MD Nadège Cordel
email: nadege.cordel@chu-guadeloupe.fr

MD Lucie Bonnecarrère

MD Benoit Tressières

Squamous cell carcinoma in the Afro-Caribbean community: an 11-year retrospective study

Keywords: squamous cell carcinoma, Bowen disease, Afro-Caribbean, black people POC: people of color SCC: squamous cell carcinoma HPV: human papilloma virus UVR: ultraviolet rays NMSC: non melanoma skin cancer CF CI: confidence interval PCR: polymerase chain reaction

Background: Squamous cell carcinoma (SCC) is considered the most frequent skin cancer in black people. Its incidence is not known in the Afro-Caribbean population.

Objective: To assess the incidence of SCC in Guadeloupe, the largest island of the Lesser Antilles (405 000 inhabitants, mostly black people of African and European descent). The second objective was to characterize clinical and histological patterns of SCC occurring in the Afro-Caribbean community.

Methods: This retrospective study was conducted over an 11-year period (2000-2010). Data regarding 723 histological confirmed cases of SCC identified using the three Guadeloupean pathology laboratories computerized databases were retrieved from the records of 551 patients. Private practice dermatologists and general practitioners were contacted to obtain any missing data.

Results:

The annual age-adjusted incidence of SCC was 15 per 100.000 residents in Guadeloupe. In the Afro-Caribbean community, SCC had a greater size (i.e.: 2.8±2.8 cm versus 1.5±1.0 cm, p<0.001), was more often located on the anogenital area (i.e. :48/79-60.8% versus 14/320-4.4%, p<0.001) in association with an underlying dermatosis due to HPV infection (15/71-21.1% versus 3/366, 0.8%, p<0.001) and led more frequently to metastasis (13/84-15.5% versus 10/366-2.7%, p<0.001) and/or fatal evolution (11/83-13.3% versus 7/365-1.9%, p<0.001).

Conclusions:

The results of this original study, which first estimated the incidence of SCC in West Indies, suggest that anogenital examination should be routinely performed in skin cancer screening of Afro-Caribbean people in order to detect the presence of SCC at an early stage.

Implication for practice

Squamous cell carcinoma is the most frequent skin cancer in black people. Its incidence is not known in the Afro-Caribbean population. In Guadeloupe, the largest island of the Lesser Antilles, the annual age-adjusted incidence of SCC was estimated to be 15.0 per 100,000 residents, 95% CI: [ 13.8; 16.2]. In the Guadeloupean Afro-Caribbean community, SCC seems to more frequently occur in the anogenital area, due to HPV infection. These results support to include a routine genital urinary examination in the skin cancer screening of people of Afro-Caribbean descent.

Introduction

Although squamous cell carcinoma (SCC) is less common in people of color (POC) than in the white population it is the most frequent skin cancer in black persons, representing 30 to 65% of skin cancers in this population [START_REF] Fleming | Skin cancer in black patients[END_REF][START_REF] Mora | Cancer of the skin in blacks: I. a review of 163 black patients with cutaneous squamous cell carcinoma[END_REF][START_REF] Bang | Skin cancer in black Americans: a review a 126 cases[END_REF][START_REF] Halder | Skin cancer in blacks in the United States[END_REF][START_REF] Halder | Skin cancer in African Americans[END_REF][START_REF] Gloster | Skin cancer in skin of color[END_REF][START_REF] Adegebidi | Skin cancers at the National University Hospital of Cotonou from 1985 to 2004[END_REF][START_REF] Asuquo | Major dermatologic malignancies encountered in a teaching hospital surgical department in South Nigeria[END_REF][START_REF] Nthumba | Primary cutaneous malignancies in sub-Saharan Africa[END_REF][START_REF] Norval | The incidence and body site of skin cancers in the population groups of South Africa[END_REF] . SCC (or epidermoid carcinoma) most commonly occurs on sun-exposed areas in white people [START_REF] Alam | Cutaneous squamous cell carcinoma[END_REF] whereas it is frequently located on sun protected sites (i.e.: lower limbs or anogenital area) in black people [START_REF] Fleming | Skin cancer in black patients[END_REF][START_REF] Mora | Cancer of the skin in blacks: I. a review of 163 black patients with cutaneous squamous cell carcinoma[END_REF][START_REF] Bang | Skin cancer in black Americans: a review a 126 cases[END_REF][START_REF] Halder | Skin cancer in blacks in the United States[END_REF][START_REF] Halder | Skin cancer in African Americans[END_REF][START_REF] Gloster | Skin cancer in skin of color[END_REF][START_REF] Adegebidi | Skin cancers at the National University Hospital of Cotonou from 1985 to 2004[END_REF][START_REF] Asuquo | Major dermatologic malignancies encountered in a teaching hospital surgical department in South Nigeria[END_REF][START_REF] Nthumba | Primary cutaneous malignancies in sub-Saharan Africa[END_REF][START_REF] Norval | The incidence and body site of skin cancers in the population groups of South Africa[END_REF][START_REF] Agbai | Skin cancer and photoprotection in people of color: a review and recommendations for physicians and the public[END_REF][START_REF] Mccall | Squamous cell carcinoma of the legs in Africans Americans[END_REF][START_REF] Woolery-Lloyd | Squamouscell carcinomas of the lower limbs in African American women[END_REF][START_REF] Cordel | Squamous cell carcinomas in Afro-Caribbean women[END_REF] . In fact additional factors other than UV radiation have been identified as major etiologic triggers in the development of SCC in the black population (1-6, 8,9,12) : i.e. chronic scarring caused by chemicals, thermal burns or skin ulcers as well as inflammatory processes such as lupus erythematosus and hydradenitis suppurativa.

