d1.3 report on framework of the project and transferable

This project has received funding in the framework of the joint programming initiative ERA-Net Smart Energy Systems’ focus initiative Integrated, Regional Energy Systems, with support from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 775970.

D1.3 REPORT ON FRAMEWORK OF THE PROJECT AND

TRANSFERABLE BEST PRACTICES VERSION 1.0

Jörgen Rosvall Neil Hancock Maria Edvall Máté Csõre

Emil Hillberg

9 June 2020

D1.3: Report on framework of the project and Transferable best practices

ANM4L – ERA-Net Smart Energy Systems – GA No 775970

INTERNAL REFERENCE

Deliverable No.: D 1.3 Deliverable Name: Report on framework of the project and Transferable best practices Lead Participant: E.ON Energidistribution AB Work Package No.: 1 Task No. & Name: T 1.3 Document (File): ANM4L Deliverable D1.3 - Ver1.0 - approved.docx Issue (Save) Date: 2020-06-09

DOCUMENT STATUS

Date Person(s) Organisation First version 2020-06-09 Jörgen Rosvall

Neil Hancock Máté Csõre Maria Edvall Emil Hillberg

E.ON Energidistribution AB E.ON Energidistribution AB E.ON Észak-dunántúli Áramhálózati Zrt. RISE Research Institutes of Sweden RISE Research Institutes of Sweden

Approval by 2020-06-24 Steering Committee: Olof Samuelsson Markus Mirz Jörgen Rosvall Hjalmar Pihl Stina Hallhagen Emil Hillberg

Lund University RWTH Aachen University E.ON Energidistribution AB RISE Research Institutes of Sweden RISE Research Institutes of Sweden RISE Research Institutes of Sweden

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DOCUMENT SENSITIVITY

☒ Not Sensitive Contains only factual or background information; contains no new oradditional analysis, recommendations or policy-relevant statements

☐ Moderately Sensitive Contains some analysis or interpretation of results; contains no recommendations or policy-relevant statements

☐ Sensitive Contains analysis or interpretation of results with policy-relevance and/or recommendations or policy-relevant statements

☐ Highly Sensitive Confidential

Contains significant analysis or interpretation of results with major policy-relevance or implications, contains extensive recommendations or policy-relevant statements, and/or contain policy-prescriptive statements. Thissensitivity requires SB decision.



Disclaimer

The content and views expressed in this material are those of the authors and do not necessarily reflect the views or opinion of the ERA-Net SES initiative. Any reference given does not necessarily imply the endorsement by ERA-Net SES.

About ERA-Net Smart Energy Systems

ERA-Net Smart Energy Systems (ERA-Net SES) is a transnational joint programming platform of 30 national and regional funding partners for initiating co-creation and promoting energy system innovation. The network of owners and managers of national and regional public funding programs along the innovation chain provides a sustainable and service oriented joint programming platform to finance projects in thematic areas like Smart Power Grids, Regional and Local Energy Systems, Heating and Cooling Networks, Digital Energy and Smart Services, etc.

Co-creating with partners that help to understand the needs of relevant stakeholders, we team up with intermediaries to provide an innovation eco-system supporting consortia for research, innovation, technical development, piloting and demonstration activities. These co-operations pave the way towards implementation in real-life environments and market introduction.

Beyond that, ERA-Net SES provides a Knowledge Community, involving key demo projects and experts from all over Europe, to facilitate learning between projects and programs from the local level up to the European level.

www.eranet-smartenergysystems.eu



EXECUTIVE SUMMARY

One of the pillars of today’s modern society, the ability to generate and distribute electricity to consumers, is critical for the stability and wellbeing of people globally. This is not new; the electrical grid has been designed and maintained for many years. The grid that we know is built upon a unidirectional flow of electricity, from large scale centralized power plants to end-users and with it has come the design principles we use to build and maintain the system. Recent technical developments have allowed small-scale renewable energy sources (RES), both wind and solar, to be economical viable. This has resulted in a paradigm shift forcing our well-known grids to be utilised in a bi-directional manner with an increased amount of distributed generation (DG).

This document, D1.3, will provide an overview of ANM concepts deemed applicable for integration into WP5 demonstration grids. In doing so provide an overview of functions relevant for the implementation of demonstrations in Hungary and Sweden.

ANM (Active Network Management) is the concept of a control system, integrated with ICT and the power system, with the ability to manage generation, load and electrical tolerances for DSO-driven purposes including for example utilisation of flexible network assets (load, production, and other controllable equipment) to provide secure means of increasing grid utilisation without breaching operational limits.

This document includes, as best practices, three different ANM areas/functions: Grid control, Generation control and Energy demand management. Each one of them containing different concepts with pros, cons and transferability from an engineering perspective.

Grid control

• Dynamic Line Rating • Transformer tap changers • Line Voltage Regulator • Reactive power compensation

Generation control

• Active power curtailment • Reactive power generation and consumption

Energy demand management

• Demand Side management • Demand Response • EVs, EVCPs & EVCHs • Energy storage



TABLE OF CONTENT

INTRODUCTION TO ANM4L ................................................................................................. 9

SCOPE OF DOCUMENT ........................................................................................................ 10 2.1 Scope ......................................................................................................................................................... 10

2.2 Notations, abbreviations and acronyms ................................................................................................. 10

BACKGROUND ....................................................................................................................... 12

DEFINITIONS .......................................................................................................................... 14

TODAYS CHALLENGES ....................................................................................................... 15 5.1 Today’s challenges - Sweden ................................................................................................................... 19

5.2 Today’s challenges – Hungary ................................................................................................................ 21

BEST PRACTICES .................................................................................................................. 25 6.1 Grid control .............................................................................................................................................. 25

6.1.1 Dynamic Line Rating (DLR) ..................................................................................................................... 25

6.1.2 Transformer tap changers .......................................................................................................................... 26

6.1.3 Line Voltage Regulator (LVR) .................................................................................................................. 26

6.1.4 Reactive power compensation ................................................................................................................... 26

6.2 Generation control ................................................................................................................................... 27

6.2.1 Active power curtailment ........................................................................................................................... 27

6.2.2 Reactive power generation and consumption ............................................................................................ 28

6.3 Energy demand management ................................................................................................................. 28

6.3.1 Demand Side management (DSM) ............................................................................................................ 28

6.3.2 Demand Response (DR) ............................................................................................................................ 29

6.3.3 EVs, EVCPs & EVCHs ............................................................................................................................. 29

6.3.4 Energy storage ........................................................................................................................................... 29

6.4 Relevant ANM projects ........................................................................................................................... 30

6.4.1 InterFLEX .................................................................................................................................................. 30

6.4.2 CoordiNet .................................................................................................................................................. 30

6.4.3 CLUE ......................................................................................................................................................... 31

6.4.4 iElectrix ..................................................................................................................................................... 31

6.4.5 PARITY ..................................................................................................................................................... 32

6.4.6 PlatOne ...................................................................................................................................................... 32



6.4.7 EUniversal ................................................................................................................................................. 33

SCADA, METERING AND ICT [16] ..................................................................................... 34

POTENTIAL RISKS ................................................................................................................ 36

