Landis+Gyr’s Automated Network Management solution validation at smart grid competence center

Public ReportLandis+Gyr’s Automated Network Management solution validation at TECNALIA’s smart grid competence center

Iñigo CobeloJon AnduagaAsier Gil de Muro

TECNALIAEnergy UnitSmart Grid Competence Center

Prepared by:

Sami HaapamäkiToshiaki AsanoIgor Dremelj

Landis+Gyr / TOSHIBA Smart Grid Solution CenterEMEA

Project Ref.: 034094 – Rev. V1 – July 2014

Index

1. Background .....................................................................................................................................3

1.1 About TECNALIA ...................................................................................................................4

1.2 About Landis+Gyr .................................................................................................................4

2. Objectives ........................................................................................................................................5

3. Validation setup ...............................................................................................................................6

4. Validation results ..............................................................................................................................8

4.1 Voltage fluctuation .................................................................................................................8

4.2 Feeder overload .................................................................................................................. 11

5. Conclusion ....................................................................................................................................15

Landis+Gyr ANM solution validation report

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Landis+Gyr engaged Spain-based independent smart grid research and validation center TECNALIA to test the company’s new smart grid solution under real-life conditions in a smart grid demo environment.

The study’s main objective was to demonstrate how existing innovative automated network management solutions, such as the µEMS / S650 Smart Grid Terminal, enable utilities to improve voltage quality, manage decentralized generation and balance energy supply and demand within the distribution network under the most-demanding conditions.

Based on the insights gained from other smart grid projects and by taking advantage of the lab’s network control capabilities, TECNALIA was able to simulate a large number of different scenarios. These included testing the impact of controlling elements, such as the voltage regulator (line and / or distribution transformer), load and generator combinations, as well as a storage system to demonstrate the usability of network assets and performance when combined with TOSHIBA’s µEMS control solution and the S650 Smart Grid Terminal from Landis+Gyr.

1. Background


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TECNALIA is the first applied research center in Spain and one of the most prominent labs in Europe with around 1,500 employees, turnover of €110 million and over 4,000 clients participating in various European smart grid projects.

The mission of TECNALIA is to transform knowledge into GDP, improving people’s quality of life by generating business opportunities for companies. To accomplish this, TECNALIA is organized in seven interconnected divisions by sector: Energy and Environment, Sustainable Construction, Industry and Transport, ICT – European Software, Innovation Strategies, Health, and Technological Services.

TECNALIA’s offer includes a range of activities: technological services, testing and certification, R&D&I projects, the transfer of industrial property, business promotion, business diversification, innovation management and foreign support.

The Smart Grid Area, included in the Energy and Environment Division, generates and develops business opportunities for utilities and their equipment and service providers by designing and developing radical solutions for the progressive transition from the current electrical systems to the 2050 smart power systems, including

Advanced power system architectures: microgrids for buildings and districts; Demand-side management and demand response; Energy management and optimization in buildings; Integration of distributed energy resources into the network; New power converters for grid connection; Communication for smart grid and smart metering applications; Electric mobility: infrastructure, grid integration and V2G applications; Business model analysis and development.

With the “ingrid” lab, which is a new, experimental infrastructure for smart grids and the integration of renewable energy, TECNALIA provides not only expertise, but also infrastructure for the qualification of smart grid solutions in Europe. Following the deployment of the new requirements of the electrical grid, TECNALIA has strengthened its activities in the functional and interoperability assessment of products for the smart grid (e.g. smart meters), conformity assessment of power electronics devices (e.g. PV inverters) and the commissioning of tests for HV cables.

As a singular station, TECNALIA operates the most highly rated and most extensive independent power test facility in the southwest of Europe and has sufficient capability to perform short-circuit and high-current testing on a wide variety of high-voltage and low-voltage electrical equipment.

