An application of IEEE 802.11ac to Smart Grid automation based on IEC 61850

Stefano Rinaldi, Paolo Ferrari, Alessandra Flammini, Francesco Gringoli, Matteo Loda, Nahla Ali University of Brescia

Via Branze 38, 25123 Brescia, Italy Tel: (+39) 030-3715913 stefano.rinaldi@unibs.it

Abstract—Smart Grids deployment is growing around the

world. The expansion of the existing Smart Grid network infrastructure in order to connect new electrical substations (or end-users) may be impaired by difficult cable deployment. For this reason, recently, wireless communication links have also been used. This paper deals with the deployment, and the first characterization, of an IEEE 802.11ac connection between IEC 61850 electrical automation devices. Some configurations of IEEE 802.11ac have been tested and compared with usual cable connection. The use of GPS based instrumentation combined with IEEE 1588 clock synchronization allows reducing measurement uncertainty and producing meaningful results. For instance, the IEC 61850 Transfer Time between GOOSE (Generic Object Oriented Substation Event) publisher and subscriber over an IEEE 802.11ac wireless link, loaded with 80Mbit/s of traffic, has an average value of 5.4 ms and a maximum value of 10 ms.

Keywords—IEC 61850; Time Synchronization; Smart Grid; IEEE 802.11ac; Transfer Time; Performance Evaluation; Latency; Grid Automation

I. INTRODUCTION

The automation of the Smart Grid involves, among other functionalities [1][2], the possibility for the DSO (Distribution System Operator) to control DERs (Distributer Energy Resources) and DESSs (Distributer Energy Storage Systems), which are typically placed at the customer side of electrical grid.

The level of interaction of the DSO with generation plants located in the customer grid ranges from sending request for active and reactive power modulation in return for an economic incentive (Demand Side Management), to more urgent requests to stop or to set the current power production to a predefined value as countermeasure to distribution grid problem (Grid Service). In addition, medium size customers have different power generators insisting on the same grid: the protections and the controllers of each plant should cooperate to implement protection and control function. From the point of view of the Smart Grid automation and its communication infrastructure [3], these different services have different requirements. For instance, the requirements related to transfer time are defined by the IEC 61850-5[4]: specifically, the control of DER and

DESS requires a transfer time ranging from 3 ms up to 1 s.

While primary substations and distribution grid are under the jurisdiction of DSO and other national Bodies, and therefore investment can cover the expenses for the deployment of a dedicated network [5][6][7], private areas and buildings are not. Such situation may obstacle the deployment of the necessary communication infrastructure to support the Smart Grid [8][9]. For this reason, in the last years, wireless communication is becoming more and more important in the smart Grid scenario [10] and for the automation of electrical substations [11], after the success of its application for industrial automation [12][13][14]. This paper is focused on the most recent IEEE 802.11ac wireless standard amendment [15], which may be able to fulfill Smart Grid requirements combining high transfer rate, reduced latency, and enhanced coexistence.

This paper investigates an application where a wireless link has been used to connect the DER and DESS automation systems located in a building. The experimental test is aimed to evaluate if communication performance offered by IEEE 802.11ac is in accordance with the requirements of the automation application in Smart Grids.

II. SHORT INTRODUCTION TO TECHNOLOGIES

A. IEC 61850 for Smart Grid

The aim of the IEC 61850 [4] is to define reference architecture for the automation of electric power systems, in the perspective of the smart grids. IEC 61850 introduces an abstract data model to simplify the modeling of electrical devices that compose electrical substations, primary as well as secondary, and equipment installed at customer side, such as protections and local controllers.

The standard defines a set of protocols: Manufacturing Message Specification (MMS), Generic Object Oriented Substation Event (GOOSE), and Sampled-Measured Values (SV). Part of these protocols are mapped over TCP/IP stack, others (such as GOOSE and SV), are directly mapped over Layer 2 to optimize the communication latency and to satisfy requirements of specific application. For example, a GOOSE message is used to map the change of state of a circuit breaker, while monitoring and data collection are transferred using MMS communication. This research activity has been partially funded by regional founding

provided by Regione Lombardia under Smart cities and communities grant no.40545387 (“Smart Campus as Urban Open LAbs - SCUOLA”), by research grant MIUR SCN00416, “Brescia Smart Living: Integrated energy andservices for the enhancement of the welfare” and by research grantFondazione Cariplo and Regione Lombardia no. 2014-2256, "NewOpportunities and ways towards ERC”.