CONCLUSIONS ....................................................................................................................... 37

REFERENCES .......................................................................................................................... 39



LIST OF TABLES

Table 1 - List of notations, abbreviations and accronyms ..................................................................... 11 Table 2 - Installed capacities of renewable generation from year 2011 - 2018 [19] ............................. 24 Table 3 - General overview of ANM functionality ............................................................................... 37



LIST OF FIGURES

Figure 1 - Installed net power generation capacity in Germany 2002-2019 [2]. ................................... 15 Figure 2 - Wind (Land and Sea) and Solar Power Generation Germany, 1990 – 2019 [3]. ................. 15 Figure 3 - European interconnections, both existing and needed in the future. .................................... 17 Figure 4 - Interconnections between ENTSO-E Members [4]. ............................................................. 18 Figure 5 - Interconnections between ENTSO-E Members. ................................................................... 18 Figure 6 - Swedish Population Growth, 1961-2018 (people per km2) [5] ............................................ 19 Figure 7 - Municipal population change in Sweden 2010-2016 to the left [6] and Population density on Öland to the right [7]. .......................................................................................................... 19 Figure 8 - Hydro and wind power generation overview [8]. ................................................................. 20 Figure 9 - Population of Hungary between 2008 and 2019 [17] ........................................................... 21 Figure 10 - Hungarian population density [17] ..................................................................................... 21 Figure 11 - Transmission power grid structure [18] .............................................................................. 22 Figure 12 - Supply share by sources [18] .............................................................................................. 22 Figure 13 - Installed photovoltaic density (kW) [19] ............................................................................ 23 Figure 14 - Share of renewable power generation in the Hungarian energy mix [19] .......................... 24 Figure 15 - Building blocks of ANM solution ...................................................................................... 35



INTRODUCTION TO ANM4L The ANM4L (Active network management for all) project, anm4l.eu, will develop solutions to enable integration of renewables with the agility required from developments in demand and production.

Alternatives to traditional network expansion are needed to ensure sustainable development of the power grids. New technologies, methods, and markets are emerging to provide increased flexibility in consumption, generation, and power transfer capacity.

ANM4L aims at demonstrating innovative active network management (ANM) solutions to increase integration of renewable energy sources (RES) in electricity distribution systems.

ANM solutions will consider management of active and reactive power to avoid overload situations, maintain voltages within limits, minimize the need of RES curtailment, and enable further RES uptake even above the theoretical design limit of the electricity network.

Core research and development activities include development of:

• Active network management methods for local energy systems.

• Business models to provide decision support for market players.

• An integrated toolbox to support the planning and operation of the distribution system.

The toolbox, methods and business models for ANM will be demonstrated in Sweden and Hungary. The project will also prepare solutions and recommendations for replication in other local and regional energy systems.

The ANM4L project is an international cooperation with a consortium consisting of partners in Sweden, Germany and Hungary:

• RISE Research Institutes of Sweden (coordinator)

• Municipality of Borgholm

• Lumenaza GmbH

• Lund University

• RWTH Aachen University

• E.ON Energidistribution AB

• E.ON Észak-dunántúli Áramhálózati Zrt.

• E.ON Solutions GmbH



SCOPE OF DOCUMENT 2.1 Scope

This deliverable is part of Work package 1 (WP1): Functional specifications based on the needs and need-owners.

The main objective of WP1 is to set the framework of the project and ensure that the demonstrations and associated toolbox take into account the needs of the need-owners and that the KPIs used are able to reflect the true value of the proposed solutions. The needs and need-owners have been outlined previously in deliverables D1.1 & D1.2.

This document, D1.3, will provide an overview of ANM solutions deemed applicable for integration into WP5 demonstration grids. In doing so provide an overview of functions relevant for the implementation of demonstrations in Hungary and Sweden.

2.2 Notations, abbreviations and acronyms

The table below provides an overview of the notations, abbreviations and acronyms used in this report.



Table 1 - List of notations, abbreviations and accronyms

ANM Active Network Management

ANM4L Active Network Management for all (project name)

BESS Battery Energy Storage Systems

DG Distributed Generation

DLR Dynamic Line Rating

DER Distributed Energy Resources

DR Demand Response

DSM Demand Side Management

ERA-Net SES ERA-Net Smart Energy Systems

EVCH Electric Vehicle Charging Hub An electric vehicle charging hub where multiple charging points are gathered.

EVCP Electric Vehicle Charging Point. An electric vehicle charging point is a charging point for a single vehicle.

ICT Information and Communication Technology

LIFO Last-In-First-Out

NLTC No-load Tap Changer

OLTC On-load Tap Changer

PV Photovoltaic

RES Renewable Energy Source

STATCOM Static Compensator

SVC Static Var Compensator

VPP Virtual Power Plant

VRE Variable Renewable Energy

WTG Wind Turbine Generator



BACKGROUND One of the pillars of today’s modern society, the ability to generate and distribute electricity to consumers, is critical for the stability and wellbeing of people globally. This is not new; the electrical grid has been designed and maintained for many years. The grid that we know is built upon a unidirectional flow of electricity, from large scale centralized power plants to end-users and with it has come the design principals we use to build and maintain the system. Recent technical developments have allowed small-scale renewable energy sources (RES), both wind and solar, to be economical viable. This has resulted in a paradigm shift forcing our well-known grids to be utilised in a bi-directional manner with an increased amount of distributed generation (DG).

The grid is built roughly like a spiderweb, with many strong, heavy lines centred on large generation facilities like nuclear power stations. As one travels away from the centre, lines become fewer, lighter and longer. The grid as such is made to manage central generation. Initially this is not a major challenge as grid dimensioning tolerances are able to manage small scale power fluctuations. With increasing demand for renewable energy solutions, the matter becomes increasingly difficult. This is further exacerbated with integration of generation facilities on the periphery of the grid, as often is the case for wind power turbines. Suddenly the small-scale fluctuations caused by intermittent generation (when the wind blows, or the sun is shining) become large scale fluctuations on relatively weak grid infrastructure. To avoid total collapse of the grid, current and voltage tolerances are implemented (i.e. capacity constraints). These levels result in the automatic curtailment of generation installations.

Thus, without help, the grid as we know it will eventually be unable to further integrate renewable generation, as capacity constraints are reached. As has been seen during 2019 [1], these constraints will in turn reduce the ability of, for example, industries to develop. To solve the problem, grids can be rebuilt, but as can be imagined, the total renewal of the grid is unacceptably costly. Fortunately, whilst renewable generation has been developing, so to have communication systems.

Grids are generally passive systems. They are designed with forecasted load profiles and are often over-dimensioned to be able to manage daily load peaks during the morning and evening. By implementing active communication solutions, we can now actively monitor voltage and current loads in the grid and by doing so are able to know exactly how much capacity is available in the grid before renewable energy curtailment is required. Furthermore, it allows us to maximise the number of integrated RES on each part of the grid before needing to investigate grid reinforcement options.

