This table displays the results of Data table for Chart 1 Short-term rentals and Shares , calculated using number of units and percent units of measure (appearing as column headers). Short-term rentals Shares number of units percent
The PLTD estimates are obtained using data from AirDNA. No surveys were conducted, and no ownership data can be linked to specific STR units to better understand which units could feasibly be used as long-term dwellings. Caution should be used when interpreting the PLTD figures, and they should be considered only an estimate, not an actual count of dwellings that have been removed from the long-term housing stock. Nevertheless, the PLTD estimates provide a more reliable indicator than assuming all Canadian STR listings, over 355,000 in 2023, have the capacity to function as long-term dwellings.
Several studies have investigated the influence of private STRs on rental markets and housing shortages. The findings from these studies offer insights into the extent to which STR activity affects the housing market.
A recent Conference Board of Canada report Note suggests that the level of Airbnb activity had no meaningful impact on the cost of rent, stating that “the share of dwellings used for Airbnb activity is too small in most neighbourhoods—on average less than 0.5 per cent—to have a meaningful impact.” That estimate was determined based on what it referred to as “high-use Airbnb” units, defined as “an entire home or apartment that has been rented out for more than 30 nights in the previous three months, and likely to be a full-time short-term rental and therefore unlikely to be a host’s principal place of residence.”
McGill University’s Urban Politics and Governance research group has also published several papers examining the impact of STR activity on housing availability. In a 2017 paper, Note researchers associated with the group attempted to estimate the number of units removed from the housing supply because of STR activity in Canada’s three largest cities. They found that “there are now 13,700 entire homes rented 60 days or more per year on Airbnb in Montreal, Toronto and Vancouver, each of which is unlikely to be rented to long-term tenants. These entire homes account for one sixth of all Airbnb listings, and a majority of nights booked on the service.” The number comes from their calculation of “full-time Airbnb” use. They defined this concept as the number of days per year that a unit is booked (“occupancy”) and the number of days that a unit is either booked or available to be booked (“availability”). They define “full-time” as 60 days of occupancy and 120 days of availability.
In 2019, members of the group published another paper, Note which used the concept of frequently rented entire-home (FREH) listings to identify the subset of STRs that may be removing units from the housing supply. They define FREH listings as STRs that were “available for rent at least half the year (183 nights) and actually rented at least 90 nights. FREH listings represent a conservative estimate for housing either directly converted to STRs or under serious threat of conversion since it is highly unlikely that a home that spends the majority of the year listed on Airbnb is housing a long-term resident.” This estimate suggests that Airbnb has removed approximately 31,100 units of housing from the long-term rental market.
These studies show that there is no standardized measurement for estimating the number of dwellings being removed from the long-term housing market because of STR activity. The FREH concept aligns more closely with the PLTD concept defined in this paper. A notable difference with all three referenced papers is the use of a threshold for days rented. The PLTD concept in this analysis did not account for days rented, since whether a unit was successfully rented out is not a requirement for removing it from the long-term stock. An empty unit listed on an STR platform could otherwise accommodate a long-term tenant or owner but currently remains vacant.
Another distinction between PLTDs and the concepts used in these papers is the threshold used for the number of days listed. The Conference Board of Canada paper, for example, employs a shorter listing time threshold of 120 days. Shorter timelines may capture units that are made available for only part of the year and still primarily function as long-term housing, such as units listed during the winter months by snowbirds.
A final difference between PLTDs and these other concepts is the exclusion of certain property types. Specifically, the PLTD estimates try to exclude vacation-type properties such as cottages, purpose-built vacation homes and other vacation properties that would be unlikely to enter the long-term housing market. Note
In summary, these studies show previous efforts made to understand STR activity in Canada. The present study reinforces the use of the PLTD concept in an environment with no standardized measurement practices.
Total STR listings increased by more than 60% in Canada from 2017 to 2023, while the number of PLTDs grew by more than 80%, from 58,441 to 107,266 units, over the same period (Chart 2). As a result, the share of listings considered as PLTDs rose from 27.2% of total listings in 2017 to 30.2% in 2023 (Chart 3).
All short-term rentals | Potential long-term dwellings | |
---|---|---|
number of units | ||
Statistics Canada, custom tabulation from AirDNA data. | ||
2017 | 214,808 | 58,441 |
2018 | 267,634 | 74,083 |
2019 | 303,521 | 88,494 |
2020 | 266,444 | 72,796 |
2021 | 245,109 | 63,589 |
2022 | 278,841 | 70,139 |
2023 | 355,070 | 107,266 |
Yet the progression did not follow a linear path, with STR activity declining after the onset of the COVID-19 pandemic. Total listings in Canada fell 19.2% from 2019 to 2021, while the PLTD subset decreased even more, by 28.1% over the same two years. In 2022, even as STR activity started to pick up, the share of PLTDs (25.2% of total listings) was still lower than in 2019 (29.2%).
Percent | |
---|---|
Statistics Canada, custom tabulation from AirDNA data. | |
2017 | 27.2 |
2018 | 27.7 |
2019 | 29.2 |
2020 | 27.3 |
2021 | 25.9 |
2022 | 25.2 |
2023 | 30.2 |
As mentioned previously, the decline in PLTDs during the pandemic was more severe than the overall decrease in STR activity. This greater decline in the PLTD subset may support the notion that these units could be used as long-term dwellings. After the decline in tourism during the pandemic, many property owners may have converted their STRs to long-term rentals. This could also explain why 2022 marked a low point in the proportion of PLTDs , since many thousands of units may have still been tied up in 12-month leases during the onset of the recovery. However, this assumption could be confirmed only with property ownership data, which are not available for this analysis.
Housing stock data Note for the intercensal years indicate that there were 15.5 million housing units Note in Canada in the last quarter of 2023. This highlights a pronounced disparity in scale, with the total number of dwellings being orders of magnitude larger than the estimate of PLTDs . At the national level, PLTDs accounted for 0.69% of Canadian housing units in 2023 (Chart 4). This figure is an all-time high for Canada, with the previous high of 0.60% occurring in 2019.