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The IEC 61850-5 standard defines also the communication performance of each service, in term of transfer time, time synchronization, availability and security. In particular, this work is focused on the characterization of transfer time, defined as the entire delay occurring in the transmission of information from a sender application to the receiver. Six Transfer Time Classes are defined with their respective limits (TT0 > 1s, TT1 < 1s , TT2< 0.5s, TT3 < 100 ms, TT4 <20 ms, TT5 < 10 ms, TT6 < 3 ms). The transfer time includes not only the communication delay, but also the time to process the message. The deployment of IEC 61850 compliant installations typically is done using high speed switched Ethernet in order to satisfy service requirements. However, the standard does not impose any constraint on the physical transmission media, so the network may be heterogeneous (using wired, wireless or mixed transmission technology). Clearly, the proper selection of the communication media, of the network architecture, and of the protocol type is essential to guarantee the correct behavior of the smart electrical system.

The services defined by IEC 61850 connect several interfaces in the substation systems, or the substations themselves, as shown in Fig. 1. IEC 61850-7 models every substation component in term of services used to exchange the data among interfaces (IFs). The defined interfaces are: protection data exchange between bay and station level (IF1); protection data exchange between bay level and remote protection, e.g. line protection (IF2); data exchange within bay level (IF3); analogue data exchange between process and bay level, i.e. samples from CT and VT (IF4); control data exchange between process and bay level (IF5); control data exchange between bay and station level (IF6); data exchange between substation (level) and a remote workplace (IF7); direct data exchange between the bays especially for fast functions like interlocking (IF8); data exchange within station level (IF9); control-data exchange between the substation and remote SCADA (IF10); control-data exchange between substations.

Fig. 1. The communication model defined by IEC 61850.

B. IEEE 802.11ac and its characteristics

The IEEE 802.11ac standard [15] was published in January 2014 after a development of three years. It introduces many amendments at the physical layer which advance the overall Wi-Fi performance along the same directions explored by the previous enhancements, in details: larger aggregated channel

bandwidth with up to 160 MHz available for a single transmission; denser modulations together with more aggressive Forward Error Correction (FEC) mechanisms, i.e., 256-QAM and code-rate 5/6; and up to eight spatial streams with Multiple Input/Multiple Output (MIMO) encoding. Thanks to these features, the Very-High-Throughput physical layer (VHT-PHY) potentially allows data-rate up to 866.6Mb/s per stream: if we consider the MultiUser-MIMO (MU-MIMO) feature we get to a more than tenfold performance increase if compared to the previous High-Throughput physical layer (HT-PHY) defined by the IEEE 802.11n document, i.e., 6.77 Gb/s vs. 600 Mb/s of total aggregate throughput.

Many features that concurred to the success of the HT-PHY have been further improved within the VHT-PHY, such as: the sounding options with the associated Long Training Fields (LTFs) and all the mechanisms for the beam-forming of the channel that mimics (and enhances) the IEEE 802.11n explicit compressed feedback protocol; the procedures for calibrating the transmission power and for selecting the antennas; the possibility to dynamically switch from Long to Short Guard Interval to fight respectively hard or soft multi-path issues with decreasing overheads; and the FEC codes based on Low Density Parity Check (LDPC) which are further refined. Other features, instead, have been dropped like support of the 2.4 GHz band. This happened for a few reasons: first, this frequency range may accommodate only a single 80 MHz channel, leading to very crowded neighborhoods; second, it prohibits larger channel bonding scheme; and finally, IEEE plans to reserve the 2.4 GHz spectrum in the long term to applications with lower bandwidth requirements based on Bluetooth and ZigBee. With respect to IEEE 802.11n, the ac amendment drops also the support for the HT-only Greenfield preamble to increase the compatibility with legacy devices. Each frame, in fact, starts with a legacy preamble that all 11a/n receivers understand so that they can correctly manage the back-off procedure and avoid useless collisions during the entire transmission of the frame’s data, even when this spans across an 80 MHz or 160 MHz channel. For the same reason, every Access Point advertises its Basic Service Sets by transmitting legacy beacons on a specific (and fixed) 20 MHz channel inside the larger spectrum it manages: legacy clients may hence see the network and eventually associate and exchange traffic on this “primary” channel.

At the Medium Access Control (MAC) level, the IEEE 802.11ac standard introduces a “smart” multi-channel carrier-sense and mandatory RequestToSend/ClearToSend (RTS/CTS) procedure for allowing legacy BSSs to interoperate with IEEE 802.11ac APs. The features mentioned in the previous paragraphs, in fact, are effective when the legacy client is associated to an IEEE 802.11ac Access Point but they do not work if the client belongs to a separate BSS tuned on a channel different from the primary one of the IEEE 802.11ac BSS. For this reason, an IEEE 802.11ac node willing to transmit over an 80 MHz channel senses each of the four legacy channels composing the larger aggregate and sends valid legacy RTS frames only over those found free. The intended destination replies then with valid CTS frames only on the channels where RTSs have been correctly received. Finally, the IEEE 802.11ac transmitter uses the information

FCT.BFCT . A

PROCESS INTERFACE

CONTR PROT. PROT.CONTR CONTRPROT.