As always, it’s never that easy. As RES are implemented on actively monitored powerlines, we increase the electrical current in the lines. At the same time the RES cause voltage fluctuations, and with increasing size or numbers of RES, these voltage fluctuations grow until the voltage becomes a limiting factor for curtailment.

With this in mind, the ANM4L project will demonstrate methods for Active Network Management (ANM) to actively monitor powerlines, allow for increased RES integration and demonstrate voltage control through integration of both hardware and IT solutions, whilst also providing an economic understanding of the solutions demonstrated.

Reasons for taking this step now:

• Providing connections faster and cheaper than with traditional solutions



• Facilitation of increased renewable integration

• Managing intermittent low-carbon technologies

• Reducing capital expenditure due to reduced demands for grid reinforcement

• Technological readiness – the technology required to implement ANM is now sufficiently fast, reliable and has a low cost



DEFINITIONS ANM (Active Network Management): is the exploitation of flexible network assets for the purpose of providing secure means of increasing grid utilisation.

ANM solution: is the concept of a control system, integrated with ICT and the power system, with the ability to manage generation, load and electrical tolerances for DSO-driven purposes.

Flexible network assets: assets in the grid (load, production, and other controllable equipment) with the ability of being controlled to support grid needs.

Power transfer capacity: the ability of the grid (cables, lines, transformers, etc.) to transfer electricity between generation and demand. 1

Demand Side Management (DSM): flexible load assets which can be directly controlled by the DSO for operational network security purposes. DSM is used for balancing intermittent generation (wind and solar generation) when the timing and magnitude of energy demand does not coincide with the generation.

Demand Response (DR): flexible load assets which need to be procured on the market by the DSO (e.g. direct from suppliers or via aggregators), but not being directly controlled by the DSO itself due to market distortions.

1 The power transfer capacity has physical limitations (thermal and stability) and limitations based on

standards (power quality) and protection settings.



TODAYS CHALLENGES The 11th of March 2011 could be considered the day the world changed its views on renewable energy solutions for grid infrastructure. It was on this day that the Tōhoku earthquake and tsunami caused irreparable damage to the Fukushima Daiichi nuclear power plant in Japan. The consequences were profound with many countries banning the use of nuclear power. Germany declared that it would close all of its nuclear power facilities by 2022.

In its place, a major programme was started for the integration of new solar and wind power solutions. Large scale introduction of RES to not only replace nuclear power but also meet future demand has put a new demand on existing electrical grids. Central generation is being replaced by local “prosumption”.

Figure 1 - Installed net power generation capacity in Germany 2002-2019 [2].

Figure 2 - Wind (Land and Sea) and Solar Power Generation Germany, 1990 – 2019 [3].



As a result, the energy policies, generation and consumption profiles of each country impact the energy characteristics of other countries. Thus, the German RES initiative, see

Figure 1 - Installed net power generation capacity in Germany 2002-2019 [2]. and

Figure 2, has had a resounding effect on surrounding countries in Europe. Furthermore, the German initiative is not stand-alone. Many EU countries face similar challenges and have adopted similar strategies. The Continental European Power System is a single synchronous AC grid, the equilibrium of which is the responsibility of each connected country, so as to maintain a 50Hz balance of the total system. The connection with surrounding synchronous systems (such as the



Nordic power system) have a direct impact on the electricity market, see Figure 3, Figure 4 andFigure 5.

Figure 3 - European interconnections, both existing and needed in the future.



Figure 4 - Interconnections between ENTSO-E Members [4].

Figure 5 - Interconnections between ENTSO-E Members.



Figure 6 - Swedish Population Growth, 1961-2018 (people per km2) [5]

5.1 Today’s challenges - Sweden Sweden is an oblong country (approx. 1500x400km) with large areas of sparsely populated landmass found especially in the northern two-thirds of the country. The country is seeing a continuous population growth (Figure 6) which is not expected to reduce in the coming years. Furthermore, there is a continuing trend for urbanization of the population with migration of people towards city centres, (Figure 7).

Figure 7 - Municipal population change in Sweden 2010-2016 to the left [6] and

Population density on Öland to the right [7].

This population growth, and clear urbanisation of the population is putting great strain on the existing grid infrastructure. The delivery of electricity is regulated such that all applications for electrical connection and supply must be met with the same supply quality and delivery requirements as all other connections. As such the cost for maintenance of rural grids, with a reduction in population, is increasing to such an extent that integration of local energy systems may be economically feasible. With this in mind it is also important to consider the placement of generation facilities in the country.

Natural resources allow for hydroelectric and wind generation of electricity in the north of the country see Figure 8, whilst additional nuclear generation is contained to the south of the country. With most of the population situated in the south of the country, one of the major electrical challenges is transmission and distribution of northern power production to southern power consumption. The site for the ANM4L demonstration in Sweden is Öland, an island off the eastern



coast of the southern mainland. Öland can be compared to the mainland of Sweden in both its shape, power generation and population demographics. A large portion of Öland’s power requirement is generated by RES in the northern end of the island, whilst much of the consumption occurs in the mid to southern end of the island.

To further compound the problem, the influx of tourists and short-term residents to the island from Easter to the end of August each year results in an inverted power consumption profile (compared to the typical Swedish electricity profile with maximum demand occurring during winter). The problems are expected to increase with the integration of electric car chargers, especially in areas of high “short term residential” populations.

Figure 8 - Hydro and wind power generation overview [8].



5.2 Today’s challenges – Hungary Hungary’s population was slightly above 10 million at the end of the 2000’s, but this number has started to decrease, and last year measured less than 9,8 million according to the Hungarian Cen-tral Statistical Office, Figure 9. The population density of Hungary differs regionally, but the central region around the capital, Budapest, has the highest numbers as seen in Figure 10.

Figure 9 - Population of Hungary between 2008 and 2019 [17]

Figure 10 - Hungarian population density [17]

9600000

9650000

9700000

9750000

9800000

9850000

9900000

9950000

10000000

10050000

10100000

2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019

Popu

latio

n [p

erso

n]

Time [year]

Population of Hungary

person/km2



The Hungarian power grid is moderately interconnected with the neighboring countries, as seen in Figure 11 below.

Figure 11 - Transmission power grid structure [18]

The landscape enables the utilization of different renewable energy resources, such as solar, wind or hydro, but biomass and waste are also common solutions. The energy mix of Hungary is slightly inhomogeneous, but for a long time the Paks nuclear power plant has been providing half of the produced electricity in the country. The share of supply from different sources in the past years can be seen in Figure 12, in which the contribution of electrical power provided by RES is almost negligible.

Figure 12 - Supply share by sources [18]



The country has several challenges that require modern technical solutions and well-planned short-, mid- and long-term strategies. Hungary is in need of significant electricity and gas imports, so reliable interconnections with neighboring networks are critical. Paks has been providing 50% of the country’s electricity demand for the past 50 years, but now reaches the end of its operational lifetime, expected between 2030 and 2040. Expansion of nuclear power capacity of the plant are expected: 2x 1200MW power units will replace the currently operational 4x 500MW power units [21].