Percent | |
---|---|
Statistics Canada, Table and custom tabulation from AirDNA data. | |
2017 | 0.41 |
2018 | 0.51 |
2019 | 0.60 |
2020 | 0.49 |
2021 | 0.42 |
2022 | 0.46 |
2023 | 0.69 |
These trends differ at the provincial level. Note In Ontario, the share of housing units defined as PLTDs more than doubled, jumping from 0.35% in 2022 to an all-time high of 0.69% in 2023 (Table 1). In Quebec, there was a jump from 0.38% in 2022 to 0.51% in 2023. However, this did not exceed Quebec’s pre-pandemic high of 0.61%, which occurred in 2019. It is possible that these differences are the result of different regulatory approaches, since Quebec has enacted province-wide STR regulations, while regulations have been enacted only at the municipal level in Ontario.
At the provincial level, only British Columbia and Prince Edward Island had a share of PLTDs that exceeded 1% of housing units in 2023. This finding aligns with those provinces being the leaders in STRs , with their STR markets claiming the greatest share of revenue within their respective accommodation services subsectors. Note
Province or territory | Housing units | PLTDs | PLTDs as a share of housing units |
---|---|---|---|
Number of units | Number of units | Percent | |
PLTD = potential long-term dwelling. Statistics Canada, Table 36-10-0688-01 and custom tabulation from AirDNA data. | |||
Newfoundland and Labrador | 226,800 | 1,515 | 0.67 |
Prince Edward Island | 67,795 | 880 | 1.30 |
Nova Scotia | 443,510 | 2,987 | 0.67 |
New Brunswick | 347,503 | 1,442 | 0.41 |
Quebec | 3,866,386 | 19,614 | 0.51 |
Ontario | 5,673,597 | 38,955 | 0.69 |
Manitoba | 532,654 | 1,485 | 0.28 |
Saskatchewan | 458,071 | 975 | 0.21 |
Alberta | 1,690,412 | 9,514 | 0.56 |
British Columbia | 2,144,966 | 29,643 | 1.38 |
Yukon | 18,272 | 165 | 0.90 |
Northwest Territories | 15,380 | 62 | 0.40 |
Nunavut | 10,015 | 29 | 0.29 |
Total for Canada | 15,495,361 | 107,266 | 0.69 |
Housing unit estimates are not available at the subprovincial level between census years. As a result, the following estimates are available only for 2021. In 2021, PLTDs accounted for less than half a percent of housing units in Canada’s five largest CMAs by population (Table 2). Additionally, among the largest CMAs , only Vancouver (0.45%) had a PLTD share of housing units that exceeded the 2021 national average of 0.42%. These findings are similar to those of the Conference Board of Canada report mentioned in the “Current literature” section, which showed that “on average less than 0.5 per cent” of dwellings were high-use Airbnb units in the neighbourhoods it studied. Note
Census metropolitan area | Housing units | Potential long-term dwellings | Share of housing units |
---|---|---|---|
Number of units | Number of units | Percent | |
Statistics Canada, Census of Population, 2021; and custom tabulation from AirDNA data. | |||
Toronto | 2,270,741 | 8,266 | 0.36 |
Montréal | 1,842,890 | 7,185 | 0.39 |
Vancouver | 1,048,029 | 4,714 | 0.45 |
Ottawa–Gatineau | 605,768 | 1,565 | 0.26 |
Calgary | 565,286 | 1,846 | 0.33 |
The shares were higher in tourist areas, especially in ski towns. Whistler had the highest share by far in 2021, with 35.0% of housing units being PLTDs (Table 3). A situation in which PLTDs make up more than one-third of housing units can be expected to have a significant impact on a community’s housing market. However, the nature of the market as a tourist hotspot likely changes the approach to STRs for policy makers and other stakeholders. These areas may be disproportionately reliant on STR activity since it often supports tourism and stimulates the local economy. Other popular tourist markets in more rural areas, such as Mont-Tremblant (16.4%), Canmore (15.0%) and The Blue Mountains (13.2%), all have similar shares of PLTDs as part of their housing supply. The Prince Edward County census subdivision had the fifth-highest share of PLTDs , at 4.9%.
Census subdivision | Housing units | Potential long-term dwellings | Share of housing units |
---|---|---|---|
Number of units | Number of units | Percent | |
The table includes only census subdivisions with a minimum of 500 potential long-term dwellings. Statistics Canada, Census of Population 2021; custom tabulation from AirDNA data. | |||
Whistler | 8,611 | 3,016 | 35.0 |
Mont-Tremblant | 6,468 | 1,058 | 16.4 |
Canmore | 8,007 | 1,202 | 15.0 |
The Blue Mountains | 5,007 | 662 | 13.2 |
Prince Edward County | 11,909 | 579 | 4.9 |
This analysis has shown that the subset of STR units capable of serving as long-term housing, defined as PLTDs , is generally small in most Canadian markets. The degree to which STR activity impacts housing affordability was not a focus of this paper, and so the results should not necessarily be used to draw conclusions on price impacts without further analysis.
Housing market dynamics are complex, Note and there is unlikely to be a simple and straightforward solution to the current challenges of affordability and supply faced by many Canadians. This paper has focused on STR activity within the housing market. However, it is important to acknowledge the influence of many other factors affecting affordability and supply, including, but not limited to, multiple-property owner investors, Note the housing supply in relation to population growth, Note and factors relating to interest rates and financing.
Responding to concerns regarding STR activity, numerous municipalities Note Note and some provinces Note Note have enacted or strengthened regulations. Additionally, in its 2023 Fall Economic Statement, the federal government introduced new tax policies targeting non-compliant STR operators. Note This analysis offers a clearer understanding of STR activity across Canada and its relation to the Canadian housing market. For detailed data from this analysis, refer to the appendices.