Moreover, high risk human papillomaviruses (HRHPV) have now been identified due to their implication in the development of anogenital SCC although specific studies focusing on POC have, to our knowledge, not yet been reported in the literature [START_REF] Serrano | Human papillomavirus genotype attribution for HPVs 6,11, 16,18,31,33,45,52 and 58 in female anogenital lesions[END_REF] .

Though SCC is less common in Black rather than in Caucasian people, the mortality rate, in this population, is still high, ranging from 17% to 30% depending on the series [START_REF] Fleming | Skin cancer in black patients[END_REF][START_REF] Mora | Cancer of the skin in blacks: I. a review of 163 black patients with cutaneous squamous cell carcinoma[END_REF][START_REF] Halder | Skin cancer in blacks in the United States[END_REF][START_REF] Mora | Surgical aesthetic consideration of cancer of the skin in the black American[END_REF] .These data underline the need for prevention, early detection and treatment of SCC in the African American and Afro-Caribbean communities.

The current incidence of SCC among Afro-Caribbeans is difficult to estimate because non melanoma skin cancers (NMSC) are not consistently reported in most national or regional tumor registries. Moreover, cancer registries are not common in the Caribbean and only recently have become available for consultation in the French West Indies. Therefore, we were prompted to retrospectively study SCC occurring in Guadeloupe, an overseas department of France which is the largest island of the Lesser Antilles within the West Indies (405 000 inhabitants, mostly black people of African and European descent), over an 11-year period. Our aims were first to evaluate the incidence of skin and mucous SCC in residents of Guadeloupe and second to study the clinical and histological characteristics of SCC in Afro-Caribbeans.

Patients and methods

Study design

This retrospective study was conducted from the 1 st January 2000 to the 31th December 2010 within the French overseas department of Guadeloupe. Histological confirmed cases of skin and mucous SCC were retrieved from the computer database of the three Guadeloupean pathology laboratories, using DIAMIC software (Infologic Santé-Châteauneuf-sur-Isère-France).

Inclusion criteria were the following: i) histological diagnosis of SCC or Bowen disease ii) excision during the study period iii) residence within the department of Guadeloupe at the date of histological diagnosis. Albinism (phototype 0) was an exclusion criteria because it represents a genetic disorder as were pediatric cases.

Data collection

All pathological records were reviewed in order to retrieve demographic data of patients (i.e. age, gender) clinical features of SCC (i.e. site, size) and pathological characteristics (i.e. histological type, degree of cytological differentiation, associated dermatosis, node or systemic metastasis). Main SCC locations were distributed among 5 representative areas: face and neck, upper limbs, lower limbs, trunk and back, and anogenital area. Histological types were divided as follows: common form of SCC (CF), SCC in situ or Bowen disease (BD), keratoacanthoma (KA) and verrucous carcinoma (VC). Associated dermatoses mentioned in the pathology records were divided into: HPV induced lesions (condyloma or morphological HPV infection with koilocytes), chronic leg ulcer, scar, lichen sclerosus and others. For SCC located on the anogenital area, HPV genotyping analysis was collected when available. Clinical data of patients (i.e.: phototype, previous medical history of skin cancer and of HIV infection, intentional sun exposure, death in relationship with SCC) were obtain in medical records by contacting private practice dermatologists and general practitioners. HIV status of patients was also recorded from the HIV regional computer database.

Statistical analysis

Data were recorded using EPI INFO software. Results were presented as the mean ±standard deviation (SD) for continuous variables and as numbers and frequencies for categorical variables. Student's t-test and Chi-square or Fisher's exact tests were used, where appropriate, to compare continuous and categorical variables between patients with phototypes V or VI representing Afro-Caribbeans and patients with phototypes I to IV.

Incidence rates were calculated with a confidence interval of 95%. Age-adjusted incidence rates were calculated using the references from IARC [START_REF]Cancer incidence in five continents[END_REF] . For all analyses, two-sided p-values of less than 0.05 were considered statistically significant. Data management and statistical analysis were performed using SPSS 21.0 software (IBM SPSS Statistics, Chicago, IL.).

The Ethics Committee for non-interventional research of Rouen University Hospital approved this retrospective study (Registration number: E 2015-41).

Results

Incidence of SCC in Guadeloupe

We identified 738 SCC that occurred in 566 patients during the study period. Of these, 15 patients living in the territorial collectivity of St Martin were excluded because this island is currently separated from the Guadeloupe administrative department. A total of 723 cutaneous and mucous SCC from 551 patients fulfilling the inclusion criteria were taken into account for incidence rates 'calculation. Crude and age-adjusted annual incidence rates were estimated to 16.5(95% CI: [12.5; 20.5]) and 15.0 per 100.000 (95% CI : [13.8 ; 16.2]) residents in Guadeloupe respectively. Age-adjusted and crude incidence rates according to gender and histological types of SCC are indicated in Table I.