Reduction of coal-based energy production is ongoing. Compared to 2018, last year 16% less lignite-, and 23% more gas-based power was generated [19]. Hungary’s biggest coal-fired power plant, the Mátra Power Plant, is going to reach the end of its operational lifetime by the end of decade, so the share of coal-based power generation will be further reduced – Reutilization of the land will allow for a new solar park, gas turbine, energy storage system and incineration plant [21]. Natural conditions in this northeastern region enables efficient utilization of PV generation, but PV generation is popular in other areas across the entire country. (Figure 13)

Figure 13 - Installed photovoltaic density (kW) [19]

The Hungarian National Energy Strategy 2030 and the National Energy and Climate Plan consid-ers the Hungarian energy mix to mainly consist of nuclear and RES - energy. The level of RES integration is increasing as can be seen in Figure 14.



Figure 14 - Share of renewable power generation in the Hungarian energy mix [19]

Regarding RES power supply, Hungary relies mainly on solar, hydro and wind power generation, of which photovoltaic capacities are the fastest growing sources: in the last few years the PV generation grew more than 40%. By the end of 2019, slightly less than 1000 MW photovoltaic capacity became available – this number can be expected to grow up until 8-10 GW by 2030 –, of which 400 MW was household-size small power plant [20]. The Hungarian regulation of wind power is strictly controlled, limiting the installation of new turbines. The wind power capacity has stagnated at the level of 330 MW, and its utilization is around 20-25%, whilst, in for example hydro power capacities are over 40% [19]. Statistics of weather dependent renewable resources can be seen in Table 2 below.

Table 2 - Installed capacities of renewable generation from year 2011 - 2018 [19]



BEST PRACTICES In this chapter we present some of the ANM solutions available today to avoids grid reinforcements due to capacity and voltage problems.

The focus in ANM is to control active and reactive power to maintain voltage limits throughout the network as well as avoiding overload situations. Due to the relatively low X/R ratio of the cables and line in the distribution network overload and voltage control cannot be decoupled as in transmission network. Both active and reactive power has an impact on both line loading and voltages in the network.

To avoid blackouts and/or potential damage to customer equipment, it is important to keep the voltages at the customer point of connection within their limits. Therefore, development of methods for voltage control (in distribution systems) are needed. The voltage control can be performed by different means, for example by a physical equipment such as an online tap changer or by changing and/or limiting the flow of active and/or reactive power.

6.1 Grid control

6.1.1 Dynamic Line Rating (DLR) Dynamic line rating is a known method to maximize the ampacity the powerline/cable depending on the environmental conditions. This method is also known as real-time thermal rating (RTTR). Real-time information of the temperature of the powerline/cable and the installation can ensure the safety of the powerline/cable, avoid unnecessary stress of the material and calculate the actual ampacity of the powerline/cable.

One example is that for an overhead line used for a windfarm is normally exposed to the same wind that makes the turbines generate power and therefore the cooling of the line is higher than for the conditions when the static rating of the line is calculated. The more the wind blows the more the turbines generate and the more ampacity of the line.

Generally, most electrical grids have historically been developed without the need for ‘real time’ measurements of grid loads. In most cases the grid has been designed to maintain a safe distance between electrified powerlines and the ground. Powerlines, being metal, expand when heated, either as a direct result of the environmental conditions, or in direct response to line resistance, resulting in heat generation. Expansion of the lines causes them to sag and can eventually cause them to hang at an unsafe height above ground unless the line loading is somehow controlled.

Most powerlines have historically been engineered to manage single directional power distribution. Expected power loads are relatively easy to calculate in this type of system and thus relatively accurate predictions of maximum sag due to temperature can be made. With the advent of distributed power generation and the requirement for multidirectional power solutions, this technique, whilst still generally applicable is becoming less accurate. Eventually a replacement technique will be needed likely entailing active measurement solutions capable of providing real time data of power loads, temperatures and even height above ground.

Grids designed without active management are basically over-dimensioned to cater for sag. Unfortunately, increases in power demands on the periphery of the grid due to, for example, integration of RES has resulted in the capacity demand outgrowing the physical and safe capability of the powerlines. Rebuilding the grid to cater for RES is in most cases not an economically viable option. Secondly the time required to do so, often due to permit processes, is too long to be able to manage the expected rate of integration of RES and other decentralized technologies such as electric vehicles in a safe and controlled manner.

DLR is a technique whereby a measurement unit is physically attached to a critical aerial power line. This unit is then able to measure real time temperature and electrical current levels, along



with wind speed, ambient temperature. The real time data is transmitted remotely to the electrical operations center. In most cases the increased accuracy allows for increased power transmission through the line without breaking line height requirements – as such less curtailment of RES is needed, increasing available renewable power, whilst decreasing the need for acute and expensive line reinforcement projects.

This method has been previously tested by E.ON Sweden [9] resulting in decreased curtailment of integrated wind turbines. Whilst the technique is good for aerial grids, it is less accurate for measurement of ground cable grids whereby buried cables can alter temperature across the length of the line due to ground environmental conditions. Some parts of the same cable may be laid in wet environments allowing effective cooling, whilst others parts may be tunneled through bedrock whereby the surrounding air actively insulates the cable and warms the rock surrounding, lower the cables ability to cool and thus reducing its maximum power distribution capability.

6.1.2 Transformer tap changers Most often found within the distribution grid, no-load tap changers (NLTC) allow limited voltage flexibility of transformer voltages at the given geographical point. This allows grid planners to effectively mitigate voltage drop of long distribution lines by increasing local transformer voltage output. This setting is most often set during powerline deployment work, and never altered. It is however possible to alter, but requires that power is cut before doing so.

The opposite to no-load tap changer, an on-load tap changer (OLTC) can be managed during operation and are usually found in the transmission grid. They are normally operated by an automatic voltage control relay that decides the position of the tap changer and usually give a larger voltage flexibility. An online tap changer can be operated remotely.

The automatic voltage controller can be configured in different ways, to consider the actual total load (line drop compensation) or to keep the voltage at the secondary side at a certain level. In an ANM project the automatic voltage controller can be controlled so it is coordinated with other ANM devices to keep the voltage on the whole line within the limits.

The advantages with on-load tap changers are that they do not introduce any additional losses and that the voltage range, in which it can be controlled, is rather wide.

The disadvantage with on-load tap changers are that they are rather slow and there are mechanical wearing/deterioration when operating them.

6.1.3 Line Voltage Regulator (LVR) A Line Voltage Regulator (LVR) (also known as Series Voltage Regulator) can be used in a distribution system to have control over the voltage for an individual feeder without affecting other feeders in the grid. The LVR decouples the medium voltage line and resets the voltage bandwidth of the line, i.e. the voltage is maintained unaffected at the HV/MV substation.

The LVR automatically adjusts the voltage to the wanted voltage level. The LVR can be installed close to DG, where there are voltage violations due to local generation but still not limited by the ampacity of the applicable connected grid. This will prevent that the DG is curtailed due to the voltage level and as such, increased integration of RES is possible.

6.1.4 Reactive power compensation In the transmission network where the X/R ratio is large, reactive power is used to control the voltage level. For distributed network the ratio is not as large and therefore both the active and reactive power influences the voltage level.

