Camille Le Guen
email: cam.leguen@gmail.com

Samuele Tecchio

Jean-Claude Dauvin

Gwenola De Roton

Lobry

Mario Lepage

Jocelyne Morin

Géraldine Lassalle

Aurore Raoux

Assessing the ecological status of an estuarine ecosystem: 4 linking biodiversity and food-web indicators 5 6

Keywords: ecology, biodiversity, food web, ecosystem functioning, ecosystem health 58 indicators 59 60

The Seine estuary ecosystem was described before and after the Port2000 extension.

29

A toolbox of various indices was used, describing complementary characteristics. 30 Port2000 effects were complex to separate from other human-induced and natural effects.

31

Ecological Network Analysis was useful in defining functional indicators.

32

The need to continue long-term monitoring and to use multiple tools is emphasized.

continuous dredging activities, and that the southern channel could be seen as the least disturbed 141 area for both periods (Tecchio et al., 2016).

142

In addition to these anthropogenic disturbances, the Seine Estuary is also subject to an 143 increase of salinity in the lower part of the estuary, called marinisation. Marinisation is due to 144 a decrease in freshwater input coming from the river, associated with intrusion of marine water 145 in the lower part of the estuary. Marinisation is a common evolution in estuaries receiving water 146 from rivers and influenced by human activities (e.g. irrigation, dams) (David et al., 2007; 147 Goberville et al., 2010;Chaalali et al., 2013).

148

We used here an original combination of methods to assess the ecosystem health of the Seine 149 estuary before and after the construction of Port2000. These analyses were performed on six 150 spatial boxes previously defined to describe the estuary (Tecchio et al., 2016). and (c) two marine spatial boxes (E2 and E14) (Fig. 1). Hydro-sedimentary and salinity 167 conditions were considered homogenous within each spatial box (Tecchio et al., 2015). For β-diversity is the ratio between γ and (Eq. 2) [START_REF] Anderson | Navigating the multiple meanings of β 687 diversity: A roadmap for the practicing ecologist[END_REF] and represents the ᾱ 203 number of times by which the taxonomic richness in the whole region considered (i.e. the entire 204 estuary) is greater than the average taxonomic richness in the different spatial boxes. In other 205 words, it corresponds to the ratio between regional and local species diversity and is related to

273

Metabolic parameters as well as dietary constraints (i.e. proportion of prey in predator diet)

274

were implemented as "inequalities": minimum and maximum values were included in the linear 275 equations to partially constrain the related flows. This approach produces solutions that are 276 robust to the effect of parameterisation uncertainty (Hines et al., 2015;Hines et al., 2018).

Omnivory Index (SOI), the Finn's Cycling Index (FCI), the Ascendency (A), the relative et al., 2019). The

295

Total system throughput (T..) corresponds to the sum of all flows occurring in the system, and 296 acts as an indicator of system size and activity (Rutledge et al., 1976;[START_REF] Aoki | Entropy laws in ecological networks at steady state[END_REF] In the estuary boxes CH and FN, fish and macrozoobenthos biomasses increased between 336 periods (Fig. 2, Table 1). For the southern channel (FS), while macrozoobenthos biomass 337 increased, fish biomass remained stable, and it appeared that this was the case for all fish groups 338 (Fig. 2). For instance, the biomass of piscivorous fish in FS averaged 0.057 g C.m -2 in the first 339 period and approached 0.055 g C.m -2 in the second one. In CH, while total fish biomass 340 increased, the biomass of planktivorous fish decreased (Fig. 2). This was mainly related to two 341 pelagic species: Clupea harengus and Sprattus sprattus. In the same way, for FN, while the 342 total fish biomass increased, the biomass of piscivorous and planktivorous fishes slightly 343 decreased (Fig. 2). This was quantitatively compensated by a strong increase in benthos feeders' 344 biomass. The decrease in planktivorous fish biomass in FN was due to four species Clupea 345 harengus, Gasterosteus aculeatus, Osmerus eperlanus and Sprattus sprattus. The overall 346 biomass (including fish, macrozoobenthos and the suprabenthos) increased for the three 347 estuarine spatial boxes. Among the three estuarine boxes, the ratio of fish biomass on benthic 348 invertebrate biomass (BFish/BMacrozoobenthos) was the highest in CH (0.09 in the first period 349 and 0.03 in the second one). Nonetheless, this ratio was divided by three in CH congruently to 350 the sharp increase in benthic macrofauna biomass between periods that was multiplied by 7

351

(Fig. 2, Table 1). 359 Table 1. Summary of comparisons between periods (Before and After Port2000 construction)

362

for biomass values, biodiversity indices, and the ELFI index. See text for details on the indices.

363

< indicates that the value of the index is lower Before than After Port2000; > indicates that the 364 value of the index is greater Before than After Port2000.

Spatial boxes

CH FN FS E4 E14 E2 Fish < < < > < > Biomass Benthos < < < < < < Fish < < < < > > TR Benthos < < < < < < Fish < < < < > > α Benthos < < < < < < Fish < ᾱ * Benthos < Fish < β * Benthos > Fish < γ * Benthos < Diversity ELFI* < 365
* ᾱ, β and γ diversity indices are computed for the whole estuary 366 367

Taxonomic richness and species composition 368

The taxonomic richness increased between periods, from 16 to 47 fish taxa and from 5 to 29 369 macrozoobenthos taxa in the navigation channel (CH) (Fig. 3). The same trend was observed The α, β and γ taxonomic diversity analyses between periods showed that the average 388 number of fish species ᾱ increased from 32.8 to 41 species, and from 65.7 to 177.2 for 389 macrozoobenthos. γ-diversity increased from 54 to 71 taxa for fish and from 195 to 353 taxa 390 for macrozoobenthos, and β-diversity increased from 1.65 to 1.73 for fish and decreased from 391 2.97 to 1.99 for macrozoobenthos (Table 1).

393

The MDS ordination based on fish composition data showed a remarkable spatial 394 segregation according to the salinity gradient between the estuarine and the marine spatial boxes where FN and FS were grouped and CH isolated from these two other estuarine boxes. Similar 411 results were obtained for macrozoobenthos. But in the 'After' period, the marine box E4 was 412 grouped, for fish, with not only the estuary boxes FN and FS, but also CH (Fig. 4). This 413 similarity in biodiversity composition was only limited to fish compartment; the benthos 414 remained structured in a very similar way, in both periods. stable in all the other spatial boxes (Table 2); Cliff's delta; Fig. 6).

435

The SOI, reflecting the omnivory in the system, significantly decreased in the estuary box

436

FS between the two periods. (Fig. 6). The D/H ratio significantly increased in the estuary boxes 437 CH, FN and in the intermediate box E4, while remaining stable in the marine boxes E14, E2

438 and in FS (Table 2, Fig. 6).

439

The FCI reflecting the recycling in the system, significantly increased between the two 440 periods in the estuary boxes CH, FN and in the intermediate box E4 (Table 2, Fig. 6).