ACTUAT.SENSORS

STATION LEVEL

PROCESS LEVEL

BAY/UNIT LEVEL

HWEQUIPMENT

1,6 1,6 9

10 7

3 3

8

4,5 4,5

11

2

Remote Control & Automatics

Remote Protections

SUBSTATION A

SUBSTATION B

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collected during the RTS/CTS exchange to properly transmit only on the free portion of the 80 MHz spectrum. This mechanism can reduce the total bandwidth down to 20 MHz in the worst case but it also decreases the chance of collision and greatly improves the coexistence with legacy independent BSSs. A similar mechanism allows two independent IEEE 802.11ac BSSs sharing the same 80 MHz spectrum to selectively use portions of the channel for transmitting frames: the cost for the reduced data-rate is compensated by the smaller latency. Finally, it worth noting that IEEE 802.11ac mandates frame aggregation: not only each transmission must be performed in such a way, the standard also drops support for Reduced Inter Frame Space (RIFS) which was introduced in the IEEE 802.11n standard for shortening the time between consecutive transmission.

III. THE CONSIDERED AUTOMATION SYSTEM

A. The automation system for Smart Grid

In the campus of University of Brescia, an experimental system for the scheduling and the control of energy flows generated by Photo Voltaic fields and electrical storages has been deployed on the Medium Voltage grid. A controller is installed in the DSO secondary substation to send requests (Demand Side Management as well as Grid Servicing) to the local controller of each power plant installed in the campus and to protections (Fig. 2). In this paper, the attention is focused on Grid servicing applications, which have strict requirements in term of communication. Since in these cases, the services are mapped using both MMS (Modulation of power generated) and GOOSE (protection and fast interaction with local controllers) messages, only GOOSE communication has been taken into account because it has the most strict time constrains according to IEC 61850.

Fig. 2. The architecture of the automation system for the control of DER/DESS in a Smart Grida t the Campus of the University of Brescia.

B. The communication architecture

We show the wireless communication infrastructure in Fig. 3. We connected building A and C with a pair of directional point-to-point links that pass through point B: this was necessary as buildings A and C are lower than the intermediate one. Each link is made by a couple of MikroTik SXT 5 ac antennas for a total of four devices. These are cheap outdoor units based on a QCA design whose main components are: a QCA9557 MIPS single core CPU clocked at 720MHz that executes MikroTik RouterOS on top of a v3.3.5 Linux kernel;

128MB Ram; and a Wireless 802.11ac Interface based on the QCA9882 chipset. The wireless section is connected to two antennas and can manage Modulation and Coding Schemes (MCS) with two spatial streams over 80MHz channels: the maximum theoretical data-rate is 866Mb/s when 256-QAM with FEC rate 5/6 modulation is used. The power received at every node is pretty high as these are directional units: e.g., on the longer 159 m link A-B each node claims an average received power of -41dBm; on link B-C (approximately one third the length of A-B) we monitored -28dBm as average power.

At point B, we installed a copper Ethernet Layer 2 Switch (SG100D-08 by CISCO) to bridge the traffic between the two wireless links A-B and B-C.

Regarding the configuration of the four wireless devices, we carefully chose the one that better satisfied the requirements of the grid monitoring application. Such application monitors the Photo Voltaic generator equipment located on the roof of building A and reports information to the power grid interconnections located in building C: its main requirement is hence to advertise as soon as possible any issue affecting the energy production process to the interconnection switches. According to the signaling protocol used by the power equipment, advertisement messages are embedded in layer two frames: for this reason we setup a flat data-link domain by configuring the MikroTik nodes to create a Wireless Distribution System. This enabled to transparently bridge the networks at point A with that at point C, avoiding more complex configurations based either on IP or MPLS that would have increased the frame processing time at the Linux kernel. Finally we configured nodes at location A (link A-B) and location B (link B-C) as Access Points so that their messages are less exposed to beaconing delays.

Fig. 3. The topology of the communication system.