The reactive power can be controlled by shunt capacitors and reactors, STATCOMs, SVCs and similar equipment. Shunt capacitors and reactors provide static passive compensation and they



are either permanently connected or possible to switch. STATCOMS and SVC (Static VAR compensators) devices provide active compensation, have fast switching capability and can both absorb and generate reactive power.

Devices with static passive compensation should be used to supply the normal reactive load requirements in the grid. Switching of shunt capacitors/reactors can cause stress of other electrical equipment in the grid why unnecessary switching should be avoided. Instead devices that provide active compensation should be used for instantaneous responses to transients or other events in the grid. A balance between static and dynamic devices is necessary to maintain the system voltage.

Whilst these devices are expected to provide large scale voltage management of the transmission grid, the distribution grid is expected to host a large portion of RES installations. The decoupling between active and reactive power is based on the fact that the series impedance of transmission lines is largely reactive, and the descriptive X/R ratio is typically 10-20.

While it is easy to believe that transfer capacity and voltage management is easier in distribution networks since they have a radial structure and largely unidirectional power flow, it is rather the opposite. Distribution lines and cables instead have an X/R ratio of about 0.5-1. Without the decoupling between active and reactive power, control in distribution grids is suddenly more complicated than that of transmission grids: Active power has a considerable impact on both line loading and voltages, and the same is true for reactive power which here has less impact on voltage. [16] However, the sheer number of available assets capable of reactive compensation (e.g. PV installations) in tomorrow’s grid is expected to allow smaller contributions to ANM but with greater flexibility than found in large scale, single site ANM assets.

6.2 Generation control

6.2.1 Active power curtailment Normally RES wants to deliver as much active power as possible. The active power, due to the low X/R-ratio in the distribution grid, leads to a voltage rise at the point of connection. One way to limit the voltage rise is to curtail the active power from the RES. This type of voltage control is not optimal due to that it means spilling a part of the available energy from sources as wind power and PV plants. This energy is, without storage, not possible to shift to another time of consumption.

The active power curtailment should be used first after the DG has depleted its capability to reduce the voltage by reactive power consumption.

It is important to note that active power curtailment is rarely used, and then usually for short durations to alter a small percentage of available energy. If the cost of curtailed energy is lower than the cost of rebuilding the network, or if the connection of the DG can be provided faster (i.e. connection cost reduction) active power curtailment can be cost-effective for the owner of the DG.

One problem with curtailment is, when there are several DGs in the grid, how should the schedule for curtailment be - which DGs should be curtailed and at what cost?

Curtailment of generation can be considered as Active Network Management in a native form. Curtailment of WTGs and PVs in an ANM perspective requires a set of rules that allows for non-discriminative control and at the same time can protect the generator. For example, Last-In-First-Out (LIFO) or Pro-rata.



LIFO means that any binding network constraint is resolved by curtailing all generators in reverse order in which they applied for connection to the network. In this way, generators are protected against greater curtailment caused by the connection of another DG.

Pro-rata curtailment resolves constraints based upon each generator’s proportional contribution. As such, curtailment is shared equally amongst all generators that are exporting into the network at the moment of the constraint.

6.2.2 Reactive power generation and consumption As mentioned in 6.1.4, in the transmission network where the X/R ratio is large, reactive power is used to control the voltage level. For distribution grids, the ratio is not as large and therefore both the active and reactive power contributes to the voltage level.

DG with power electronic converters can control the reactive power and contribute to the voltage control.

PVs can contribute to immediate reactive power support to the grid for voltage regulation since they have reactive power capability integrated into the inverter’s control features. Provided that the PVs terminal voltage and current ratings are not exceeded the inverters have the capability to both generate and consume reactive power. The reactive capability of inverters is normally limited by the internal current, voltage, and temperature constraints. As such, in a simplified understanding, the amount of reactive power the PV inverters can provide might not be proportional to the active power generation, depending on consumption.

The total reactive power requirements from the grid owner can sometime be beyond the reactive capability of the PV inverters. This demands installation of additional dynamic or static reactive power devices that need to be managed and controlled in coordination with the PV inverters to effectively control the voltage.

6.3 Energy demand management The voltage can also be controlled in the distribution grid by controlling the load, by shifting active power flows. Not all types of loads can be used for this control method, typically it should be loads that do not affect the comfort for the users in the grid, suitable types include loads with storage or loads that have a slow system such as ventilation, heating/cooling. Charging of electrical vehicles can also be considered.

Load control can be used both for preventing overload and to maintain bus voltages. To be able to regulate the voltage both up and down the loads needs to be controlled in both ways, both a reduction and an increase of the active power consumption must be possible.

This method demands a complex coordination and control between the loads and the grid.

There are different flexibility solutions related to customers in the grid, related to both demand response (DR) and demand side management (DSM).

6.3.1 Demand Side management (DSM) Flexibility assets as part of DSM can be directly controlled by the DSO for operational network security purposes.

In the case of DSM (direct DSO activation), a contractual bi-lateral agreement between DSO and customer can allow the DSO to control flexible loads directly. This provide the ability to increase or decrease e.g. household power consumption, thus making residents direct contributors and part of the solution by adding grid supporting flexibility. Such an approach cuts down on transaction costs, allows reactive strategies and reduces complexity. However, the difficulty lies in ensuring



efficient allocation of flexibility and identification of adequate remuneration rates, which implies new tariff constructions but with the limitation of grid fees.

One of the challenges faced by ANM4L is the active engagement of locally connected households. Normally household electrical meters do not have high enough resolution to perform DSM actions with the correct timestamp and/or at an optimal interval. A possible solution, or mitigation, can be to add high resolution metering in an aggregated point of high strategic value (such as on the LV level in a substation) and treat all underlying controllable assets as one unit (similar to VPP strategies).

6.3.2 Demand Response (DR) Flexibility in the form of DR need to be procured on the market by the DSO (e.g. from suppliers or aggregators), not being directly controlled by the DSO itself due to market distortions.

In case of a market-based approach (i.e. DR), flexibility requests and offers are matched in a market. This is usually done by aggregators handling the bidding and end-customer activation to ensure adequate pricing, efficient allocation and access to flexibility. This is a more complex approach with numerous interactions and limited number of market participants for liquid transactions.

6.3.3 EVs, EVCPs & EVCHs EVs, EVCPs and EVCHs are loads that can potentially be controlled for utilization as an ANM asset.

Limitations for charging vehicles equipment can for example be implemented so that they correspond to the actual availability of power in the grid and capacity of the grid. There is also a possibility to shift the charging power in time depending on the usage of the car. There are today existing solutions of smart charging vehicle equipment, where the user allows the equipment to schedule the charging depending on when the car will be used.

Some DSOs have customized their solutions by constantly limiting the power of charging, together with a lower charging cost (tariff construction with decreased grid fee). This results in longer charging time but is an easily performed action for mitigation of capacity issues.

6.3.4 Energy storage With development of aggregation potential, the utilization of large-scale storage facilities and commercial sized batteries potentially allows for flexibility and ANM-solutions.