The term “potential long-term dwellings” in this paper refers to the subset of Canadian short-term rental units that satisfy the following conditions:
Property type | Defined as vacation type? |
---|---|
Statistics Canada and AirDNA. | |
Condominium (condo) | No |
Apartment | No |
Guest house | No |
Bungalow | No |
House | No |
Townhouse | No |
Guest suite | No |
Loft | No |
Dome house | No |
Villa | No |
Serviced apartment | No |
Place | No |
Earth house | No |
Studio | No |
Estate | No |
Building | No |
Property type | Defined as vacation type? |
---|---|
Statistics Canada and AirDNA. | |
Farm stay | Yes |
Bed & breakfast | Yes |
Boutique hotel | Yes |
Cottage | Yes |
Chalet | Yes |
Cabin | Yes |
Camper or RV | Yes |
Hotel | Yes |
Tiny house | Yes |
Vacation home | Yes |
Boat | Yes |
Hostel | Yes |
Tent | Yes |
Resort | Yes |
Barn | Yes |
Nature lodge | Yes |
Treehouse | Yes |
Castle | Yes |
Cave | Yes |
Shipping container | Yes |
Yurt | Yes |
Tipi | Yes |
Campsite | Yes |
Aparthotel | Yes |
Island | Yes |
Hut | Yes |
Igloo | Yes |
Lighthouse | Yes |
Train | Yes |
Bus | Yes |
Holiday park | Yes |
Ranch | Yes |
Tower | Yes |
Windmill | Yes |
Country house or chateau | Yes |
Lodge | Yes |
Farmhouse | Yes |
Yacht | Yes |
Caravan | Yes |
Other | Yes |
Casa particular | Yes |
Shepherd's hut | Yes |
House boat | Yes |
Ryokan | Yes |
Pension | Yes |
Heritage hotel | Yes |
Cycladic house | Yes |
Minsu | Yes |
Kezhan | Yes |
Corporate apartment | Yes |
Mobile home | Yes |
Mas | Yes |
Area | Short-term rentals | PLTDs | Housing units | PLTD ratio | Population |
---|---|---|---|---|---|
number of units | percent | number of persons | |||
PLTD = potential long-term dwelling. Statistics Canada, custom tabulation from AirDNA data. | |||||
Canada | |||||
2017 | 214,806 | 58,439 | 14,333,148 | 0.41 | 36,494,341 |
2018 | 267,630 | 74,082 | 14,527,043 | 0.51 | 37,009,341 |
2019 | 303,516 | 88,491 | 14,722,631 | 0.60 | 37,555,217 |
2020 | 266,443 | 72,796 | 14,890,801 | 0.49 | 37,997,799 |
2021 | 245,109 | 63,589 | 15,067,760 | 0.42 | 38,222,632 |
2022 | 278,840 | 70,139 | 15,264,940 | 0.46 | 38,866,587 |
2023 | 355,069 | 107,266 | 15,495,361 | 0.69 | 39,965,952 |
Alberta | |||||
2017 | 12,416 | 3,426 | 1,554,086 | 0.22 | 4,232,820 |
2018 | 16,650 | 4,602 | 1,576,050 | 0.29 | 4,286,099 |
2019 | 19,765 | 5,897 | 1,598,493 | 0.37 | 4,348,515 |
2020 | 18,293 | 5,477 | 1,619,585 | 0.34 | 4,404,480 |
2021 | 17,897 | 5,539 | 1,641,530 | 0.34 | 4,431,482 |
2022 | 21,669 | 7,029 | 1,665,281 | 0.42 | 4,504,684 |
2023 | 26,952 | 9,514 | 1,690,412 | 0.56 | 4,673,843 |
British Columbia | |||||
2017 | 55,075 | 16,687 | 1,933,936 | 0.86 | 4,925,007 |
2018 | 66,505 | 22,399 | 1,970,964 | 1.14 | 5,009,885 |
2019 | 72,325 | 26,062 | 2,006,616 | 1.30 | 5,100,179 |
2020 | 62,747 | 21,034 | 2,034,219 | 1.03 | 5,169,146 |
2021 | 59,060 | 18,953 | 2,065,264 | 0.92 | 5,218,564 |
2022 | 67,709 | 21,736 | 2,102,231 | 1.03 | 5,339,114 |
2023 | 83,457 | 29,643 | 2,144,966 | 1.38 | 5,499,535 |
Manitoba | |||||
2017 | 2,065 | 392 | 495,755 | 0.08 | 1,331,885 |
2018 | 2,924 | 597 | 501,671 | 0.12 | 1,350,414 |
2019 | 3,609 | 811 | 507,697 | 0.16 | 1,367,580 |
2020 | 3,519 | 784 | 513,583 | 0.15 | 1,379,626 |
2021 | 3,755 | 694 | 519,510 | 0.13 | 1,390,212 |
2022 | 4,639 | 1,081 | 526,020 | 0.21 | 1,410,716 |
2023 | 5,657 | 1,485 | 532,654 | 0.28 | 1,449,223 |
New Brunswick | |||||
2017 | 1,893 | 390 | 324,617 | 0.12 | 766,049 |
2018 | 3,063 | 591 | 328,291 | 0.18 | 770,036 |
2019 | 4,217 | 895 | 332,124 | 0.27 | 776,408 |
2020 | 4,093 | 865 | 335,690 | 0.26 | 782,703 |
2021 | 4,202 | 815 | 339,218 | 0.24 | 789,627 |
2022 | 4,968 | 1,058 | 343,231 | 0.31 | 806,942 |
2023 | 6,155 | 1,442 | 347,503 | 0.41 | 831,245 |
Newfoundland and Labrador | |||||
2017 | 2,159 | 731 | 220,413 | 0.33 | 529,943 |
2018 | 3,447 | 1,119 | 221,706 | 0.50 | 528,999 |
2019 | 4,438 | 1,486 | 222,990 | 0.67 | 528,101 |
2020 | 4,088 | 1,156 | 223,588 | 0.52 | 527,224 |
2021 | 3,905 | 1,068 | 224,439 | 0.48 | 526,870 |
2022 | 4,359 | 1,213 | 225,535 | 0.54 | 530,813 |
2023 | 5,050 | 1,515 | 226,800 | 0.67 | 537,570 |
Northwest Territories | |||||
2017 | 245 | 37 | 15,077 | 0.25 | 44,645 |
2018 | 402 | 53 | 15,136 | 0.35 | 44,672 |
