Dutch smart energy meters and tourism in the Netherlands

This project and subsequent desk research has been made possible by action grants from Eurostat in the field of business statistics under the European Statistics strand of the Single Market Programme (SMP ESS).

European statistics on tourism

In most countries, tourism statistics are compiled using 20th century methodologies, heavily relying on traditional business and household surveys. A built-in threat is that the available statistical indicators are not only driven by user needs but also by the constraints of those methodologies. It is therefore essential that tourism statistics embrace new sources and new methods to ensure that the statistical output lives up to user expectations in terms of relevance, timeliness, punctuality, accuracy, completeness and granularity, while considering the cost-efficiency of the statistical production system and the burden on respondents and administrations. The grant that has been awarded to Statistics Netherlands will support the modernization of the development, production and dissemination of European statistics on tourism, by integrating new sources (single or combined) and methodologies.

General objectives

This modernization of the development of European statistics will be realized as a feasibility study that looks into the patterns of energy consumption of Dutch tourist accommodations like camp sites, hotels and such, and other types of accommodations that are used for tourism (mainly private dwellings like second homes). For this study, data from Dutch smart energy meters will be used. This will be used in trying to answer two research questions:

I: What can we learn in order to detect any seasonal pattern in energy consumption in private dwellings, that could contribute to identifying these dwellings as second homes or as locations primarily used for tourism purposes?

II: What can we learn in order to detect to detect the seasonal pattern in energy consumption in (known) tourist accommodations to track activity and seasonal openings?

Concept and methodology

The Dutch tourism sector is at an all-time high. In 2024, the Netherlands received a total of 84,5 million Dutch and foreign tourists (CBS, 2026; 2026), which contributes for 4% to the Dutch economy (CBS, 2025). Statistics Netherlands keeps track of the number of tourists staying at hotels, camp sites and bungalow parks by conducting questionnaire-based research.

Given this large influx of tourists, innovative ways of collecting data to quantify the numbers of tourists are of the essence. The recent implementation of smart energy meters may provide an opportunity to utilize the data to track tourism flows (Eurostat, 2017; Raun et al., 2023). Whether a place is used as a touristic accommodation and what its occupation level is, may be deduced from the energy consumption levels.

The link between energy use and tourism has received some attention previously. For example, one study showed that the energy consumption patterns differ between various touristic accommodations in New Zealand (Becken et al., 2001). Hotels used significantly more energy than other accommodation types such as hostels, b&b’s and campsites, also when taking capacity into account. Comparisons to the energy use of non-touristic sites are rare. Based on a literature review it appears that, in general, the average energy consumption per square meter of hotels may be relatively high (Zarco-Soto et al., 2025). It was found that the energy use by hotels is much higher than by residential and office buildings and appears to be more in line with the consumption of hospital and commercial buildings. A meta-analysis based on twenty-three studies also put forward that for hotels, floor area and star level correlate positively with energy use (Schons Arenhart et al., 2024). For the whole hotel and restaurant sector, the energy consumption increases with more tourists (Pablo-Romero etal., 2017). Also on the level of the accommodation, several studies comfirmed the positive relation between the occupancy level and its energy use (Becken et al., 2001; Schons Arenhart et al., 2024). This relation differs however per accommodation type; for example, with more guests, the energy use of hotels increases more steeply compared to b&b’s (Becken et al., 2001).

Besides the commercial tourist accommodations, second homes are used for touristic purposes. The number of second homes has drastically increased over the past years, especially after the COVID-19-pandemic (Raun et al., 2023). In Denmark, energy use in second homes has increased rapidly from 1982 to 2004, presumably due to an increased number of second homes, as well as their larger size and more intensive use throughout the year (Andersen et al., 2008). A previous study into energy use measured by smart energy meters of second homes in Denmark, found the highest energy use in the winter months, despite the holiday homes being frequented more in the summer period (Hjalager & Piihl, 2025). There were also peaks of energy use coinciding with school holidays. One should note, however, that second homes differ considerably in their energy use due to different use patterns (Andersen et al., 2008). For example, some second homes are just used during the holidays by their owners, where others are being used year-round, for example by retired seniors. In general, second homes are often less well insulated than primary residences and may include high energy consuming luxuries as pools, making second homes have a relative higher energy consumption pattern compared to primary homes (Hjalager & Piihl, 2025).

Lessons from the existing research

Based on previous research there is a clear, positive relation between the energy use of a touristic accommodation and its occupation level. However, this energy consumption is also influenced by floor area and star level. It therefore seems promising to deduce occupation level from energy use, if the other factors are properly controlled for.

