Preventing cascading tripping of distributed generators during non-islanding conditions using thermostatic loads

Preventing cascading tripping of distributed generators during non-islanding conditions using thermostatic loads

Electrical Power and Energy Systems 106 (2019) 183–191 Contents lists available at ScienceDirect Electrical Power and Energy Systems journal homepag...

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Electrical Power and Energy Systems 106 (2019) 183–191

Contents lists available at ScienceDirect

Electrical Power and Energy Systems journal homepage: www.elsevier.com/locate/ijepes

Preventing cascading tripping of distributed generators during non-islanding conditions using thermostatic loads

T

Vincenzo Trovatoa,b, , Inmaculada Martínez Sanza, Balarko Chaudhuria, Goran Strbaca ⁎

a b

Dept. of Electrical and Electronic Engineering (Control and Power Research Group), Imperial College London, Exhibition Road, London SW7 2AZ, UK EDF Energy R&D UK Centre, Croydon, UK

ARTICLE INFO

ABSTRACT

Keywords: Distributed energy resources (DER) Inertial response RoCoF-sensitive protections Thermostatically controlled loads (TCLs) Power system dynamic performance

Integration of large amounts of asynchronous renewable energy sources (RES) would reduce the effective inertia of the future Great Britain (GB) network. As a result, after a large infeed loss, containing the grid frequency and limiting its rate of change (RoCoF) above certain thresholds would be a challenge for the system operator. In particular, large RoCoFs could activate RoCoF-sensitive loss-of-mains (LoM) protections of distributed generators (DGs) and trigger cascading disconnections. In this context, thermostatic loads (TCLs) can be controlled to collectively provide support and contribute to the overall system inertial and frequency response. This paper focuses on the transient response period after a frequency disturbance and the fast protection events occurring in this time frame. In particular, this works evaluates the interplay between the local activation settings of LoM protection of DGs and those used to enable the TCL support. This interaction is analysed through a case study on a 36-bus dynamic equivalent of the GB network which shows how local post-fault frequency dynamics drive the overall system response. Results show that TCLs are able to prevent RoCoF-driven DG tripping and reduce the need to adopt high LoM settings, decreasing the risks of maloperation associated with desensitised protections.

1. Introduction Ambitious targets for the decarbonisation of the electricity supply system would result in drastic changes in the traditional generation mix in Great Britain (GB). Large shares of electricity demand are expected to be supplied by renewable energy sources (RES) to reduce greenhouse gas emissions and to cut down dependence on fossil fuel reserves [1]. Most of the RES are converter-interfaced generation technologies and do not inherently contribute to the system inertia which makes grid frequency control difficult. In future, the power imbalance resulting from a sudden infeed loss will therefore lead to larger rate of change of frequencies (RoCoF) and worse frequency nadirs [1]. A high RoCoF value is likely to trigger the RoCoF-sensitive loss-of-mains (LoM) protections of the distributed generation (DG) units, accelerating the frequency decay even further. This increases the risk of activating expensive low frequency demand disconnection schemes (LFDD [2]) or even a black out [3]. In this context, mitigating the risks associated with large RoCoFs and frequency excursions is currently a major concern for the GB system operator, National Grid (NG) [1]. DGs are equipped with LoM protections to avoid islanding conditions [4]. In practice, the most common types of LoM protections rely

on passive methods based on local measurements [4]. In particular, RoCoF relays and vector surge relays are usually employed [5,6]. However, standard RoCoF relays are subject to misoperation if they cannot properly discern if, under certain scenarios, the DG is effectively disconnected from the main grid [6]. In the system protection area, significant research efforts have been devoted to improve the current protection algorithms of DGs to effectively determine islanded conditions [7]. In addition, use of wide area measurements from PMU units has been investigated to further enhance the protection relay performance [8]. For the GB case, it has been proposed to increase the overall LoM protection settings of DGs, ‘desensitising’ the relay operation [9]. Modifications to the Distribution Code (in its Engineering Recommendation G59) are seeking to adapt the current generator connection requirements [10]. As a result, this measure is expected to reduce the costs of balancing the system as the likeliness of having to deal with RoCoF-driven disconnection of DGs reduces [10]. However, use of higher protection settings may affect the detection of islanding conditions [3]. Hence, there is a need to revisit these thresholds in the long term future in order to maintain system security and operational costs, if small or large thresholds, respectively, are applied. It has to be noted that threshold values cannot be

⁎ Corresponding author at: Dept. of Electrical and Electronic Engineering (Control and Power Research Group), Imperial College London, Exhibition Road, London SW7 2AZ, UK. E-mail address: [email protected] (V. Trovato).

https://doi.org/10.1016/j.ijepes.2018.09.045 Received 18 March 2018; Accepted 28 September 2018 0142-0615/ © 2018 Elsevier Ltd. All rights reserved.

