0:30 D D+ 1 Contingency simulation Estimation of relevant contingencies Results Contingency list

Outage A Branch i: , Node j: , Θ Outage B Branch k: , Outage …

Optimization of transmission system operation

Possible switching states Continuous optimization Topology optimization Remedial measure utilization Umbrella Optimization Tool

Secure network state

Uncertainty accounting in optimization Uncertainties

(45)

Agenda

I. Background and overview

II. Challenges

III. Preliminary results

IV. Outlook

V. Conclusions

Challenges

System size

o

Large number of elements in European transmission grid

o

Cross border flows couple neighbouring transmission networks

(n-1)-criterion

o

Transmission grid operation needs to cope with contingencies

o

Optimization problem size grows linear with number of relevant outages

Discrete decisions

o

Several remedial actions require binary variables

(46)

Physical interpretation

o

Complete mathematical formulation of optimization problems in

transmission system operation computational barely feasible



Application of heuristic methods to reduce problem size and decouple

optimization sub problems

o

Optimization algorithms aim at identifying remedial measures for

congestion management



Minimizing deviation from initial operating point

o

Identification of relevant constraints

o

Neglecting dispensable contingencies

o

Predicting adjustments in the optimization procedure

o

Heuristic topology optimization

o

Searching topology modifications for specific congestions

o

Load flow approximation methods

Computational considerations

o

System size and performance

requirements are very

demanding from a

computational perspective

o

Scalability and maintainability

are key success factor

o

Available storage and

computational time limited

o

In depth analysis of the

optimization procedure shows

huge potential



Efficient data handling based on customized data structures and latest

programming techniques

(47)

Agenda

I. Background and overview

II. Challenges

III. Preliminary results

IV. Outlook

V. Conclusions

Simulating remedial measures

Constraints

o

Currents

o

Voltages

in (n-1)-situations

Remedial measures

o

Topology switching

o

Transformers

o

Longitudinal

o

Quadrature

o

Redispatch

o

Shunt elements

o

HVDC lines

Network use cases 0:30 2:30 4:30 6:30 8:30 10:30 12:30 14:30 16:30 18:30 20:30 22:30 0:30 D D+ 1 Network use case Contingency simulation Estimation of relevant contingencies Results Contingency list

Outage A Branch i: , Node j: , Θ Outage B Branch k: _, Outage … Optimization of transmission system operation Possible switching states Continuous optimization Topology optimization

(48)

Result curative measures

0 20 40 60 80 100 Base Curative 10%Curative 20%Curative 30% Re d is p atc h co st s % Increase Curtailment

o

Simulation of 674 hours of the year 2010

o Generation estimated by market simulation o Synthetic network model based on public data o Assumption of 120% TATL on all lines

o

Variation of curative (after outage) redispatch

o 0% (Base) to 30% of nominal power

curatively available

o

Comparison with real network operation

still pending

Brussels, 14/01/14 _{Optimization algorithms for transmission system operation} 12 Congestions in base case Redispatch in base case Selected substations in base case Redispatch after TM 1, TM 2 Redispatch after TM 1 Selected substations after TM 1 165 % 100 % 104 % 105 % 126 % 104 % 101 % 98 % 107 % 107 % 126 % 107 % 99 % 103 % 104 % 107 % 98 % 105 % 104 % 98 % 108 % Before: 165 % After TM: 88 % Redispatch after TM 1, TM 2, TM 3 0 25 50 75 100 Zielfunktionswert Angepasste Leistung Redispatch Kosten Ausgangszustand TM 1 TM 1, TM 2 TM 1, TM 2, TM 3 %

Result topology

Base case Objective function Redispatch power

Redispatch costs _Curtailment _Increase

 Synthetic network model based on public data

 Exemplary winter situation for year 2010

 Load: 62.8 GW  Wind infeed: 9.6 GW

 Iterative estimation of three changes of

network topology (TM 1, TM 2, TM 3)

 Base case does not represent todays

(49)

Real time optimization

Remedial

measures

Running

time

Enhanced

OPF:



Redispatch



Shunt

elements



HVDC

lines

10 sec

N

‐1 security OPF

3 min

Heuristic

topology

optimization

Extra

OPF for

each

candidate

line

Initial system state

Enhanced

OPF

Topology optimization Topology (fixed bus‐bars) Generation profile Constraints description Assigned values Optionally HVDC lines Shunt elements Transformers N‐1 security “Unprofitable” lines off Current injection methodology Brussels, 14/01/14 _{Optimization algorithms for transmission system operation} 14

