High volume demand response. Finally.

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A tricky problem. And the solution.

IoT technology that is designed to manage an infrastructure, not just one system.

Demand response as a concept is very straightforward. When there is too much consumption compared to production, remotely instruct the consuming loads to reduce it. Or if more consumption is needed to balance the grid, do the opposite.

But the practice is much more complex. Let's start with the simple problem of getting access to a suitable load. Where is it? Who owns it? Who controls it? How will the change affect the people using it? How much does it cost to control it?

In fact, there are five core problems to be solved:

  1. Finding a load to control.
  2. Determining the control capabilities of the load to control.
  3. Negotiating access rights to the load to control.
  4. Commanding the load in a way the load understands.
  5. Paying a compensation for the owner of the load for allowing control.

The Smart Energy API Standard ("SEAS" in short) is a technology framework designed to solve these five core problems of demand response. It is one consitent set of software, services and design references that help (a) manufacturers create demand response compatible equipment and (b) network operators use the equipment remotely as a unified fleet.

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"The dirty secret of clean energy is that while generating it is getting easier, moving it to market is not."

The New York Times

In practice, what is the Smart Energy API?

Here are the components

An open specification

A data definition for software engineering on how energy systems should communicate.

An open specification

A data definition for software engineering on how energy systems should communicate.

Open source software

An open source software development toolkit (SDK) to easily engineer compatible energy systems.

A reference design

A free design reference for manufacturers that guides in how to design compatible IT systems.

Cloud services

A set of services that enable system discovery in high volume, high speed, and with low overhead.


SEAS contains the software and specifications for plugging into a heterogeneous set of devices in the field with one unified view to the data. It defines identifiers that allow pointing at each device unambiguously and data specifications that let systems do unit conversions and the interpretation of data automatically.


Handling timeseries of production and consumption is the bread and butter of energy management systems. Historical values of the past, especially those that match the same season of the year the year before or similar weather conditions, are the basis of creating a prediction of what happens in similar conditions in the future. Consequently SEAS has an extensive set of timeseries handling features that allow exchangin such data between systems accurately, unifying the data, and using mathematical methods to reveal correlations that feed into the predictive models.

Assign targets

In energy management, it is not necessarily wise to try to remotely micro manage complex targets such as large buildings. The buildings themselves have internal structure that is usually something that cannot be known without very detailed knowledge of who occupies it and when. Consequently, a better way is to just set broad targets, preferably with some heads-up margin, instead of specific commands. The local systems can take appropriate action to perform the actual actions that lead to that target. SEAS models such targets and then delegates them within the infrastructure.

Trigger action

There is a range of factors that for instance building automation systems react to. These include for instance timers that deactivate systems after office hours, carbon dioxide sensors that adjust the air conditioning, temperature sensors that drive the heating systems, and much more. SEAS contains technology to monitor not only the values in real-time but also follow the triggering of events. The events can then be linked together in logic engines to further create local and remote control logic.


SEAS was designed for control applications and contains a vast set of methods to send not only direct commands but also abstract targets to controllable loads, energy production, and energy storage. Data can be fetched per request as secured timeseries or subscribed to to receive real-time updates in the form of a secure notification stream.


SEAS includes an extensive set of features and software for commercializing data. It supports signing, end-to-end encrypting, and notarizing data. These serve as a legal guarantee for payments and contract compliance for demand response actions and data delivery