Considering the identification of second homes used for touristic purposes, it appears that the energy use of second homes is relatively high compared to primary residences. Holiday periods may additionally help to pinpoint second homes.

Although the proposed study is a feasibility study, we know beforehand which sources can be used in the study. This chapter will outline our general knowledge about energy consumption patterns and will give a preliminary operationalization. This is so we can formulate proposed methods in the concluding chapter of our desk research.

Consumption patterns

The energy data collected has information on the approximate location of energy consumption, identified through EAN (European Article Number) codes, which can be linked to addresses of tourist accommodations. For each EAN we have access to the energy delivery of electricity and gas, and the backflow of electricity due to the use of solar panels, by which we can approximate the energy consumption. 

The number of residents and the number of nights spent at an accommodation follow seasonal patterns throughout the year. Typically, there are peaks in both May and August, which are associated with the summer season. During the winter months, fewer tourists are expected, particularly in January. Over the years, the number of tourists appears to be increasing steadily, especially during the summer months (CBS, 2026; 2026). In contrast, (global) energy usage in the Netherlands follows the opposite pattern. Electricity and gas consumption are highest in winter and lowest in summer (CBS, 2024). Unfortunately, we do not have specific data on energy expenses in the energy sector. Overall, energy usage seems to be declining over time, likely due to measures against global warming, higher energy prices and measures to save energy. On the other hand, the production of solar energy is increasing rapidly, both in relative and absolute terms (CBS, 2026). In 2024, 79 PJ of solar energy was consumed, compared to 31 PJ in 2020.

Preliminary operationalization

As stated Statistics Netherlands already possesses information about the available sources we plan to use for the feasibility study. We will therefore describe the variables we are planning to utilize directly or indirectly.

Guests

Visitors who stay one or more consecutive nights in a lodging accommodation. A guest who stays for more than two consecutive months in a lodging accommodation is considered a regular guest and is not counted for the statistics. Asylum seekers and seasonal workers are not counted as guests, even if they stay for less than two consecutive months in a lodging accommodation. Each month, guests who leave during that month are counted, regardless of the month in which they arrived. Note that it is possible that a person is counted as a guest two or more times in the same month, either in the same accommodation or in different accommodations.

Types of tourist accommodations

Hotel

A hotel is a location where one can stay overnight and have hotel service. Also motels, youth accommodations and b&b's which provide hotel service are counted as hotel.

Campings

A piece of land or part of a land with tourist sleeping places, where it is possible to stay in tents, caravans, camping cars, cabins, or trekker tents. Our statistics apply a minimum threshold of at least 4 tourist parking spots for these accommodations.

Holiday Park

A site with a number of summer cottages, motorhomes, (holiday-)bungalows, or (holiday-)apartments, which are mainly available for rental by the operator or manager of the complex. Apartments that are rented with hotel services are not considered a holiday home complex but rather as (apartment) hotel. Apartments without hotel services, which are often part of a larger building, are considered as bungalows or summer cottages. Our statistics apply a minimum threshold of at least 10 sleeping places for these accommodations.

Group accommodation

Accommodation providing lodging primarily to people in group settings (not family settings), with sleeping arrangements in rooms, halls, cottages, cabins, apartments, and/or tents, where guests may have to share with strangers.

Units of energy

The SI unit for energy is the joule (J). It is commonly used with prefixes, such as terajoules (1TJ = 10¹²J) and petajoules (1PJ = 10¹⁵ J). Another unit of energy frequently used in electricity is the kilowatt-hour (kWh), where 1 kWh equals 3.6 megajoules (MJ). Additionally, 1 PJ is equivalent to about 31.6 million cubic meters of natural gas or 278 million kWh of electricity.

Types of consumable energy

Natural gas

Natural gas supplies from the public grid. This refers to natural gas supplies from the national gas grid managed by Gas Transport Services (GTS), the Zebragas network, and the gas networks of the regional network operators. For long-distance transport by ship, natural gas is liquefied. The use of gas measured as m³ has been corrected for the weather, so that it approximates the gas usage in a fictional year with average weather conditions. In other words: after a mild winter, the weather-corrected gas usage is higher than the real gas usage because in a normal and colder winter the gas consumption would haven been higher. 

Electricity

Electricity deliveries from the public grid. This refers to electricity deliveries from the national electricity grid managed by TenneT and the electricity networks of the regional network operators. Electricity is the flow of electrons used, for example, to light lamps or to operate washing machines. Gross electricity delivery refers to the amount of electricity delivered regardless of whether it is consumed. Net electricity delivery only include electricity that is not delivered back to the net.

