Methods and Tools for Validating Cyber-Physical Energy Systems

Methods and Tools for Validating Cyber-Physical Energy Systems Antonello Monti1, Ferdinanda Ponci1, Marco Cupelli1, Thomas Strasser2 1E.ON

Energy Research Center, RWTH Aachen, Aachen, Germany

2Center

for Energy, AIT Austrian Institute of Technology, Vienna, Austria

Tutorial 1 44th Annual Conference of the IEEE Industrial Electronics Society Washington DC, USA, October 21, 2018

Motivation and Aims for the Tutorial ▪

Ongoing challenges and needs – Integration of renewables requires advanced Information and Communication Technology (ICT), automation, and control

– The raising complexity of such CyberPhysical Energy Systems (CPES) / smart grid systems urge for integrated, multi-domain based design and validation methods and tools – Well-educated researchers and engineers in the domain of CPES / smart grid systems

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Tutorial: Methods and Tools for Validating CPES

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Motivation and Aims for the Tutorial ▪

Tutorial introduces and provides – Challenges in CPES development and validation – A holistic validation procedure for system-level testing of CPES – Enhanced simulation, Hardware-in-the-Loop (HIL) and lab-based testing methods – Interoperability issues in CPES – An overview of selected validation examples

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About the Speaker: A. Monti ▪

1989 “Laurea cum Laude” at Politecnico di Milano in Electrical Engineering

▪

1994 PhD at Politecnico di Milano in Electrical Engineering

▪

1991-1995 Project Manager for Digital Control at Ansaldo Industria

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1995-2000 Assistant Professor at Politecnico di Milano

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2000-2007 Associate Professor at University of South Carolina

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2007-2008 Full Professor at University of South Carolina

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2008- Professor and Institute Director at E.ON Energy Research Center, RWTH Aachen University. Coordinating a group of more than 50 full time scientists

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Involved in several projects at EU and National level

▪

Associate Editor of IEEE Electrification Magazine, IEEE System Journal, Elsevier SEGAN, Springer Energy Informatics

▪

Research areas: Distribution Grid Automation, Real-time simulation, Hardwar-inthe-Loop

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About the Speaker: Ferdi Ponci ▪

1998 MSc Electrical Engineering, Politecnico di Milano, Milan, Italy

▪

2003 PhD Electrical Engineering, Politecnico di Milano, Milan, Italy

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2003 Professor of Electrical Engineering, University of South Carolina, Columbia SC, USA

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2009 Adjunct Professor, Institute for Automation of Complex Power Systems, E.ON ERC at RWTH Aachen University

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2013 Professor, Chair of Monitoring and Distributed Control of Power Systems, Institute for Automation of Complex Power Systems, E.ON ERC at RWTH Aachen University

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Involvement in several national and international research projects, sponsored by US ONR, EU FP7, EU H2020

▪

Associate Editor of IEEE Transactions on Instrumentation and Measurements, member of the AdCom of the Instrumentation and Measurement Society

▪

Core topic(s): distribution monitoring and automation, design and validation of smart grid systems

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About the Speaker: M. Cupelli ▪

2008 Dipl.-Wirt.-Ing Electrical Engineering Technische Universität Darmstadt, Darmstadt, DE

▪

2008 Consultant at Syracom Consulting, Wiesbaden, DE

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2009 Research Associate at RWTH Aachen, Aachen, DE

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2015 Dr. Ing, Electrical Engineering RWTH Aachen, Aachen, DE

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2016 Team Leader Power System Control

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2017 Head of Division – Power System Control and Automation RWTH Aachen

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Involvement in several national and international research projects, sponsored by US ONR, EU FP7, EU 2020, BMBF

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Active in IEEE – P2030 Working Group

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Core topic(s): power system control, design and validation of smart grid systems

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About the Speaker: T. Strasser ▪

2001 MSc Industrial Engineering, Vienna University of Technology (VUT), Vienna, AT

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2003 PhD Mechanical Engineering, VUT, Vienna Researcher at PROFACTOR Research, Steyr, AT

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2007 Senior Researcher at PROFACTOR Research

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2010 AIT Austrian Institute of Technology, Vienna, AT Scientist Electric Energy Systems

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2012 AIT Austrian Institute of Technology, Vienna, AT Senior Scientist Electric Energy Systems

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Involvement in several national and international research projects

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Evaluator for various international research programs

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Teaching at VUT as a docent (Privatdoz.) and active in IEEE, CIGRE and IEC

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Core topic(s): power utility automation, design and validation of smart grid systems

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Acknowledgements ▪

This tutorial/work received funding from the European Communities Horizon 2020 Program (H2020/2014-2020) under the following projects – RESERVE (GA No. 727481)

– InterFlex (GA No. 731289) – ERIGrid (GA No. 654113) ▪

This work is also supported by the “Förderer der Energie- und Informationstechnik für zukunftsfähige Netze Aachen e.V. (FEIN Aachen e.V.)“

▪

This tutorial is also sponsored and technically supported by the – IEEE IES TC on Smart Grids (TC-SG) – IEEE IES TC on Industrial Cyber-Physical Systems (TC-ICPS) – IEEE IES Standards TC

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Outline of the Tutorial 1. Introduction into CPES 2. Validation and testing approaches – Requirements for testing CPES

– Holistic validation approach – Validation description method – Definition of interoperability 3. Methods and tools – Real-time simulation for electric systems – Application of Hardware-in-the-Loop concepts – Coupling of distributed real-time simulation systems

– Distributed lab-based testing of power systems 4. Application fields and examples

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1. Introduction Into CPES IECON 2018 Tutorial Methods and Tools for Validating Cyber-Physical Energy Systems

Introduction into CPES ▪

Driving forces for research in electric energy infrastructure – Urbanization – Stochastic behavior of renewables

– Distributed generation – Electrification of mobility – Aging infrastructure

– Power electronics

System

Technology

– Communication and automation – Electrical storages

– Generation (PV, wind power, etc.)

Market

– Condition monitoring

– Liberalization and regulation of markets

– New business models for energy and mobility – New industry players in energy business – Market for primary energy, CO2, nuclear waste, etc. 21.10.2018


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Typical structure of the electricity system (~1900-2000) – Central generation infrastructure

(Bulk) Generation

– Unidirectional power flow – Hierarchical structure

Transmission Grid

Distribution Grid

Transmission Grids (e.g., 380 kV, 220 kV, 110 kV) Medium Voltage Distribution Grids (e.g., 10 kV, 20 kV, 30 kV) Low Voltage Distribution Grids (e.g., 0,4 kV)

Consumer (Load) Source: H. Brunner (AIT)

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“New” structure of the electricity system (from ~2000) – Central and distributed generation infrastructure

– Fluctuating distributed generation (e.g., solar, wind) – Bidirectional power flow

(Bulk) Generation

Transmission Grid

– Hierarchical structure Distribution Grid

Distributed Generation (Renewables)

Consumer (Load)

Distributed Generation (Renewables) Source: H. Brunner (AIT)

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Integration of renewable generators (example Denmark) 1980

2000

Source: www.ens.dk

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Possible actions? – Best solution • Build a new power grid • Thicker lines, storages, etc. • However, that is beyond price – Smart solutions required • Smart inverters • ICT, advanced automation and control • Monitoring and advanced measurement systems, etc.