Landis+Gyr is the leading global provider of integrated energy management products tailored to energy company needs and unique in its ability to deliver true end-to-end advanced metering solutions. Today, the Company offers the broadest portfolio of products and services in the electricity metering industry, and is paving the way for the next generation of smart grid. Landis+Gyr an independent growth platform of the Toshiba Corporation (TKY:6502) and 40% owned by the Innovation Network Corporation of Japan, operates in 30 countries across five continents, and employs 5,500 people.

With the ambition to contribute to tomorrow’s Smart Communities by offering the technology for a secure and efficient energy infrastructure, a Team of smart metering solution experts from Landis+Gyr and smart grid solution specialists from Toshiba came together in a Smart Grid Solution Center to design innovative smart grid applications that will provide flexibility in renewables integration and intelligent balancing of energy supply and demand. The first of such applications has now been supplied to TECNALIA for technical validation.

1.1 About TECNALIA

1.2 About Landis+Gyr


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The EU aims to generate 20% of its energy from renewable sources by 2020. More renewable energy will enable the EU to cut greenhouse gas emissions and make it less dependent on imported energy. Moreover, end-users’ consumption habits and the characteristics of the loads that are connected to the grid are changing. The penetration of new electric loads such as electric vehicles and heat pumps grows day by day.

The integration of distributed energy resources (DER) coming from renewable generation is technically challenging in existing medium-voltage (MV) distribution networks. Existing distribution networks were designed to distribute the centrally generated energy to the different customers. The design and operation of the electricity distribution networks always assumed power flows from higher-voltage networks to lower-voltage networks. This assumption is valid for passive networks. However, the connection and operation of significant DER (of varying technologies) alter many network characteristics, in turn making the existing assumptions of network design and operation less applicable to distribution networks.

The combination of intermittent renewable generation and changing consumption habits causes several technical difficulties, such as:

Voltage fluctuation effect (especially in long and rural feeders). Existing voltage control systems such as line drop compensation may no longer be suitable if generation is connected to the feeder. Overvoltage situations have a negative impact on the service life of electrical devices cause higher technical losses and can trigger the feeder line / transformer safeguards. Undervoltage situations can cause flicker, alter the operation of synchronous machines and unintentionally trigger safeguards;

Line and network equipment overloading that reduces their service life; Reverse power flows that alter normal operating procedures.

In island systems, microgrids and weak networks, the challenges are even higher and include stability problems and frequency deviations.

Distribution system operators tend to apply the “fit-&-forget” operational approach when dealing with DER connection requests. This implies that at any given network point, a generator is only connected if in the worst case scenario it would not cause any disturbance. As the ratio between the output power of the DER and the short-circuit power of the connection point increases, the probability of problems also increases. Connection at higher-voltage levels causes fewer disturbances, but is much more expensive and prevents widespread connections of this kind.

The reinforcement of existing distribution networks to allow them to cope is often economically unviable, so the solution must come from innovative network control, active management and adequate signals from regulation. The role of regulators is critical.

To accommodate as much distributed generation as possible, it is necessary to find solutions to these problems. The objective of this project is to demonstrate that the use of innovative smart grid technologies such as TOSHIBA’s μEMS solution is a viable alternative to help utilities solve the challenges caused by the distributed energy resources and the changing consumption habits in Europe.

The tests are performed by using existing products from Landis+Gyr and TOSHIBA, installed in TECNALIA’s smart grid laboratory network.

2. Objectives


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In order to test the functionalities of TOSHIBA’s µEMS in a real and controlled environment, TECNALIA’s smart grid laboratory is used. TECNALIA’s laboratory features flexible, low-voltage infrastructure that can adopt different network topologies and run either connected to or isolated from the main power grid. It includes different renewable generators, storage technologies, loads and controllable equipment.

For this project, a particular laboratory setup representing a distribution feeder with renewable generation and loads connected at various points to this feeder (Figure 2) has been selected. Different scenarios were generated and analyzed by programming the power output from the generator and the loading profiles. The characteristics of the line impedance have been taken into account as well: All of the tests are performed with purely resistive, purely inductive and mixed-line impedance.