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changed frequently since this is a long and high-cost procedure. In addition, in the aftermath of a disturbance, RoCoFs can be very different across the system. As grid inertia reduces with more RES integration, spatial variations in frequency under transient condition play a crucial role and have to be accounted. Ref. [11] discussed the zonal characteristics of the RoCoF in the future GB network and its impact on DG anti-islanding LoM protection. Furthermore, [12] demonstrated this effect and compared the effectiveness of distributed rapid frequency response provision versus a concentrated one to enhance the system RoCoFs. As discussed in these works, sources of inertia may not be homogeneously distributed across the network and would directly impact regional protection schemes. Finally, the presence of flexible and distributed assets (e.g. battery storage, DSR, interconnectors, etc.), which are able to respond in the subsecond window, can also play a key role in enhancing the system response and need to be considered. In particular, this paper recognises fast-responsive capabilities of demand-side response through thermostatically controlled loads (TCLs) as an effective option for limiting grid frequency variations and RoCoFs [13,14]. The regular operating cycle of TCLs (refrigerators, air-conditioners, etc.) can be altered to provide frequency support without any noticeable impact on the controlled temperature [15,16]. Moreover, TCLs are highly distributed across the electricity network. In this context, TCLs possess the required scale and speed of response to avoid RoCoF protection misoperation and, potentially, to help the system maintain high-sensitive thresholds for LoM protections, despite a large integration of RES. Recent research [17] has presented different control strategies for TCLs in order to provide frequency response using the general properties of an accurate stochastic, distributed and non-disruptive control scheme [18]. However, the transient response in the subsecond time frame was not analysed in [17], hence neglecting cascading RoCoF-driven disconnections of DG units. Alternatively, this paper focuses on the possible interplay between RoCoF dynamics and local activation settings of LoM protection of DGs and other responsive assets. This interaction has not been reported in detail in the literature before. The main contributions of this work are as follows:

activated in islanding situations. Their purpose is to protect the generator by disconnecting it from the island when the connection to the main AC system is lost [6]. Commonly, the rate of change of frequency (RoCoF) is employed for this type of protection [5]. RoCoF [Hz/s] is defined as the frequency variation calculated over a certain time window ts as in (1). By varying the width of the window ts , different RoCoFs can be calculated.

RoCoFi t , ts =



ts )

ts

(1)

We point out the difference of RoCoF with the derivative of frequency (the limit of RoCoF as ts approaches zero) which is not suitable for practical implementations. For the remainder of this paper, we will use RoCoF calculated over different window lengths for the activation of the considered protection and support (response) schemes. In future low-inertia scenarios, high RoCoF values may lead to false DG tripping in non-islanding situations. Fig. 1 shows an example of the expected operation of a RoCoF-sensitive protection relay in these circumstances. To cope with this, in GB, current protection requirements in new and existing connections have been reviewed. Activations settings have been raised from 0.125 Hz/s to 1 Hz/s (for non-synchronous generators) and to 0.5 Hz/s (for synchronous generators), using a delay-setting (measurement period) of 500 ms [10]. This desensitisation of the protection settings may avoid undesired DG tripping but introduces the risk of not detecting islanding scenarios [11]. 2.2. Settings for RoCoF-sensitive LoM protection activation The principle of operation of a RoCoF-sensitive LoM protection relay is shown in Fig. 2. When the measured RoCoF (t , ts ) is above a security value RoCoFlimit , a trip signal is sent to open the DG circuit breaker. We consider that fi is measured in intervals of 20 ms (for fairness in the comparison with the RoCoF-sensitive TCL support, see Section 3.3) and then filtered using a standard low-pass filter with a 100 ms time constant. The value RoCoFlimit that triggers the DG protection activation is set to 1 Hz/s calculated over a time window ts of 500 ms, according to the proposal for new or asynchronous connections [10]. This work assumes that all the DGs in the system fall in one of these categories.

• First, this paper contributes to the existing literature by showing the



fi (t ) fi (t

ability of TCLs to implicitly contribute to system inertial response by preventing DG tripping due to large RoCoFs. RoCoF-driven DG disconnections can have a severe impact on the operation of future low-inertia systems. Distributed TCLs are proved to effectively measure local RoCoFs/frequency deviations and react accordingly (by collectively adjusting its power consumption) when these quantities drop below the specified thresholds. The second contribution is to investigate the link between fast frequency dynamics and activation settings of LoM protections and other frequency response providers. The effect of varying the RoCoF activation threshold and the RoCoF calculation window is analysed in the context of the new LoM protection setting choices in GB. It is shown that, under certain settings, some fast frequency transients might not be captured, which might impact the placement of future network assets. In addition, establishing appropriate local activation settings for the TCLs (which highly depend on local post-fault frequency dynamics) is crucial to ensure acceptable frequency variations under extreme low-inertia scenarios. Finally, the last contribution of this work is to show that TCLs can provide some leverage to retain relatively high RoCoF threshold for LoM protection settings. This is of course, in addition to the ability of TCLs to reduce the transient frequency deviations.