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Vision of intelligent electric networks (“Smart Grids” / CPES)

Source: European Technology Platform Smart Grids

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Smart grid activities/developments at different levels – Transmission system (Trans-European demand/supply matching)

• Super grids (offshore wind farms in northern Europe – hydro storages in the Alps – large scale solar/PV systems in southern Europe/Africa) – Medium Voltage (MV) / Low Voltage (LV) distribution system • Smart grids (active distribution grids, integration of distributed generators and storage systems) – Local energy community/system (e.g., for buildings or small areas; low voltage systems) • Micro grids (islanded, grid-connected)

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Integration of (critical) infrastructure systems: electrical + ICT/automation

Source : NIST

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Technology areas

Source: IEA 21.10.2018


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2. Validation and Testing Approaches IECON 2018 Tutorial Methods and Tools for Validating Cyber-Physical Energy Systems

Requirements for Testing CPES ▪

Planning and operation of the energy infrastructure becomes more complex – Large-scale integration of renewable sources (PV, wind, etc.) – Controllable loads (batteries, electric vehicles, heat pumps, etc.) Trends and future directions – Digitalisation of power grids

– Deeper involvement of consumers and market interaction

Prosumers Energy Markets

Privacy

Building (residential/ commercial)

Industry

Power grid

– Linking electricity, gas, and heat grids for higher flexibility and resilience 21.10.2018

Security Threats

ICT and Automation

▪

Gas network Heat network

CHP

Supply network ICT infrastructure

 Integrated Cyber-Physical Energy System (CPES) or smart grid Tutorial: Methods and Tools for Validating CPES

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Key elements of future integrated smart grids for mastering the increasing requirements and system complexity are – Power electronics

– Advanced communication, automation, and control systems

System

Technology

– Smart algorithms – Monitoring and data analytics

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Market

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In the past individual domains of power and communication systems have been often designed and validated separately

▪

Available methods and approaches are Req. & Basic Design Phase

Detailed Design Phase

Implementation & Prototyping

Deployment / Roll Out

Software Simulation

+

++

O

-

Lab Experiments and Tests

-

-

++

+

Hardware-in-the-Loop (HIL)

-

-

++

++

Demonstrations / field tests / pilots

-

-

-

++

Legend: - … less suitable, o … suitable with limitations, + … suitable, ++ … best choice

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Vision: “Providing support from design to implementation & installation” – Integrated system design – Validation and testing – Installation and roll out

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Requirements for Testing CPES

REAL SYSTEM / COMPONENTS

SIMULATED SYSTEM / COMPONENTS

Power System Analysis

Communication

Components

Power Grid

Electrical Signals Power, Voltages

Generators, Storages, Loads, etc.

+

-

Control Signals Control System

SCADA / DMS / HMI

Power Quality, etc.

Control Center

Central Control

Measurements Parameters

IED Local Control IED Local Control


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– System integration topics including analysis and evaluation are not addressed in a holistic manner



– Existing methods focusing mainly on component level issues


A cyber-physical (multi-domain) approach for analysing and validating smart grids on the system level is missing today


▪




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A holistic validation and testing framework for advanced system-level testing needs to be developed with a multi-domain focus on – Proper methods and tools

– Comprehensive research infrastructure ▪

Harmonized and standardized evaluation procedures need to be developed

▪

Well-educated professionals, engineers and researchers understanding integrated smart grid configurations in a cyber-physical manner need to be trained on a broad scale

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Holistic System-level Validation and Testing Challenges ▪

Testing/validation of novel CPES components and concepts

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Many domain involved (holism)

▪

Setups/workflows differ across Research Infrastructures (RI)

Validate this!

– Experiments are often hardly reproducible – Often limited by RI capabilities

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Holistic System-level Validation and Testing Specification

Testing

Aims ▪

Formalize testing process – Testing  documented and reproducible – Basis for knowledge exchange

Objectives

▪

Formal process covering all stages of test planning – Overview of resources

– Consider state-of-the-art – Operationalize, refine

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WHY TO TEST? WHAT TO TEST? WHAT TO TEST FOR? HOW TO TEST?


&Debugging

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Holistic System-level Validation and Testing Component Test

Holistic/System Test

▪

Example: inverter MPPT tests, anti-islanding and LVRT tests

▪

No interactions with the system

▪

Usually open loop test (predefined voltage, frequency; setpoints are applied to the hardware under test)

▪

Combining several tests (testing process)

▪

Using simulations

▪

Testing a system rather than just component Central Controller

DC

PV simulator

(optimization)

AC

Hardware inverter under test

RTDS Simulated Network

AC gid simulator

PH IL PV simulator

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PV inverter

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Holistic System-level Validation and Testing Specification

I.

Testing

System validation alignment of Specifications & Testing

II. Integrated hardware & software testing Validate “systems” not components

III. Tests that combine multiple domains e.g., power, comm., and automation

&Debuggin g

IV. Systematically design tests & integrate results from various experiments for a holistic assessment i.e., combine simulation, co-simulation, HIL, PHIL, CHIL, different labs, etc. 21.10.2018


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Holistic System-level Validation and Testing

"Holistic testing is the process and methodology for the evaluation of a concrete function, system or component (object under investigation) within its relevant operational context (system under test), corresponding to the purpose of investigation”

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Mapping from SC, UC, TO to holistic test case

2

3

Mapping of holistic test case to (sub-) test specifications, i.e. specific (sub-) test system(s)

Mapping of (sub-)tests to RI and specify experiments

x 35 Process steps

1

x – mapping step

Holistic Test Case

6 holistic

Division into individual (sub-)tests

test evaluation

3 Sub-test specification

4

5

Experiment Specification

Subtest spec. 2

…

Exp. Spec.

…

Exp. in RI 1

in RI 2

RI 1

RI 2

4

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Test Objective

Use Cases

2

Scenario & Generic Use UseCase(s) Case(s) System Configuration

2

1

research infrastructure (RI) capability profiles

Holistic System-level Validation and Testing

Exp.

…

Sub-test specification n

Mapping of results of experiments to represent holistic result

7 test refinement

Experiment Specification Experiment in RI n

5 6

Mapping (preliminary) results to test adjustments

RI n

Exchange of data and results Mapping between tests resp. experiments


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Holistic Test Description (HTD) - Defines components of a system - Includes: Object of investigation - Defines functions of a system - Requirements define Test Criteria

System Configuration Use Case

Purpose of Investigation  

Experimental design Test procedure

Test Case

Configuration Input

Test/ Experiment

controllable & uncontrollable

input parameters

Object of investigation Experimental setup Boundaries of experiment Testing Tools Data Exchange

experiment assessment:

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Target Test Criteria Performance indicators/ Test metrics

Quality of experiment: error type; uncertainty; quantification of error Tutorial: Methods and Tools for Validating CPES

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THREE levels of specification

Holistic Test Description (HTD) Use Cases

Test Objective(s)

Generic

Test Case (TC) Map/split Test Specification Test specification(TS) Test specification

Specific

Map/split Experiment Experiment Experiment Specification Specification Specification (ES)

Lab

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Holistic Test Description (HTD) ▪

Template-based process – Structured test development (documentation & test quality) – Common understanding of concepts (avoid misunderstandings) – Separating test planning from RI (replicability/reproducibility) – Splitting into sub-tests (allow for complex validation)

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Key questions to be answered for test specification Why to test? What to test? What to Test For? How to test?

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Validate this!