441

The ascendency (A) and relative redundancy (R/DC) indices significantly increased in CH

442

between the two periods. The ascendency also significantly increased in the intermediary box

443

E4 between the two periods (Table 2, Fig. 6).

444 Fish species were sampled using beam trawls, which target the first 50cm above the seafloor.

466

The fish assemblage was therefore biased, the pelagic species likely being underestimated. In 467 addition, the edges of each habitat were not sampled. Therefore, a few fish species might not 468 have been sampled. However, the sampling gears and methods were similar between periods and among spatial boxes, allowing comparison between time periods and spatial boxes. ELFI 470 values, for both periods, need to be considered with some caution, given the differences in 471 sampling protocol between periods that may slightly affect the comparability. spatial boxes can also be a sign of increasing stress (Vasconcellos et al., 1997). However,

530
increasing FCI and D/H values could also be interpreted by a sign of increasing maturity 531 (Odum, 1969;[START_REF] Christensen | Ecosystem maturity-towards quantification[END_REF][START_REF] Allesina | Cycling in ecological networks: Finn's index revisited[END_REF]Vasconcelos et al., 2007) The FS, which was initially considered as the least varying spatial box (Tecchio et al., 2015) 541 and thus a reference, showed a reduction in redundancy (R/DC), omnivory (SOI) and detritivory

542

(D/H), while maintaining a stable system activity (T..) and carbon recycling (FCI). The trophic

564

This might be explained by a potential increasing turbidity in E2 due to the dumping of 565 sediments that could affect fish more than the benthic communities. However, the effect of the 566 Port2000 construction on these two marine boxes cannot be evidenced. In FS, both fish and macrozoobenthos taxonomic richness increased. However, the ratio 590 BFish/BMacrozoobenthos remained stable. The MDS analysis showed that the fish 591 composition in this spatial box did not deeply change between periods. ENA indices suggest a 592 mature system for FS for both periods. Therefore, this estuarine spatial box could be confirmed put forward that E4 could be seen as an intermediate spatial box for fish, but as a marine box 605 for the macrobenthos community. Indeed, this confirmed that E4 itself can be considered as an

606

'ecocline', i.e. a boundary of progressive changes (spatial and ecological) between two different 607 systems, the ocean and the estuary [START_REF] Attrill | Ecotone or Ecocline: Ecological Boundaries in Estuaries. 691[END_REF][START_REF] Basset | A unifying approach to understanding 699 transitional waters: Fundamental properties emerging from ecotone ecosystems. 700[END_REF]. Finally, show no significant differences between the two periods for both spatial boxes. Indices based The effects of the Port2000 construction were not as evident as expected due to the presence

151

  We first addressed the methodological question "Do the different indicators used in this 152 study (species-based, guild-based and ecosystem-based indices) bring similar, complementary 153 or different information on the ecological status of this estuarine ecosystem?" We then 154 addressed two ecological questions using this set of indicators: (i) How did physical distinct 155 areas of the estuary (spatial boxes) react to perturbations? (ii) Can we distinguish the effects 156 due to Port2000 from global change effects in the context of the estuary's natural marinisation? , based on habitat characteristics and sediment types of the Seine estuary 163 and the adjacent eastern part of the Seine Bay, previously defined in Tecchio et al. (2015) were 164 considered: (a) three estuarine boxes: the navigation channel (CH), the northern channel (FN), and the southern channel (FS); (b) an intermediate box located at the mouth of the estuary (E4), 166

Fig. 1 .

 1 Fig. 1. Map showing the geographical position of the Seine estuary in France. The spatial boxes

  diversity = taxonomic diversity of the entire region of interest and = mean α-diversity. ᾱ 209 Biodiversity analyses were performed using the software package PRIMER-E v.6 (Clarke 210 & Gorley, 2006). A two-dimensional non-metric Multi-Dimensional Scaling (nMDS) 211 ordination was implemented for the six spatial boxes for each of the two periods, based on 212 square-root-transformed biomasses to reduce the asymmetry in species distributions, and a 213 Bray-Curtis similarity index computed on a species composition matrix. The nMDS plot gives 214 a visual representation of the proximity in species composition between samples: the closer 215 they are on the plot, the more similar they are in their species composition (Clarke and Warwick, 216 2001). The 'stress' index calculated by the routine in PRIMER reflects how well the ordination 217 is capable of preserving the rank of similarities in a bi-dimensional space, providing information 218 on the quality of the representation. Port2000' were standardized data, collected from surveys following a 223 normalized protocol especially designed for fish monitoring in the French estuaries for the 224 WFD (Appendix A). Fish data used for multimetric fish-based indicator ELFI (Delpech et al., 225 2010) calculation 'Before Port2000' were collected from surveys designed for various other 226monitoring purposes but were obtained using similar sampling gear (i.e. beam trawls with similar net features). For standardization and comparison, we accounted for sampling effort these indices are consistent. Data were provided by 'Agence de l'Eau Seine Normandie' for the conversion efficiency (i.e. ratio of the biomass produced by one compartment compared to its 265 food intake[START_REF] Christensen | Ecopath with Ecosim: Methods, capabilities and 729 limitations[END_REF])), respiration, and excretion ratios. Data sources and 266 references used for the construction of the LIM-MCMC models are presented in detail in 267Tecchio et al. (2015Tecchio et al. ( , 2016)). Briefly, a system of linear equations was set up, linking species 268 metabolic ratios (such as production/biomass, respiration/biomass, excretion/consumption 269 ratios), species biomass, and diet compositions. In these equations, the unknowns were the 270 flows connecting the compartments. The flow constraints were established using data from 271 literature or other modelling works (Appendix C). Known equalities such as those including 272 the biomass stocks were included to constrain the model into a finite multi-dimensional space.

292

  Redundancy (R/DC) and the Detritivory/Herbivory ratio (D/H). This set of indices was used by 293 Tecchio et al. (2016) to characterize the inner part of the Seine estuary and most of them have 294 been proposed as management tools in the OSPAR Convention context (Safi

Fig. 2 .

 2 Fig. 2. Barplots representing fish biomass, macrozoobenthos biomass, the sum of fish and

370

  in the Northern and Southern channels (FN and FS; Fig.3). The estuary box CH showed 371 particularly low values of macrozoobenthos taxonomic richness compared to the other spatial 372 boxes (Fig.3). The intermediate box E4 was the richest spatial box in terms of fish (with 51 373 taxa during the first period and 59 taxa during the second one) and benthic macrofauna (with 374 177 taxa during the first period and 307 during the second one). No strong changes were 375 observed for the fish taxonomic richness in the marine spatial boxes E14 and E2. All taxa that 376 were gained between periods, both for fish and macrozoobenthos, were exclusively of marine 377 origin. Results on standardised taxonomic richness are given in Figure3.

Fig. 3 .