3. Advanced control of thermostatic loads for inertial and frequency response The TCL control strategy adopted in this work is described here. It relies on the concepts described in [17,18] in order to provide both inertial and frequency response support. An overview of the control scheme for TCLs connected at a generic bus i in the network is shown in Fig. 3. Two main stages can be distinguished in the design of this TCL demand response controller. The first stage ‘Switching Controller’ (described in Section 3.1) establishes the individual TCL ON/OFF switching strategy in order to collectively follow a desired power profile (t ) . Details on this stochastic, distributed and non-disruptive control strategy can be found in [18]. Note that the control strategy alters the regular operation of the appliances (number of ON/OFF switching actions1) if the reference power profile (t ) differs from the steady-state condition. Alternatively, the controller acts like a regular deadband controller. The second (high-level) stage in Fig. 3 is named as ‘Linear

2. RoCoF-sensitive LoM protection of distributed generators

1 As the switching in between the threshold temperatures is stochastic, an appliance may occasionally be requested to cycle more than once in a short period, affecting the compressor lockout requirements. The method described in [18] may be expanded to allocate switching events preferentially to devices that have not recently switched and, if the lockout period is strictly enforced, slight deviations from the desired curve may occur.

2.1. RoCoF-sensitive LoM protection Many distributed generators (DGs) connected to the grid at the low and medium voltage level have loss-of-mains (LoM) protections that are 184

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Controller’ (described in Section 3.2) and it tailors the signal (t ) to provide rapid inertial and frequency response. The activation settings of this TCL control are covered in Section 3.3. 3.1. Basics of TCL control framework The basics of the TCL control strategy presented in [18] to regulate the total power consumption of a cluster of TCLs are summarised here. The control strategy in (2) modulates the steady state power consumption P0 [MW] of the entire cluster by means of a reference power signal (t ) in order to control, in expectation, the aggregate TCL power P (t ) [MW]. The reference profile is common to all the appliances and in steady state, (t ) = 0 = 1. For a large cluster (as in practice), we can infer P (t ) = P0· (t ) . (2)

E [P (t )] = P0· (t ) Fig. 1. Expected operation of the RoCoF-sensitive LoM protection of a DG.

Pmin = P0·

Tmin

min

T (t )

P (t )

Tmax

Pmax = P0·

max

(3) (4)

The feasibility of tracking a power profile is constrained by the limits on instantaneous power levels in (3) where min and max only depend of the parameters of TCL thermal models [18]. Constraint (4) has to be satisfied to prevent the TCLs from violating the permissible temperature limits [Tmin, Tmax ] to safeguard the TCL primary function at all times. The main practical implication of this control algorithm is that any power consumption profile that satisfies (3) and (4) has been demonstrated to be realisable (in expectation) by the individual TCLs without the need for device-level simulations making the control strategy nondisruptive.

Fig. 2. Overview of RoCoF-sensitive LoM protection of DGs at bus i.

Fig. 3. Overview of TCL control connected at bus i.

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It is worth pointing out that the average temperature of the TCL cluster T (t ) evolves as function of the reference power (t ) :

dT (t ) = dt

1

T (t ) Toff +

(t )· Toff T0

(5)

where is the devices thermal time constant [s], Toff [° C] the ambient temperature and T0 [°C] the steady state average temperature [18]. Details on the thermal time constant derivation and other TCL parameters can be found in [19].

Fig. 4. Activation settings of TCL control connected at bus i.

3.2. The TCL linear controller for inertial and frequency response

4. Great Britain (GB) network

Using the general results of the preceding control strategy and, following our previous work [17], we consider an implementation of the control law in which (t ) is evaluated according to external variables (e.g. frequency, time) to provide inertial and frequency response. This is just a possible control law for TCLs whose choice was motivated because of its simplicity and its direct link with frequency and RoCoF dynamics. Accordingly, the response profile i (t ) for a cluster of TCLs connected to a bus i of a multi-machine system is defined as:

4.1. Reduced dynamic equivalent model of the GB network

i (t )

= 1 + K1·(f0 fi (t )) + K2·RoCoFi (t , ts )

