Energy Management - Canada

Canada

Revenue in the Energy Management market is projected to reach €301.0m in 2024.
Revenue is expected to show an annual growth rate (CAGR 2024-2029) of 11.24%, resulting in a projected market volume of €512.6m by 2029.
In the Energy Management market, the number of active households is expected to amount to 2.4m users by 2029.
Household penetration will be 21.6% in 2024 and is expected to hit 21.3% by 2029.
The average revenue per installed Smart Home currently is expected to amount to €128.30.

Mercado

Región

Comparación de regiones

Moneda

Analyst Opinion

The Energy Management market in Canada is experiencing significant growth and development.

Customer preferences: Customers in Canada are increasingly concerned about energy efficiency and sustainability. They are looking for ways to reduce their energy consumption and carbon footprint. This has led to a growing demand for energy management solutions that can help them monitor and control their energy usage. Customers are also interested in solutions that can help them optimize their energy consumption, reduce costs, and comply with environmental regulations.

Trends in the market: One of the key trends in the Energy Management market in Canada is the adoption of smart grid technology. Smart grids enable the efficient integration of renewable energy sources, such as wind and solar power, into the electricity grid. They also allow for real-time monitoring and control of energy consumption, which can help utilities and customers make informed decisions about energy usage. The implementation of smart grids is supported by government initiatives and regulations aimed at promoting renewable energy and reducing greenhouse gas emissions. Another trend in the market is the increasing use of data analytics and artificial intelligence (AI) in energy management. These technologies can analyze large amounts of data from smart meters, sensors, and other devices to identify patterns and anomalies in energy consumption. This enables businesses and individuals to optimize their energy usage and identify opportunities for energy savings. AI-powered energy management systems can also make real-time adjustments to energy consumption based on factors such as weather conditions and electricity prices.

Local special circumstances: Canada has a diverse energy landscape, with a mix of traditional and renewable energy sources. The country is a major producer and exporter of oil and gas, but it is also investing in renewable energy, such as hydroelectric power, wind power, and solar power. This creates unique challenges and opportunities for energy management. For example, energy management solutions need to be able to integrate and optimize energy from different sources, as well as manage the variability of renewable energy generation.

Underlying macroeconomic factors: The growth of the Energy Management market in Canada is driven by several macroeconomic factors. The country has committed to reducing its greenhouse gas emissions and transitioning to a low-carbon economy. This has led to government incentives and regulations that promote energy efficiency and renewable energy. The increasing cost of energy and the need to reduce energy consumption and costs are also driving the adoption of energy management solutions. Additionally, advances in technology, such as smart meters and IoT devices, have made it easier and more cost-effective to monitor and control energy usage.

Methodology

Data coverage:

The data encompasses B2C enterprises. Figures are based on the sales of smart home products, excluding taxes.

Modeling approach:

Market sizes are determined through a bottom-up approach, building on a specific rationale for each market category. As a basis for evaluating markets, we use the Statista Global Consumer Survey, market data from independent databases and third-party sources, and Statista interviews with market experts. In addition, we use relevant key market indicators and data from country-specific associations, such as household internet penetration and consumer spending for households. This data helps us estimate the market size for each country individually.

Forecasts:

In our forecasts, we apply diverse forecasting techniques. The selection of forecasting techniques is based on the behavior of the relevant market. For example, the S-curve function and exponential trend smoothing are well suited for forecasting innovative products due to the non-linear growth of technology adoption. The main drivers are GDP/capita, level of digitization, and consumer attitudes toward smart home integration.

Additional notes:

The data is modeled using current exchange rates. The impact of the COVID-19 pandemic and the Russia-Ukraine war are considered at a country-specific level. The market is updated once a year, in case market dynamics change we do more frequent updates.