Agenda

I. Background and overview

II. Challenges

III. Preliminary results

IV. Outlook

(50)

Uncertainty Accounting

o

Uncertainties can lead to critical system

states and higher risk of cascading events

due to insufficient network flexibility



Accounting uncertainties in operational planning

to minimize risk

o

Consideration of uncertainties beneficial for remedials with long

activation time, such as power plant start-ups

Concept:

o

Quantile-wise continuous optimization with penalties (probabilistic

criteria) separately for each branch to minimize risk

o

Finding standardized switching measures for uncertain use cases

o

Estimating the necessity for power plant start-ups

(N‐1) ‐ Expectation insecure system states Pr obabilit y Line Loading 85 90 95 100 % 110 Brussels, 14/01/14 _{Optimization algorithms for transmission system operation} 16

Agenda

I. Background and overview

II. Challenges

III. Preliminary results

IV. Outlook

(51)

Conclusions

o

The developed algorithms promise to be capable of providing valuable

input to system operators by suggesting appropriate and secure

remedial measures

o

All required optimization steps can be carried out in day ahead time

horizon and even assist the operators in real-time

o

Further work will enable the consideration of uncertainties in the

operational planning processes

Thank

you very much for your attention!

Questions?

Comments?

www.e-umbrella.eu

This research work has been carried out within the scope of the project UMBRELLA, supported under the 7th Framework Programme of the European Union, grant agreement 282775.

(52)

4.4 Risk-based

Security

Assessment:

(53)

Brussels, 14/01/14 Risk‐based Security Assessment 1

Risk-based Security Assessment:

Incorporating Forecast Uncertainty and

Cascading Events

Brussels, 14-01-2014

Line Roald, Frauke Oldewurtel, Thilo Krause, Göran Andersson – ETH Zürich

Klaus Köck, Herwig Renner – TU Graz

Martijn de Jong, George Papaefthymiou, Domenico Lahaye – TU Delft

Brussels, 14/01/14 _{Risk‐based Security Assessment} 2

Risk-based Security Assessment

I. Objectives and Overview

II. Risk-based Optimal Power Flow

III. Risk-based Security Assessment

IV. Publications

(54)

WP4: Objective

Goal: Maintaining power system security while

facilitating integration of renewable energy and

market operations!

Approach: Risk-based Security Assessment

o

Utilize information about

- forecast uncertainties

- outage probabilities

- availability of corrective measures

- cascading events

o

Develop

risk-based measures of power

system security for use in operational

planning and market design.

Severity

:

Expected

loss

Probability

Figure 1: Risk zones in operation based on different risk levels. [UCTE OH]

Risk =

Probability ∙ Severity

WP4: Overview

Task

4.2: Evaluation of risk regarding

cascading

events

Task

4.3: Integration of state‐of‐the‐art

technological

means (e.g. FACTS)

Task

4.4: Evaluation of market designs

Task

4.1: Implementation of improved risk‐

based

methods, based on literature review

Comparison

with

ex

is

tin

g crit

eria

Risk

‐based security assessment

(55)

Presentation Outline

I. Objectives and Overview

II. Risk-based Optimal

Power Flow

III. Risk-based Security

Assessment

IV. Publications

V. Key messages

contingency list

Risk-based

acceptable risk level Risk-based Optimal Power

Flow

Risk-based Security Assessment

I. Objectives and Overview

II. Risk-based Optimal Power Flow

III. Risk-based Security Assessment

IV. Publications

(56)

II. Risk-based Optimal Power Flow (OPF)

Development and comparison of different OPF formulations:

1. Probabilistic Security-Constrained OPF

2. Risk-based, probabilistic SCOPF with remedial actions

3. Risk-based SCOPF accounting for cascading risk

II. Risk-based Optimal Power Flow (OPF)

Development and comparison of different OPF formulations:

1. Probabilistic Security-Constrained OPF



Accounts for

normally distributed wind forecast uncertainty

2. Risk-based, probabilistic SCOPF with remedial actions

(57)

1. Probabilistic Security-Constrained OPF

o

Standard DC Optimal Power Flow formulation

o

Normal distributions of wind in-feed forecast errors

o

Deterministic constraint:

o

Probabilistic constraint:

ℙ

1 1. Probabilistic Security-Constrained OPF

o

Standard DC Optimal Power Flow formulation

o

Normal distributions of wind in-feed forecast errors

o

Deterministic constraint:

o

Probabilistic constraint:

Φ

1

, 0 10 20 30 40 50 Line Number D e c re a s e [M W ] 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38

Lines

most influenced by wind in‐feed deviations have largest decrease!