In this work, the GB network is represented by a reduced dynamic equivalent model, developed by NG in DIgSILENT PowerFactory for academic research purposes [22]. A schematic overview of the system is shown in Fig. 5. This model allows spatial variation of transient frequencies at the different 400 kV buses to be captured to analyse the impact of TCL contribution to enhance the system inertial response. This is done by preventing, in a sub-second time window, cascading RoCoF-driven DG disconnections. The operating scenario considered in this study assumes a low total system demand of 20 GW and significant RES penetration (40%). This value is usually adopted by NG in their system studies as the lowest demand level in the network [9]. The total system level inertia is therefore extremely low (due to the large wind penetration) and equal to 66.45 GVAs which is in agreement with NG’s projection for future scenarios [1]. DGs (embedded generators connected at the distribution

(6)

We assume that all the TCLs connected to the same system bus i sense the same network frequency fi (t ) . Hence, each device in the cluster computes reacting only to its locally measured frequency deviation (from the nominal value f0 ) and the corresponding RoCoF acting in a a fully decentralised way. Considering (6), we propose:

K1

(fmin ) =

min

K2

(RoCoFmin) =

min

(7)

The values of K1 and K2 are chosen such that when the frequency deviation and RoCoF achieves the minimum security thresholds, fmin and RoCoFmin , respectively, the reference power level equals min . The controller at each bus enforces that the aggregate power consumption respects constraint (3) at all times. Hence, if the frequency drops below the security limit, the aggregate TCL consumption will be constant at mini = P0i· min . Temperature limits in (4) are also applied, but are not binding on the time scale of inertial response which is the focus of this paper. 3.3. Settings for TCL inertial and frequency response activation The implementation, in a multi-machine system, of the decentralised controller for rapid frequency response in (6) is shown in Fig. 4, for the TCLs connected to bus i. Similarly to what has been presented in Section 2.2, frequency fi is measured locally every 20 ms (following the ENTSO-E Demand Connection Code [20]) and filtered using a low-pass filter (with T = 100 ms). The rapid RoCoF/frequency-sensitive contribution from the TCLs is then activated according to two alternative criteria: flimit violation or RoCoFlimit violation, if the frequency variation or its rate of change are outside the specified limits, respectively. We consider that flimit corresponds to violating NG operational limit, which flags an abnormal condition for fi below 49.8 Hz [21]. The RoCoFlimit value that triggers the TCL activation is again set to 1 Hz/s calculated over 500 ms. It is important to note that RoCoFi employed by the control law in (6) is calculated over a time window of 20 ms, coherent with the sampling frequency of fi . These activation settings allows us to consider the large amounts of response available that would be used only during abnormal operating conditions.

Fig. 5. Reduced dynamic equivalent GB network model with coherent areas. The system contains 64 lines at 400 kV level, corresponding to the main transmission corridors in the system, and 36 buses representing the principal generation and demand areas. 186

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level) produce a total of 0.8 GW and are equipped with RoCoF-sensitive LoM protections, as described in Section 2. The system loads are represented following a top-down modelling approach, using an aggregated representation at the high voltage level. In addition, they are split into two aggregate loads at each bus: ‘General load’ (P constant current, Q constant impedance) and ‘TCL load’ (P constant power, Q constant power). The TCL loads represent domestic refrigerators with built-in freezer compartments with parameters as in [17]. Extension of this approach to other types of TCLs (e.g. heating systems) is straightforward following [18]. Assuming 65 million domestic refrigerators across the GB network, the aggregate power consumption is approximately 2.56 GW. The total minimum power level Pmin is 1.18 GW (see Section 3) [17]. 4.2. Overview of GB network inertial response and fast frequency services Using this reduced dynamic model, we study the response of the GB network following large frequency events. Since the focus of this work is on short-term dynamics, we only consider the first seconds after a severe generation infeed loss. Within this time interval, conventional generators supply their intrinsic inertial response and start to provide their primary response through the automatic governor control. Longterm responses/reserves are out of the scope of this work. NG has recently introduce a new frequency service, ‘enhanced frequency response’ (EFR), in order to better manage the initial frequency transients by providing a fast response in less than 1 s [23]. The objective of this service is to speed up the response delivery to account for low-inertia conditions. Demand-side technologies like TCLs are well suited to provide this type of support. However, in this work we do not specifically consider the TCL support as EFR. This is because this particular service is not yet well-established and may change in future [24]. Alternatively, we opted to highlight the speed of the TCL support and unlock the full flexible response available rather than focusing on the settings of a particular service. Nonetheless, note that the contribution from TCLs is delivered in the time-frame of EFR (power response supplied within 1 s).