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Holistic Test Description (HTD) System under Test (SuT): Is a system configuration that includes all relevant properties, interactions and behaviours (closed loop I/O and electrical coupling), that are required for evaluating an OuI as specified by the test criteria

OuI

Object under Investigation (OuI): The component(s) (1..n) that are subject to the test objective(s) Remark: OuI is a subset of the SuT Domain under Investigation (DuI): Identifies the domains of test parameters and connectivity relevant to the test objectives

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Holistic Test Description (HTD) optimization in the controller

Use Cases of Systems

state estimation

OuI DER P,Q control measurements measurements measurements OLTC tap control

define Functions (IEC 62559 approach)

SuT

Functions under Test (FuT): The functions relevant to the operation of the system under test, as referenced by use cases Function(s) under Investigation (FuI): The referenced specification of a function realized (operationalized) by the object under investigation Remark: the FuI are a subset of the FuT 21.10.2018


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Validate this!


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Holistic Test Description (HTD) Purpose of Intestigation (PoI) ▪

Verification

▪

Validation

▪

Characterization

Modeling / Understanding

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Test objectives/PoI: Characterization and validation of the DMS controller 1. Convergence of the optimization (validation) 2. Performance of the optimization under realistic conditions (characterization) 3. Accuracy of the state estimation (characterization) Scoring / Performance


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Test objective  PoI  Test Crit.

▪

Test criteria How to break down the PoIs?

– Target Metrics (TM, criteria): List of metrics to quantify each PoI – Variability attributes: Controllable or uncontrollable parameters to “disturb” SuT – Quality attributes (thresholds): Test result level or quality of the TM required to pass or conclude the testing

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Target metrics: 1. 1.1 convergence (when/how often?), 1.2 how fast? 1.3 solution quality 2. 2.1 voltage deviation 2.2 number of tap changes, 2.3 network losses 3. Voltage, P, Q estimation errors Variability attributes: load patterns (realistic, annual variation; applies to criteria 1-3); communication attributes (packet loss, delays) Quality attributes (thresholds): “1.2: convergence within 2 sec” (validation) “3.* estimation quality characterized with confidence 95%” …


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Validate this!


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Test Specification and Design SC

UC

▪

TO

✓ Purpose of Investigation (PoI) and Test Criteria

1

✓ System and Domain categories and relations

Test Case SuT, FuT, PoI, TC

▪

test evaluation

3

TestSpecification Specification Test

map

4

To Specify  Precise system (specific system configuration)  Which variables to manipulate and which to measure?

TestDesign, Design,I/O I/O Test

7 test refinement

 How to quantify the test metrics (based on test data)? 

Sampling of the input spaces (design of experiments methodology)



Combination and interpretation of the outputs

Experiment Specification

2

research infrastructure (RI) capability profiles

Given

Experiment in RI

5

Research Infrastructure (RI)

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 The test design / procedure  Mapping to actual lab setup (experiment setup) Tutorial: Methods and Tools for Validating CPES

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Detailing Test Setup and Mapping to the Lab

Scoping & specification of test system

Separate specification of lab implementation

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Additional Structure and Documentation ▪

Qualification strategy – How many tests/experiments are derived from the test case?

– Which PoI & Test Criteria are associated with which test? – Are different SuT associated with different tests? – Which tests/experiments need input from each other? Or can be done in parallel? – Information gained from comparison between tests

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RI selection and mapping – Prerequisite: open RI database – Guidelines to… • Select the most suitable RI for the realization of a test • Find the right components in an RI • Check cross RI potential (if gaps exist)

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RI-Database Data Model Tutorial: Methods and Tools for Validating CPES

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Design of Experiments (DOE) – Aligning the testing process with statistical experiment planning – Efficiency  maximal information from limited experiment number – Result significance (against system noise) – Target measures/ metrics (e.g., “average control error”) Test/ Experiment

Input Params

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Choose samples

Target


– Design sampling space on a ‘need-to-know’ basis (e.g., 3 levels of package loss rate, 20 levels of disturbance)

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Holistic Testing Application Examples ▪

Applied in the ERIGrid project – Project-internal demonstration cases – Transnational Access (TA) projects

– Gathering feedback and continuous improvement/extension ▪

Other EU projects

▪

Official publications – First papers out – Comprehensive guideline paper and templates soon to be public

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TA project “DiNODR” at SYSLAB (DTU) – Mitigating local problems in distribution grid via aggregated flexible loads (Demand Response – DR) – Coordinate distribution-level DR with utility-driven DR

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Three test cases  list associated PoI – TC1: Validate usefulness distribution-level DR • Validate voltage improvement (PoI1), overload prevention (PoI2), phase balancing (PoI3), network reconfiguration support (PoI4) – TC2: Characterize harmful impact of utility-driven DR • Characterize impact on bus voltage (PoI5), and line loadings (PoI6)

– TC3: Validate application of concurrent DR approach • Verify local DR effectiveness (PoI7), and utility-level DR effectiveness(PoI8)

▪

All PoI are associated with several Target Metrics

▪

Each TC split up into several Test Specifications

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ERIGrid Trans-national Access (TA): Preparation & Documentation “The preparation work helped us a lot. Except minor changes in the plan and configurations due to a number of device, communication and control unavailabilities, we are following our test and experiment specifications. The template is also useful for our user team to exchange ideas in an organized and effective way.” - Alparslan Zehir (DiNODR)

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Why interoperability? ▪

Key challenge – Convergence of many industrial sectors with different standards, culture and technical background – Single/multi-vendor devices, components should be able to inter-work

▪

Definition CEN-CENELEC-ETSI SG-CG: Interoperability is the “ability of two or more networks, systems, devices, applications, or components to interwork, to exchange and use information in order to perform required functions” – SGAM reference architecture: interoperability across all the 5 layers

– Interwork at power level? ▪

Status – Standards and detailed experimental methods for testing the interoperability of CPES missing

– Standards do not guarantee interoperability, even if they promote it ▪

The EC-JRC proposal: Design of Experiments (DoE) methodology

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Interoperability testing methodology ▪

The Smart Grid Interoperability Lab SGILab of the DG JRC - Energy Security, Distribution and Markets Unit (C.03) “DG JRC Energy Security, Distribution and Markets Unit (C.03), “Guidelines to the specification developer for building a successful interoperability test”, 2018

– Does a given EUT communicate effectively with the other components? – Are different subsystems/electric grid components interoperable?

▪

Six interconnected stages: creation of UC, BAP, BAIoP, DoE and Testing & Analysis of Experiments 21.10.2018


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3. Methods and Tools IECON 2018 Tutorial Methods and Tools for Validating Cyber-Physical Energy Systems

Real-Time Simulation of Electrical Systems ▪

Why Real-Time (RT) simulation? – Testing of Control Software – Hardware-in-the-Loop (HIL) – Testing of components at Power Level • Electrical • Mechanical • Thermal

Interface RT Sim (Rest of the System)

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Hardware under Test (HuT)


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Definition of Real-Time – Soft Real-Time • Soft Real-Time is a response to an instruction that is not necessarily exact or precise, but an average response time to a task. It is neither preemptive nor deterministic. – Hard Real-Time • Hard Real-Time requires a guaranteed, preemptive, deterministic response to an instruction. In a hard real time system, the deadlines are fixed and the system must guarantee response within a fixed and well-defined time.