Decrease

in line transfer capacity!

(58)

1. Probabilistic Security-Constrained OPF

o

Influence of violation probability

ɛ

380 400 420 440 460 480 500 520 540 0 0.2 0.4 0.6 0.8 1 Line Flow [MW] Cu m u la ti v e P ro b a b ilit y

Exp. Value SCOPF Line Limit

CDF SCOPF

1. Probabilistic Security-Constrained OPF

o

Influence of violation probability

ɛ

CDF SCOPF

(59)

1. Probabilistic Security-Constrained OPF

o

Influence of violation probability

ɛ

CDF SCOPF

ɛ = 50% ɛ = 5%

1. Probabilistic Security-Constrained OPF

o

Influence of violation probability

ɛ

Capacity decrease leads to the desired violation probability!

Exp. Value SCOPF Exp.Value pSCOPF Line Limit CDF pSCOPF CDF SCOPF ɛ = 50% ɛ = 5%

(60)

1. Probabilistic Security-Constrained OPF

Effect of uncertainty on cost:

o

Cost of security

o

Introduction of additional

security constraints increases

cost

o

Cost of uncertainty

o

Tightening of line constraints

increases cost

o 0 20 40 60 80 100 120 Base Case Re la ti v e G e n e ra ti o n Co s t in % OPF pOPF SCOPF pSCOPF Brussels, 14/01/14 _{Risk‐based Security Assessment} 16

1. Probabilistic Security-Constrained OPF

o

Extension to include state-of-the-art technological measures

o

Preliminary results:

o Preventive and corrective control of PSTs

Cost

decreases with

number

of PSTs

Corrective

control opportunities

influence

cost‐of‐security more

than

cost‐of‐uncertainty

Gener a tion Cos t [% of OPF] Gener a tion Cos t [% of OPF] Number of PSTs in the network OPF formulation

UMBRELLA Deliverable D 7.3 “Workshop results on innovative operational tools”

SEVENTH FRAMEWORK PROGRAMME

THEME [ENERGY.2011.7.3-1]

[Innovative tools for the future coordinated and stable

operation of the pan-European electricity transmission

system]

Project Deliverable

Deliverable D 7.3 “Workshop results on innovative

operational tools”

Project acronym:

UMBRELLA

Project full title:

Toolbox for Common Forecasting, Risk

assessment, and Operational Optimisation

in Grid Security Cooperations of

Transmission System Operators (TSOs)

Grant

agreement

no.:

282775-2

Contents

1 Joint Cooperation between iTesla and UMBRELLA

2 Organization and structure of common workshop

3 Summary of the workshop presentations

3.1

Morning Session: iTesla

3.2

Afternoon Session: UMBRELLA

4 UMBRELLA Workshop presentations

Innovative Tools for the Future Coordinated Operation of the

Pan-European Electricity Transmission System

Overview on and state of the Umbrella project

2nd iTesla/Umbrella Open Workshop, Brussels, 14-01-2014

Overview on and state of the Umbrella

project

I.

Project Objectives

II.

Project Participants

III.

Project Structure

IV. Present situation and Challenges

V.

Dissemination and Website

Develop an innovative toolbox to support the decentralised grid

security approach of TSOs. This toolbox shall include

 simulation of uncertainties due to market activities and

renewables on different time scales

 optimisation of corrective actions in reaction to simulated risks

on different time scales according to total costs and

transmission capacities.

 development of risk based assessment concepts for anticipated

system states with and without corrective actions

Demonstrate the enhancement of existing and running procedures

by utilisation of the developed toolbox

Provide a scientifically sound basis to support common TSO

decisions.

Main Objectives of UMBRELLA

Overview on and state of the Umbrella

project

I.

Project Objectives

II.

Project Participants

III.

Project Structure

IV. Present situation and Challenges

V.

Dissemination and Website

Project Participants

Project Participants

Overview on and state of the Umbrella

project

I.

Project Objectives

II.

Project Participants

III. Project Structure

IV. Present situation and Challenges

V.