Demographics data of the 551 patients

The main demographic characteristics are summarized in Table II. At the date of SCC histological diagnosis, the 551 patients had a mean age of 65 ± 15 years (range 15-99 years).

Sex ratio was 1.1 (M: 287/F: 257, missing data for 7 patients). Intentional sun exposure and previous medical history of skin cancer were reported for 94/147 (64%) and 96/192 (50%) patients for whom information could have been collected, respectively. Fifteen patients (2.7%) had a positive HIV status. Death in relationship with SCC was reported for 13/538 (2.4%) patients. Finally, 327 phototypes were collected (i.e.: albinos: n=4, phototype I: n=4, phototype II: n=73, phototype III: n=127,phototype IV: n=39, phototype V: n=67, phototype VI: n=13).

Pathological data of SCC

Table III shows the main pathological features of the 723 SCC representing the entire series.

"Face and neck" was the most reported location of SCC with a mean size of 1.8 ± 1.9 centimeters (cm). The most frequent types of SCC were KA (43.3%)(fig 1) and CF (42.9%) with a high degree of differentiation in most cases (94.5%). An underlying skin dermatosis was associated to 59/704 informed SCC (8.4%) including HPV induced lesions (n=21), chronic leg ulcers (n=6), scars (n=5), lichen sclerosus (n=5) and other dermatoses (n=22) (i.e.: ichthyosis, radiodermatitis, chronic inflammation, missing data n=6). Squamous cell carcinoma led to complications in 27 cases of node or systemic metastases (27/712: 3.8%).

SCC in the Afro Caribbean community

Eighty-four SCC occurred in 80 patients, 38 men, 41 women (missing data for one patient) with phototype V or VI, representing Afro-Caribbeans. The most frequent type of SCC in the Afro-Caribbean population was the CF (45.2%) and mean size of the tumor was 2.8± 2.8 cm.

Location of the tumor was well-informed in 79 cases: i.e.: anogenital area (n=48), face and neck (n=10), trunk (n=9), upper limbs (n=4), lower limbs (n=8). HIV status was positive for 7/15 Afro-Caribbean patients. Interestingly, HIV seropositive patients had more often a SCC located on the anogenital area than patients with a negative HIV status (i.e.: 7/39 versus 0/29, p=0.039). An underlying dermatosis was reported in 21/71 informed SCC (29.6%), mostly condyloma or morphological HPV infection (n=15, 71.4%). Data on HPV genotyping analysis were available for 10 anogenital SCC from 9 Afro-Caribbean patients. The high risk HPV type distribution was as follows: HPV 16 (n=4), HPV18 (n=2), HPV 31 (n=1), HPV 33 (n=1), HPV 35 (n=1), HPV 51 (n=1). Finally, 11/79 (13.9%) Afro-Caribbean patients for whom this information was available had a fatal evolution.

Comparison between Afro-Caribbean patients and patients with phototypes I to IV is shown in table IV. In the Afro-Caribbean's group, SCC had a greater size (i.e.: 2.8±2.8 cm versus 1.5±1.0 cm, p<0.001),was more often located on the anogenital area (ie:48/79-60.8% versus 14/320-4.4%, p<0.001) in association with an underlying dermatosis due to HPV (15/71-21.1% versus 3/366, 0.8%, p<0.001), led more frequently to metastasis ( 13/84-15.5% versus 10/366-2.7%, p<0.001) and/or a fatal evolution (11/83-13.3% versus 7/365-1.9%, p<0.001).

A lower frequency of intentional sun exposure (8/26-30.8% versus 86/117-73.5%, p<0.001) and of past history of skin cancer (2/27-7.4% versus 67/136-49.3%, p<0.001) also characterized Afro-Caribbean patients.

Discussion

To our knowledge, this11-year population-based study, conducted on Guadeloupe Island with focus on the Afro-Caribbean community, is the first epidemiological study on SCC in the Caribbean.