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Real-Time Simulation of Electrical Systems

Soft Real Time

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Hard Real Time


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COMMERCIAL SOLUTIONS: RTDS – For a long time absolute leader of the market

– Modular structure based on racks – Typical time step: 50 µs – Smaller time steps possible

– Extension based on FPGA for power electronics – Emulation of typical data protocols

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COMMERCIAL SOLUTIONS: OPAL RT – Main competitor of RTDS – Based on a multi-core approach – Similar characteristics – Variety of solvers • eMegasim • HyperSim • ePhasorSim • eFPGASim

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Other products in the market – Typhoon-HIL  focus on microgrid and power electronics – PLECS  focus on power electronics – Dymola  multi-physics – SimulationX  multi-physics – dSpace  focus on control prototyping

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You can try at home!!! – Simple extension of Linux for RT (e.g., RTAI) allow the development of RT machine with off-the-shelf hardware

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Real-Time Simulation of Electrical Systems ▪ Co-Simulation Interface Algorithm (IA) for geographically distributed real-time simulation (GD-RTS)

– Objectives: conservation of energy at the interface and interface transparency

▪ Violation of energy conservation at the interface is inherent problem in (geographically) distributed cosimulation due to the following

– system decoupling (subsystems are solved separately)

– communication medium (delay, delay variation, packet loss, limited data sampling…

▪ Co-simulation IA should preserve stability of the simulation and ensure simulation fidelity 21.10.2018


Violation of energy conservation in GD-RTS

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Real-Time Simulation of Electrical Systems 𝑋 𝑏𝑝

Dynamic phasors for decoupling large-scale distributed simulation ▪

Fourier spectrum of real-valued signal is symmetric around the 𝜔 = 0 axis → negative part can be omitted

▪

We could shift the bandpass signal 𝑋𝑏𝑝 by a certain frequency which results in a baseband representation

▪

The resulting signal still contains all the information of the original signal except for the carrier frequency

▪

In the time domain the baseband signal envelopes the original signal

𝜔𝑐

𝜔

𝑋𝑏𝑏 = 𝑋𝑏𝑝 (𝑗𝜔 − 𝑗𝜔𝑐 )

0

𝜔

By Brews ohare - Own work, CC BY-SA 3.0, https://commons.wikimedia.org/w/index.php?curid=19014255

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Co-Simulation IA for geographically distributed real-time simulation

▪

current and voltage interface quantities are exchanged between the simulators in the form of time-varying Fourier coefficients, known as dynamic phasors

▪

time clocks of the two simulators are synchronized to the global time

▪

dynamic phasor concept includes absolute time that enables time delay compensation based on the phase shift

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Local Power System co-simulation Interconnection of RTDS and OPAL-RT at ACS lab ▪

Hard real-time communication

▪

Synchronized execution of simulation time steps

OPAL-RT OP5600

RTDS racks

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Models Transmission: Benchmark Network for DERs testing (by CIGRé) ▪

High Voltage Transmission Network Benchmark – European Configuration

▪

13 buses, 4 generators

▪

220 and 380 kV, 50 Hz

▪

Simulated on RTDS

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Models Distribution: Benchmark Network for DERs testing (by CIGRé) ▪

Simulated on OPAL-RT

▪

Medium Voltage Distribution Network Benchmark – European Configuration – 14 buses – 2 feeders – 2 transformers – 46 MVA contractual load – Different PV penetration levels: • 6% • 20 %

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Models PV Power Plants ▪

According to Italian rules for distributed generation, PV power plants with a rated power ≥ 6 kW cannot disconnect immediately after a voltage drop. They must observe the Low-Voltage Ride-through (LVRT) curve:

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TN & DN interactions Simple Demonstration: Scenario ▪

The loss of generator 2 at bus 3 of TN causes a voltage drop in neighbouring buses and, consequently, the disconnection of PVs in DN (details represented) connected to bus 4.

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TN & DN interactions Simple Demonstration: Interface values ▪

Currents and voltages measured at the interface point on the two simulators.

▪

Instantaneous voltages decrease after G2 disconnection

▪

Interface accuracy is guaranteed also during transients

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TN & DN interactions Simple Demonstration: Results ▪

In this scenario, the Italian LVRT capability allows most of the PVs to stay connected in the detailed DN:

▪

Using co-simulation, new LVRT curves and different placement for PV plants can be analysed with regard to the voltage security after an event in the transmission network.

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An open framework for real-time distributed real time simulation: tools and applications ▪

Main Problem: Real-time simulation capacity

Simplified diagram of the Romanian transmission system Source: TransE

RTDS PB5 card Source: rtds.com

The Romanian transmission system alone has already more than 1500 network nodes

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Pan-European Real-Time Simulation •

Distributed co-simulation to couple real-time simulators and share simulation capacity and hardware

•

Distributed simulation allows participants to keep their data confidential

•

Still real-time to interface with real hardware for prototyping

→ cause for new a problem

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Challenges & requirements ▪

▪

▪

Several ms

Latency between simulators and simulation sites caused by distance between labs Different simulators generate different results and there is no reference implementation Compatibility with existing grid descriptions (CIM) → new simulator called DPsim as part of simulation platform

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Simulation

Web

Simulation

Latency between simulators interconnected through the web

𝑖𝐷𝐶 in A

Time in ms RTDS

PLECS

Different simulation results of a Dual Active Bridge (DAB): PLECS & RTDS


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A Meta-Simulator ▪

Ingredients for a global virtual testbed – A common model format

for exchanging and retargeting models – Flexible interfaces

for interconnecting a heterogenous set of simulators and devices – A common user interface

for collaborative editing, control and monitoring – Open solvers

for verifiable and scalable simulations

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RESERVE Pan-European Laboratory Infrastructure Pan-European Real-Time Simulation Infrastructure as part of project RESERVE (EU Horizon 2020)

Scenario from RESERVE project: Black line: Connection between Ireland and Germany as use case in this study, composed of 15 hops Fig. 7. Network connection of Pan-European Laboratory infrastructure

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Round-trip Time and Packet Rate • RTT measurements between laboratories in Ireland and Germany • Average RTT is 47.7 ms • Latency is mainly caused by geographical distance!

RTT over communication hops

•Verify quality of connection: •RTT also depends on packet rate for exchanging simulation samples •Keep below congestion threshold to avoid packet loss 21.10.2018

Cumulative probability of RTT


77

VILLASframework Open source tool kit for distributed real-time simulation (GPLv3 license)

VILLASnode • A gateway for real-time simulation data VILLASweb • A web-interface for planning, executing and controlling distributed simulations DPsim • A real-time simulation kernel for the EMT / DP domain CIM++ • A library for parsing and compiling CIM to Modelica, GLM Pintura • Web-based Graphical Editor for CIM models 21.10.2018


78

Villas Architecture

21.10.2018


79

VILLASnode Gateway

Hard- and soft real-time interfaces for Lab interconnections and HIL

21.10.2018


80

VILLASweb Interface

Screenshot of VILLASweb user interface 21.10.2018


81

Pintura Editor A Web-based editor for CIM models – Modern Web technologies: HTML5, SVG, XML/XSTL, JavaScript

Screenshot of Pintura Editor 21.10.2018


82

CIM++ Deserialzer ▪

Automated generated open-source CIM Deserializer library for C++

▪

Very easy to use with original and extended IEC61970/68 versions

▪

Used by several projects: DPsim, CIM2GLM, CIM2Mod:

▪

Automated resolving of cyclic class dependencies

▪

Automated serialization code generation

21.10.2018


83

CIM2Mod

21.10.2018


84

CIM2Mod: ModPowerSystems and PowerSystems

21.10.2018


85

DPsim: Simulator for Distributed RT-Simulation ▪ Distributed simulation via integration with VILLASnode