 3 Fig. 3. Barplots representing taxonomic richness divided by the log-transformed total number

395(

  Fig. 4 top). The same pattern was observed with the MDS ordination based on 396 macrozoobenthos species (Fig. 4 bottom). The 'stress' value of 0.05 was very low, underlying 397 the good quality of the representation.

Fig. 4 .

 4 Fig. 4. MDS ordination based on Bray-Curtis similarity matrices from biomass data (square-

  A community-based index for fish: ELFI 417 During the period before Port2000, the Seine estuary showed lower values of ELFI (from 418 0.1 to 0.14) compared to the period after Port2000, the highest value recorded being 0.68 in 419 2006 (Fig. 5). The metric DDIA, indicator of habitat connectivity related to diadromous species, 420 showed strong changes in the recent period (after Port2000), with a value of 0.88 in 2006, 0.70 421 in 2010 and 0.71 in 2012 (missing value in 2011), meaning that this metric gradually decreased 422 after the Port2000 construction.

Fig. 5 .

 5 Fig. 5. ELFI values for the whole estuary for 10 years, between 1995 and 2012, with the class

  4273.3. Ecosystem-based indicators: food webs and ENA428ENA indices showed that all indices in the two marine zones (E2 and E14) remained similar 429 between the two periods (

Fig. 6 .

 6 Fig. 6. Ecological network analysis (ENA) indices for all spatial boxes for the period before

458

  Means and standard deviations are represented. Asterisks represent significant changes assessed 459 from Cliff's delta statistics (level 0.05; between before and after construction).

  marine species increased between both periods in the Seine estuary. For 475 example, Pomatoschistus minutus biomass increased in two estuarine boxes(FN, FS), and in 476 the intermediate box (E4), and P. microps was newly observed in these areas after Port2000.477These two fish species, especially P. minutus are mostly marine species(Leitão et al., 2006), 478 suggesting a tendency of marinisation. Previously termed byDavid et al. (2007) and later used 479 in several papers(Pasquaud et al., 2012; Chevillot et al., 2016 Chevillot et al., , 2017)), « marinisation » 480 describes the process whereby marine waters flow far upstream into the basin along with a 481 higher abundance of marine species in the estuarine transitional zone. The Seine estuary, as 482 many north-eastern Atlantic Ocean estuarine ecosystems (Goberville et al., 2010), is going 483 through a process of 'marinisation'. The time period 2005-2012 was characterised by a 484 significantly lower discharge of the Seine river (Dauvin and Pezy, 2013), resulting in an 485increase of salinity up to 5 in the estuarine boxes[START_REF] Bacq | Projet MESSCENE: 693 modélisation des fonctions écologiques de l'estuaire de la Seine et Scénarios 694 d'évolution[END_REF]. The salinity in the marine 486 boxes remained stable between periods. The arrival of marine species finding newly suitable 487 conditions in most spatial boxes might explain the increase in taxonomic richness. This 488 marinisation tendency was supported by the MDS ordination showing a clear spatial (along the 489 salinity gradient) and temporal (before and after Port2000) segregation, indicating that 490 marinisation modified the ecological structure of communities. This is also supported by the 491 higher ELFI values in the Seine estuary after Port2000 which is likely a consequence of the 492 marinisation enhancing the taxonomic richness and biomass of fish in the estuarine spatial 493 boxes. The same trend has already been observed in the Gironde estuary where changes in fish assemblages and an increase of the ELFI index were attributed to an increase in temperature 495 and salinity indicating marinisation (Pasquaud et al. 2012; Chevillot et al., 2016, 2017). estuary, the ELFI indicator increases with ecosystem quality (Le Pape et al., 500 2015). The ecological status of the Seine estuary therefore improved from a 'bad' status before 501 Port2000 to a 'poor' status after Port2000. Diadromous species abundance was associated to 502 habitat connectivity, as opposed to habitat fragmentation (barriers to migratory fish) (Pasquaud 503 et al., 2013). After Port2000, the highest DDIA value recorded was 0.88 in 2006 and then the 504 general pattern of this metric for that period was characterized by an overall decrease of DDIA, 505 with values dropping down to 0.71 in 2012, likely due to a lower connectivity for migrant 506 species such as eel Anguilla anguilla or grey mullet Liza ramada, associated with the extension 507 of the breakwaters between FN and CH during the Port2000 construction. As an example, smelt 508 O. eperlanus is a diadromous species which was formerly abundant in the upper part of the 509 northern channel for reproduction (Morin et al., 2015). Extending the breakwaters between FN 510 and CH during the Port2000 construction might have impacted the connectivity between these 511 two zones, and O. eperlanus has been negatively affected by this rupture of connectivity. 512 Moreover, it seemed that the differences in fish assemblages between the spatial boxes widened 513 (β-diversity increased from 1.65 to 1.73), which might be related to availability of new habitats 514 for marine species inside the estuary. Concerning benthic species, the diversity trend between 515 spatial boxes showed the reverse trend, showing signs of standardisation (β-diversity decreased 516 from 2.97 to 1.99). 517 518 4.3.2. Estuarine disturbed boxes Comparatively to the rest of the estuary, strong effects of perturbations were expected in the 520 navigation channel (CH) because of the continuous dredging and the high hydrodynamics. The 521 estuarine box FN was the spatial box the most directly affected by the construction of Port2000 522 and by the mitigation measures such as the artificial formation of meanders, which might have 523 modified the hydrodynamics (Cuvilliez et al., 2015). In addition, an increase in water turbidity 524 was noted in this box (S. Lesourd, personal communication). 525 The increase in detritivory/herbivory ratio (D/H) observed in both CH and FN between the 526 two periods suggests an ecosystem more stressed after the Port2000 construction (Niquil et al., 527 2014), probably reacting to perturbations by enhancing opportunistic behaviours such as 528 detritivory. The higher carbon recycling (FCI) observed after Port2000 in these two estuarine 529

543

  specialisation was evidenced by the congruent reduction in omnivory (leading to a more chain-like structure of the food web) and redundancy (reduction of parallel pathways), which can be 545 a sign of maturity. Results for FS therefore suggested that the reduced disturbance conditions 546 here favoured an expected ecological succession. transitional area between the inner estuary and the marine environment. Results550from ENA indices show an increase in system activity (T..), redundancy (R/DC), carbon cycling 551 (FCI), omnivory (SOI) and detritivory (D/H). Therefore, as for CH and FN, following the same 552 interpretation framework, we could assume that the system in E4 was increasing its stabilizing 553 mechanisms when facing stronger disturbances. indices show no significant differences between the two periods for both 557 spatial boxes E14 and E2. Therefore, we can assume that the construction of Port2000 has no 558 negative effect on the food web dynamics of these two marine boxes. However, the spatial box 559 E2 contains the dumping site of Octeville for dredged sediments from the Le Havre harbour 560(Marmin et al., 2014). For these two spatial boxes, we noticed that the fish taxonomic richness 561 decreased whereas the benthic macrofauna richness increased. The relative importance of 562 benthic communities had intensified in E2, as shown by the decrease in the 563 BFish/BMacrozoobenthos ratio between both periods, contrary to what was noticed in E14.