The study shows a high SCC annual age-adjusted incidence rate of 15.0 per 100 000 residents (men: 16.9/women:12.5). The exhaustiveness of these results is assured by current practice of Guadeloupean dermatologists and surgeons who routinely direct all suspected cases of SCC samples to the three pathology laboratories of the island. This incidence rate is considerably higher than that of 3 per 100 000 inhabitants currently reported in black people [START_REF] Scotto | Incidence of non melanoma skin cancer in the United States[END_REF][START_REF] Gray | Trends in the population-based incidence of squamous cell carcinoma of the skin first diagnosed between 1984 and 1992[END_REF] . Nonetheless it is similar to SCC annual age-standardized incidence rate previously reported in South Africa (i.e.: men: 20.8/women: 8.5) whose population is as intermixed as that of Guadeloupe island [START_REF] Norval | The incidence and body site of skin cancers in the population groups of South Africa[END_REF] . As expected the SCC incidence rate calculated in our study is still lower than that of SCC in Caucasians reported to be 100 to 300 per 100 000 in white Americans, and about 30 per 100 000 in Northern Europe [START_REF] Alam | Cutaneous squamous cell carcinoma[END_REF][START_REF] Scotto | Incidence of non melanoma skin cancer in the United States[END_REF][START_REF] Gray | Trends in the population-based incidence of squamous cell carcinoma of the skin first diagnosed between 1984 and 1992[END_REF][START_REF] Norval | The incidence and body site of skin cancers in the population groups of South Africa[END_REF][START_REF] Miller | Non melanoma skin cancer in the United States: incidence[END_REF][START_REF] Hoy | Nonmelanoma skin carcinoma in Albuquerque, New Mexico: experience of a major health care provider[END_REF][START_REF] Harris | Trends in incidence of non-melanoma skin cancer in southeastearn Arizona, 1985-1996[END_REF][START_REF] Karia | Cutaneous squamous cell carcinoma: estimated incidence of disease, nodal metastasis, and deaths from diseases in the United States, 2012[END_REF][START_REF] Robsahm | Cutaneous squamous cell carcinoma in Norway: 1963-2011: increasing incidence and stable mortality[END_REF][START_REF] Hollenstein | Trends of cutaneous carcinomas in the Netherlands: increased incidence rates, but stable relative survival and mortality: 1989-2008[END_REF] .

As regards the demographic characteristics of our series, sex ratio and mean age of patients are similar to that previously reported in the largest series of SCC in black people [START_REF] Yakubu | Squamous cell carcinoma of the skin in Africans[END_REF] from Africa due to the composition of the Guadeloupean population (i.e.: 90% of African descent [START_REF] Levinson | Ethnic Groups Worldwide[END_REF] ).

Interestingly, the most frequent form of SCC found in our study was KA (43%) with an incidence rate that was almost equal to that of CF (i.e.: 6.6 per 100,000 population and 6.3 per 100,000 population respectively) whereas the commonly reported KA versus SCC incidence ration is 1/3. Chuang et al. previously published adjusted age incidence rates of KA and SCC with a ratio similar to our (i.e.:104 cases per 100,000 persons per year for KA and 118 cases per 100,000 persons per year for SCC) [START_REF] Chuang | Keratoacanthoma in Kauai, Hawaii. The first documented incidence in a defined population[END_REF][START_REF] Chuang | Squamous cell carcinoma in Kauai, Hawai[END_REF] in white residents of Hawaii . In the light of this Caucasians focused study, we found that KA was the most common form in patients with phototypes II and III (i.e.: 143/179:80%), the largest group of patients with informed phototypes of our series (i.e.:200/327: 61%). It is likely that the KA/SCC ratio found in our study was in related to this unequal distribution.

The main result of our study is the description of a SCC Afro-Caribbean pattern. In the present series as in previously reported studies on black patients, SCC rarely occurred in relationship with intentional sun exposure or located in sun exposed areas. Moreover, we found that the most affected site was the anogenital area representing 48/79: 61% of the SCC locations in black patients of our series whereas the current prevalence of the anogenital area damage in black people is 10% to 23% [START_REF] Mora | Cancer of the skin in blacks: I. a review of 163 black patients with cutaneous squamous cell carcinoma[END_REF][START_REF] Gloster | Skin cancer in skin of color[END_REF] . It is likely that this high prevalence of anogenital area location was due to HPV infection which was identified in 21% of SCC in Afro-Caribbeans versus 0.8% in other patients of our series. In fact, HPV designated as "high risk" (HR) types are implicated in approximately 30 to 90 % of anogenital cancers other than cervix [START_REF] Serrano | Human papillomavirus genotype attribution for HPVs 6,11, 16,18,31,33,45,52 and 58 in female anogenital lesions[END_REF] and are highly prevalent in Caribbeans (i.e.:36% in Guadeloupe to 57% in English speaking islands in healthy individuals) [START_REF] Cordel | High-risk HPV cervical infections among healthy women in Guadeloupe[END_REF][START_REF] Ragin | Prevalence of cancerassociated viral infections in healthy Afro-Caribbean populations:a review of the literature[END_REF] . Interestingly HR HPV type distribution of our samples was not exclusively focused on current types 16 and 18 but implicated other HR HPV types (i.e. : 31,33,35,51) according to recent reports from the African Caribbean Cancer Consortium [START_REF] Cordel | High-risk HPV cervical infections among healthy women in Guadeloupe[END_REF][START_REF] Ragin | Dinstinct distribution of HPV types among cancer-free Afro-Caribbean women from Tobago[END_REF][START_REF] Watt | High-risk and multiple human papillomavirus (HPV) infections in cancerfree Jamaican women[END_REF] . As reported in the literature, positive HIV status was significantly associated with HRHPV infections since all HIV seropositive Afro-Caribbean patients had a SCC located on the anogenital area [START_REF]-Human papillomaviruses[END_REF] .