Fig. 6. (a) RoCoF evolution at each bus of the network without TCL support; (b) RoCoF evolution at each bus of the network with TCL support.

cases, with values close to the 1 Hz/s (RoCoFlimit ) threshold (see Fig. 6(a) and (b)). In the case without TCL support (Fig. 6(a)), the RoCoF protection of some DGs located in the southern part of the network (Area 1 and part of Area 2) would trip. As a result, 254 MW of DGs were disconnected from the system. This, in addition to the generator outage, makes it impossible to restore the grid frequency, as seen in Fig. 7(a) (red traces). With TCL support, DG tripping is avoided as the maximum RoCoFs are restricted within 0.9 Hz/s (Fig. 6(b)). Note that in Fig. 7(a), when TCL support is not deployed (red traces), all the bus frequencies collapse after the generator outage, going outside security limits and activating low frequency demand disconnection (LFDD) protection schemes [2]. In order to prevent this, wind generation would have to be curtailed, which increases the system operational costs. Alternatively, with TCL contribution (Fig. 7(a) in green traces), the grid is able to accommodate the entire 8 GW of wind power available without violating the frequency limits. It is important to note that without TCL support to the overall system inertial response, the DGs are tripped in England/Wales, despite the fact that the frequency event occurred in Scotland. The more severe RoCoFs in England are a direct consequence of the 500 ms measuring window. It can be seen in Fig. 7(b) that frequencies in Scotland (Area 4) drop sharply at the beginning but after 500 ms they are above those in England (Area 1 and 2). Therefore, as previously mentioned, the strategic locations of RoCoF/frequency-sensitive assets providers should consider their activation settings and not just the distribution of local inertia between different areas. A zoomed view of the frequencies at the different system buses (for the case without TCL support) is shown in Fig. 7(b), where the spatial variation of frequencies is clearly manifested. Four coherent areas in the network can be identified, which are shown on Fig. 5. Table 1 presents a summary of the system characteristics on each grid area, which corresponds to this repartition. It is to be noted that for this

5. Simulation results Simulation results are presented in three separate subsections. Section 5.1 demonstrates how the inertial response and frequency transients of the GB network can be improved when fast contribution from TCLs is considered. Then, Section 5.2 presents the impact of RoCoF limits and measuring window on the RoCoF-sensitive activation of the TCL support and the LoM protection of DGs. Finally, Section 5.3 illustrates the effectiveness of using different RoCoF activation settings for TCLs to avoid undesired DG tripping. 5.1. Dynamic system response with nominal settings This paper focuses on the inertial transient period after a frequency disturbance and the fast protection events occurring in this time frame. Sudden loss of a 1.8 GW generator at bus 27−E in the north of GB network (Area 4 in Fig. 5) is simulated to investigate the dynamic variations in grid frequency and associated RoCoFs for this extreme low-inertia scenario. Note that this loss amount is the maximum infeed loss for which NG has to ensure system security and impose frequency/ RoCoF thresholds accordingly [21]. In order to deal with such an infeed loss, the system spinning reserves are kept at 1.8 GW. Fig. 6(a) and (b) show the measured RoCoFs at each system bus calculated using a 500 ms moving window for the cases without and with contribution from TCLs, respectively. To complete the analysis, the dynamic variations in frequency at the different buses without and with TCL contribution are also shown in Fig. 7(a) in red and green traces, respectively. Under the considered operating scenario, the above mentioned 1.8 GW infeed loss causes severe RoCoF conditions in both 187

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Fig. 7. (a) Dynamic variation of system frequencies -measured at generator terminalswithout TCL support (red) and with TCL support (green); (b) Dynamic variation of system frequencies -measured at generator terminals(ZOOM); (c) Total power consumption of aggregate TCL population; (d) Total power consumption of TCL population at each bus i (ZOOM). This grid response is ultimately due to the local inertia distribution connected at each bus, the inertia levels at buses in close electric proximity, the line impedances connecting them and the proximity to the outage location [12]. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Table 1 Characteristics of the GB network identified power system areas.

Area Area Area Area

1 2 3 4

Total

Hj

DGs

TCLs

[GVAs]

[MW]

8.91 36.11 0.76 20.67 66.45

[MW]

min f / t (over 500 ms) [Hz/s]

avg f / t (over 500 ms) [Hz/s]

min f / t (over 20 ms) [Hz/s]

avg f / t (over 20 ms) [Hz/s]