TOSHIBA’s µEMS is capable of sending control commands to a wide variety of field devices. For this demonstration project, a Thyristor Voltage Regulator (TVR) and a Battery Energy Storage System (BESS) have been used. In order to test the capabilities of the control system under extreme conditions, load and generation control capabilities have also been implemented for those extreme scenarios.

It was impractical to move a TOSHIBA TVR and battery energy storage system to TECNALIA’s premises, which is why a TVR and a BESS have been simulated using laboratory hardware and specifically designed software. The TVR simulator is implemented by means of two laboratory

3. Validation setup

Figure 1: View of one part of TECNALIA’s smart grid laboratory

Figure 2: Simplified one-line diagram of the test feeder

Line simulator

Load 2

Simulation Data Setting for each equipment model

TVR simulator

Storage simulator

Load 3

L 4

Gen 3

G 4

Bus-1Tap

Bus-2 Bus-3


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power sources. One of the power sources provides the Bus-1 voltage and the other provides the Bus-2 voltage. The ratio between the two control signals emulates the TVR turns ratio for the selected tap. There is a software application that simulates the TVR operating logic and sends the signals to both power sources. The storage simulator is composed of one diesel generator connected to a TECNALIA back-to-back inverter and a controllable load. A software application that controls the active and reactive power of the generator and the load is responsible for the simulation of the battery capacity and dynamics.

The integration of TOSHIBA’s µEMS control equipment into the experimental grid is performed in exactly the same fashion as it would be in a real distribution feeder.

TOSHIBA’s μEMS solution, consisting of a server and controller, along with five Landis+Gyr S650 Smart Grid Terminals and several commercially available RTUs and interfacing devices have been installed in the network and integrated using MODBUS / TCP and DLMS communication protocols.

The system architecture is shown in Figure 3.

The control equipment is shown at the top of the diagram (grey background). It comprises the TOSHIBA µEMS server and controller, Landis+Gyr S650 Smart Grid Terminals, standard RTUs and interfacing equipment. The lower part of the figure (green background) represents TECNALIA’s laboratory equipment.

iRTU-1

Line simulator

Load 2

iGW-B0 iGW-B1

iRTU-2µEMS Controller

Simulation Data Setting for each equipment model

Grid SimulatorManagement Server

TVR simulator

Storage simulator

µEMS ServerDisplay

Load 3

L 4

Gen 3

G 4

Bus-1

P0%30%60%100%

P

0%30%60%100%

TapBus-2 Bus-3

Figure 3: System architecture


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Figure 4: Programmed load and generation profiles at the end of the feeder

Figure 5: Voltage at the end of the feeder without control

Figure 4 shows the programmed load profile and power output from the generator connected to Bus-3 (end of the feeder) for the test period. Figure 5 shows the resulting Bus-3 voltage profile measurements if no control action is performed.

4.1 Voltage fluctuation

The objective of the project is to demonstrate the capabilities of the TOSHIBA / Landis+Gyr solution and show how it can be used to remove the technical barriers associated with connecting DER to distribution networks. For this purpose, different scenarios have been tested using the laboratory setup.

The use cases are representative of the real challenges of operating a distribution feeder with renewable generation and variable load. Extreme scenarios in which both voltage and feeder currents exceed set limits have been created. Each use case is defined by:

a load profile; a renewable generator’s power generation profile; line characteristics; list of field devices available for the μEMS to control.

4. Validation results


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16kW

Load Programmed Power (kW) RES Programmed Power (kW)

Time

14

12

10

8

6

4

2

0

450V

Bus Voltage w/o control

Time

440

430

420

410

400

390

380

370

360

350

Figure 6: Controlled voltage at the end of the feeder and performed control actions

As shown in Figure 5 four different situations are simulated representing a typical 24 hour cycle:

At the beginning, there is no generation with a gradual increase on the load. Voltage at the feeder end drops below acceptable limits.

Next, the generation begins to gradually increase and the load decreases. Voltage at the feeder end gradually increases.

Afterwards, the generation reaches its maximum and the load begins to gradually increase again. Voltage at the feeder end exceeds acceptable limits, but gradually begins to decrease.