A high mortality rate of 13.9% was recorded in Afro-Caribbeans with SCC of our series whereas it was estimated to be 0.8% for the other patients (p<0.001). These results are in accordance with the literature data where the mortality rate ranges from 17% to 29% depending on the series. As this higher mortality rate was associated with a higher prevalence of metastasis (15.5% versus 2.7% , p<0.001) and a greater tumor size (2.8±2.8 cm versus 1.5±1.0 cm, p<0.001), this may be relative not only to more natural aggressiveness of SCC in Black people but may also reflect a later diagnosis and consecutive more advanced disease [START_REF] Thompson | Risk Factors for Cutaneous Squamous Cell Carcinoma Recurrence, Metastasis, and Disease-Specific Death: A Systematic Review and Meta-analysis[END_REF] . These data underline the role of prevention, early detection and treatment of SCC in the African American and Afro-Caribbean communities and emphasizes the need for physicians to be more familiar with SCC in Black people [START_REF] Gloster | Skin cancer in skin of color[END_REF] .

The limitations of our study are primarily due to its retrospective design. Patients and physicians were contacted to collect clinical data such as phototype, intentional sun exposure, past history of skin cancer, etc.. Unfortunately, as the histological diagnosis of SCC went back 11 years ago in some cases, missing clinical data were numerous except for HIV status of the series that could be retrieved from the regional computer database.

Overall the present study showed the occurrence of a high frequency of anogenital area location of SCC in Afro-Caribbean people, probably related to the high prevalence of HPV infection in Caribbeans. Moreover, this study confirmed the high mortality rate of SCC previously reported in people of African ancestry from other countries. These findings suggest that a genital urinary examination in the skin cancer screening of black people of Afro-Caribbean descent should be routinely performed in order to detect the possible presence of SCC at an early stage, particularly in cases of a positive HIV status.

Figures legendFig 1 .

 1 Figures legend

Fig 2 .

 2 Fig 2. Keratoacanthoma in an Afro-Caribbean patient referred for this nasal lesion to the

Table II .

 II Demographic data of the 551 patients of the series

	Age		65 years ± 15
	Sex ratio (Male/Female)		1.1 (287/257)
	Intentional sun exposure		94/147 (64%)
	Previous medical history of skin cancer		96/192 (50%)
	Phototype (n=327)	0	4 (1.2%)
		I	4 (1.2%)
		II	73 (22.3%)
		III	127 (38.9%)
		IV	39 (11.9%)
		V-VI 80 (24.5%)
	HIV positive status		15 (2.7%)
	Death in relationship with SCC		13/538 (2.4%)

Table III :

 III Pathological data of the 723 SCC of the series

	Local recurrence		15/711 (2.1%)
	Node or systemic invasion		27/712 (3.8%)
	Type of SCC	Common form	310 (42.9%)
		Keratoacanthoma	313 (43.3%)
		In situ-BD	76 (10.5%)
		Verrucous SCC	18 (2.5%)
		Others	6 (0.8%)
	Size of SCC (cm)		1.8 +/-1.9
	Site of SCC (n=648)	Face and neck	248 (38.3%)
		Upper limbs	130 (20.1%)
		Trunk	98 (15.1%)
		Lower extremities	93 (14.3%)
		Anogenital area	79 (12.2%)
	Associated skin disease (59/704 : 8.4%)
		HPV induced lesions	21
		Chronic ulcer	6
		Scars	5
		Lichen sclerosus	5
		Other	16
	Cytological differentiation (n=703) high	664 (94.5%)
		Medium	22 25 (3.6%)
		Low	14 (2.0%)
	Perinervous invasion		1/705 (0.1%)

Table IV :

 IV Comparison of SCC clinical and histological data between patients with phototypes V-VI representing Afro-Caribbeans and patients with phototype I to IV.

			phototypes V/VI	phototypes I/II/III/IV	p
	Patients / SCC : N/n		80/84	243/368
	mean age (years)		64.7±16.1	66.1±14.8	p=0.470
	sex ratio (M/F)		0.93 (38/41)	1.08 (126/117)	p=0.562
	previous medical history of skin	2/27 (7.4%)	67/136 (49.3%)	p<0.001
	cancer
	intentional sun exposure		8/26 (30.8%)	86/117 (73.5%)	p<0.001
	SSC histological type	CF	38 (45.2%)	164 (44.6%)	p=0.911
		KA	17 (20.2%)	161 (43.8%)	p<0.001
		BD	17 (20.2%)	36 (9.8%)	p=0.007
		VC	8 (9.5%)	6 (1.6%)	p<0.001
	SSC mean size (cm)		2.8± 2.8	1.5± 1.0	p<0.001
	SSC site		n=79	n=320
	head and neck		10 (12.7%)	139 (43.4%)	p<0.001
	trunk		9 (11.4%)	48 (15.0%)	p=0.412
	upper limbs		4 (5.1%)	74 (23.1%)	p<0.001
	lower limb		8 (10.1%)	45 (14.1%)	p=0.356
	anogenital area		48 (60.8%)	14 (4.4%)	p<0.001
	HPV underlying dermatosis		15/71 (21.1%)	3/366 (0.8%)	p<0.001 P<0.001

Acknowledgements:

The authors are grateful to the following Guadeloupean pathologists for providing their computerized databases to collect SCC data: Anne Mareel, M.D., Brigitte Theron, M.D., and Monique Trival, M.D. and to Richard Medeiros-Medical Editor, Medical Editing International, for review the manuscript in English.