Utility scale stationary battery storage systems is also referred to as front of meter, large scale or grid scale battery storage. Because of the battery storage system unique capability to quickly absorb, maintain and then reinject electricity, they are evolving as one of the potential solutions to increase system flexibility. This flexibility will enable a greater share of variable electricity sources like wind and PV in the distribution system and enabling optimal use of them minimizing the need for curtailment. Congestions in the grid can be avoided by shifting power generation in time.

Besides increasing the flexibility, the batteries can also provide with grid services such as frequency response, regulation reserves and ramp rate control.

These battery storage systems have a typical storage capacity ranging from around a few megawatt hours (MWh) to hundreds of MWh. Li-ion batteries is the most common technology used today for large scale battery storage.

Local residential energy storage solutions, when aggregated, can allow for extended flexibility and can add to the overall ANM-solution. The difficulty of local residential assets is the



investments required by the residential customer (consumer/prosumer) and also enabling remote control for ANM purposes of such local assets. However, the potential energy saving and the possibility to retrofit legacy solutions (for example existing heat pumps and water boilers) with new functionality can become an advantage for the residential customer – likely then driven by an aggregator.

6.4 Relevant ANM projects Below are relevant projects listed and reviewed to find out lessons learnt and best practices in the projects but also to investigate if solutions can be reused and integrated in the ANM4L toolbox.

6.4.1 InterFLEX InterFlex was co-funded by the European Union’s Horizon 2020 research and innovation programme. The project was completed in December 2019 [10].

InterFlex investigated the use of local flexibilities to relieve distribution grid constraints.

The project explored new solutions to foster the development of distributed energy resources and to prepare the electric system for new uses, including e-mobility.

Business cases

• InterFlex experimented the local trade of flexibilities for distribution grid purposes in DSOs developed dedicated IT platforms to share actual and potential flexibility demands with commercial service providers, the aggregators. The DSOs aimed at sourcing flexibilities on local markets to optimize the operational performance of the grid management.

• InterFlex experimented the use of a wide range of demand response flexibilities, through different activation channels and based on country-specific needs. In the German demonstration, the effective need for frequent curtailments gave preference to the direct DSO-control of flexible loads. Flexibility activations by service providers, through local flexibility markets, have been tested in France and The Netherlands, whereas the Swedish demonstration in Simris has looked into the specificities of a Citizen Energy Community. In the Czech Republic, the charging power of electric vehicles connected to the DSO’s charging stations could be curtailed in case of distribution grid constraints. The comparative analysis provided insights into the respective advantages and challenges.

• InterFlex experimented the local trade of flexibilities for distribution grid purposes. In the French and the Dutch demonstrations, the respective DSOs developed dedicated IT platforms to share actual and potential flexibility demands with commercial service providers, the aggregators. The DSOs aimed at sourcing flexibilities on local markets to optimize the operational performance of the grid management. Grid automation relies on a set of technologies that can enhance distribution grid management, for example by stabilizing the grid voltage through autonomous power control, by remotely managing distributed generation units and by deploying control boxes associated to smart meters that can contribute to relieving grid constraints.

6.4.2 CoordiNet The CoordiNet project [11] is about large-scale demonstrations of innovative grid services through demand response, storage and small-scale (RES) generation.



The CoordiNet project will help to demonstrate how DSOs and TSOs shall act in a coordinated manner and use the same pool of resources to procure grid services in the most reliable and efficient way through the implementation of large scale “TSO-DSO-Consumer” demonstrations, in cooperation with market participants (and end users):

• To a smart, secure and more resilient energy system through demonstrating cost-efficient model(s) for electricity network services that (i) can be scaled up to include networks operated by other TSOs and DSOs, (ii) that will be replicable across the EU energy system, and (iii) provide the foundations for new network codes, particularly on demand-response.

• Contribute to opening up significant new revenue streams for consumers to provide grid services and increase the share of RES in the electricity system.

• Test different services such as balancing, congestion management, controlled islanding and voltage control. Tests are performed with the resources considered in the different demonstration locations.

6.4.3 CLUE The CLUE project (Climate Neutral Urban Districts in Europe) [12] tackles the challenges modern sustainable cities are facing. A climate neutral urban district uses innovative new technology and building techniques to reduce its carbon footprint.

The objective of the CLUE project is to increase the local and regional capacity in policy development which aim to facilitate the implementation and assessment of new solutions and technologies for a low carbon economy in urban areas. The consortium brings together local and regional authorities as well as universities from 9 European countries, which are developing climate neutral urban districts.

CLUE explores best practices in planning and implementation of systems, solutions and technologies for climate neutral urban districts as well as methods for measuring, monitoring, reporting, verifying and assessing climate mitigating efforts. The project activities result in best practice guides and policy recommendations on the integration of climate aspects in the urban development process. In addition, CLUE partners develop guidelines for measuring, reporting, verifying and assessing climate neutral technology as well as implementation plans for all participating regions.

6.4.4 iElectrix iElectrix is a response to the Horizon 2020 call for proposals of the European Commission to: “Integrated local energy systems (Energy islands)” [13]. This call addresses the challenge of a single and smart European electricity grid in integrating renewable energy sources. This call promotes the enabler role of the Distribution system operators to connect Local Energy Communities to the network.

Objectives and ambitions

• Increase RES integration into the network

• Connect Local Energy Communities to MV & LV networks

• Build flexible and smart micro-grids

• Increase grid resilience and thereby security of supply

• Improve consumers’ involvement (prosumers)



• Develop innovative and sustainable technical solutions and business models

6.4.5 PARITY The aspiration of PARITY project is to address the “structural inertia” of existing distribution grids by delivering a transactive grid & market framework [14].

PARITY will go beyond the traditional “top-down” grid management practices by delivering a unique local flexibility market platform through the seamless integration of IoT and blockchain technologies.

By delivering a market for automated flexibility exchange based on smart contracts & blockchain, PARITY will facilitate efficient and transparent local flexibility transactions and reward flexibility in a cost-reflective and symmetric manner, through price signals based on real-time grid operational constraints and available DER flexibility.

By deploying State-of-the-Art IoT technologies PARITY will offer distributed intelligence (DER profiling) and self-learning/self-organization capabilities (automated real-time distributed control), orchestrated by the cost- reflective flexibility market signals generated by the blockchain market platform. Within PARITY, DERs will form dynamic clusters that essentially comprise self- organized networks of active DER nodes that will efficiently distribute and balance global and local intelligence, enabling real-time aggregated & P2P transactions through enhanced forecasting, optimization and control of DER flexibility.

Finally, the PARITY solution includes novel tools for Active Network Management, including an innovative STATCOM and PQ monitoring device, that will enable the DSO to enhance its management capabilities, grid observability and RES hosting capacity.

6.4.6 PlatOne PlatOne – PLATform for Operation of distribution NEtworks – is a four-year Horizon 2020 funded European project [15].

PlatOne aims at defining new approaches to increase the observability of renewable energy resources and of the less predictable loads while exploiting their flexibility.

The consortium of 12 partners from Belgium, Germany, Greece and Italy will develop advanced management platforms to unlock grid flexibility and to realize an open and non-discriminatory market, linking users, aggregators and operators. The solutions developed in the project will be tested in three European demonstration examples - German demo, Italian Demo and Greek demo.