Last but not least, load and generation become balanced again. There is no load flow along the feeder, therefore the voltage remains unchanged through the feeder.

The same test case is run using TOSHIBA’s μEMS control system. The controllable devices available are the TVR and the BESS. With the TVR used in the test five different tap positions with 1.5% step are utilized. Energy storage system used is able to linearly adjust its output for var-control.

The resulting voltage and control actions can be seen in Figure 6:

Vertical lines in Figure 6 represent the instances in which TOSHIBA’s μEMS system has sent a control signal to the field devices, i.e. a TVR on-load tap changer and a BESS inverter. Yellow lines represent tap-up or tap-down control signals to the TVR, and black lines control signals to the BESS. In this scenario, the battery only injects or absorbs reactive power.


9

V

Bus-3 voltage Bus-3 voltage w/o control Tap control action BESS control action

Time

440

430

420

410

400

390

380

370

360

Figure 8: Resulting TVR tap positions

Figure 7: Comparison between controlled and uncontrolled voltages at the end of the feeder

The measured voltage at the end of the feeder (Bus-3) during the four tests is kept within acceptable limits during the day and it remains much more constant as compared to the uncontrolled situation (Figure 7).

The control actions over the TVR and battery system can be seen in detail in Figure 8 and Figure 9.


10

V

Bus-3 voltage Bus-3 voltage w/o control

Time

440

430

420

410

400

390

380

370

360

6 420Tap V

Tap Position Bus-3 voltage

Time

5415

4104

405

3 400

3952

3901

385

0 380

Figure 9: Reactive power injected / absorbed by the battery system

Priorities set in the µEMS controller assumed prioritization of TVR control over battery control (Figure 6) the reactive power injection / absorption capability is only implemented when the TVR has reached the maximum or minimum tap position given by physical capabilities of TVR.

Several different use cases have been run using the same parameters and for which the line impedance is modified according to typical distribution feeder characteristics between the runs. Line characteristics define the effectiveness of the reactive power control. Studies show the benefits obtained by the reactive power control are greater for the more inductive feeders, whereas for some resistive line characteristics using energy storage system with active power control could be more effective for voltage regulation.

Test scenarios in which feeder rating limits are explored have also been conducted. Figure 10 shows the programmed load profile and power output from the generator connected to Bus-3 (end of the feeder) for the test period. Figure 11 shows the measured current that results flowing through the feeder (Bus-2 current) if no control action is performed. The maximum allowable current through the feeder was limited to 25 amperes.

4.2 Feeder overload

Figure 10: Programmed load and generation profiles at the end of the feeder


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15 420kVAr V

BESS Q Control Bus-3 voltage

Time

10415

4105

405

0 400

395-5390

-10385

-15 380

kW

Load Programmed Power (kW) RES Programmed Power (kW)

Time

30

20

10

0

As shown in Figure 11 four different situations are simulated representing a typical 24 hour cycle:

At the beginning, there is no generation with a gradual increase on the load. Current flow from Bus-2 to Bus-3 increases and exceeds the maximum rating.

Next, the generation begins to gradually increase and the load decreases. Current flow from Bus-2 to Bus-3 decreases and reaches zero when generation and load at the end of feeder are balanced, and changes its direction when generation exceeds load.

Afterwards, the generation reaches its maximum and the load begins to gradually increase again. The reverse current flowing from Bus-3 to Bus-2 exceeds the maximum rating.

Last but not least, load and generation become balanced again. There is no load flow along the feeder.

The same test case is run using TOSHIBA’s μEMS control system. The controllable devices available for this test were the battery energy storage system (BESS) load and generation with step-wise curtailment capability, connected to the end of the feeder. Renewable generation curtailment is a standard procedure for the operation of big plants connected to higher voltage levels. The implementation of a generation curtailment procedure for distributed generators is also a viable control alternative that is especially appropriate for generators connected by means of smart inverters. Load and / or generation curtailment as such should be managed according to local legislation and contractual conditions of prosumers. For validation we have assumed load and / or generation curtailment can be done as last resource, stress testing the solution with extreme changes in curtailment of load and / or generation. For this purpose, three control steps have been defined for the load and generation curtailment: a reduction of 40%, 70% and 100%.

