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Time Series for Climate Change: Forecasting Energy Demand
How to use time series analysis and forecasting to tackle climate change
This is Part 4 of the series Time Series for Climate Change. List of articles:
- Part 1: Forecasting Wind Power
- Part 2: Solar Irradiance Forecasting
- Part 3: Forecasting Large Ocean Waves
So far, we explored how forecasting is important to integrate clean energy sources into the electricity grid.
Forecasting also plays a key role on the demand side of energy systems.
Balancing the demand and supply of energy
Power systems need to ensure the balance between the supply and demand of energy at all times. This balance is critical for the reliability of the electricity grid. If demand is greater than supply, this leads to power outages. When supply exceeds demand, there’s a surplus of energy which often goes to waste.
Power systems use forecasting models to help them predict the demand for energy. Accurate demand forecasts contribute to more efficient production and use of energy. This has a direct impact on climate because of waste reduction.
Analyzing energy consumption is also valuable within households. For example, individuals can examine which appliances consume more energy, and use this information to avoid higher costs during peak hours. As a bit of trivia: It’s estimated that about 8% of residential electricity demand comes from standby power consumption [4].
Forecasting energy demand
Forecasting energy demand is a difficult problem.
Energy consumption depends on several factors, some of which might not be readily available for modeling. Examples include weather and economic conditions that affect the use of electronic devices for heating or cooling. Weather is characterized by highly variable patterns. These make it difficult to predict the magnitude of weather impact on energy demand.
Energy demand data exhibit seasonal patterns at different time scales, including daily, monthly, or yearly scales. In winter, for example, energy demand…