32 431 56 279

130 2057 120 248

−1.12 −1.06 −0.91 −0.92

−1.20 −1.01 −0.91 −0.92

−1.30 −1.24 −1.29 −1.90

−1.30 −1.20 −1.20 −1.40

799

2556

current dispatch scenario, other infeed loss disturbances would lead to similar (or less) number of coherent areas. Table 1 also includes the the minimum and average RoCoF values measured over 500 ms and 20 ms. This shows that, with a narrower measuring window, the obtained RoCoF values are higher and, more importantly, much higher for Area 4 (Scotland, where the generator outage took place) than in the rest of the system. With a 500 ms RoCoF measuring window, this is no longer true and the higher RoCoF values in the system are observed in Area 1 (England). Therefore, RoCoF measurement settings may impact the placement of flexible assets to provide grid support in future. This idea is expanded later in this section. The power consumption of the aggregate TCL population (Pi (t ) ) at each bus is shown in Fig. 7(d) and the total TCL power consumption (P (t ) = Pi (t ) ) in Fig. 7(c). The TCLs are able to collectively reduce the power consumption by about 1370 MW (down to the lower limit of 1180 MW as shown in Fig. 7(c)) within one second after the activation condition is triggered. Such a ramp rate is significantly higher than what could be offered by conventional generation technologies. For this study, the primary response required from conventional generators equals 1174 MW, which means that with such a rapid contribution from TCLs, the spinning reserve requirements could be lowered while keeping the system within security limits.

adopted 1 Hz/s as the RoCoF threshold (calculated using a 500 ms moving window) to trigger these actions, following NG recommendation [10]. However, RoCoF relays can adopt different measuring windows which usually vary between 2 and 40 cycles [8]. Table 2 summarises the system performance (for the generator outage at bus 27−E) using four different RoCoF thresholds (RoCoFlimit ) calculated over different moving window lengths ( ts ), with or without contribution from TCLs. The rightmost two columns (corresponding to 0.125 Hz/s) in Table 2 clearly illustrate the need to modify the current RoCoF setting (0.125 Hz/s) for LoM protections [10]. Regardless of the RoCoF calculation window and the presence of active TCLs (whose maximum contribution P0 Pmin is 1.37 GW), the GB network experiences frequency problems wherein the 49.2 Hz security limit is violated. This is in part due to the tripping of all DG units (800 MW in this extreme scenario) which further increases the imbalance between generation and demand, leading to larger frequency excursions across the network. For the case without contribution from TCLs, the frequency drops below the threshold for LFDD activation (48.8 Hz) [2]. Increasing the RoCoF threshold to avoid DG tripping in this extreme scenario is proven to be ineffective in containing the frequency variations without effective TCL support to the system inertial response, leading to LFDD activation for all the considered settings (last row). However, the amount of DG tripping reduces due to less RoCoF violations across the system. Analysing the cases of TCL responses, RoCoFlimit has to increase up to 0.9 Hz/s to prevent violation of frequency limits. This occurs when ts is equal to 500 ms is used for the RoCoF calculation. In this case, the minimum frequency nadir (among all the buses) is above the 49.2 Hz limit, although 106 MW of DG is still tripped. For

5.2. Impact of RoCoF settings on TCL support and DG protection activation We now focus on the RoCoFlimit setting for the activation of the LoM protection of DGs and the RoCoF/frequency-dependent contribution from TCLs, as seen in Figs. 2 and 4, respectively. So far, we have 188

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Table 2 Frequency nadirs and amounts of DG trips for varying RoCoF limits and measuring window (uutage at bus 27−E).

Table 3 Frequency nadirs and amounts of DG trips for varying RoCoF limits and measuring window (uutage at bus 12).

Table 4 Amounts of DG trips (MW) for varying measuring window with TCL support activation only (outage at bus 27 E).

Table 5 Amounts of DG trips (MW) for varying measuring window with TCL support activation only (outage at bus 12).

this setting, using a reduced measuring window (both to 100 ms and 40 ms), would lead to tripping of all DG units. Similar system performance is observed for the new proposed LoM protection setting of 1 Hz/ s [10]. Promising results with TCL support are obtained for scenarios with a RoCoF threshold of 1.35 Hz/s (even for reduced 40 and 100 ms moving windows) with the system frequency staying within limits (leftmost column). For all the presented scenarios with contribution from TCLs, these devices collectively provide their maximum contribution (1.37 GW) within one second after the event. The observed trends are valid irrespective of the loss of infeed location, although the extent of it would depend on where the outage takes place. For instance, Table 3 presents the same analysis for a 1.8 GW generator loss located in bus 12 (Area 2 in the South-East of the GB network). For this event, the observed frequency transients are slightly less severe but the overall effect of varying the RoCoF activation and measurement settings remains the same. The results shown in Tables 2 and 3 are consistent with NG’s analysis and their choice to adopt a higher RoCoF threshold calculated over

Fig. 8. RoCoF evolution at bus 1 without TCL support (red) and with TCL support for three different RoCoF activation settings: measured over 40 ms (black), 100 ms (blue) and 500 ms (green) windows. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

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a wider window in order prevent LoM protection tripping of DGs [9]. However, this action in conjunction with TCL contribution can allow further shares of RES to be integrated in the system. Without any support to the system inertial response (from TCLs in this case), the governor response of the conventional units is not able to contain the maximum frequency deviation, which would require additional system reserves from fast-acting generators.

