Smart Grid: Electricity storage and variable energy pricing

Buying and storing electricity when it is cheap, and selling it when it is expensive. What are the benefits, both public and private?

Buying and storing electricity when it is cheap, and selling it when it is expensive. What are the benefits, both public and private?

Welcome to the Smart Grid: Electricity storage and variable energy pricing simulation. The objective of this simulation is to study how seizing variable energy pricing thanks to smart charging and discharging of batteries can be beneficial for:

  • Households: earning some revenue buying cheap energy and selling it expensive.
  • Distribution network: Diminishing the rate of interaction with the grid, leaving more power capacity available for renewable energies and electric vehicles.
The model simulates two households equiped with solar panels and a battery, each one of them identical in its physical features: Energy production, consumption, battery size, etc.

The households are able to exchange electricity with the grid, and when this happens, are applied the APX prices. This means that there is an economic benefit in purchasing electricity at low prices and providing it into the grid when prices are more expensive.

The difference in household B is that its battery is charged and discharged dynamically depending not only on the household production and consumption, but also on:

  • Variable electricity prices (APX prices).
  • The level of battery charging.
  • The estimated consumption of electricity during the next hours.
  • The estimated solar production of electricity during the next hours.
The optimization algorithm that I sketched is aimed at two objectives:

  • Buy electricity when it is cheap, sell it when it is expensive. In this way, it is possible for the household to get some revenue using just the right software solution.
  • Do not load too much the battery when it is expected a peak of production in the next hours and do not discharge it totally if it is expected a peak of demand. The objective is to increase the self-sufficiency of the household, avoiding unnecessary energy interactions with the grid.
You can run the model with the Simulate button, in the upper bar. The simulation is rather slow, so I included in the model a Quick results butoon, that display the main results after a shorter delay.

In this preliminary example, the revenues obtained commercing with electricity are scarce, just 35 euros for a small household over a whole year.  This figure can probably be optimized with a more elaborated algorithm.

The reduction of grid interaction is much more spectacular: almost 70%, what suggests a potential for reducing grid usage and accomodate more renewable energies and electric vehicles in the system.
This is the end of the explanation. Some ideas about how can I help you from here:
  • Customize the model with your own data, and algorithms that fit better your needs.
  • Consider additional sources of revenues ("onbalansprijzen" energy market, supervised by Tennet) and expenses (battery inefficiencies and degradation are not considered by the model).
  • Make a business case out of energy storage at household or district level.

View the model in Insight Maker