2019 | 547 | 164 | 15,291 | 1.07 | 44,547 |
2020 | 384 | 76 | 15,248 | 0.50 | 44,499 |
2021 | 229 | 31 | 15,249 | 0.20 | 44,578 |
2022 | 228 | 42 | 15,310 | 0.27 | 44,742 |
2023 | 253 | 62 | 15,380 | 0.40 | 44,731 |
Nova Scotia | |||||
2017 | 5,395 | 1,485 | 409,619 | 0.36 | 951,050 |
2018 | 7,918 | 2,163 | 415,427 | 0.52 | 961,061 |
2019 | 9,751 | 2,710 | 421,197 | 0.64 | 974,449 |
2020 | 8,938 | 2,135 | 425,956 | 0.50 | 987,164 |
2021 | 8,567 | 1,928 | 431,112 | 0.45 | 997,671 |
2022 | 9,666 | 2,197 | 437,024 | 0.50 | 1,021,600 |
2023 | 10,875 | 2,987 | 443,510 | 0.67 | 1,053,277 |
Nunavut | |||||
2017 | 41 | 7 | 9,848 | 0.07 | 37,541 |
2018 | 83 | 10 | 9,872 | 0.10 | 38,154 |
2019 | 106 | 13 | 9,896 | 0.13 | 38,768 |
2020 | 88 | 7 | 9,916 | 0.07 | 39,302 |
2021 | 55 | 3 | 9,937 | 0.03 | 39,987 |
2022 | 72 | 9 | 9,970 | 0.09 | 40,423 |
2023 | 152 | 29 | 10,015 | 0.29 | 40,623 |
Ontario | |||||
2017 | 69,403 | 16,988 | 5,257,816 | 0.32 | 14,056,827 |
2018 | 86,472 | 20,820 | 5,325,042 | 0.39 | 14,297,687 |
2019 | 101,978 | 25,992 | 5,394,537 | 0.48 | 14,545,973 |
2020 | 91,725 | 22,045 | 5,455,664 | 0.40 | 14,747,481 |
2021 | 83,403 | 18,296 | 5,517,856 | 0.33 | 14,841,395 |
2022 | 96,647 | 19,670 | 5,586,326 | 0.35 | 15,118,655 |
2023 | 142,289 | 38,955 | 5,673,597 | 0.69 | 15,561,348 |
Prince Edward Island | |||||
2017 | 2,435 | 597 | 61,186 | 0.98 | 149,125 |
2018 | 3,796 | 887 | 62,472 | 1.42 | 151,948 |
2019 | 4,878 | 1,080 | 63,685 | 1.70 | 155,277 |
2020 | 4,311 | 929 | 64,577 | 1.44 | 158,567 |
2021 | 4,047 | 847 | 65,552 | 1.29 | 161,371 |
2022 | 4,058 | 724 | 66,521 | 1.09 | 166,513 |
2023 | 4,636 | 880 | 67,795 | 1.30 | 172,841 |
Quebec | |||||
2017 | 61,711 | 17,264 | 3,598,347 | 0.48 | 8,284,231 |
2018 | 73,533 | 20,248 | 3,644,066 | 0.56 | 8,374,735 |
2019 | 78,260 | 22,522 | 3,689,710 | 0.61 | 8,470,681 |
2020 | 64,896 | 17,399 | 3,728,526 | 0.47 | 8,547,809 |
2021 | 56,831 | 14,656 | 3,770,080 | 0.39 | 8,570,537 |
2022 | 61,327 | 14,513 | 3,815,423 | 0.38 | 8,661,144 |
2023 | 65,215 | 19,614 | 3,866,386 | 0.51 | 8,851,067 |
Saskatchewan | |||||
2017 | 1,642 | 378 | 436,732 | 0.09 | 1,145,931 |
2018 | 2,335 | 513 | 440,224 | 0.12 | 1,155,439 |
2019 | 3,064 | 740 | 443,847 | 0.17 | 1,163,703 |
2020 | 2,847 | 798 | 447,341 | 0.18 | 1,167,953 |
2021 | 2,707 | 695 | 450,714 | 0.15 | 1,167,668 |
2022 | 2,966 | 761 | 454,298 | 0.17 | 1,177,607 |
2023 | 3,757 | 975 | 458,071 | 0.21 | 1,205,873 |
Yukon | |||||
2017 | 326 | 57 | 15,716 | 0.36 | 39,287 |
2018 | 502 | 80 | 16,122 | 0.50 | 40,212 |
2019 | 578 | 119 | 16,548 | 0.72 | 41,036 |
2020 | 514 | 91 | 16,908 | 0.54 | 41,845 |
2021 | 451 | 64 | 17,299 | 0.37 | 42,670 |
2022 | 532 | 106 | 17,770 | 0.60 | 43,634 |
2023 | 621 | 165 | 18,272 | 0.90 | 44,776 |
Census metropolitan area | Short-term rentals | PLTDs | Housing units | PLTD ratio | Population |
---|---|---|---|---|---|
Number of units | Number of units | Numbers of units | % | Number of persons | |
PLTD = potential long-term dwelling. Statistics Canada, Census of Population, 2021; and custom tabulation from AirDNA data. | |||||
Toronto | 35,939 | 8,266 | 2,270,741 | 0.36 | 6,202,225 |
Montréal | 24,909 | 7,185 | 1,842,890 | 0.39 | 4,291,732 |
Vancouver | 18,947 | 4,714 | 1,048,029 | 0.45 | 2,642,825 |
Ottawa–Gatineau | 6,969 | 1,565 | 605,768 | 0.26 | 1,488,307 |
Calgary | 6,937 | 1,846 | 565,286 | 0.33 | 1,481,806 |
Edmonton | 4,169 | 1,228 | 549,853 | 0.22 | 1,418,118 |
Québec | 5,817 | 1,843 | 389,798 | 0.47 | 839,311 |
Winnipeg | 2,297 | 487 | 330,812 | 0.15 | 834,678 |
Hamilton | 2,076 | 486 | 307,871 | 0.16 | 785,184 |
Kitchener–Cambridge–Waterloo | 1,697 | 346 | 219,406 | 0.16 | 575,847 |
London | 1,821 | 362 | 222,602 | 0.16 | 543,551 |
Halifax | 3,286 | 812 | 201,952 | 0.40 | 465,703 |
St. Catharines–Niagara | 4,967 | 1,488 | 180,713 | 0.82 | 433,604 |
Windsor | 1,318 | 288 | 165,963 | 0.17 | 422,630 |
Oshawa | 706 | 92 | 149,142 | 0.06 | 415,311 |
Victoria | 4,987 | 1,597 | 178,367 | 0.90 | 397,237 |
Saskatoon | 932 | 216 | 125,316 | 0.17 | 317,480 |
Regina | 702 | 215 | 100,430 | 0.21 | 249,217 |
Sherbrooke | 1,123 | 257 | 104,907 | 0.24 | 227,398 |
Kelowna | 4,596 | 1,376 | 95,711 | 1.44 | 222,162 |
Barrie | 1,029 | 258 | 78,798 | 0.33 | 212,856 |
