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Why New Daedalus?

Daedalus was the mythical great architect and artificer of the classical world. Today, embedded intelligence is enabling the most profound changes in the way we create and use buildings since his day.

Building Intelligence meets the Intelligent Building. The Intelligent Building negotiates with the Intelligent Grid. How will this transform how we interact with the physical world?

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Surfaces – the kind of Abstractions I like best

My personal interests are in making each building a participant in an open market of energy sources that span a continent. (\) At the same time, within a building (or campus) there might be mix of energy generation (PV, wind, Stirling Engine,..) and energy storage (Battery, Hydrogen, water pools, …) systems.

The complexity of such systems is impossible to manage, or orchestrate, or choreograph unless it is hidden behind abstract interfaces. If they are all tied into one tight control system, then we have created a realm wherein the producer of each system cannot be held accountable for performance. We also create a rigid system wherein individual system failures lead to cascading failures rather than simple degradation of overall performance. This means that I want abstract interfaces even between systems in the same building.

With these abstract interfaces in place, one could add new systems as new technologies become available. I can swap in substitute systems without re-programming the others. This intensifies competition between these large systems by reducing the friction on the transaction of switching from one to another in an existing facility.

If we make these abstract interfaces discoverable, the we can easily imagine a competitive market of agents that can find and interact with these building systems as well as with the business processes (or life preferences, if in a home) of the building inhabitants. Those agents could interact with the power grid and live energy pricing on the basis of a single building. As the abstraction level grows, the agent could be located outside the building, to bid aggregate power use for an industrial combine, or for a portfolio of homes with either similar desires (I want all wind power. I want a carbon-neutral mix. I want the cheapest power available.) or complimentary power use patterns.

In other words, I want to place Intelligent Buildings as fully actualized agents on an Intelligent Grid. To do that, I hope to leverage Building Intelligence (NBIMS) to discover abstract interfaces to the point-by-point complexity of the underlying control systems. Rather than create these abstract interfaces from scratch, I had hoped that the pre-existing interfaces between the Building Model and Energy Models would be a good starting point. By doing so, I hope to avoid the complexity of introducing Yet Another Acronym and Yet Another Interface, thereby avoid increasing complexity.

Abstract interfaces that hide rather than reveal complexity are the key. Here is an example from within oBIX discussions. When we discussed abstract interfaces for scheduling, each control system developer quickly claimed that “scheduling systems are quite complex, and there are no agreed standards.” Spirited discussions ensued about factoring how long it takes to air condition a room in advance. Should we factor in humidity. and on. and on. But there is already a standard for scheduling. We each receive ICAL invitations to each NBIMS event. It is a W3 specification. Our own systems know how to adjust for where we are in the world, including such local oddities as when Daylight Savings Time begins. Each of us considers whether we have to drive to the meeting, or fly, or simply be near a phone. Those details are not the concern of the interface but of each of us and the complex systems we represent. I want to simply invite the conference room or class room to an event on a certain date, with a certain number of attendees anticipated.

If these questions are answered correctly, they expand the value of capital assets by extending their ability to provide services and amenities to the owners and tenants, not merely to avoid costs. An Energy Model consists of Envelope, Weather, and System Operations. An abstract interface that works for energy modeling could be re-usable in tuning System Operations in response to Weather Predictions to improve quality of service provided. It becomes the basis for external system analytics to enable predictive maintenance and thereby economically provide enhanced reliability.

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Reader Comments (1)

Toby's point about focusing on the "surfaces" is spot on. The example about scheduling reminded me of an important aspect of distributed decision-making in complex systems: forecasting. More effective operation can be achieved with a predictive component in the control loop. In the intelligent building and grid systems, the competitive components will develop good forecasting skills including future demand for service, cost of energy, and related environmental parameters, such as weather.

The ownership for forecasting needs to reside in each component. In healthy systems, there isn't one, shared forecast, but components will use information from many competing sources. This keeps the vision for the future distributed as well -- responsive to change and open to innovation.

May 2, 2007 | Unregistered CommenterSteve Widergren

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