The German demo focusses on a low voltage network in a rural area with a high penetration of distributed energy resources (DER). It is these regions where a high potential for DER meets a low residential and commercial load where the challenges of the energy transition surface first.

The main objectives of the trial are the coordination between local balancing mechanism and centralized grid operation and the allocation of flexibility in local networks between the local network and higher-level networks. A further objective is an effective informational and temporal uncoupling of low and medium voltage networks by handling energy supply and export in bulk packages rather than a real time exchange

The Italian demo will carry out a comprehensive implementation of a local flexibility market, realizing it within a large metropolitan area of Rome. Therefore, it will involve various types of users located in different parts of the eternal city. Specifically, there will be a wastewater treatment plant connected directly to the primary cabin, a virtual energy community in low-voltage, residential homes equipped with renewable energy sources, a business smart building and electric vehicle charging station pools.



The Greek demo is located in the area of Mesogeia at the south-eastern part of Attica, near Athens. The area combines parts of mainland and interconnected islands with a good penetration of various types of renewable energy sources, provides a mix of rural, urban and suburban areas with a customer mix including households and small, medium and large industries.

6.4.7 EUniversal The recently started EUniversal project is an innovative European funded project that aims to enable the provision of market-based flexibility services to system operators through the implementation of the so-called Universal Market Enabling Interface (UMEI), which represents an innovative, universal, adaptable and modular approach to interlinking active system management with electricity markets.

The primary goal of EUniversal is to implement the UMEI concept by bringing forward a universal, open, adaptable and modular approach to interlink active system management with electricity markets and foster the provision of flexibility services, also acknowledging the activation needs of and the coordination requirements with other commercial parties and TSOs.

A set of market-oriented flexibility services from DERs will be implemented to answer DSOs’ needs in a cost-effectively way, supporting the energy transition.



ICT INTEGRATION OF THE ANM4L TOOLBOX [16] Interoperability is becoming increasingly important in the digitalized power system, especially vertically between TSO and DSO. This is highlighted by the TSO-DSO Data Management Report, which describes the need for a deeper cooperation between TSOs and DSOs. Furthermore, the focus should be on services rather than platforms. The same service can be provided by different platforms. Hence, a deeper integration does not necessarily require the use of the same platform. Focusing on services enables a faster transition than trying to move all partners to a specific platform. To provide access to a service, the user only requires a specification of its Application Programming Interface (API). The source code implementing the service is not required.

While IEC61970 Common Information Model (CIM) is becoming the standard to exchange grid data for planning purposes, a standard API for planning and operational services is not yet defined. Similar efforts can be observed in other EU projects, such as PlatOne, which propose APIs for operational tools. Services for grid management facilitate not only the data exchange but also the access to functions on this data by TSOs. Besides, standardized interfaces support flexibility in the IT system of DSOs, which allows them to replace parts of their infrastructure without affecting other parts. An API description is required to be able to use a service. The intention is to build a modular toolbox using Representational State Transfer (REST) APIs, which are widely used for webservices and programming language agnostic. Hence, all partners using or implementing parts of the toolbox are free to select a new or maintain their current technology stack. OpenAPI is a project to standardize the specification of REST APIs. The advantage of OpenAPI is that many tools exist to either present the API in a human readable format or generate source code to implement the API in a certain programming language. This further increases the accessibility of the provided services.

The ANM4L toolbox, will essentially consist of two parts:

1. Planning package

2. Operations package

The aim of the planning package is to provide information to the grid planners on the level of impact a set of ANM solutions (technical and financial) would have on the network. The planning package features an API that allows the user to upload grid data, manipulate the data and run various types of simulation and analysis. The main use cases considered are:

• Outage Planning and Contingency Analysis

Reinforcement and Reinvestment Planning

To support these use cases, the modules presented in Figure 15 are identified as basic building blocks of the planning package.



Figure 15 - Building blocks of ANM solution

The aim of the operational package is to provide the operators of the grid with knowledge on the status of the grid and available ANM capabilities to maintain the grid in secure operation. The operational package interacts with field devices to monitor the grid and distribute new set points for controllable field devices and flexible assets.

In order to maximize the control possibilities, the operational package will be open for all possible flexibility solutions, related to both DR and DSM. Flexibility in the form of DR need to be procured on the market by the DSO (e.g. from suppliers or aggregators), but not being directly controlled by the DSO itself due to market distortions. Flexibility assets as part of DSM can be directly controlled by the DSO for operational network security purposes.

In the case of DSM (direct DSO activation), a contractual bi-lateral agreement between DSO and customer can allow the DSO to control flexible loads directly. This provide the ability to increase or decrease e.g. household power consumption, thus making residents direct contributors and part of the solution by adding grid supporting flexibility. Such an approach cuts down on transaction costs, allows reactive strategies and reduces complexity. However, the difficulty lies in ensuring efficient allocation of flexibility and identification of adequate remuneration rates.

In case of a market-based approach (i.e. DR), flexibility requests and offers are matched on a market platform. This is usually done with aggregators handling the bidding and end-customer activation to ensure adequate pricing, efficient allocation and access to flexibility. This is a more complex approach with numerous interactions and limited number of market participants for liquid transactions.

The operational package includes a flexibility market platform with the aim to facilitate the engagement with end users to provide supply and demand side flexibility potential to the ANM solution. The market platform handles all aspects of end user engagement (business, technical, and communication) and is integrated with the ANM via open APIs.



POTENTIAL RISKS The following potential risks are identified if ANM is not practiced:

• Where ANM would have been motivated to use, the connection might be more expensive, take longer time due to reinforcements.

• The connection of new RES might be more difficult, when facilitating for these connections to the grid, resulting in a reduced number of new connections of renewables.

• Increased cost to customers due to reinforcements. Operational solutions enabled by ANM have the potential, in certain circumstances, to be more cost effective and less carbon intensive than traditional capital expenditure approaches.

The following potential barriers are identified to establish ANM:

• Timing and the risk of stranded investments: Which customer will start accepting the ANM conditions, and will others follow?

• Operational costs, lack of value: is there a business case for the customer?

• The complexity is large, raising the thresholds for DSOs and customers.

• Industry culture, the electric industry is often perceived as conservative, giving priority to conventional solutions rather than innovation.

• Due to unbundling regulations, DSOs are prevented from engaging in certain activities. Depending on the type of flexibility market, this could make implementation legally complex.

• DSOs are treated as natural monopolies with revenues regulated by national regulators. Depending on how these regulations are designed, DSOs may not have any financial incentives to engage in flexibility markets.

• There is a risk that the ANM system would be underutilized and may impose large costs on a small number of customers if there are not enough customers that wish to connect to that part of the network.

• ANM requires sharing of a large amount of information between the DSO, customers and/or aggregators.



CONCLUSIONS The ANM4L project deliverable D1.3 has attempted to highlight potential concepts viable for application in the ANM4L ambition of finding alternatives to traditional network expansion. These findings are laid out in Table 3 below, along with expected pros and cons to their utilization.