The advantage of a modern battery energy storage system (BESS) is that it can import / export power and linearly adjust its output by controlling the smart inverter of such a BESS. Due to this, the corrective action (control) priority was given first to BESS, followed by RES curtailment and finally load curtailment.

Figure 11: Current flow without control


12

A

Bus-2 Current w/o control

Time

60

50

40

30

20

10

0

Figure 12 shows the resulting active power absorbed / injected by the battery energy storage system and the resulting current flowing through the feeder.

Figure 13 shows the resulting power consumed by the load connected at the end of the feeder and the resulting power injected by the generator connected at the end of the feeder. The curtailment steps can be seen very clearly.

Figure 12: Active power absorbed / injected by the BESS and the resulting current flowing through the feeder

Figure 13: Resulting load and generation profiles


13

Cur

rent

(A)

Act

ive

Pow

er (k

W)

BESS Q Controll Bus-2 Current

Time

14

30

9

25

4

20

-115

-610

-11 5

-16 0

35

Act

ive

Pow

er

Load Active Power (kW) RES Active Power (kW)

Time

30

25

20

15

10

5

0

Figure 14: Comparison between controlled and uncontrolled currents2

Figure 14 shows that the resulting controlled current flowing through the feeder is kept below the limit (25 amperes). The μEMS control system tries to maintain the current below the maximum rating using only the battery. The controller decides to curtail load and / or generation only once the battery’s limits have been reached.

2Arrows indicate power flow direction in the feeder.


14

Cur

rent

(A)

Bus-2 Current Bus-2 Current w/o control

Time

60

50

40

30

20

10

0

Comprehensive tests conducted as part of this validation show that the high-performance equipment and technology from Landis+Gyr and TOSHIBA, can be deployed for automated network management as core capability of the modern smart grid. The tests proved that the solution as presented in this report, can successfully resolve network constraints in areas exposed to DER. With this solution, it was possible to control and keep the voltage within foreseen limits, hence preventing flicker that results from undervoltage and losses that result from overvoltage situations. With the potential to manage state of charge for grid-connected energy storage and the curtailment of loads and / or renewables, the solution is able to perform predictive capacity management and therefore match a particular region’s supply and demand. The solution is able to predict mismatch between supply and demand in the selected region, automatically apply corrective measures to the grid and maximize its operational efficiency and reliability as a result.

Achieving the 20-20-20 goals dictates the rise of renewable energy sources and an efficient use of resources in the current grid, along with other related issues described in this report. In order to overcome these challenges, similar to smart metering the regulatory framework for the deployment of smart grid solutions must be established. The technology is ready, and the elements for making the business case viable are also in place.

TOSHIBA’s μEMS solution is flexible. It can be integrated with existing legacy systems and easily adapted to the available controllable field devices and regulatory schemes. The solution is complementary to smart metering, hence increasing the value of investments made in Advanced Metering Infrastructure (AMI). As an example, Landis+Gyr S650 Smart Grid Terminal can be easily utilized for balancing and monitoring transformer stations, in addition to serving as a sensor for μEMS active network management without additional cost.

Tests have shown the need and added value of controllable resources in the network, such as voltage regulators, grid scale energy storage systems and STATCOMs. Such resources are flexible and do not directly impact prosumers. Curtailment is viable but needs to be managed according to local legislation and contractual conditions of prosumers.

One of the challenges observed in distribution network control systems is the massive amount of data that would have to be transmitted if the control schemes remain centralized. TOSHIBA’s μEMS solution applies distributed intelligence and does not rely on real-time communication with central SCADA systems. The communication between the μEMS control system and the field devices is localized and limited to the feeder area, which reduces the cost of operation and increases reliability and robustness.

5. Conclusion


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Landis+Gyr’s Automated Network Management solution validation at smart grid competence center