St. John's | 1,182 | 377 | 90,377 | 0.42 | 212,579 |
Abbotsford–Mission | 429 | 97 | 67,712 | 0.14 | 195,726 |
Kingston | 998 | 211 | 73,716 | 0.29 | 172,546 |
Greater Sudbury | 453 | 93 | 73,478 | 0.13 | 170,605 |
Guelph | 316 | 49 | 64,224 | 0.08 | 165,588 |
Saguenay | 830 | 192 | 74,997 | 0.26 | 161,567 |
Trois-Rivières | 366 | 84 | 76,719 | 0.11 | 161,489 |
Moncton | 837 | 201 | 67,386 | 0.30 | 157,717 |
Brantford | 177 | 26 | 56,031 | 0.05 | 144,162 |
Saint John | 534 | 100 | 55,965 | 0.18 | 130,613 |
Peterborough | 659 | 117 | 53,487 | 0.22 | 128,624 |
Lethbridge | 279 | 70 | 48,715 | 0.14 | 123,847 |
Thunder Bay | 319 | 69 | 54,274 | 0.13 | 123,258 |
Nanaimo | 875 | 212 | 49,557 | 0.43 | 115,459 |
Kamloops | 1,078 | 441 | 47,546 | 0.93 | 114,142 |
Chilliwack | 656 | 176 | 44,546 | 0.40 | 113,767 |
Belleville–Quinte West | 405 | 93 | 46,308 | 0.20 | 111,184 |
Fredericton | 385 | 64 | 46,424 | 0.14 | 108,610 |
Drummondville | 89 | 24 | 45,724 | 0.05 | 101,610 |
Red Deer | 268 | 55 | 40,570 | 0.14 | 100,844 |
Census subdivision | Short-term rentals | PLTDs (minimum 50) | Housing units | PLTD ratio | Population |
---|---|---|---|---|---|
Number of units | Number of units | Numbers of units | % | Number of persons | |
PLTD = potential long-term dwelling. Statistics Canada, Census of Population, 2021; and custom tabulation from AirDNA data. | |||||
Toronto | 27,077 | 6,628 | 1,167,518 | 0.57 | 2,794,356 |
Montréal | 21,378 | 6,300 | 822,655 | 0.77 | 1,762,949 |
Calgary | 6,406 | 1,733 | 504,038 | 0.34 | 1,306,784 |
Ottawa | 4,499 | 1,010 | 408,265 | 0.25 | 1,017,449 |
Edmonton | 3,673 | 1,113 | 397,513 | 0.28 | 1,010,899 |
Winnipeg | 2,197 | 474 | 300,904 | 0.16 | 749,607 |
Mississauga | 2,778 | 555 | 245,130 | 0.23 | 717,961 |
Vancouver | 8,678 | 2,392 | 307,727 | 0.78 | 662,248 |
Brampton | 1,464 | 288 | 182,758 | 0.16 | 656,480 |
Hamilton | 1,653 | 398 | 223,208 | 0.18 | 569,353 |
Surrey | 1,749 | 329 | 185,999 | 0.18 | 568,322 |
Québec | 4,046 | 1,457 | 267,172 | 0.55 | 549,459 |
Halifax | 3,190 | 803 | 191,308 | 0.42 | 439,819 |
Laval | 674 | 184 | 169,969 | 0.11 | 438,366 |
London | 1,559 | 308 | 174,968 | 0.18 | 422,324 |
Markham | 724 | 112 | 110,982 | 0.10 | 338,503 |
Vaughan | 737 | 169 | 104,084 | 0.16 | 323,103 |
Gatineau | 1,581 | 415 | 126,890 | 0.33 | 291,041 |
Saskatoon | 883 | 202 | 107,252 | 0.19 | 266,141 |
Kitchener | 734 | 181 | 99,991 | 0.18 | 256,885 |
Longueuil | 686 | 193 | 113,278 | 0.17 | 254,483 |
Burnaby | 1,995 | 376 | 101,511 | 0.37 | 249,125 |
Windsor | 642 | 124 | 94,399 | 0.13 | 229,660 |
Regina | 658 | 209 | 92,339 | 0.23 | 226,404 |
Oakville | 448 | 56 | 73,611 | 0.08 | 213,759 |
Richmond | 1,877 | 547 | 81,627 | 0.67 | 209,937 |
Richmond Hill | 866 | 140 | 69,455 | 0.20 | 202,022 |
Burlington | 346 | 67 | 73,247 | 0.09 | 186,948 |
Sherbrooke | 374 | 64 | 80,539 | 0.08 | 172,950 |
Greater Sudbury | 425 | 92 | 71,572 | 0.13 | 166,004 |
Abbotsford | 335 | 73 | 53,303 | 0.14 | 153,524 |
Lévis | 518 | 144 | 65,894 | 0.22 | 149,683 |
Coquitlam | 569 | 94 | 56,044 | 0.17 | 148,625 |
Barrie | 394 | 65 | 55,380 | 0.12 | 147,829 |
Saguenay | 545 | 130 | 67,650 | 0.19 | 144,723 |
Kelowna | 2,560 | 724 | 62,934 | 1.15 | 144,576 |
Trois-Rivières | 306 | 79 | 66,904 | 0.12 | 139,163 |
St. Catharines | 567 | 145 | 59,045 | 0.25 | 136,803 |
Langley | 367 | 77 | 47,002 | 0.16 | 132,603 |
Kingston | 621 | 150 | 57,985 | 0.26 | 132,485 |
Waterloo | 684 | 117 | 47,157 | 0.25 | 121,436 |
Saanich | 984 | 251 | 48,301 | 0.52 | 117,735 |
St. John's | 962 | 286 | 49,546 | 0.58 | 110,525 |
Thunder Bay | 290 | 60 | 48,465 | 0.12 | 108,843 |
Delta | 313 | 58 | 38,118 | 0.15 | 108,455 |
Red Deer | 268 | 55 | 40,565 | 0.14 | 100,844 |
Nanaimo | 743 | 180 | 43,345 | 0.42 | 99,863 |
Lethbridge | 259 | 65 | 40,290 | 0.16 | 98,406 |
Kamloops | 335 | 57 | 39,972 | 0.14 | 97,902 |
Niagara Falls | 2,218 | 769 | 38,564 | 1.99 | 94,415 |
Cape Breton | 334 | 58 | 42,373 | 0.14 | 93,694 |
Chilliwack | 279 | 71 | 35,831 | 0.20 | 93,203 |
Victoria | 2,053 | 732 | 49,952 | 1.47 | 91,867 |
Brossard | 316 | 66 | 35,951 | 0.18 | 91,525 |
North Vancouver (District municipality) | 947 | 234 | 32,934 | 0.71 | 88,168 |
Moncton | 592 | 160 | 35,275 | 0.45 | 79,470 |