The comments/conclusions found in Table 3 are needed to be understood from the perspective of pure engineering solutions. There applicability needs now to be weighed against the techno-economic constraints found in real world application. This work is to be produced in the next phase of the project, through application of business models and cost benefit analysis of the proposed solutions.

Furthermore, many of the solutions presented below are available in some form today. These will need to take into account necessary requirements required of each, in order to be utilized in the greater ANM4L solution. This will include such things as ICT solution integration.

The development of algorithms, and their accuracy, will partly be based on the sensitivity and specification of components found within the transferable technologies. As such, general concept specifications will be developed as part of the project documentation.

The transferability of these concepts to an ANM4L demonstration is also shown below. The determination of transferability is again based solely on the engineering applicability of the concept, and is most likely to alter after economic and ICT considerations are taken into account. Every grid is unique creating a necessity to consider the application of viable concepts to each individual grid or topologies to get a full view of possibilities. Innovation lies in creating the possibility for large scale application of these concepts to any grid through active network management, without compromising grid security.

Table 3 - General overview of ANM functionality

Function Concept Pros Cons Comments/Conclusions Transferability

Grid control Dynamic Line Rating (DLR) • Allows increased utilization of

existing aerial powerlines without reinforcement.

• Simple installation and maintenance

• Less applicable for ground cable networks

• Many systems needed to cover large scale voltage control

• Good for singular aerial lines

• High cost volatility depending on location

• High

Tap changer • Automatic or passive control of voltage from existing transformer stations

• Voltage control for limited power supply area gives high resolution flexibility

• Reduces curtailment risk for assets fed by transformer.

• Rate of voltage change

• Integration may require new transformer installation

• May require station alteration as current station bay size may not cater for size of system

• Potential increase in wear of station systems

• Standard option (expansion module) for new transformers

• Interesting to understand rate of adjustment for LV grid (reaction time)

• Medium

Line Voltage Regulation (LVR)

• Individual feeder control

• Reduces need for curtailment locally

• High speed alteration

• Systems needed for each individual feeder line

• Can be suitable to increase capacity (especially PV or load) at the extremities of long feeders

• Medium

Reactive power compensation • Active compensation devices

provide dynamic voltage support

• Individual assets required for reactive power support

• Switching passive compensation devices may have negative impact on other parts of the grid

• Conventional solution on higher voltage levels

• High cost

• High



Function Concept Pros Cons Comments/Conclusions Transferability

Generation Control

Active power curtailment

• Curtailment gives ‘last line of defense’ power stability

• No cost for new grid components

• Pro-rata curtailment offers a non-discriminative ANM solution

• Application of LIFO creates intrinsic friction to further development works - Enforcement of LIFO generates a situation by which new market players will suffer a reduction in business case potential.

• Pro-rata curtailment fails to compensate pioneer installation risk.

• Curtailment level can reduce power generation more than necessary with associated economic losses.

• Reduced efficiency of connected RES – potential generation missed or generated power radiated to atmosphere.

• Model based control of curtailment

• Fall-back procedures more than innovative control measures

• Low cost alternative

• Difficulty with mass steering of household assets and associated contract requirements

• Can align with export limitation scheme (ELS) in G100 requirements (UK IDNO)

• High

Reactive power generation and consumption

• Utilizes reactive power, often considered a biproduct, to manipulate voltage.

• Can be applied to both high and low voltage grid solutions.

• Whilst more effective at higher voltages, the number of potential assets capable of reactive power contributions at lower voltages are exponentially higher.

• Communication systems may need to be co-ordinated between assets.

• Reactive power utilization may reduce the capability to supply active power.

• Expected to improve WTG integration potential

• Large scale of PV expected to give bottom-up control

• Local variations due to intermittency and consumption requirements need to be investigated in real life

• High

Energy Demand Management

Demand Side management (DSM)

• Transaction cost reduction

• Allows reactive strategies

• Reduces complexity

• Difficult to ensure efficient allocation of flexibility

• Difficult to identify adequate remuneration rates

• SMEs

• DSO initiative

• Medium

Demand Response (DR)

• Ensures adequate pricing and efficient allocation

• Potentially improved access to flexibility

• Potential for value-stacking of price and flexibility

• Facilitates customer enrolment by allowing offer

• Bundling with other customer value proposals

• Complex system with numerous interactions

• Highly susceptible to size of market participation

• Market size affects transaction liquidity

• Considering and meeting local grid needs through aggregators

• Penetration of DR assets is dependent on customers willingness to invest

• Demands high level of penetration to respond sufficiently

• Private IP (mostly 3rd party solutions)

• Non-DSO initiative

• Low

EVs, EVCPs & EVCHs

• Theoretically easy to control

• Large increase in availability expected in coming years

• Fast response

• Private IP hinders controllability

• Utilization of EV systems increases longer charge cycles

• Depending on componentry, chargers are potentially a large source of reactive power

• Further investigation would help understand the best way to utilize as an ANM resource

• Medium

Energy storage • Creates a high degree of flexibility

• Fast response

• Multiple market concepts for flexibility solutions

• High cost

• Regulatory difficulties for TSO/DSO application

• Difficult to ascertain exact level of energy available at any given time

• Battery storage is a good way to buffer the grid and offset consumption based voltage variations

• Medium



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[3] Bundesministerium für Wirtschaft und Energie - Zeitreihen zur Entwicklung der erneuerbaren Energien in Deutschland, p6, Feb 2020. (https://www.erneuerbare-energien.de/EE/Redaktion/DE/Downloads/zeitreihen- zur-entwicklung-der-erneuerbaren-energien-in-deutschland-1990-2019.pdf;jsessionid=08E83A7F780DE0B01093DF00C1EE3CD7?__blob=publicationFile&v=26)

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[10] InterFLEX project. European Union’s Horizon 2020 research and innovation programme under grant agreement n°731289. https://interflex-h2020.com/, 2020-05-31.

[11] CoordiNet project. Response to Horizon 2020 Call for proposals LC-SC3-ES-5-2018-2020 of the European Commission. https://coordinet-project.eu/projects/coordinet, 2020-05-31.

[12] CLUE - Climate Neutral Urban Districts in Europe - within the INTERREG IVC programme. http://www.clue-project.eu/, 2020-05-31.

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[14] PARITY project. European Union’s Horizon 2020 research and innovation programme under grant agreement n°864319. https://parity-h2020.eu/, 2020-05-31.

[15] PlatOne project. European Union’s Horizon 2020 research and innovation programme under grant agreement n°864300. https://platone-h2020.eu/, 2020-05-31.

[16] ANM4L paper: Active Network Management for All – Alternatives to network expansion, (to be published).

[17] https://www.ksh.hu/adatvizualizaciok, 2020-06-05



[18] https://www.iea.org/countries/hungary, 2020-06-05

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[21] https://ec.europa.eu/energy/sites/ener/files/documents/hu_final_necp_main_hu.pdf,2020-06-05



FUNDING

This project has received funding in the framework of the joint programming initiative ERA-Net Smart Energy Systems’ focus initiative Integrated, Regional Energy Systems, with support from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 775970.

d1.3 report on framework of the project and transferable

Documents