EMT Domain

Phasor Domain

▪ Latency ▪ Dynamic Phasor & EMT solver for real-time ▪ Simulate only envelope function and reduce required sampling rate

▪ Open source to serve as reference implementation

Original EMT signal

Simulated base band signal

EMT results after post processing

▪ Input directly from utilities via Common Information Model (CIM) 21.10.2018


86

Coupling of Distributed Real-Time Simulation ▪

Create grid model in Pintura or any other tool that supports the Common Information Model (CIM)

▪

Load data directly from the CIM file

▪

Use VILLASnode to interface the simulation to many other products

▪

Dedicated Python packages allow the control of simulations and post processing of simulation data

CIM Data

I/O Scripting & Scenarios

21.10.2018


87

DPsim: Complex Models – Synchronous Generator ▪ Implementation of – Classic DQ and – Voltage-Behind-Reactance (VBR)

synchronous generator models in Dynamic Phasors ▪ Coherent with Simulink and PLECS simulations

DQ and VBR synchronous generator models compared to Simulink for load change 21.10.2018


88

Tools Summary User Interface

Gateway between User Interface and Simulators

Real-Time Simulators

Gateway between Simulators and Hardware

Hardware

21.10.2018


89

Coupling of Distributed Real-Time Simulation Objectives – Establish a vendor-neutral distributed platform based on interconnections Digital Real-Time Simulators (DRTS), Power-Hardware-In-the-Loop (PHIL) and Controller-Hardware-In-the-Loop (CHIL) assets hosted at geographically dispersed facilities. – Demonstration of multi-lab real-time simulation and distributed PHIL and CHIL setup for simulation and analysis of next generation global power grids.

21.10.2018


90

Global Real-Time SuperLab: Participants Laboratory

Subsyste m ID

ss1

Acronym

Idaho National Laboratory

INL

Western Systems Coordinating Council (WSCC); HVDC converter station

National Renewable Energy Laboratory

NREL

PHIL for wind turbines

ss5

Sandia National Laboratories

SNL

PHIL for PV inverters

ss6

Colorado State University

CSU

IEEE 13-bus distribution test feeder

ss4

University of South Carolina

USC

Modified IEEE 123-bus distribution system, CHIL, communication emulation

ss7

Washington State University

WSU

Simplified CERTS microgrid

ss8

RWTH Aachen University

RWTH

European transmission network benchmark model (CIGRÉ); HVDC converter station

ss2

Politecnico di Torino

POLITO

European distribution network benchmark model (CIGRÉ);

ss3

EU universities

US universities

National Labs

Full Name

Simulation model / HIL setup

21.10.2018


91

Global Real-Time SuperLab ▪ 8 Labs – 5 OPAL-RT – 4 RTDS

– 1 Typhoon

▪ 2 TN ▪ 6 DN

▪ 1 HVDC link ▪ CHIL at USC ▪ 2 PHIL – NREL – SNL 21.10.2018


92

GRTS Results #1: INL-USC ▪

Dynamic load/PV-profile in IEEE 123-bus distribution system (USC) Simulation results at ss1-ss7 co-simulation interface (INL-USC)

PV inverters are controlled to minimize reactive power at the main substation of IEEE 123-bus system 21.10.2018


93

GRTS Results #2: INL-RWTH ▪

Reference for converter control of power in the HVDC link is decreased by 25 MW ss1-ss2 co-simulation interface (INL-RWTH)

21.10.2018


94

GRTS Results #3: INL-NREL ▪

Wind turbines at NREL respond to over-frequency transient based on droop settings Simulation results at ss1-ss5

21.10.2018


95

5g Networks & Hardware integration

Distributed Edge Cloud System

Real-Time Simulation Infrastructure

Deployable Control Algorithms

Central Control Algorithms

Communication Stack

Power System Simulation

Core Network

Field Trial in Ireland

Co-Simulation Environment Field Trials

ESB Field Devices

VILLASnode Gateway

5G Base Station

Control Concepts

User Interface

Gateway between User Interface and Simulators

Real-Time Simulators

Wireless

Internet

Gateway between Simulators and Hardware

Power System Field Devices

21.10.2018


Communication Network Equipment

96

4 MW system level test bench – Overview Research WTG Controller

1 DOF

Recuperation Loop

Load Unit Controller Prime Mover

HIL

User

Wind

Interface

set point

Control Units

-

10kV Grid 5 DOF

HIL Grid

= =

DC-Link

_

_ _

PCC 20 kV

RTDS

n

U,I

DUT-Transformer 21.10.2018


97

Grid Emulator ▪

Interleaved medium-voltage converters

▪

Programmable short-circuit impedance

▪

Key specification

21.10.2018


98

Distributed Lab-based Testing of Power Systems Overview of the connection of the real time simulator

PCC

Real time communication interface at ACS real time lab

21.10.2018

500 µs Loop

2 km fiber optic cable Communication line ACS lab – CWD test bench


Measured values at PCC

Grid emulator CWD test bench

Reference value grid emulator

Measured values of DUT at PCC

Target values grid behavior

Real time lab at ACS

Real time communication interface at CWD test bench

99

FVA Nacelle Electrical Drivetrain Parameter Nominal power

3.06 MVA

Nominal active power

2.75 MW

LVRT

▪

Low-voltage full-converter concept

▪

Asynchronous generator

21.10.2018

Value

SDLWindV 2009

Nominal generator speed

1100 rpm

Nominal generator torque

24.7 kNm


100

PHIL – Problem Description ▪

Naturally Coupled System (NCS)

▪

Power Hardware in the Loop (PHiL)

Power Device

ROS

DUT

– Time delays – Sensing noise

Split Point

– Limited bandwidth of power amplifier

D/A

➢ Accuracy and stability issues

Simulator ROS

A/D

Software

21.10.2018


AMP

Power Device

Sensors

DUT

Hardware

101

PHIL system with ITM IA and low pass filter iA_ITM vA_ITM

vB_ITM iB_ITM

ZA

v'2

i'1

ZB u2

u1 e  sTs

e  sTd

TLPF

Hardware

Software

u1 s 

+

vA_ITM s 

e  sTs

+ v Z A s 

e  sTd

v ' 2 s 

 v

B_ITM

s 

+

1 ZB

iB_ITM s 

u 2 s 

ZA

TLPF

i '1 s   i s  A_ITM

21.10.2018


102

PHIL system with ITM IA and impedance shifting ZSFT

iA_ITM vA_ITM ZA

ZAB v'2

i'1

e  sTs

e  sTd

Hardware

Software

+

ZB u2

u1

u1 s 

vB_ITM iB_ITM

vA_ITM s 

e  sTs

+ v Z A s 

e  sTd

v ' 2 s 

 v

B_ITM

s 

+

1 Z B  Z SFT

iB_ITM s 

u 2 s 

Z A  Z SFT

i '1 s   i s  A_ITM

21.10.2018


103

PHIL system with DIM IA ZA

i'1

v'2

v'1

ZB u2

u1 TD

TFF TFB TFB

Hardware

Software

u1 s 

v11 s  + Z AB  Z * Z A  Z AB  Z * +

vA_DIM s 

TD

TFF

v14 s 

+

1 Z AB  Z B

ZB

u 2 s 

u 2 s 

v12 s 

v13 s 

21.10.2018

v ' 2 s 

ZAZ* Z A  Z AB  Z *

ZA Z A  Z AB  Z *

i '1 s  v '1 s 

TFB

TFB


iB_DIM s  vB_DIM s 

104

Simulation Case

Equivalent circuit of the grid emulator and device under test

Z AB s   sLS1, AB

 1  sLS2, AB   RP, AB  sLP, AB   sC P, AB    1 sLS2, AB  RP, AB  sLP, AB  sC P, AB

 1   sLS2, B   RP, B   sC P, B   Z B s   RS1, B  sLS1, B  1 RS2, B  sLS2, B  RP, B  sC P, B

Sketch of Grid Emulator

R

S2, B

21.10.2018


Sketch of Device Under Test

105

Simulation Results

Nyquist Diagram of the open-loop transfer functions of the PHIL system with ITM IA and effect of the low pass filter technique