Kawartha Lakes | 883 | 127 | 32,837 | 0.39 | 79,247 |
New Westminster | 286 | 52 | 36,152 | 0.14 | 78,916 |
Wood Buffalo | 342 | 76 | 26,011 | 0.29 | 72,326 |
Saint John | 333 | 65 | 31,890 | 0.20 | 69,895 |
Grande Prairie | 440 | 108 | 24,928 | 0.43 | 64,141 |
Fredericton | 268 | 51 | 28,526 | 0.18 | 63,116 |
North Vancouver (City) | 564 | 140 | 27,430 | 0.51 | 58,120 |
Georgina | 290 | 55 | 17,950 | 0.31 | 47,642 |
Langford | 395 | 112 | 19,162 | 0.58 | 46,584 |
Vernon | 436 | 132 | 19,922 | 0.66 | 44,519 |
West Vancouver | 471 | 136 | 17,826 | 0.76 | 44,122 |
Innisfil | 566 | 173 | 15,883 | 1.09 | 43,326 |
Charlottetown | 644 | 156 | 17,341 | 0.90 | 38,809 |
Penticton | 633 | 237 | 17,597 | 1.35 | 36,885 |
West Kelowna | 661 | 208 | 14,183 | 1.47 | 36,078 |
Stratford | 262 | 78 | 14,818 | 0.53 | 33,232 |
Fort Erie | 462 | 124 | 14,204 | 0.87 | 32,901 |
Courtenay | 173 | 50 | 13,050 | 0.38 | 28,420 |
Magog | 304 | 88 | 13,528 | 0.65 | 28,312 |
Prince Edward County | 1,693 | 579 | 11,909 | 4.86 | 25,704 |
Lunenburg | 398 | 99 | 11,599 | 0.85 | 25,545 |
Wasaga Beach | 480 | 130 | 10,940 | 1.19 | 24,862 |
Collingwood | 527 | 153 | 11,328 | 1.35 | 24,811 |
Squamish | 476 | 129 | 9,314 | 1.39 | 23,819 |
Oro-Medonte | 244 | 69 | 8,709 | 0.79 | 23,017 |
White Rock | 177 | 51 | 10,786 | 0.47 | 21,939 |
Huntsville | 554 | 119 | 8,934 | 1.33 | 21,147 |
Niagara-on-the-Lake | 782 | 226 | 8,086 | 2.79 | 19,088 |
Sylvan Lake | 174 | 53 | 6,448 | 0.82 | 15,995 |
Canmore | 2,067 | 1,202 | 8,007 | 15.01 | 15,990 |
Lake Country | 365 | 116 | 6,321 | 1.84 | 15,817 |
Sooke | 271 | 82 | 6,212 | 1.32 | 15,086 |
Sainte-Adèle | 200 | 58 | 6,953 | 0.83 | 14,010 |
Whistler | 5,204 | 3,016 | 8,611 | 35.02 | 13,982 |
Parksville | 247 | 93 | 6,843 | 1.36 | 13,642 |
Gravenhurst | 436 | 61 | 5,556 | 1.10 | 13,157 |
Tiny | 550 | 95 | 5,530 | 1.72 | 12,966 |
North Saanich | 160 | 53 | 5,063 | 1.05 | 12,235 |
Summerland | 231 | 77 | 5,162 | 1.49 | 12,042 |
Lambton Shores | 430 | 87 | 5,392 | 1.61 | 11,876 |
Saltspring Island | 483 | 124 | 5,244 | 2.36 | 11,635 |
Saint-Sauveur | 281 | 82 | 6,017 | 1.36 | 11,580 |
Bromont | 227 | 53 | 5,113 | 1.04 | 11,357 |
Nelson | 209 | 77 | 5,022 | 1.53 | 11,106 |
Mont-Tremblant | 2,110 | 1,058 | 6,468 | 16.36 | 10,992 |
Sechelt | 348 | 131 | 5,256 | 2.49 | 10,847 |
Chester | 306 | 80 | 5,105 | 1.57 | 10,693 |
Hinton | 140 | 50 | 4,055 | 1.23 | 9,817 |
Stoneham-et-Tewkesbury | 445 | 54 | 3,919 | 1.38 | 9,682 |
The Blue Mountains | 1,441 | 662 | 5,007 | 13.22 | 9,390 |
Qualicum Beach | 165 | 54 | 4,489 | 1.20 | 9,303 |
Comox Valley C (Puntledge-Black Creek) | 304 | 96 | 3,831 | 2.51 | 9,158 |
South Bruce Peninsula | 597 | 65 | 4,210 | 1.54 | 9,137 |
Columbia-Shuswap C | 372 | 109 | 4,109 | 2.65 | 8,919 |
Banff | 199 | 65 | 2,995 | 2.17 | 8,305 |
Revelstoke | 418 | 167 | 3,522 | 4.74 | 8,275 |
La Malbaie | 294 | 96 | 3,921 | 2.45 | 8,235 |
Kimberley | 341 | 153 | 3,748 | 4.08 | 8,115 |
Comox Valley A | 219 | 53 | 3,723 | 1.42 | 7,926 |
Muskoka Lakes | 1,016 | 203 | 3,733 | 5.44 | 7,652 |
Baie-Saint-Paul | 335 | 111 | 3,536 | 3.14 | 7,371 |
Dysart et al | 475 | 86 | 3,426 | 2.51 | 7,182 |
Minden Hills | 279 | 50 | 3,280 | 1.52 | 6,971 |
Wainfleet | 202 | 84 | 2,699 | 3.11 | 6,887 |
Nanaimo E | 195 | 61 | 3,136 | 1.95 | 6,765 |
Trent Lakes | 340 | 61 | 3,011 | 2.03 | 6,439 |
Fernie | 333 | 178 | 2,773 | 6.42 | 6,320 |
Southern Gulf Islands | 284 | 61 | 3,241 | 1.88 | 6,101 |
Peachland | 187 | 85 | 2,775 | 3.06 | 5,789 |
Osoyoos | 307 | 118 | 2,768 | 4.26 | 5,556 |
Seguin | 334 | 69 | 2,204 | 3.13 | 5,280 |
Inverness, Subd. A | 375 | 110 | 2,505 | 4.39 | 5,207 |
Juan de Fuca (Part 1) | 286 | 130 | 2,330 | 5.58 | 5,132 |
Orford | 306 | 70 | 2,315 | 3.02 | 5,007 |
Inverness, Subd. B | 173 | 50 | 2,215 | 2.26 | 4,865 |
Gibsons | 153 | 52 | 2,337 | 2.23 | 4,758 |
Sutton | 257 | 73 | 2,463 | 2.96 | 4,548 |
North Okanagan C | 569 | 165 | 1,880 | 8.78 | 4,511 |
Nanaimo H | 186 | 58 | 2,058 | 2.82 | 4,291 |
New Glasgow | 344 | 50 | 1,745 | 2.87 | 4,277 |
Rossland | 189 | 88 | 1,888 | 4.66 | 4,140 |
Beaupré | 368 | 153 | 2,008 | 7.62 | 4,117 |
Victoria, Subd. B | 209 | 57 | 1,922 | 2.97 | 4,077 |
Okanagan-Similkameen D | 129 | 54 | 1,899 | 2.84 | 4,016 |
Golden | 213 | 52 | 1,787 | 2.91 | 3,986 |