  diversity and ELFI index values observed after Port2000 in a context 571 of marinisation suggest a decrease of ecosystem stress after Port2000, as taxonomic richness is 572 considered a key factor in ecosystem stability in response to anthropogenic pressures (e.g.573McCann[START_REF] Bondavalli | Insights into the processing of carbon in the 702 South Florida Cypress Wetlands: a whole-ecosystem approach using network analysis[END_REF] Chapin et al., 2000). However, investigations in the different spatial boxes were 574 necessary to detect potential effects of the Port2000 construction. 575 576 4.4.1. Estuarine disturbed boxes 577 The food web in CH is continuously disturbed due to the dredging activity, greatly limiting 578 the colonisation of the seafloor by benthic organisms, as seen in other locations (e.g. in the 579 Venice lagoon: Pranovi et al., 2003). In CH, the community was characterized by an extremely 580 low benthos richness and biomass compared to the other spatial boxes. Nonetheless, 581 communities subjected to regular disturbances are also more adapted, less sensitive, and recover 582 more quickly than undisturbed communities (Dernie et al., 2003; Marmin et al., 2014). Results 583 from ENA indices in the two boxes CH and FN suggest an ecosystem more stressed after the 584 Port2000 construction. Species-based indices were very useful to detect the effects of dredging 585 activities which directly affect the settlement of benthic communities. This effect was also 586 reflected in the ENA indices.

608

  results from ENA indices demonstrated an increase in system activity, redundancy, cycling, 609 omnivory and detritivory between the two periods. Therefore, as for CH and FN, ENA indices 610 enabled us to identify that the system was increasing its stabilizing mechanisms, probably to the bay, E14 and E2 marine boxes appeared similar in terms of fish and 615 macrozoobenthos taxonomic composition between the two periods. Results from ENA indices 616

Fig. 1 . 944 Fig. 2 .

 19442 Figure legends

Fig. 3 .

 3 Fig. 3. Barplots representing taxonomic richness divided by the log-transformed total number

Fig. 4 .Fig. 5 .Fig. 6 .

 456 Fig. 4. MDS ordination based on Bray-Curtis similarity matrices from biomass data (square-

970

  Means and standard deviations are represented. Asterisks represent significant changes assessed 971 from Cliff's delta statistics (level 0.05; between before and after construction).

  Table 2). R/DC and SOI decreased between before and after "Port Total System Throughput (T..), representing the size and activity of the system, significantly 433 increased in the estuary boxes CH and FN as well as in the intermediate box E4 and remained

	430	2000" in the estuary box (FS). All indices, except SOI, increased between the two periods in
	431	the intermediate box E4 and in the estuary boxes CH and FN.
	434

432

Table 2 .

 2 ENA means and standard deviations, derived from LIM-MCMC models, for all spatial 447 boxes before(1996)(1997)(1998)(1999)(2000)(2001)(2002) and after (2005-2012) Port2000 construction. < indicates that the 448 value of the index is lower Before than After Port2000; > indicates that the value of the index 449 is greater Before than After Port2000. Only statistically significant results based on Cliff's delta

	450	are listed. ns: non-significant.
	451
		ENA	Period	CH	FN	FS	E4	E14	E2
				1935 ±	2244 ±	2600 ±	2424 ±	2475 ±	2447 ±
		T..	Before	337	251	240	347	296	364
				2332 ±	2463 ±	2507 ±	2687 ±	2494 ±	2564 ±
		T..	After	361	273	227	352	294	328
		Evolution T..		<	<	ns	<	ns	ns
				0.087 ±	0.124 ±	0.163 ±	0.128 ±	0.135 ±	0.149 ±
		FCI	Before	0.03	0.03	0.03	0.03	0.02	0.04
				0.119 ±	0.175 ±	0.178 ±	0.153 ±	0.131 ±	0.145 ±
		FCI	After	0.03	0.04	0.04	0.03	0.02	0.03
		Evolution FCI		<	<	Ns	<	ns	ns
				3542 ±	4066 ±	4648 ±	4382 ±	4480 ±	4408 ±
		Ascendency Before	675	465	461	692	589	721
				4285 ±	4453 ±	4532 ±	4942 ±	4590 ±	4649 ±
		Ascendency After	742	534	450	737	588	667
		Evolution Ascendency		<	<	Ns	<	ns	ns
		R/DC (%)	Before 32.6 ± 2 40.6 ± 2 43.7 ± 2 40.6 ± 2 40.9 ± 2 41.5 ± 2
		R/DC (%)	After	39.2 ± 2 41.8 ± 1 41.7 ± 2 42.4 ± 2 41.6 ± 2 42.6 ± 2
		Evolution R/DC(%)		<	<	>	<	ns	ns
				0.145 ±	0.133 ±	0.136	0.146 ±	0.143 ±	0.130 ±
		SOI	Before	0.02	0.02	±0.01	0,01	0.01	0.01
				0.146 ±	0.125 ±	0.119 ±	0.148 ±	0.142 ±	0.137 ±
		SOI	After	0.01	0.01	0.01	0.01	0.01	0.01
		Evolution SOI		ns	ns	>	ns	ns	ns
				0.317 ±	0.589 ±	0.796 ±	0.600 ±	0.637 ±	0.692 ±
		D/H	Before	0.12	0.12	0.13	0.11	0.11	0.16
				0.553 ±	0.776 ±	0.758 ±	0.760 ±	0.658 ±	0.718 ±
		D/H	After	0.12	0.16	0.15	0.15	0.11	0.12
		Evolution D/H		<	<	ns	<	ns	ns

Table 3 .

 3 Main information about the functioning and the status of the six spatial boxes.

	633
	Method	Main results	Conclusions
		Increase of the taxonomic richness	Arrival of marine species
		between periods for the estuarine	such as P. minutus in relation
		spatial boxes (CH, FN, FS) and	to the marinisation of the
		the biomass of fish and	estuary (lower river discharge
		macrozoobenthos increased	in the second period)
		CH: low values of	Low benthos biomass due to
	Biotic indices based on diversity and biomasses => give information about the structure of communities	macrozoobenthos richness E4: the richest area for both periods	dredging and high hydrodynamics in this part of the estuary This corresponds to the rich Abra alba-Lagis koreni macrobenthic community and the feeding zone for fish
			(mainly flatfish).
		The MDS ordination showed a	Evolution in salinity plays a
		spatial segregation between CH	determinant role in the
		and the other zones, and a	spatial gradient of the fauna;
		temporal change between periods,	both periods were clearly
		both for fish and macrozoobenthos	distinguished
	Biotic indices based	FN: higher carbon recycling and
	on the classification	detritivory (increase in detritus
	of species in trophic	input) + higher redundancy (more
	groups => give	species)
	information about	CH: increase in system activity,
	the functioning of	carbon cycling, ascendency,
	the food web	redundancy and detritivory