21.10.2018

Nyquist Diagram of the open-loop transfer functions of the PHIL system with ITM IA and effect of the impedance shifting technique


106

Simulation Results

LS1 LS2 RP LP CP fc

Power Amplifier = 12.5 mH = 10.9 mH = 35.59 Ω = 1.1 mH = 1.89 µF = 100 Hz

ZA = Rros + s*Lros

Td1 = 600 µs

Nyquist Diagram of the open-loop transfer functions of the PHIL system with ITM IA compared to the DIM IA with two sub-optimal damping impedances Z*

21.10.2018


LS1 RS1 CP RP LS2 RS2

= = = = = =

DUT 17.9 mH 421.9 mΩ 2.4637 µF 6.5813 Ω 28 mH 53.2 mΩ

ROS Lros = 50 mH Rros = 10 Ω

Interface Delays Ts = 50 µs

DUT Values

107

Simulation Results

Voltage (top) and current (bottom) waveforms comparing NCS (black) and PHIL system with ITM IA at simulation side (red) and at DUT side (blue)

21.10.2018

Voltages (top) and currents (bottom) waveforms comparing NCS (black) and PHIL system with ITM IA with low-pass filter technique at simulation side (red) and at DUT side (blue)


108

Simulation Results

Voltages (top) and current (bottom) waveforms comparing NCS (black) and PHIL system with ITM IA with impedance shifting technique at simulation side (red) and at DUT side (blue)

21.10.2018

Voltages (top) and current (bottom) waveforms comparing NCS (black) and PHIL system with DIM IA at simulation side (red) and at DUT side (blue)


109

Distributed Lab-based Testing of Power Systems ▪

Joint Test Facility for Smart Energy Networks with DER (JaNDER) – Result from FP7 DERri – Proof-of-concept of real-time data exchange between lab facilities

▪

Several shortcomings of DERri JaNDER version (addressed in ERIGrid) – Installation effort (e.g., requirement for firewall changes)

– Lack of official multi-lab test cases in DERri – No context information beyond raw real-time data ▪

Virtual Research Infrastructure (VRI) – Integration of all ERIGrid participating labs – Virtually integrated pan-European smart grid research infrastructure

21.10.2018


110


General idea and concept

21.10.2018


111

Distributed Lab-based Testing of Power Systems Interoperability considerations ▪

A crucial aspect to take into account for the implementation of the VRI concept is the fact that the assets of each participating RI must be accessible to a great number of external entities (interoperability aspect)

▪

In order to allow such a great number of potential stakeholders to easily implement the needed tests, an interoperable solution must be implemented: this means that the “common interface” must be based, to the possible extent, on open and globally accepted standards

▪

ERIGrid adopted a layered approach to the VRI implementation, and with respect to the SGAM layers this means that more than one solution is supported at both Information and Communication layers

21.10.2018


112

Distributed Lab-based Testing of Power Systems For interoperability reasons there are (at the moment) three levels: ▪

LEVEL-0: the basic layer, it is based on solutions developed within the ERIGrid project in order to fulfil its specific needs of flexibility, innovation and ease of use

▪

LEVEL-1: interoperable with IEC 61850 , an internationally recognized standards

▪

LEVEL-2: interoperable with IEC 61968 (CIM), another internationally recognized standards

21.10.2018


113


Coupling of research infrastructures for integrated and joint testing (multi-lab)

ERIGrid JaNDER approach for online coupling of laboratories

21.10.2018


114


Coordinated voltage control between a simulated grid and two physical grid segments

▪

Using JaNDER levels L0 or L1

Grid simulator

RI1

Jander-L1 P,Q set points

P,Q set points Available and actuated P&Q

RI2

RI3

Real microgrids 21.10.2018


115

4. Application Fields and Examples IECON 2018 Tutorial Methods and Tools for Validating Cyber-Physical Energy Systems

IDE4L Architecture

HV grid Primary Substation

TSO

Primary Substation

SAU

SAU IED

1. Use Cases

IED

DSO MV grid

DMS or SCADA

MGCC Microgrid MV

Customer MV SM

HEMS

HEMS Secondary Substation

Secondary Substation

SAU

2. SGAM Architecture

SAU

IED

IED

LV grid

LV grid MGCC Microgrid LV

Customer LV SM

HEMS

HEMS

3. Implementation of architecture

4. Field and Lab Demonstration 21.10.2018


117

Substation Automation Unit – Distributed Intelligence SA

Reports

U

Data Acquisition State Estimation

SAU Int

MMS

e rf

ace

Da s

ta

ba

Ap se

p li

cat

Forecast i on

s

DLMS/ COSEM

Arbeitsstation Server

DMS and Control Center

FLISR

Substation IEDs

Management model Smart Meters

Bridge model

CIM

IEC 61850

▪

A complete set of services for substation automation in a single low cost machine developed in FP7 IDE4L

▪

Structured with a distributed intelligence approach to support scalability in distribution networks

▪

Running live in the grid of Unareti (A2A)

21.10.2018

Power control


118

Use cases – lab and field tests

21.10.2018


119

Use cases – lab and field tests

21.10.2018


120

Grid model Rack 1 OLTC

Rack 4 HV / MV FD2SCe

Rack 3

0545

FD2SC1

FD2SCw

FD3SC1

FD3SC2

FD3SC3

FD8SC1

FD8SC2

FD8SC3

FD7SC1

FD7SC2

FD7SC3

FD1SC1

FD1SCe

0952 OLTC

Feeder 3

1217

Feeder 2

Feeder 1

Rack 2

MV / LV

1023

1464

1056

1024

1073

0732

0338

1341

1462

0145

1006

0297

1136

1512

0468

1190

0987

0378

0827

1070

0605

1354

1180

1438

1340

0585

0117

0603

0870

FD1SCw

0749

1187

0060

0937

0604

1143

Automation system under test ▪

▪

LV + MV Monitoring Analog connection

PMUs C37.118 reports

Simulation environment

Digital connection

Laboratory electrical grid

Analog connection

C37.118 Client

Laboratory Computer SAU

Virtual IEDs (VIEDs) – Laboratory computer

SM

- C37.118 client - MMS client - DLMS/COSEM client - RDBMS

MMS Report

DLMS/COSEM read

▪

RDBMS

DmdWh Laboratory LV grid

SupWh

21.10.2018 Phase A Phase B Phase C

Ia Ib Ic

Tutorial: Methods and Tools for Validating CPES Va

Vb Vc

Neutral

Pa, Qa, PFa

Pb, Qb, PFb Pc, Qc, PFc

The load are amplifiers and other laboratory devices in the lab

122

Automation system under test ▪

▪

LV + MV SE

Laboratory Computer SSAU forecast Power and generation Oracle VM (Ubuntu 14.04)--SSAU