Invermere | 279 | 141 | 1,801 | 7.83 | 3,917 |
Central Kootenay E | 174 | 54 | 1,854 | 2.91 | 3,897 |
Saint-Ferréol-les-Neiges | 337 | 131 | 1,936 | 6.77 | 3,806 |
Lake of Bays | 438 | 50 | 1,810 | 2.76 | 3,759 |
East Kootenay F | 671 | 301 | 1,891 | 15.92 | 3,521 |
Columbia-Shuswap A | 692 | 192 | 1,687 | 11.38 | 3,325 |
Columbia-Shuswap F | 281 | 87 | 1,647 | 5.28 | 3,200 |
Sunshine Coast A | 208 | 57 | 1,617 | 3.53 | 3,039 |
Kootenay Boundary E / West Boundary | 1,058 | 468 | 1,888 | 24.79 | 3,004 |
Sunshine Coast B | 189 | 72 | 1,437 | 5.01 | 2,969 |
Central Okanagan West | 592 | 169 | 1,459 | 11.58 | 2,897 |
Victoria, Subd. A | 297 | 57 | 1,277 | 4.46 | 2,673 |
Sicamous | 171 | 73 | 1,318 | 5.54 | 2,613 |
Tofino | 524 | 291 | 1,236 | 23.54 | 2,516 |
Okanagan-Similkameen I | 385 | 145 | 1,115 | 13.00 | 2,307 |
Ucluelet | 429 | 212 | 1,092 | 19.41 | 2,066 |
Lac-Supérieur | 426 | 58 | 1,053 | 5.51 | 1,972 |
East Kootenay A | 418 | 240 | 1,025 | 23.41 | 1,875 |
Bighorn No. 8 | 369 | 220 | 860 | 25.58 | 1,598 |
New London | 300 | 65 | 700 | 9.29 | 1,521 |
Osoyoos 1 | 150 | 55 | 625 | 8.80 | 1,426 |
Sun Peaks Mountain | 635 | 364 | 984 | 36.99 | 1,404 |
Radium Hot Springs | 261 | 119 | 754 | 15.78 | 1,339 |
L'Anse-Saint-Jean | 230 | 85 | 705 | 12.06 | 1,301 |
Fraser Valley C | 126 | 50 | 600 | 8.33 | 1,133 |
Kerrobert | 64 | 51 | 461 | 11.06 | 970 |
Petite-Rivière-Saint-François | 652 | 181 | 606 | 29.87 | 953 |
Columbia-Shuswap B | 138 | 54 | 354 | 15.25 | 663 |
Juan de Fuca (Part 2) | 204 | 73 | 183 | 39.89 | 399 |
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Title: long-term energy management for microgrid with hybrid hydrogen-battery energy storage: a prediction-free coordinated optimization framework.
Abstract: This paper studies the long-term energy management of a microgrid coordinating hybrid hydrogen-battery energy storage. We develop an approximate semi-empirical hydrogen storage model to accurately capture the power-dependent efficiency of hydrogen storage. We introduce a prediction-free two-stage coordinated optimization framework, which generates the annual state-of-charge (SoC) reference for hydrogen storage offline. During online operation, it updates the SoC reference online using kernel regression and makes operation decisions based on the proposed adaptive virtual-queue-based online convex optimization (OCO) algorithm. We innovatively incorporate penalty terms for long-term pattern tracking and expert-tracking for step size updates. We provide theoretical proof to show that the proposed OCO algorithm achieves a sublinear bound of dynamic regret without using prediction information. Numerical studies based on the Elia and North China datasets show that the proposed framework significantly outperforms the existing online optimization approaches by reducing the operational costs and loss of load by around 30% and 80%, respectively. These benefits can be further enhanced with optimized settings for the penalty coefficient and step size of OCO, as well as more historical references.
Comments: | Submitted to Applied Energy |
Subjects: | Optimization and Control (math.OC); Systems and Control (eess.SY) |
Cite as: | [math.OC] |
(or [math.OC] for this version) |
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4. Write your abstract. Because the abstract is a summary of your entire paper, it's usually best to write it after you complete your first draft. Typically, an abstract is only 150-250 words, so focus on highlighting the key elements of your term paper like your thesis, main supporting evidence, and findings.
2. Gather Research on Your Topics. The foundation of a good term paper is research. Before you start writing your term paper, you need to do some preliminary research. Take your topics with you to the library or the Internet, and start gathering research on all of the topics you're interested in.
A term paper is typically given at the conclusion of a course, serving as a comprehensive summary of the knowledge acquired during that term. It follows a structured format and may delve into specific topics covered within the course. On the other hand, a research paper delves deeper, involving original research, thorough analysis, and the ...