Stress increased in the estuary mainly for CH and FN zones. The other zones were less disturbed.

  de la Vega et al., 2018; Safi et al., 2019). In addition, their association with 641 biodiversity indicators made the analysis more robust as suggested byRombouts et al. (2013).For instance, the arrival of new species and the higher biomasses observed in some spatial boxes

	642
	643	between periods can also explain increases in some ENA indicators such as system activity,
	644	omnivory or redundancy but this cannot be evidenced and requires further investigations.
	645
	646	5. Conclusions
	647
	648
		Biotic index based	FS: still in 'high ecological status'	Reference box
		on the classification	Increase in ELFI values between	The ecological status was
		of species in	periods	supposed to have improved but
		ecological groups		it is likely due to the arrival of
		=> give		marine species only
		information about the health status of ecosystems	Decrease of the metric DDIA (diadromous species) in the second period, indicator of a lower habitat	Lower connectivity due to the extension of the breakwaters between FN and CH during the
			connectivity	Port2000 construction
	634
	635	ELFI was sensitive to the arrival of marine species and therefore was highly relevant in a
	636	context of marinisation of the estuary. ENA indices appeared as good 'surveillance indicators',
	637	that Shephard et al. (2015) proposed as indicators that would be a good complement to

638 operational indicators, for example in the context of the Marine Strategy Framework Directive 639 application. ENA indices are also useful to take ecosystem-based management measures for such ecosystems (

& Lau, 2014), along with scripts developed for the present study [seeTecchio et al. (2016) for

Acknowledgements 666 667

The authors would like to acknowledge Valérie Girardin and Justine Lequesne (UMR CNRS 668 LMNO) for their help in the statistical analysis, Anik Brind'Amour (IFREMER) for her help

Then, this space was sampled by using a Markov-Chain Monte Carlo routine to obtain 200,000 278 solutions of the set of flow values. Ecological Network Analysis was applied to these 200,000 279 solutions, using the R software packages NetIndices (Soetaert et al., 2015) and enaR (Borrett additional methodological details].

282

To assess statistical differences in ENA indices between both periods, the non-parametric We assumed that E4 should exhibit the highest taxonomic richness and biomasses given its 599 intermediate position between marine and estuarine waters (Dauvin & Desroy, 2005). It had the 600 highest fish and benthic macrofauna taxonomic richness of all spatial boxes. Similar results

601

were found by Martino and Able (2003), who showed that in the Mullica river-Great Bay 602 (USA), fish species richness increased from the marine stations to the ones at the mouth of the 603 estuary, and then strongly decreased towards the estuarine sampling stations. The MDS analysis on diversity and biomasses showed the importance of benthic communities has intensified in 618 E2 but the origin of this change remains unknown. 3.


Félix Bigand
email: felix.bigand@limsi.fr

Elise Prigent
email: elise.prigent@limsi.fr

Bastien Berret
email: bastien.berret@u-psud.fr

Signing Avatar Motion: Combining Naturality and Anonymity

Keywords: Language, Virtual Signer, Signing Avatar, Animation, Biological Motion, Identity, Anonymization

This paper deals with the movement of virtual signers, and more particularly with the notion of biological motion and the issue of anonymization. Animating an avatar from motion models as biological as possible is important to ensure perceptual acceptability. Recording real movements thanks to motion capture systems and mapping them to an avatar can ensure this acceptability. However, such accurate systems may convey extra-linguistic information such as the signer's identity. For some applications, it will be necessary to determine the parameters of the movement that carry identity in order to control them.

INTRODUCTION

The use of virtual signers (or signing avatars) brings many advantages: It is possible to reuse, adapt, or modify the content of the SLTAT 2019, September 29, 2019, Hamburg, Germany animation; the appearance of avatars (age, gender, style of clothing, etc.) can be modified according to the target population; they can be dynamic and interactive [START_REF] Kipp | Sign language avatars: Animation and comprehensibility[END_REF]. However, their use is still limited to date.

A first reason is that the existing models of language are still very incomplete. Research on SL is recent compared to that of spoken languages. SL grammar is not yet fully described, in particular with regard to all phenomena related to the visual-gestural nature of the channel used: multilinearity of articulators. Criticisms of animations particularly concern non-manual parameters (facial expression, movement of the mouth, head and chest) [START_REF] Kipp | Sign language avatars: Animation and comprehensibility[END_REF] that are important elements of the language. In addition, we can also mention the linguistic use of space, and the linguistic structures used for depiction (classifiers). It should be noted that promising work is currently being done on these aspects [START_REF] Filhol | Synthesizing sign language by connecting linguistically structured descriptions to a multi-track animation system[END_REF], [START_REF] Filhol | Extending the azee-paula shortcuts to enable natural proform synthesis[END_REF], but much remains to be done.

A second reason concerns the quality of the animations. When they are automatically generated from oversimplified models, motions will be too robotic. An alternative is to record movements on a person, for example using a motion capture system, and to animate the avatar from these pre-recorded movements. Such accurate systems provide much more natural motion that can be applied to the avatar, but they also can make the actor identifiable. The ideal would be to have motion models or processes able to hide the identity of the signer, while keeping motions as 'natural' as possible and preserving the linguistic information.

In this abstract, we explore this issue and more particularly that of the identity conveyed by motion and what this implies in the context of virtual signers.

BIOLOGICAL MOTION AND PERCEPTUAL ACCEPTABILITY

The properties of human motion have been studied for more than a century. It has been shown that human movements have remarkable properties, such as the 2/3 power law (implying a relationship between the speed and the radius of curvature of the trajectory), the principle of isochrony (movement duration is almost independent of its amplitude), the law of asymmetry in vertical movements due to gravity (depending on whether the movement is upward or downward), or the Fitts' law (which expresses the minimum time required to reach a target according to its width and distance). The term 'biological motion' defines motion that comes from actions of a biological organism, that is humans or animals. The ability to perceive biological motion seems to appear very early in human life. A study conducted on infants showed that newborns are able to differentiate between biological and non-biological kinematics despite their immature visual system. The authors define biological kinematics as the movement that satisfies the constraints of the 2/3 power law mentioned above. In the study, infants spent more time observing the movements of light points that did not comply with this law. These results could be explained by the 'expectation violation model', i.e. the observation time of motion was larger because it did not correspond to the observer's expectations [START_REF] Méary | Four-dayold human neonates look longer at non-biological motions of a single point-oflight[END_REF]. There are many studies on human motion, for example on human gait. In [START_REF] Venture | Recognizing emotions conveyed by human gait[END_REF], subjects are able to recognize the emotional state (joy, sadness, etc.) from point-light stimuli. These studies show that biological motion convey higher-level information (contextual, emotional, etc.). The human brain uses low-level motion-detecting processes to recognize biological movements. It is assumed that it makes perception more pleasant and economical from a cognitive effort point of view [START_REF] Mather | Low-level visual processing of biological motion[END_REF].