Laboratory Computer SSAU

PostgresSQL

Octave

Oracle VM (Ubuntu 14.04) --PSAU PostgresSQL MMS Server SCL file server

Read SE at SS

IDE4L standard RDBMS

Octave Read measurements Read grid data


State estimator

Read historian Read weather forecast

State estimator

Write FC results

Write SE results

Report with SE at SS

Oracle VM (Ubuntu 14.04)--SSAU PostgresSQL

MMS Client Write SE at SS


Octave Read measurements Read grid data

State estimator

Write SE results

▪ Simulation environment

21.10.2018

LV + MV Power Control Digital connection

Virtual IEDs (VIEDs) – Laboratory computer


Laboratory Computer SAU MMS write

- MMS client - RDBMS

123

Automation system under test Laboratory Computer SAU Oracle VM (Ubuntu 14.04) PSAU Analog connection

PMUs C37.118 reports

C37.118 client

Write measurements

PostgresSQL

Python Read historian Read weather forecast

Forecaster

Write power forecast

Laboratory Computer IED

Digital connection

Oracle VM (Ubuntu 14.04) VIEDs MMS Server

PostgresSQL

MMS Report MMS write

Write measurements

MMS Client

Write SE at SS

Octave Read measurements Read grid data Write SE results Read grid status and forecast

Write control set points Report with SE at SS

Grid IEDRTDSMV

IEDRTDSMVgen

Oracle VM (Ubuntu 14.04) VIEDs

Digital connection

MMS Server

PostgresSQL

SCL file server



MMS Client

Analog connection

SCL file server

IEDRTDSgen

SM

DLMS/COSEM read

DLMS/ COSEM client

Power Control

Oracle VM (Ubuntu 14.04) SSAU PostgresSQL

Write measurements Write SE at SS Read set points

MMS Server

IEDRTDS

State estimator

Read set points

SCL file server



Read SE at SS

Write measurements

Python Read historian Read weather forecast

Forecaster

Write power forecast


Octave Read measurements Read grid data Write SE results Read grid status and forecast

Write control set points

State estimator Power Control

Simulation Environment   Automation 1st method, with DNP3 Simulation environment

Connection Simulation to Automation

Automation system

Virtual IED (VIED) Laboratory Computer

RTDS Run time

V P Q P ctrl Q ctrl OLTC

read GTNET (RTDS output card) DNP3 slave

write

DNP3 Master)


Oracle VM (Ubuntu 14.04)

KEPServerEX


PostgresSQL ODBC Client

read write


read write

Link Master

MMS Server SCL file server


MMS Client

2nd method, with SV Simulation environment

Connection Simulation to Automation

Automation system

Virtual IED (VIED) Laboratory Computer

V I

GTNET (SV output card) SV publisher

write

SV publiser write

GTNET (SV output card) SV subscriber

read


PostgresSQL

RTDS Run time P ctrl Q ctrl OLTC



LibIEC61850

SV subscriber

read


read write

MMS Server SCL file server


MMS Client

Real-Time Aggregator Testing

Results of Aggregator Emulation

1. Congestion Detection and CRP activation request 2. First Flexibility allocation 3. Setpoints transmission 4. CRP activation verification and Flexibility reallocation 5. Updated setpoints transmission 6. Stop flexibility delivery

1

2

3

4

5

6

Breakthrough 7. Congestion management using flexibility offered by LV customers trough the Aggregator. Coordination among Aggregator and Market Agent and communication between Tertiary Controller and the grid and between the Aggregator and its customers.

Center for Wind Power Drives (CWD) Prime Mover 1 DOF

10kV Grid

Controller

5 DOF

User Interface

HIL Grid DC-Link

=

Wind

Load Unit

= Recuperation Loop

HIL

_

_

20 kV _

Drive Train Model

PCC

RTDS

Wind Load Calculator

Wind Field Generator nrotor

Pitch System Model

Emulated Sensors

set point

Control Units

-

Original WTG Controller 21.10.2018


128

Center for Wind Power Drives (CWD) System-Level Nacelle Tests ▪

System-Level Multi-Physics Power Hardware in the Loop Test emulate: – Forces and moments on the rotor hub – Grid at the point of common coupling of the nacelle – Sensor-interfaces

▪

Advantages of approach: – Deterministic – Repeatable – Time-invariant – High load capacity

21.10.2018


129

Center for Wind Power Drives (CWD) Comparison of grid emulator to FRT container ▪

Wind turbine connected to the public grid via the FRT-container (in black at the top)

▪

Wind turbine connected to the grid emulator (in 10red) kV

Grid emulator

DC bus PCC 20 kV

10 kV

10 kV

Wind turbine converter

Motor inverter

Active front end

690 V

21.10.2018

Device under test (DUT)

HiL wind


130

Center for Wind Power Drives (CWD) Exemplary results of dynamic voltage tests ▪

FRT tests according to FGW TR 3 norm

▪

Compliance with the tolerance limits according to IEC 61400-21

▪

All tests were successfully conducted

Balanced voltage dip (0.05 p.u.)

21.10.2018

Unbalanced voltage dip (0.05 p.u.)


131

The ADMS architecture ▪

The ADMS system include two types of measurement devices – Non-Synchronized devices (RMS, power flows and injections and power quality indexes) – Synchronized devices (PMUs) which calculate current and voltage synchrophasors, frequency and ROCOF

▪

Measurement devices publish continuously measurements for the Cloud Based Network Management System (NMS)

▪

The Communication architecture uses – IEC 61850 standard for protocols and data models – Encryption and authentication technologies

21.10.2018

ADMS - Advanced Distribution Management System Tutorial: Methods and Tools for Validating CPES

132

RTDS as testing unit for the LOCO PMU ▪

IEEE C37.118.1-2011, C37.118.1a-2014, IEEE Std C37.242-2013

21.10.2018


133

Integration of LOCO into ADMS architecture, field implementation Power supply

Sensors and transducers

Voltage signals in the range ± 10 V Contribution to uncertainty in MCC USB 201 U1) max 0.098 % of reading U2) max 11 mv offset U3) max 0.014 % of full scale (20V) U4) max 2.44 mV due to discretization (12 bits) Utot = sqrt ( U1^2 + U2^2 + U3^2 + U4^2 )

The GPS antenna should have a clear sky view above about a 10-degree elevation

GPS connectivity

LOCO PMU

a - case of signal with 20V peak to peak Utot = 0.02 V  0.1% of the input b - case when the signal has only 10V peak to peak Utot = 0.0105 V  0.11% of the input d - case with signal having only 4 V peak to peak Utot = 0.0055 V 0.14% of the input

Communication bandwidth to support 200 B/s (making approximately 500 MB traffic per month) And delay < 1s

Communicati on Network connectivity 21.10.2018

Network Management System

The NMS should autentificate via OpenVPN and subscribe to SV messages of the PMU


134

Phasor Data Concentrator and cloud applications

▪

Example: testing of transducers in E.ON ERC laboratories brought some short duration voltage drops

[Hz]

▪

Example: histogram of frequency reading in the last 3 hours

21.10.2018


135

RWTH Campus Melaten MV-LV Pilot •

The point of connection to the medium voltage grid (15 kV) made of 2 MV/LV power transformers with nominal power equal to 630 kVA, which convert 15 kV to 400 V. The transformers are connected in power to supply the test hall, the laboratories and the offices of E.ON ERC.