RoCoF protection thresholds is also reduced. 6. Conclusion The paper demonstrates the ability of thermostatically controlled loads (TCLs) to effectively contribute to the system inertial response and avoid/minimise RoCoF-driven disconnection of distributed generators (DGs) in future low-inertia scenarios. The impact of local postfault frequency dynamics within each region of the Great Britain (GB) network on the local activation settings of DGs and TCLs is analysed through a reduced dynamic model for an extreme low-inertia scenario. The ability of TCLs to avoid DG tripping was demonstrated by means of an appropriate trade-off between RoCoF activation threshold and RoCoF calculation window size. This would ultimately allow larger shares of renewable integration in the grid.

5.3. Different activation settings for TCL support and DG protection In the previous subsection it was observed that, when using the same RoCoFlimit activation setting for DG protection and TCL support, a large value had to be set to ensure acceptable frequency variations in an extreme low-inertia scenario. However large RoCoFlimit protection thresholds are not desirable as the DGs could be exposed to values beyond their physical limitations, loosing the main functionality of the protection. Therefore, there is a motivation to keep this threshold low. We propose to set a narrower moving window for the RoCoF-driven activation of the TCL support while maintaining the 500 ms RoCoF window for DG protection. This way, in case of severe RoCoFs, the TCL power reduction would occur slightly earlier, limiting the frequency deviation and arresting the RoCoFs across the system. Accordingly, as the RoCoF seen by the LoM protections is less, this would minimise (or avoid) DG trippings. For LoM protection of DGs, the width of the measuring window is a trade-off between the need to avoid spurious DG trippings and the risk of accidentally energizing an electrically isolated section of network [10]. Similar concerns do not affect the TCL activation which would happen anyway when frequency drops below some activation threshold flimit (49.8 Hz in Fig. 4). Note that a faster TCL activation may also lead to less overall TCL power reduction over the transient period. Tables 4 and 5 show, for different loss of infeed locations, the effect of reducing the RoCoF measurement window of the TCL support activation while keeping the RoCoF activation threshold (RoCoFlimit ) both for TCL support and DG protection. It is clear from these results that a faster response from the TCLs is always desired as it prevents/reduces the activation of DG tripping. One of these scenarios is analyzed in detail next. Fig. 8 shows the dynamic response for the scenario where the RoCoF threshold is set to 0.85 Hz/s and the measuring window for the RoCoFsensitive LoM of the DGs is 500 ms, for the 1.8 GW outage at bus 27−E. Three cases are considered for the RoCoFlimit activation of the TCL support: measured over 500 ms, 100 ms and 40 ms. In particular, Fig. 8 shows the RoCoF values measured by the LoM protection of the DGs connected at bus 1. If TCLs do not respond to frequency variations or the RoCoF measuring window is equal to that of the DG protection (in red and green, respectively), LoM protections will trip the total of DG units (800 MW). In this case, the TCL support can only limit the frequency nadir, but it cannot avoid DG tripping. With a faster 100 ms measuring window for the TCLs, DG tripping is reduced to 393 MW (in blue). In this case, mainly DGs located in Areas 1 and 2 (England/Wales) would trip as they experience larger RoCoF values than in the rest of the network. With a 40 ms window (in black), there is no need to trip DG units as the RoCoF is limited to 0.85 Hz/s. This particular setting to avoid DG tripping is also verified for other loss of infeed locations. Fig. 8 also demonstrates the value of distributed resources to improve the frequency transients: if TCLs were all located in a single bus, they could not have reacted to, and thus quickly reduced, the large RoCoF at bus 1, still causing DG trippings. Of course, this result depends on the considered operating scenario: in some cases, the avoided DG curtailments could be much more significant or, in other cases, negligible. The fundamental idea presented here is that TCLs may not need to operate under the same requirements set for DG protection. Narrower RoCoF measuring windows for activating the TCL support may avoid cascading DG trippings. In addition, risk for the DGs under large