With regards to the configuration of the Wi-Fi PHY, we selected “11ac only” operation: we voluntarily ignored proprietary features of QCA/MikroTik chipset (i.e., nstreme and nv2) as they are not fully compliant with the standard. We then tested the wireless infrastructure with different country settings: this allowed to either comply with the local

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regulations (and coexist with other - many - neighboring installations) or to test the behavior of the infrastructure on almost free channels on selected short interval of time. In particular, these tests helped understanding the maximum performance achievable in terms of throughput and jitter by removing contenders.

IV. EXPERIMENTAL CHARACTERIZATION

The definition of the performance metrics is given in IEC 61850-5, while the IEC 61850-10 defines the testing procedures. As a result, the estimation of transfer time requires the measurement of the time interval between the signal on the electrical grid that triggers the generation of an IEC 61850 event by a device and the signal generated by a device as an acknowledge of the occurred processing of the IEC 61850 event. While the estimation of the transfer time within a substation is a well-established methodology [16][17][18] and can take the advantages from dedicated measurement equipment [19], the estimation of the transfer time over a distributed system requires the deployment of a proper measurement system in order to be able to correlate the event on the distribution grid.

A. The experimental setup

We show in Fig. 4 the measurement system that we deployed to estimate the transfer time over the considered demo test case. A couple of GPS antennas provide the Siemens RSG2488 switches with an accurate local time reference. This local time is used to generate a 1-PPS (Pulse per Second) hardware signal that, in turn, is used as the “reference event”. Two Raspberry minicomputers (PI 2 Model B, 900MHz quad-core ARM Cortex-A7 CPU, 1GB RAM) located at the two opposite sides of the network and equipped with libiec61850 open stack produce and consume IEC 61850 events: the latency that they introduce to handle hardware events is in the order of few tens of microseconds.

Fig. 4. The measurement system deployed for the estimation of the transfer time over the IEEE 801.11ac link.

More in detail, the measurement protocol is described by the following steps:

1) Generation of Trigger Event: The PPS1 signal, generated by the switch at one side of the link under test, is received on the digital input (In) of Sender board.

2) GOOSE Transmission: The Sender (IEC 61850 Publisher) sends a GOOSE message when it detects a rising edge on input pin.

3) Network Transmission: The message travels through both the switches and the wireless link under test .

4) GOOSE Reception: The Receiver (IEC 61850 Subscriber) handles the GOOSE message and it rises a signal on its output pin (Out).

5) Transfer Time Estimation: The counter (Counter) measures the time interval between the PPS2, generated by the local switch using the time information of the GPS antenna, and the Out signal, generated from the Receiver after handling the GOOSE message.

The Transfer Time (TT) can be expressed as:

TT= TIn - TOut = TPPS1 - TOut

where TIn = TPPS1 is the time at the rising edge of the PPS1 signal and TOut is the time at the rising edge of the signal generated by the Receiver. At the receiver side, the counter quantifies the Time Interval (TT’) as:

TT’= TPPS2 - TOut

where TPPS2, is the time at the rising edge of the PPS2 signal. It is clear that TT and TT’ are not equal, but, since RGS2488 switches are both referred to the GPS time, the PPS signals (PPS1 and PPS2) are synchronized and a relation exists. In particular, TPPS1 = TPPS2 + , where is the synchronization offset between the two GPS receivers. Therefore,

TT = TPPS1 - TOut = TPPS2 + - TOut = TT’ +

and TT can be estimated from the TT’ after the estimation of the synchronization accuracy of the two GPS receivers.

B. Assessment of the GPS-based instrumentation accuracy

As mentioned in the previous subsection, the accuracy of the TT estimation depends on the synchronization accuracy of the GPS receivers embedded in the RSG2488 switches, that are used to generate the PPS reference signal. The PPS signal of the two switches is directly compared using the counter (Agilent 53230A with Option 010 - high stability oscillator). The short term time offset distribution between the two signals is shown in Fig. 5 for a measurement campaign of 3600 samples (3600 s). The average value is µSyn = 6 ns, the standard deviation is σSyn = 25 ns and the maximum difference between maximum and minimum value (i.e. the synchronization jitter) is 151 ns. Hence, the synchronization extended uncertainty of the infrastructure in the short term is equal to (k=2, confidence interval 95%):

nskU SynSynSyn 5222

The results are in accordance with state-of-the-art results regarding commercial devices for professional applications. The used components allow creating an optimal situation: the

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uncertainty of the deployed measurement system is more than enough for the characterization of the transfer time classes defined by the IEC 61850. For instance, the most strict transfer time requirement (TT6 = 3ms) is four order of magnitude larger than the extended uncertainty of the measurement system. In particular, the equation 3 can be now rewritten as

TT = TT’ ± USyn .