It therefore seems essential to design motion models as 'biological' as possible in order to generate animations that are perceptually acceptable. For that, studies on motion should determine how these laws are expressed in SL. Previous work showed that there can be a 'SL effect' on these laws [START_REF] Benchiheub | Collecting and analysing a motion-capture corpus of french sign language[END_REF], [START_REF] Benchiheub | Contribution Ãă l'analyse des mouvements 3D de Langue des Signes Franaise (LSF) en Action et en Perception[END_REF]. We are still far from having enough knowledge to be satisfied with purely synthetic animations. Another possible approach is to replay movements that were recorded on people.

ANIMATING AVATARS USING MOTION REPLAY

Virtual signers can be animated using motion capture (mocap) on real actors [START_REF] Gibet | Building french sign language motion capture corpora for signing avatars[END_REF], as it provides highly realistic and comprehensible content. Thanks to mocap, the 3D trajectories of main articulations of the body are recorded and then mapped to the skeleton of a virtual character. With such accurate systems, we solve the problem of perceptual acceptability.

However, as stated above, the motion may also convey rich information about a person. As an example, it can make the actor identifiable, such as the voice can allow a given person to be recognized. As previously stated, humans can extract important information from biological motion, such as one's intentions, emotions, or identity. How such information can be retrieved from complex movements remains a challenging question for both psychology and computer vision areas. Extraction of human traits from a complex signal is a fundamental problem that has been addressed in different domains. In the auditory field, studies investigated the perception of extra-linguistic cues in speech [START_REF] Belin | Understanding voice perception[END_REF], [START_REF] Schweinberger | Speaker perception[END_REF] and notably the recognition of a particular speaker [START_REF] Kuhn | Eigenvoices for speaker adaptation[END_REF]. Similar approaches have been used in the visual domain to study the categorization and identification of human faces [START_REF] Valentin | Categorization and identification of human face images by neural networks: A review of the linear autoassociative and principal component approaches[END_REF], [START_REF] Turk | Face recognition using eigenfaces[END_REF], [START_REF] O'toole | Lowdimensional representation of faces in higher dimensions of the face space[END_REF]. Studies of Johansson [START_REF] Johansson | Visual perception of biological motion and a model for its analysis[END_REF], [START_REF] Johansson | Spatio-temporal differentiation and integration in visual motion perception[END_REF] addressed the question for human motion, introducing the notion of point-light (PL) stimuli. This display separates information given by dynamic cues from characteristics such as shape or aspect of the person. Using this device, Johansson showed that humans could recognize a set of moving dots as a human walker. Point-light displays are widely used since then. Different studies demonstrated that they contain enough information to recognize familiar people from their gaits [START_REF] Cutting | Recognizing friends by their walk: Gait perception without familiarity cues[END_REF], [START_REF] Loula | Recognizing people from their movement[END_REF], [START_REF] Jacobs | Experience, context, and the visual perception of human movement[END_REF], [START_REF] Troje | Person identification from biological motion: Effects of structural and kinematic cues[END_REF].

As mocap systems capture equivalent information as point-light displays, such information might be perceived through animations made with motion replay. We have observed on several occasions that some LSF (French Sign Language) signers were able to identify the person who had been registered with mocap, in the case of long utterances performed by an humanoid avatar, such as in alert messages in French train stations [24], and even in the case of isolated signs such as those of the serious game SignEveil by MocapLab [21], with avatars such as bear or cat. The need for producing messages anonymously is an important demand of Deaf people for some applications, such as posting anonymous content on blogs or social networks. This entails studying avatar animations from a perception point of view. Some studies are analysing SL mocap data from a linguistic point of view [START_REF] Malaia | Analysis of asl motion capture data towards identification of verb type[END_REF], [START_REF] Malaia | Kinematic parameters of signed verbs[END_REF], [START_REF] Catteau | Variation prosodique et traduction poétique (lsf/français): Que devient la prosodie lorsqu'elle change de canal?[END_REF] but as we know, no one studied the extra-linguistic cues conveyed by such signals. This is a question that we are beginning to study at LIMSI.

ONGOING STUDIES ON IDENTITY AND ANONYMIZATION

We have started addressing the question of gestural identity in LSF motion [START_REF] Bigand | Animating virtual signers: The issue of gestural anonymization[END_REF]. The aim of this work is to find critical features which differentiate the gestural identity of human signers in order to provide a better control of the animated signers. This multidisciplinary research yields contributions to psychology, computational science and LSF animation with both fundamental and applied perspectives. On the one hand, it helps us better understand how critical information can be extracted from the complex SL motion stimulus. On the other hand, it enables controlling social and human characteristics of the signing avatar regarding motion. For example, manipulating gestural identity would allow to produce signing animation 'in the style of' someone or to anonymize our own signing. Anonymizing the gesture of replayed motion can add substantial contribution to the existing virtual signing systems which only anonymize shape of the agent for now.

To undertake this work, we have adopted a pluridisciplinary approach, combining perception studies and computing methods. In a first step, we develop evaluation methods for the identification of signers from their gestures. The aim is to assess whether the identity of a signer can be transmitted through the movement only. To this aim, we present videos of real signers to the participants, shown as point-light displays. Then, we apply machine learning techniques for the analysis of mocap data [START_REF] Limsi | [END_REF] in a way to extract human features from LSF motion (e.g. identity, age, emotions...). Based on the same stimuli, we run a classifier using a similar approach to the one developed for face, voice and gait recognition.

This ongoing work also motivated the design of a new dedicated LSF mocap corpus that will be carried out in the coming months.


Felipe Gonzalez

Perez Marc Petit

Perez Yannick

Yannick Quantifying

Felipe Gonzalez Venegas
email: felipe.gonzalezvenegas@centralesupelec.fr

Yannick Perez

Quantifying the participation of EV fleets in local flexibility tenders

Keywords: ELECTRIC VEHICLES, FLEXIBILITY, VEHICLE-TO-GRID

Distribution system operators are starting to implement market-based mechanisms to use flexibility from distributed energy resources. Flexibility tenders allow distribution system operators to procure flexibility for the medium to long-term, with first implementations in Europe in the UK since 2018, and a recent pilot in France. This work seeks to quantify the potential participation of electric vehicle aggregators to a flexibility tender, considering role of market rules and product definitions. The main parameters that affect fleet participation and remuneration are the bidirectional capability (V2G), the reliability of the fleet and the match of availability profiles to the tender requirements.

Introduction

Distribution System Operators (DSOs) might face significant investments in grid reinforcement to deal with the crosssector electrification and the integration of renewable energy resources. However, connected and controllable resources, such as electric vehicles (EVs) or battery storage systems, offer the opportunity to provide flexibility to defer costly reinforcements and improve reliability and quality of supply.