A term paper is a research paper written by students over an academic term, accounting for a large part of a grade. Merriam-Webster defines it as "a major written assignment in a school or college course representative of a student's achievement during a term". Term papers are generally intended to describe an event, a concept, or argue a point. It is a written original work discussing a topic ...
Term Paper. Definition: Term paper is a type of academic writing assignment that is typically assigned to students at the end of a semester or term. It is usually a research-based paper that is meant to demonstrate the student's understanding of a particular topic, as well as their ability to analyze and synthesize information from various sources.. Term papers are usually longer than other ...
The Do's and Don'ts of Term Paper Writing. Do's: Don'ts: Write down every idea you have, even if there's no structure to them. Just record any phrases, tips, quotes or thoughts you come across. This is an outstanding way to collect a lot of material. Follow your outline, but don't be a slave to it.
A term paper is generally structured with an opening introduction, followed by several body paragraphs, and culminates with a conclusion. It articulates a central thesis statement, bolstered by corroborative evidence and critical analysis. The writing is formal in nature, adheres to a designated formatting style like APA or MLA, and is ...
The volume determines which approach you take to writing. For example, if your paper is short, you need to state your thoughts concisely and clearly, going straight to the point. If it is long, do not fill the pages with hot air, but try to do thorough research and look at the issue from different angles.
Body Paragraphs. As a rule, in writing college term papers, one must write down several subheadings and headings to divide ideas and arguments into several (at least four) paragraphs. As done below, each body paragraph should contain one idea and a strong topic sentence. Heading 1: History of the argument and background.
Steps to compose a cover page: Centrally align the title of your paper in the middle of the page. Add your name, course name, and number below the title. Include your instructor's name and the date of submission at the bottom. You might be required to add more than these common elements if your professor asks you to.
Overview of term paper. To start writing a term paper, you should first choose a topic that you are interested in that is related to the class. Then, do some pre-searching to identify preliminary sources that you could potentially use. Write a thesis statement addressing your topic that is arguable and provable.
The easiest way to understand is this. If writing a paper about wind and solar, you would need at least three topic sentences - 1)Wind 2)Solar 3)Benefits of using wind and solar. Naturally, a term paper needs much more than just three, but you get the idea.
Summarize the main points of the research - Include the main arguments and facts presented in your writing and remind the reader of the significance of your topic. Concluding sentence - Create a thought-provoking concluding sentence to make an impression on readers and leave them with something to think about.
Begin a decimal outline with "1.0" and each subsequent section with the next number ("2.0", "3.0", etc.). Change the number after the decimal point to reflect new information. For example, "2.1" might be your first subpoint, and "2.2" would be your second subpoint.
A term paper is an academic paper that is usually written at the end of the school year. It requires students to conduct thorough research on a given topic and compile their findings into a well-structured paper. It often requires students to demonstrate their knowledge and understanding of the subject matter.
To end your term paper: Restate the topic in the topic sentence of your conclusion paragraph. Also, restate the thesis statement of your term paper. Briefly present a summary of the significant points in your term paper. Be clear and concise on the arguments. Have a call to action if there is a need to do so.
In particular, one must write the title in capital letters. Then, the paper's header contains the title and page number. However, one must flush these details to the right margin. As a result, in-text citations include the author's surname, publication date, and the page containing the relevant evidence.
A term paper is a research project written by students over an academic term, typically accounting for a significant part of a grade. It is intended to describe an event, a concept, or argue a point. The paper is usually original research involving a detailed study of a subject, requiring a considerable amount of preparation and effort.
Term papers contribute significantly to a subject's overall grade. How to Write a Term Paper: 7 Simple Steps. Before writing a term paper, always keep in mind the instructions provided to you. If you have any issues in understanding the instructions, don't hesitate to ask your professor. Moreover, if you want to compose a top-notch term ...
By definition, a term paper is a type of research-based writing assignment that a student has to submit to his or her teacher at the end of an academic term. Typically, a student tries to discuss elaborately on a topic that was assigned to him or her. The topic could be an event description, a case study, a concept, or an argument.
Find suitable sources for your term paper. At this point, decide on the most likely sources of information—books, journal articles, newspapers, online databases, CD-ROM databases, interviews, etc. Dig around in the library and locate sources for your term paper. Use your library's computer access system to find books on your subject.
A well-structured college term paper outline guarantees an excellent paper at the end. You should be in a position to harmonize all the parts of a term paper into one melody that communicates an unmistakable thought of ideas. Term Paper Structure. The following layout should help you come up with a high-quality term paper this semester:
However, the investment performance of some stocks was remarkable. Seventeen stocks delivered cumulative returns greater than five million percent (or $50,000 per dollar initially invested), with the highest cumulative return of 265 million percent (or $2.65 million per dollar initially invested) accruing to long-term investors in Altria Group.
As for Trump's newly minted vice presidential pick, Ohio Sen. J.D. Vance has espoused similar views to those mentioned in Project 2025, including placing more tariffs on Chinese goods and ...
Democrats say the plan is a warning of what is to come under a second Trump term, while Trump has tried to distance himself from the policy proposals: "They are extreme, seriously extreme," said ...
Harris echoed Biden's repeated comments about the "ironclad support" and "unwavering commitment" to Israel. The country has a right to defend itself, she said, while noting, "how it ...
WASHINGTON (AP) — President Joe Biden on Sunday posted a letter to social media announcing that he would no longer seek reelection. The decision by the Democrat came after building pressure from lawmakers, donors, activists and voters within his own party who had concerns about his ability to beat Republican Donald Trump in November's election.
The paper focuses on the subset of short-term rentals (STRs) that could potentially serve as long-term housing. This subset of STRs, referred to as potential long-term dwellings (PLTDs), is intended to capture STR units that are not serving as anyone's primary residence, but could potentially function as long-term housing (either as owner-occupied or rental units).
View PDF Abstract: In recent years, transformer-based models have gained prominence in multivariate long-term time series forecasting (LTSF), demonstrating significant advancements despite facing challenges such as high computational demands, difficulty in capturing temporal dynamics, and managing long-term dependencies. The emergence of LTSF-Linear, with its straightforward linear ...
This paper studies the long-term energy management of a microgrid coordinating hybrid hydrogen-battery energy storage. We develop an approximate semi-empirical hydrogen storage model to accurately capture the power-dependent efficiency of hydrogen storage. We introduce a prediction-free two-stage coordinated optimization framework, which generates the annual state-of-charge (SoC) reference for ...