Registers available

BAG (base administration buildings)

Identifies residential properties and links gas/electricity connections to specific homes. It only includes spaces used for living, but some spaces are in dual use (e.g. for tourism).

• Building year: When the building was originally built (excluding renovations)
• Type of residence: (e.g. single family home)
• Living area: Square meters of living space according to NEN2580 standards.

BRP (base registrations of persons)

Provides information about which houses are inhabited and the number of persons registered at the address.

CERES (Central registration of system elements)

 Tracks solar panel installations and returns. Also holds the yearly registration of solar panels present at an address.

Other information

NACE

The economic sector in which activities take place, standardized throughout the European Union. Tourist accommodations can be defined by combining NACE 551 to 553 according to their definitions in NACE2025.

EAN code

An 18-digit code valid across the European Union. It is specific to a particular gas or electricity connection of a household to the grid. Our research can be limited to EAN codes that can be linked to tourist zones, such as hotels, campsites, holiday parks, or group accommodations.

Smart energy meter

A smart meter is a digital meter whose readings can be read remotely by the energy supplier and the network operator. Since 2026 every home is required to have one. It measures electricity and gas meter readings. The information from the smart meters is collected once a month. Older data has sometimes been collected by an analog meter which might be less accurate.

For the first feasibility study we will model whether energy consumption predicts whether an accommodation is a primary home or second home, thereby taking into account the degree days (temperature) and holiday periods.

Predicted variable: second home

Explanatory variables: energy use, holiday period, temperature

For the second feasibility study we will model whether energy consumption predicts occupation in known tourist accommodations, thereby taking into account the degree days (temperature) and type of accommodation (hotel, bungalow park, camp site, group accommodation).

Predicted variable: occupation

Explanatory variables: energy use, accommodation type, temperature

The models are a rough indication and will be subject to change in the respective feasibility studies.

This report will be published at the end of February 2026. The following months will be spend conducting both feasibility studies, and the results will be published at the end of 2026.

Andersen, F. M., Christensen, M. S., Jensen, O. M., Kofoed, N.-U., & Morthorst, P. E. (2008). Second-home electricity consumption. Energy Policy, pp. 280-289.  

Becken, S., Frampton, C., & Simmons, D. (2001). Energy consumption patterns in the accommodation sector—the New Zealand case. Ecological Economics, pp. 371-386.

CBS (2024). Seizoenspatronen in huishoudelijk energieverbruik. 

CBS. (2025). Toeristische bestedingen stijgen tot ruim 111 miljard euro in 2024.  

CBS. (2026). Hotels; gasten, overnachtingen, woonland, sterklasse.  

CBS. (2026). Logiesaccommodaties; gasten, nachten, woonland, logiesvorm, regio.

CBS (2026). https://opendata.cbs.nl/CBS/nl/dataset/82061NED/line?dl=D02D1

CBS (2026). https://opendata.cbs.nl/CBS/nl/dataset/82059NED/line?dl=D02D7

Eurostat. (2017). Tourism statistics: Early adopters of big data?  Luxembourg: Publications Office of the European Union.

Hjalager, A.-M., & Piihl, J. (2025). Are second homes CO2 saints or sinners? Electricity consumption from a seasonal and geographical perspective. Scandinavian Journal of Hospitality and Tourism, pp. 116-138.  https://doi.org/10.1080/15022250.2025.2454649

Pablo-Romero, M. P., Sánchez-Braza, A., & Sánchez-Rivas, J. (2017). Relationships between Hotel and Restaurant Electricity Consumption and Tourism in 11 European Union Countries. Sustainability, p. 2109.  

Raun, J., Järv, O., Okkonen, P., Rantanen, M., Hyyryläinen, T., Ryynänen, T., & Toivonen, T. (2023). New avenues for second home tourism research using big data:prospects and challenges. Current Issues in Tourism, pp. 890-902.  

Schons Arenhart, R., Martins, T., Mituso Ueda, R., Mendonça Souza, A., & Ruviaro Zanini, R. (2024). Energy use and its contributors in hotel buildings: A systematic review and meta-analysis. PLOS One, p. e0309745.  

Zarco-Soto, F. J., Zarco-Soto, I. M., Shofirun Sharif Ali, S., & Zarco-Periñán, P. J. (2025). Energy consumption in buildings: A compilation of current studies. Energy Reports, pp. 1293-1307.