To procure flexibility for investment deferral, DSOs require a medium to long-term vision of the availability and costs of flexibility resources. Indeed, DSOs can face high risks if they rely only on short-term local markets, endangering grid reliability, since they have limited options if there is no availability of flexible resources. A solution to mitigate the availability and price risks is to procure flexibility through long-term agreements, which can also provide revenue certainty to flexibility investors [START_REF]The Framework Explained[END_REF].

Within this context, UK Power Networks (UKPN) has implemented local flexibility tenders since 2018 in order to contract flexibility for the medium to long-term, in portions of the grid where they expect congestions, reducing their investment costs [START_REF] Ukpn | Future Smart: Flexibility Roadmap[END_REF].The current 2020 tender comprises 62 high voltage zones and has extended their scope to over 60 low voltage networks. Similar approaches have been followed by the rest of Great Britain DNOs [START_REF]Flexibility in Great Britain[END_REF] and by Enedis, France's main DSO, who launched a test implementation in 2019 [START_REF] Enedis | Feuille de route pour la transformation des méthodes de dimensionnement des réseaux et l'intégration des flexibilités[END_REF]. Enedis' tender comprises six zones in their medium voltage grid, with cases ranging from investment deferral to maintenance and post-fault support.

These tenders have been designed for the participation of distributed energy resources. However, the specific rules and requirements on the tender process can still present barriers to entry for operators of demand-side flexibility [START_REF] Gonzalez-Venegas | Can DERs fully participate in emerging local flexibility tenders?[END_REF].

The objective of the present work is to analyse and quantify the impact of market rules and product definition of distribution flexibility tenders, on the participation and possible revenue of an EV fleet aggregator. The main parameters reviewed are the availability windows, the minimum bid size and the baseline definition.

Methodology

Main parameters to be reviewed

Previous work [START_REF] Gonzalez-Venegas | Can DERs fully participate in emerging local flexibility tenders?[END_REF] proposed a modular framework to identify the main barriers on market design for the entry of demandside response aggregators, including EVs. This framework is composed of three hierarchical modules, each with a set of parameters that can present a barrier to the optimal participation of flexibility aggregators. This work applied the framework to the UKPN and Enedis flexibility tenders and determined that overall the tenders were designed to allow the participation of small, distributed resources aggregators. However, there were still some barriers in the design of the products and the baseline definition. The present study focuses on the following parameters: 2.1.1 Availability windows: DSO's can define a specific period of the day during which the flexibility should be available for activation. Aggregators can balance their resource availability toward the DSOs needs. Thus, shorter, well-defined windows can provide higher certainty for a type of resource that can provide the flexibility. In UKPN's 2020 tender, over 60% of the sites require an "evening" window (from 1 to 6 hours between 4pm to 10pm).

Minimum bid size:

This is the minimum amount of flexibility (in kW) that the tender admits. UKPN's tenders consider a minimum bid size of 50kW for the HV zones, and 10kW for the LV zones. Enedis' approach considers minimum bids of 500kW, while also retaining only full bids (thus only one tender winner). In both cases, the minimum bid can be attained by aggregating distributed resources. The higher the bid sizes, the less the participation of small aggregators is eased.

Baseline definition:

Flexibility is an active adjustment of normal consumption or production patterns or schedules, in response to an external signal, in this case, to a DSO activation. Thus, it is necessary to define a counterfactual baseline upon which a flexibility activation is measured and certified. Thus, baselines methodologies should be adapted to the assets that they attempt to measure. UKPN's default baseline is calculated as the average consumption or production during the availability window in ten reference days defined by the DSO. This gives a unique, static value for the whole availability window, not a profile.

On the other hand, Enedis proposes various baselines according to the type of asset. In the case of demand-side distributed assets, such as EVs, they propose a half-hourly profile based on a panel method. This method computes the baseline with respect to a panel of non-flexible customers with similar characteristics.

Methodology

To quantify the effect of the three aforementioned parameters on the participation of an EV aggregator to the flexibility tenders, a methodology based on Monte-Carlo simulations of EV charging and plug in behaviour was implemented.

First, a multi-agent simulation of EV plug-in and charging process is carried out. This module allows us simulate a high number of EVs fleets, each with a set of stochastic parameters (daily travelled distance and arrival and departure times), and a probabilistic non-systematic plug-in behaviour (users may not plug their vehicle every day, or may be absent of their usual charging point), described in [START_REF] Gonzalez-Venegas | Can DERs fully participate in emerging local flexibility tenders?[END_REF].

This simulation provideprovides the charging and flexibility profiles of the fleets. The charging profiles allow us to compute the baselines (UKPN's Unique-value and Enedis' 30-minute profile), and the flexibility profiles, which represent the amount of flexibility a given fleet can provide to the system at each moment. Given the stochastic nature of the simulation, a fleet can provide different levels of flexibility in each day. To evaluate the amount of firm flexibility to bid in the tender, we consider the minimum amount of flexibility that the aggregator can provide with 95% confidence level.

Finally, we compute the remuneration by evaluating the delivery of flexibility, randomly sampling activation events during the simulated period. If the delivered flexibility is less than what was committed, the payments are reduced proportionally. If the delivered flexibility is less than 60% of the committed, no payment is done. This emulates the payment de-rating performance factor by UKPN.

Case studies

We consider three types of fleets doing uncontrolled overnight charging: a company fleet and two fleets of commuters, one with medium plug-in probability (Commuter MP) and one with high plug-in probability (Commuter HP). The three fleets can provide unidirectional (V1G) and bidirectional (V2G) flexibility with a 7kW charger, with 95% efficiency, and have a 40 kWh battery pack.

EVs have stochastic parameters on daily travelled distances and arrival, following a lognormal distribution, and departure times, following normal distributions, as in [START_REF] Borne | Vehicle-to-grid and flexibility for electricity systems: from technical solutions to design of business models[END_REF]. The plug-in probability of an EV follows the Eq. 1 [START_REF] Gonzalez-Venegas | Can DERs fully participate in emerging local flexibility tenders?[END_REF], where ξ is the minimum state of charge (SOC) required to complete the next day trips, ρ is the range anxiety factor, and ν the probability factor. Their parameter values are shown in Table 1, and an example for the plug-in probability is shown in Fig. 1.

(1) We considered two availability windows: an evening window from 5pm to 8pm, and full-day window. The service is required for three months, only during weekdays (60 days per year). During these windows, a 30-minute 'downwards flexibility' (demand reduction or injection increase) can be required, though not necessarily activated.

Fig. 1: Plug in probability according to SOC at arrival, for a minimum SOC of 35% to complete next day trips.

Finally, the possible remuneration can vary greatly according to the tendered zone requirements. We used an equivalent yearly price of 50 € per firm kW tendered, similar to the fixed price proposed for UKPN's low voltage tenders. This represents an equivalent of 277 €/MW.h for the evening availability window (180 h/y) and 35 €/MW.h for the full day availability window (1440 h/y). This is within the range of remuneration in the high voltage UKPN tenders.