IRB approval: Ethics Committee for non-interventional research of Rouen University

Hospital (registered number: E2015-41).


Nicolas Kong
email: nicolas.kong@enedis.fr

Thibaut Barbier
email: thibaut.barbier@mines-paritech.fr

Guillaume Pelton
email: guillaume.pelton@enedis.frmaxence-externe.bocquel@enedis.fr

Maxence Bocquel

Robin Girard

Pierre Cauchois
email: pierre-externe.cauchois@enedis.fr

LONG TERM FORECAST OF LOCAL ELECTRICAL DEMAND AND EVALUATION OF FUTURE IMPACTS ON THE ELECTRICITY DISTRIBUTION NETWORK

Enedis (France's main electricity DSO) and Mines Paris Tech are working on a new method called MOSAIC that aims at assessing the impact of long term local development projects on the electrical grid. The MOSAIC method uses a bottom-up simulation tool able to determine the current and future consumption and production load curve of an area. The consumption and production simulators are based on a multi-level data model that makes it possible to run a simulation even if some data are missing. The simulation parameters are calibrated by comparing the simulated load curves with observations on MV feeders (for the consumption simulator) and on 100 renewable energy producers (PV and WP). Once the simulators are calibrated for the current situation, the load curve of each development scenario of the area is estimated (the evolution scenarios are proposed by the local government, based on infeed growing, building projects …). Enedis and Mines Paris Tech are now working on linking the load curve simulators with more traditional electrical study tools. From the simulated load curve, we estimate the most likely maximal power of the grid infrastructures and use these values in the load flow tool called ERABLE to evaluate the impact of the scenarios on the grid. Initial tests were successful and this method will be further developed in 2017 on ten experimentation projects in France. Each project will help to develop new functionalities such as integrating Demand Response or electrical vehicle infrastructures.

INTRODUCTION

In the last few years, local governments have gain many skills regarding the energy transition. Indeed, most of the necessary actions requested by the recent laws on the energy transition in France should be pursued at local level by local governments. Therefore, they are becoming to see energy as a crucial issue to be considered during urban development projects. At the same time, the features of electricity consumption are changing due to many factors such as renovations of old neighborhoods, construction of new and highly efficient buildings, growth in local renewable energy production and creation of electric car charging infrastructure. Local authorities need to correctly anticipate both the impact of these evolutions and the need for investments to succeed in their energy transition. Such a target requires a close collaboration between local authorities and their DSO: if the impact of urban planning decisions on the grid is assessed early on a project life cycle, solutions can be found in order to minimize new investment needs. This approach is essential to create sustainable cities. For that reason, Enedis and Mines Paris Tech are developing a new method, named MOSAIC, which uses a bottom-up electric load curve simulator. With MOSAIC, Enedis will be able to assess the impacts on the electrical grid of different city-development-scenarios, at different time scales.

SIMULATION OF THE ELECTRIC LOAD CURVE OF AN AREA

The MOSAIC method uses a bottom-up load curve simulator developed by Mines Paris Tech [START_REF] Barbier | A novel approach for electric load curve holistic modelling and simulation[END_REF]. The first step to perform a simulation is to be able to correctly model the current and the future study area.

Modeling of the area

The simulator evaluates the load curve of each customer (residential, tertiary as well as solar PV and Wind Power producer) before aggregating them at the relevant scale. This requires having a significant amount of information on the study area:  For simulating consumption load curve: type of premises (residential, offices, shops etc.), surface area, ceiling height, age of the building or energy efficiency, performance level, presence of electric heating, electric water heater and/or electric air conditioning, position of the premises on the building etc.  For simulating the production load curve: GPS coordinates of the producer, installed power, type of production (PV or WP) and characteristic of the infrastructure (orientation, technology etc.).

Description of a project with the MOSAIC method

Even if the simulator potentially requires a lot of input data, an accurate description of every consumer and producer of the area is not necessary. The study area is described in MOSAIC using a multi-layer model: each

Paper 0743 CIRED 2017 2/5
consumer/producer is part of a "block" and each block is part of a project (see Figure 1).

Figure 1 -Description of an area in MOSAIC

When a piece of information is missing, the simulator uses instead default values, first at block level when available, second at project level if needed. This multi-layer organization then makes it possible to simulate an area where some data are missing. The quality of the result will depend on how precise the area is described.

The MOSAIC method can be used for two main types of situations

There are two use cases in which MOSAIC can be useful for DSOs and for local governments:

1. Evolution of an existing area. The area is already connected to the electrical grid, therefore the goal of the study is to evaluate the deepness of grid modifications needed by change of power demand.

Creation of a new area.

The electrical grid will be created from scratch. The goal will be to define the infrastructures to connect the area (secondary substations, MV Feeder etc.).

Description of the reference situation

Simulating the current situation is interesting for the first case study (evolution of an existing area) as it's useful to estimate the current load curve of each secondary substation and to evaluate the gain of power that could be made by refurbishing the existing buildings. The current situation is called the "reference situation" and it will be used as a base line for comparing future scenarios. Enedis and Mines Paris Tech have assessed many potential sources of data describing the current situation.