Declarations of interest The authors have nothing to declare. This work was conducted at Imperial College London, London, UK. Later on, V. Trovato has joined EDF Energy R&D UK Centre and I. Martínez Sanz has joined National Grid, UK. V. Trovato is also a Visiting Researcher at Imperial College London, London UK. References [1] National Grid, System Operability Framework SOF 2016 – Full Interactive Document; 2016 . https://www.nationalgrid.com/uk/publications/systemoperability-framework-sof [visited on 18–03–2018]. [2] Ofgem, D09 OC6.6 Automatic Low Frequency Demand Disconnection (LFDD); 2010. https://www.ofgem.gov.uk/publications-and-updates/d09-oc6.6-automaticlow-frequency-demand-disconnection-lfdd[visited on 18–03–2018]. [3] Dysko A, Tzelepis D, Booth C. Assessment of risks resulting from the adjustment of ROCOF based loss of mains protection settings; 2015. https://www.nationalgrid. com/sites/default/files/documents/Appendix%201%20Strathclyde%20Report %201.pdf [visited on 18–03–2018]. [4] Mahat P, Chen Z, Bak-Jensen B. Review of islanding detection methods for distributed generation. In: Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies; 2008. p. 2743–8. [5] Freitas W, Xu W, Affonso CM, Huang Z. Comparative analysis between ROCOF and vector surge relays for distributed generation applications. IEEE Trans Power Delivery 2005;20(2):1315–24. [6] Liu B. Advanced rocof protection of distribution systems. Ph.D. thesis. University of Nottingham; 2012. [7] Vatani M, Amraee T, Ranjbar AM, Mozafari B. Relay logic for islanding detection in active distribution systems. IET Gener Trans Distrib 2015;9(12):1254–63. [8] Ding F, Booth CD, Roscoe AJ. Peak-ratio analysis method for enhancement of LOM protection using M-class PMUs. IEEE Trans Smart Grid 2016;7(1):291–9. [9] National grid, frequency changes during large disturbances and their impact on the total system; 2013 https://www.nationalgrid.com/sites/default/files/documents/ 16991-workgroup%20report.pdf [visited on 18–03–2018]. [10] Ofgem. Changes to the distribution code and engineering recommendation G59; 2014 https://www.ofgem.gov.uk/publications-and-updates/changes-distributioncode-and-engineering-recommendation-g59-frequency-changes-during-largedisturbances-and-their-impact-total-system [visited on 18-03-2018]. [11] Cao X, Abdulhadi I, Emhemed A, Booth C, Burt G. Evaluation of the impact of variable system inertia on the performance of frequency based protection. In: 12th IET DPSP; 2014. p. 1–6. [12] Sanz IM, Chaudhuri B, Junyent-Ferré A, Trovato V, Strbac G. Distributed vs. concentrated rapid frequency response provision in future Great Britain system. In: 2016 IEEE PESGM; 2016. p. 1–5. [13] Mokari-Bolhasan A, Seyedi H, Mohammadi-ivatloo B, Abapour S, Ghasemzadeh S. Modified centralized ROCOF based load shedding scheme in an islanded distribution network. Int J Electr Power Energy Syst 2014;62:806–15. [14] Qazi HW, Flynn D. Analysing the impact of large-scale decentralised demand side response on frequency stability. Int J Electr Pow Energy Syst 2016;80:1–9. [15] Short J, Infield D, Freris L. Stabilization of grid frequency through dynamic demand control. IEEE Trans Power Syst 2007;22(3):1284–93. [16] Conte F, Massucco S, Silvestro F, Ciapessoni E, Cirio D. Stochastic modelling of aggregated thermal loads for impact analysis of demand side frequency regulation in the case of Sardinia in 2020. Int J Electr Power Energy Syst 2017;93:291–307. [17] Trovato V, Sanz IM, Chaudhuri B, Strbac G. Advanced control of thermostatic loads for rapid frequency response in Great Britain. IEEE Trans Power Syst 2017;32(3):2106–17. [18] Tindemans S, Trovato V, Strbac G. Decentralized control of thermostatic loads for flexible demand response. IEEE Trans Control Syst Technol 2015;23(5):1685–700. [19] Trovato V, Tindemans SH, Strbac G, loads Leaky storage model for optimal multiservice allocation of thermostatic. IET Generation. Transm Distrib

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V. Trovato et al. 2016;10(3):585–93. [20] ENTSO-E. Demand connection code; 2015 https://www.entsoe.eu/major-projects/ network-code-development/demand-connection [visited on 18–03–2018]. [21] National Grid, NETS Security and Quality of Supply Standard, version 2.3; 2017 http://www.nationalgrid.com/uk/electricity/codes/security-and-quality-supplystandards [visited on 18–03–2018]. [22] Urdal H, et al. Renewable power generation. IET 2015;9(1):10–7.

[23] National grid, enhanced frequency response Frequently Asked Questions FAQs v.5. 0; 2016 http://www.nationalgrid.com/uk/electricity/balancing-services/ frequency-response-services/enhanced-frequency-response-efr [visited on 18–03–2018]. [24] National grid, future of balancing services; 2018 https://www.nationalgrid.com/ uk/electricity/balancing-services/future-balancing-services [visited on 18-032018].

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