•

LV lines and cabinets in the Test hall with testing equipment (load profiles represent a realistic instance of industrial loads)

•

LV lines and cabinets in the laboratory and offices (load profiles represent realistic instancies of residential and business loads)

Units of ADMS architecture: •

3 MV three-phase sensors (ALTEA)

•

4 LV voltage sensors based on the resistive voltage divider technology

•

1 LV voltage sensor (ALTEA)

•

5 current transducers (MAC)

•

5 Low Cost mPMUs developed by RWTH

Includes: an advanced storage system, electrical vehicles recharge points, PV plants, and wind farms

Black start of isolated distribution grid sections ▪

Direct control of street cabinets to connect/disconnect an aggregated system from the feeder

▪

The EEMS: –

▪

▪

Ensures optimal charging and discharging of batteries in case of availability of excess PV power

–

Ensures coordination of different resources to maintain grid voltage and frequency stability

–

Calculates the PQ set-points to proper utilize available PV

Voltage Controlled Voltage Source Inverter (VCVSI): controls voltage

Two main algorithms: –

Distributed Secondary Control for SOC Balancing

–

Optimization of the PVs, and EESs charging

Secondary Control solves combined voltage&frequency control and active&reactive power sharing –

–

𝜔𝑟𝑒𝑓 such that : •

Restores frequencies at the VCVSI terminal close to nominal value

•

Achieves a desired Active Power sharing among the batteries

V𝑟𝑒𝑓 such that : •

Equalize voltages at the VCVSI terminal close to nominal value

•

Achieve a desired (even) Reactive Power sharing

21.10.2018


Current Controlled Voltage Source Inverter (CCVSI): implements PQ power settings

137

Experimental setup

Implementation of controls in Calvin IoT environment on Raspberry Pi

21.10.2018


138

Results •

Each aggregated load: 20 kW, PV Profile: ascending from 12 to 44.7 kW

•

PV Generation at time 08:21 sufficient to disconnect one battery  different power sharing

•

The disconnection determines a variation of the voltage profiles (still within the 5%); PV Generation at time 09:00 enough to start charging battery at node 2

External Driver for Cyber Physical Energy Systems

Source: ERICSSON - Secrets of utility frontrunners

21.10.2018


140

DSO as a Driver for Lab Testing

21.10.2018


141

Architecture for Automation in Distribution Systems Traditional Distribution Grids HV grid Primary Substation

Smart Grid Scenarios TSO

Primary Substation

HV grid Primary Substation

IED

MV grid

HV grid

TSO Primary Substation

Primary Substation

IED

IED

MV grid

DSO

TSO

Primary Substation

IED

MV grid

DSO

DSO

MGCC

Microgrid MV

Customer MV

Microgrid MV

Customer MV

Customer MV SM

HEMS

HEMS





IED

LV grid

LV grid

IED

IED

LV grid



IED

LV grid

LV grid

LV grid

MGCC Microgrid LV

Customer LV

21.10.2018

Customer LV SM

HEMS

HEMS


142

Testing Environment – from Concept to Demonstrations

Cloud Services (FIWARE)

Power Hardware in the Loop Testing Advanced monitoring

Renewable generation forecast

Demand forecast

Energy management services

Data Analytics

FINESCE platform Distributed Generation

21.10.2018

Industrial Loads


Residential Loads

Electric Vehicles

Energy market

143

The Testing Approach – A Three-Steps Procedure Use cases, e.g.: 1. Monitoring of LV grid (PC + state estimation + RTU + Smart meters + interfaces)

Building-blocks, e.g.: 1. Algorithms 2. Devices 3. Third party devices 4. Third party software

Groups of buildingblocks, e.g.: 1. State estimation algorithm within a PC connected to an RTU via a 61850 interface

st 1 Dev. Lab

nd 2 Integration. Lab

21.10.2018


rd 3 Demo 144

Application Fields: InterFlex Swedish Demos

Dutch Demo

German Demo

French Demo Czech Demo

21.10.2018


145

Impact & Deployment Analyses of the Solutions Bulk Power

Substations

sensors

Distribution System sensors

Transmission System

– Information Flow, Data Management, Monitor & Control

DER Interconnection

Combined Heat & Power

sensors

Interoperability Source IEEE P2030

Interoperability by design – 2 Systems to be interoperable – exchange data and interpret shared data – IT aspect

▪

Demonstrate and showcase Interoperability and Interchangeability in laboratory

– Interchangeability – physical power system component like batteries

▪

Cost/benefit appraisals of the Demos

▪

Scalability and replicability analysis – Scalability – increase in number

– Communication ▪

Load Management

sensors

Communications and Information Technology

▪

EV

Interoperable APIs specification

21.10.2018

– Replicability – different regions/power grids


146

Innovation Stream Abstraction

21.10.2018

Interoperability Analysis

Scalability and Replicability Analysis (SRA)

Laboratory Based Testing

Interchangeability of Components


147

Smart Grid Architectural Model

Source: CEN – CENELEC - ETSI Smart Grid Coordination Group Smart Grid Reference Architecture 21.10.2018


148

Challenges, barriers & obstacles ▪

Same innovation stream BUT Different Use Cases AND Different Architectural Implementations

▪

Substantial wide scope of the topics under study

– SGAM (5 layers) UC Diagrams – 18 UCs in total – 90 possible differences

▪

Challenge in sharing or accessing control system of demos for simulation & Lab based evaluation

▪

Availability of data to calculate the KPIs

21.10.2018


149

Interoperability - Methodology Upper Bound Variants AGGRE GATOR

SCADA

NL USEF EV ChSt.

Lower Bound Variants SCADA

CZ – ripple Ctrl. Field GW

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EV ChSt.


150

Challenges, barriers & obstacles ▪

Selection of a generalized set of actors

▪

Large data base of interfaces

▪

Enabling:

DSO

–

Merging of all demo ICT architectures

–

Cross-demo analysis of InterFLEX demonstrators

Market

Microgrid Controller

Aggregator

▪

–

Cyber-security assessment regarding

–

NIST reference model requirements (in progress)

–

Assessment of the criticality of the interfaces

Guidelines –

To DSO on how to integrate InterFLEX solution

–

Recommendation of Protocols used

–

Input for the definition of an API for flexibility

21.10.2018


Flexibility Customer Storage Grid Storage Electric Mobility Power2Heat

151

Open Test Suite for Laboratory Testing ▪

Identification and knowledge of relevant standards for flexibility, storage, smart appliances (USEF, SUNSpec, SAREF, OneM2M, …)

▪

Define service categories for demos

▪

Selection of the relevant service combinations  Leading to Lab Based Testing

21.10.2018


152

Lab-based testing ▪

Initial teste interfaces –

DSO SCADA and Aggregators

–

Field gateway + Smart appli.

–

Field gateway + Storage

21.10.2018


153

Discussion, Feedback and Conclusions IECON 2018 Tutorial Methods and Tools for Validating Cyber-Physical Energy Systems

Discussion and Feedback ▪

Questions?

▪

Open issues?

▪

etc.

21.10.2018


155

Summary and Conclusions ▪

A structured approach for system-level testing of CPES is necessary

▪

Various simulation and HIL-based methods are nowadays available supporting the design and validation of CPESs

▪

Lab-testing is a necessary tool for rapid prototyping of solutions

▪

Rapid prototyping and laboratory testing leads to faster digitalization of utilities

▪

Lab-based testing enables replicability of experiments and understanding of “what went wrong”

21.10.2018


156

Methods and Tools for Validating Cyber-Physical Energy Systems

Methods and Tools for Validating Cyber-Physical Energy Systems

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