Results

4.1 Average profiles Fig. 2 shows the average charging and V2G potential profiles for fleets of size of 20 EVs. Company fleets have higher daily mileage, thus showing a higher peak power demand partially coincidental with the evening window. In addition, they are always plugged-in after trips; thus, having higher V2G potential. On the other hand, commuter's charging process occurs mainly during the evening window, and their lower plug-in reduces the V2G potential ratio (95% for Commuter HP and 67% for Commuter MP), as less EVs are available to deliver flexibility. Additionally, it can be seen that there will be periods of the day where no flexibility can be provided to the system, since there are no EVs connected.

Baselines

Fig. 3 shows the baselines for the company fleet (these baselines were also computed for the other two fleets): 30minute forecast, representative of Enedis' baseline, and a unique-value for the evening (1.61 kW per EV) and daily (0.9 kW per EV) windows, representative of UKPN's baseline. Such baselines do not capture the actual charging profile of the fleet, thus under-rewarding flexibility in some periods, while rewarding no real flexibility activation (after 20h, for example). This can create remuneration problems, as flexibility verification will be measured against this baseline, and not against the expected consumption profile. The average flexibility potentials are given in Table 2.

Minimum bid threshold

By performing a parametric sweep of the fleet size, the minimum size of the fleet to reach the minimum bid size required to be able to participate in the tender is identified (Table 3). Having V2G capability allows smaller fleets to participate in the tender, requiring about one tenth of the fleet size if only V1G is considered. In addition, allowing reduced minimum bid size allows a great number of participants to enter the tender, as fleets of only 10 (with V2G) to 30 EVs (with V1G) can achieve the threshold of 50kW. This can be of major importance as these tenders can have limited potential participants, due to the local characteristic of the services.

Bids & Revenues

Each of the simulated fleets will bid a different amount of flexibility on the tenders, and their reliability to provide the service will be reflected on how much they are paid per bid kW. To observe this, we tested for single day 30-minutes activations during either the evening or full-day windows (unique-value baseline are chosen accordingly). A flexibility activation that is not fulfilled by the fleet will result in a loss of remuneration proportional to the unserved flexibility, as described in Section 2.

In Fig. 4, bids and remuneration per kW bid are shown for the 24 studied cases. A fleet that can always deliver the committed flexibility, according to the respective baseline, will achieve a 50 €/kW remuneration. The total remuneration per EV per year will be given by the bid per EV [kW] times the remuneration per bid kW [€/kW]. From these results, several observations are drawn:

First, it is necessary to match the availability profiles of the fleets to those required in the tender process. The simulated fleets can provide flexibility for the evening window with high reliability, which is not the case for the full-day window, since there are periods of the day where no flexibility can be provided. This translates into higher bids per EV and higher remunerations for the evening window, both for the V1G and V2G cases, while for the full-day window a loss on remuneration per bid kW is observed, due to a reduced reliability of service. Highly reliable fleets, in this case the company fleet and Commuter HP, obtain a better participation and remuneration per EV than the less reliable Commuter LP.

Second, V1G-only EVs have limited participation in the tenders, being able to bid at most 1.6 kW per EV in the evening window, equivalent to 49-81 €/EV per year (revenue depending on the baseline methodology). Having V2G capability can increase the bid up to 8.6 kW per EV (1.6kW from demand reduction plus 7kW of power injection) in the case of highly reliable company fleets for the evening window, equivalent to 409-428 €/EV per year.

Finally, the baseline methodology has limited impact for V2G-capable fleets in the studied case. The main impact is seen in V1G only fleets, where the remuneration obtained by the same flexibility activation (reduction of EV demand) can vary greatly according to the considered baseline. In this case, the unique-value baseline rewards the absence of EV charging as flexibility, even when there would not be any need (see Fig. 2). Therefore, under this baseline the EV fleets are always remunerated at the maximum level.

Conclusion

A methodology to evaluate the potential participation of EV fleets into flexibility tenders was developed and the impact of three main the tender design parameters of were evaluated.

First, allowing small minimum bids can increase the participation of multiple EV fleets aggregators, allowing increased competition in local flexibility markets. This can be crucial, as these markets can have limited participants. The high minimum bid in the Enedis' case is only explained by their one-winner policy, who will need to group several different distributed assets to fulfil the tender requirement.

Second, the potential participation of EV fleets will depend on the match of their availability profiles to those required by the tender. Highly reliable fleets with V2G capability can earn over 400 €/EV/y in favourable tender conditions.

Third, the baseline definition can have a significant impact on the remuneration of the flexibility services, especially for V1G-only fleets, while providing the same physical service. UKPN's unique-value baseline provides a simple schedule that can over-or under-reward flexibility activation.

Finally, several paths are open for further research, such as the complementarity of flexible DER for full-day availability windows, the optimal bidding of flexibility under availability uncertainty, the effect of penalties for under-delivery on the remuneration profile of EV fleets and the coordination of distribution flexibility with other flexibility services, such as frequency response. Some other countries can also be added to explore other market design alternatives.

Fig. 2 :

 2 Fig. 2: Average charging profiles and V2G potential for a 30minute service per fleet (20 EVs), and examples of VxG flexibility levels.

Fig. 3 :

 3 Fig. 3: 30-minute and unique-value baselines and a simulated charging profile, for company fleet of 20 EVs.

Fig. 4 :

 4 Fig. 4: Bid per EV and remuneration per bid kW per EV for the three simulated fleets, and two baselines methodologies

4

 4

Table 1 :

 1 Stochastic parameters of EV fleets

	Fleet	Daily	Arrival	Departure	Plug-in
		distance	time	time	probability
		[µ, σ]	[µ, σ]	[µ, σ]	[ρ, ν]
	Company	[80, 10]	[15, 1]	[9, 1]	[1.5, ∞]
	Commuter HP	[3.43, 0.73] [17, 2]	[8, 2]	[1.5, 5]
	Commuter MP	[3.43, 0.73] [17, 2]	[8, 2]	[1.5, 1]

Table 2 :

 2 Average flexibility potential, V2G and V1G [kW],

	Fleet (20 EVs)	Evening Window	Full-day Window
		V2G	V1G	V2G	V1G
	Company	8.59	1.61	5.73	0.73
	Commuter HP	5.78	1.45	4.05	0.36
	Commuter MP	4.24	1.39	2.77	0.34

Table 3 :

 3 Minimum fleet size to participate in tender, according to minimum bid threshold.

	Fleet	Evening Window	Full-day Window
	(V2G / V1G)	50 kW	500 kW	50 kW	500 kW
	Company	6 / 30	59 / 309	10 / 69	88 / 688
	Commuter HP	9 / 33	87 / 346	13 / 132	124 / -
	Commuter MP	12 / 34 118 / 357	18 / 136	181 / -

Acknowledgements

This research benefits from the support of the Chair Armand Peugeot: "Hybrid Technologies and Economy of Electromobility", led by CentraleSupélec and ESSEC, and sponsored by Groupe PSA.