Fig. 5. The frequency distribution of time offset of PPS1 with the respect to PPS2, evaluated over 3600 samples (1 hour).

C. Reference case with wired links

In the first experiment, the contribution of the wired part of the network to the transfer time has been evaluated. The two Ethernet switches RSG2488 (used at point A and C, respectively) and the switch SG100D-08 (used at point B) have been directly connected replacing the two wireless links (A-B and B-C) with copper cables of 75 m. This test was carried out before installing the hardware devices in their respective remote locations: during the test all the hardware devices were at the same place (point C), close to each other.

The measurement procedure is the same as described in section IV.A but without the contribution of the wireless link since they have been removed: the Sender sends a GOOSE message that triggers the Receiver to generate the Out signal.

The frequency distribution of the transfer time TT measured with the GPS based setup is shown in Fig. 6 (7000 samples, 2 hours). The mean value is µTTwired = 0.8 ms, the standard deviation is σTTwired = 0.3 ms. The distribution of the transfer time seems almost uniformly distributed in the interval between 0.3 ms and 1.4 ms being the variability of the transfer time mainly introduced by switches and Sender/Receiver Ethernet port queues.

D. First characterization of IEEE 802.11ac wireless link

In the following section, the transfer time has been evaluated considering the wireless link described in section III.B. In particular, the transfer time evaluation has been performed also changing the traffic throughput. Nominally, IEEE 802.11ac is able to sustain high throughput on a link. As shown in Fig. 4, two devices (which are able to produce and consume UDP traffic) have been deployed in the network

under test. One of the devices has been configured as an iPerf UDP client, the others as an iPerf UDP server generating and sinking up to 80Mbit/s. The configuration of the IEEE 802.11ac link used during the test is summarized in TABLE I.

Fig. 6. The frequency distribution of transfer time estimated considering a cabled infrastructure, obtained over 7000 samples (two hours).

TABLE I. THE WI-FI CONFIGURATION PERFORMED DURING THE EXPERIMENTS.

Test Bandwidth

(MHz) Traffic

Ch. 1 (MHz)

Ch. 2 (MHz)

Retries

4 80 UDP 5600 5745 7

The estimated probability density functions (pdf) of the

transfer time evaluated during the test, obtained with different load in the network is shown in Fig. 7. Each of the pdf has been estimated using 1000 samples. The statistics are summarized in TABLE II. During the experiment, also the packet loss has been estimated. As expected, the larger is the throughput, the greater the number of packet that have been lost (2 packets lost over a total amount of 800 k packets at 10 Mb/s, 16 packets lost over a total amount of 6.5 M packets at 80 Mb/s). No GOOSE packets have been lost during the test.

Fig. 7. The estimated pdf obtained with different level of traffic on the IEEE 802.11ac link.

The obtained results fulfill the requirements of IEC 61850 automation within Smart Grid applications. The results are very close to the ones obtained with the wired connections in section IV.C. Below 30 Mbit/s of traffic load the Deployed

0 2 4 6 8 10 120

0.5

1

1.5

Tranfer Time (ms)

Est

imat

ed P

DF

No Traffic10 Mb/s30 Mb/s80 Mb/s

02468

10121416

-77 -47 -17 14 44 74

Fre

qu

en

cy

(%)

Time offset (ns)

0%

5%

10%

15%

20%

0.0 0.3 0.6 0.9 1.2 1.5

Fre

qu

enc

y (%

)

Transfer Time (ms)

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systems satisfies the most stringent TT6 Class defined by IEC 61850-5 (protections). When the load increases the worst case values (max Transfer Time) increases as well.

TABLE II. THE TRANSFER TIME EVALUATED WITH DIFFERENT LEVEL OF UDP TRAFFIC.

UDP Traffic (Mb/s)

Transfer Time (ms)

Mean Std. Dev. Min Max 95-Perc 99-Perc.

No 1.3 0.1 0.7 2.3 1.8 2

10 1.2 0.4 0.6 2.7 1.8 2

30 1.4 0,5 0.6 4.8 2.1 3

80 5.4 0.9 3 10.1 7.4 9

V. CONCLUSIONS

The expansion of existing Smart Grid networks may benefit from a suitable wireless protocol. The paper investigates the deployment of an IEEE 802.11ac connection between IEC 61850 electrical automation devices belonging to the Campus of the University of Brescia. Some IEEE 802.11ac modes of operation have been compared with usual cable connection, by means of GPS based instrumentation. The results shows that the IEEE 802.11ac link under test is able to fulfill IEC 61850 requirements even regarding critical applications (1.4 ms of transfer time, compatible also with protection applications) unless the network is loaded with heavy traffic.

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