Census data are open-access on the French Statistics Office (INSEE) website and were therefore the first source of data to be tested with MOSAIC. They describe quite precisely the residential building of a designated area, however there is very little information on the location of these buildings (we only know to what district they belong).

Recently acquired MAJIC (Land-registry) data are more convenient than census data as they provide a more detailed description of buildings including their address.

Coupled with Enedis' database, they will be used from now on.

Enedis own database includes customer information system (CIS). For all customers, CISs store their electrical connection to the grid, their annual consumption, their type of contract, and their contracted power. Most of DSOs have similar data [START_REF] Mutanen | Customer classification and load profiling method for distribution systems[END_REF]. INSEE or MAJIC database need to be coupled with Enedis' database in order to simulate the current load curve of a substation or an electrical feeder. Mines Paris Tech therefore developed an efficient method for matching the INSEE and Enedis' residential customers [START_REF] Barbier | An optimisation algorithm for matching large scale databases on customers for improved characterisation of electricity consumption[END_REF].

The MAJIC/Enedis matching is easier than the INSEE/Enedis matching, as it's possible to compare addresses. Unfortunately, the two database have different ways of recording addresses. Mines Paris Tech developed an algorithm able to homogenize addresses structures between the two databases and to correct spelling mistakes in street names. This method has been tested on 22 MV feeders (around 135,000 customers) and only 3% of the customers could not be match with a MAJIC data: For the second use case (creation of a new area) there is no need to simulate the current situation. The reference scenario is therefore one of the potential scenarios (usually the business-as-usual evolution).

Description of future evolutions

The goal of the MOSAIC method is to compare the impact on the electrical grid of different evolution scenarios of the study area.

Electric load curve simulation Description of the models

The electric load curve simulation is performed with a compromise between physical and statistical models of appliances, consumers and buildings. It allows simulating in a bottom up way with a short computation time: few minutes to simulate the electricity demand of thousands of customers for one year at one hour time step. A complete description of the structure of the model is described in [START_REF] Barbier | A novel approach for electric load curve holistic modelling and simulation[END_REF].

Evaluation of results and calibration

The results given by the model have to be evaluated by comparing them to reference values. Default values are

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CIRED 2017 3/5 calibrated in order to minimize the gap between the results and the reference.

The first evaluation we did was to check if all the devices were correctly simulated by comparing them to campaign measurement results or the literature. In Figure 3 are examples of different checks for use laundry. In the example of laundry we compared our values to the French campaign described in [START_REF] Ademe | Campagne de mesures des appareils de production de froid et des appareils de lavage dans 100 logements[END_REF]. We did this kind of evaluation for all uses, and all type of customer.

-Example of simulation characteristics for use laundry.

Another evaluation was done by comparing aggregated load curve from feeders' measurement and simulation results. Thanks to Enedis' CIS, and the matching with land registry data described in 1.1, we can have the list of premises per electric feeder. We then remove diffuse renewable production thanks to the production load curve simulator (1.3). Then, we can perform a simulation for a feeder. Without any calibration, result can be seen in Figure 4. We clearly see that the simulated load curve (blue) is higher than the measured one: many influent parameters, such as temperature target for electric heaters or mean thermal resistance of building, were set by default.

Figure 4 -Example of simulation and measurement of a feeder with default parameters (before calibration)

The most influent parameters can be chosen, and tuned in order to minimize the RMSE (root mean square errors). In our case we choose electric heaters temperature target and mean thermal resistance of buildings. The result after calibration is depicted in Figure 5. The two load curves are closer, the RMSE was minimized by adjusting the two parameters.

Figure 5 -Example of simulation and measurement of a feeder with calibrated values.

Our method allows to calibrate the parameters of the model learning from measurements. It is then possible to simulate either evolution of an existing area or a new area by using these calibrated values. We use this approach in the following case study.

Production load curve simulation

Description of the models MINES ParisTech has developed models to compute the normalized renewable energy production on a region by using meteorological data such as the horizontal irradiation, temperature and wind speed. These data can be retrieved from either measurement or reanalysis data.

For the production from photovoltaic panels (PV) we use the Muneer model [START_REF] Muneer | Solar radiation and daylight models for the energy efficient design of buildings[END_REF] to compute the diffuse part of the radiation over the tilted solar module and a physical model for the module itself. It is possible to choose a predefined statistical distribution for inclination and orientation of panels on roofs. Several technologies and integration architectures are modelled and the user can select the characteristics of the panels.

For the wind production we can choose specific parameters of the technology of the wind turbine, the altitude of the hub to extrapolate wind speed data using a logarithmic profile. We have also the possibility to specify a wind power curve, to use a default one or to compute a power curve using the region wind speed measures, the installed capacity and the historical production on the region. This last option allows locally calibrating the relationship between wind speed and production and improving the production simulation result. This model is particularly useful to simulated diffuse production before the calibration of the electric load curve simulator. It is also of a great interest to test different local renewable production penetration rates and its influence on electrical grid sizing [START_REF] Rogeau | Evolution of electrical distribution grids sizing considering self-consumption of local renewable production[END_REF].

Evaluation of results and calibration

Enedis collects some individual measurement of solar and wind farm and individual PV producers. Knowing the location and the installed power of each producer, it is possible to compare simulation and measurements. In Figure 6 production simulated and measured.

Figure 6 -Simulated and measured PV production for a 12kW producer in Paris

As it is difficult to collect information at large scale about the installed technology, the precise orientation and inclination of panels, the shadow effects (especially for PV on roofs), we by default the different values according to national statistics. In the same way as simulation of electricity demand, we can tune the different parameters in order to get a better fit with measurements.

SIMULATION RESULTS

Result analysis on the MOSAIC HMI

MOSAIC Human Machine Interface (HMI) provides many functionalities for the visualization of the simulation's results: load curve analysis, energy analysis, load duration curve. The first analysis module shows simulated load curves either in an aggregated way or with a separation by usage, substations, or bulding block. This module provides important information on the diversity factor of the area. When assessing the impact of connecting new building on the grid, it's important to determine what would be the most likely peak demand value for each grid infrastructure. Usually this value is estimated by adding the maximum power of each customer and using a default value for a diversity factor between the residential customers. MOSAIC is able to find the most probable maximum load of an area/building depending on individual consumer consumption, but as well on diversity factor. Indeed maximum consumption of a building is not the sum of individual consumptions. For example in figure 7, the maximum power demand is 171 kW, which is 15% smaller than the sum of the residential power peak (73 kW) and the tertiary power peak (127 kW).

Figure 7 -Load curve of residential and tertiary customers simulated by the MOSAIC method

Furthermore, comparing consumption and production load curves made for many meteorological scenarios gives information on the likeliness of some critical situations such as a 100% production with very little consumption.

Finally if the simulator is not able to simulate some very specific consumers or producers, it's still possible to take them into consideration by uploading directly their load curves (got from observations or from another simulator).

Characterization of the most likely peak demand

The French electrical grid is designed to be able to resist in critical situations such as very cold temperatures (demand is heavily dependent on the temperature due to high use of electric heating). In this context, Enedis is designing its grid for severe temperature conditions to be able to resist power value that are on average reached around 1 day per year (power value called Ptmb).

The goal of the MOSAIC method is to evaluate the impact on the grid of the changes in the area. It's therefore necessary to translate the results of the simulator into power values that can be used in an electrical simulator software.

Enedis and Mines Paris Tech are currently testing different methods to determine the power value to be used for impact assessment. In the first use case, the simulation results are aggregated at a gird scale (MV/LV substation) and they are represented on a load duration curve (see Figure 8). By running the simulation for many years of weather data and by using this load duration curve, it's possible to estimate Ptmb for each substation. What's interesting with this method is that it gives the contribution of each substation to the global power peak and not their individual maximum (different due to the diversity effect). Furthermore, when it's too early in the project life to be able to locate precisely a future consumer or producer, a Monte Carlo method is used to locate them. In use case 2, Ptmb is estimated the same way but at the scale of the building (or building block).

Figure 8 -Load duration curve with division by substation

Mines Paris Tech and Enedis are now working on the automation of this process in order to directly get the power value with a chosen probability.

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EVALUATION OF THE IMPACT ON THE GRID

The last step in the MOSAIC method is to evaluate the impact on the grid of the area evolutions. This step is still under development and it will be done using Enedis' load flow computation tool ERABLE (based on the software PowerFactory by DIgSILENT). will allow to highlight grid constraints (voltage/current) for the diversity of scenarios submitted based on load calculated at Ptmb.

Relevant and comprehensive representation of the results of these calculations is still under development.

FIRST RESULTS ON MV FEEDERS

The matching method between premises per electric feeder was applied in a case study of 10 feeders in Brest, France. The sample characteristics are illustrated in table 1. We apply the same method for calibrating the main influence default parameters as described in 1.2. Thanks to the simulation of electricity feeders and MV/LV substations with MOSAIC, we perform a large range of simulations with various meteorological conditions. In Figure 9 we plot the overpass of the reference power of a MV/LV substation with the meteorological conditions of the past 30 years. Enedis therefore continue to improve its methods (larger area, demand response, electric vehicle), the modeling parameters and the interactions with load flow computation by applying the MOSAIC method on ten areas of France. Thanks to MOSAIC, Enedis will be able to integrate in its planning methods local specificities such as economical or urban planning decisions. Furthermore, MOSAIC makes possible to run successively different scenarios. Therefore, for important projects, the local government will have feedbacks on the potential impact of its development project early in the project life cycle. This knowledge can help to make the best decision for the energy transition. MOSAIC won't replace Enedis' traditional planning methods. However, it can improve them especially when radical changes in future area makes it impossible to rely on past consumption trend.

  we plot an example of

Figure 9 -

 9 Figure 9 -Frequency (%) of overpass of the reference power in a MV/LV substation with 30 meteorological years

Table 1

 1 Characteristics of the 10 feeders data set used

	Characteristics	Min value	Mean value	Max value
	Number of customers	357	751	1471
	supplied
	Fraction of residential	34%	62%	91%
	consumption

Acknowledgments

The authors tank Hugues Souchard de Lavoreille and Maxence Leroy for their important contribution in the development of the Majic/Enedis matching method, the adaptation to MOSAIC and for the Brest case study results.