Lessening the Integration Barrier to Smart Energy

We do not have a problem of knowing what to do to make buildings participants in smart energy. We do not have a problem that the technology is too expensive. We do have a problem that it takes too long to integrate systems. High integration costs lead to vendor lock-in. High integration costs lead to long sales cycles for replacements and upgrades. High integration costs will continue to slow the adoption of distributed energy resources. High integration costs lead to islands of automation, unable to participate in smart energy and demand response.

In design and in construction, today’s best practice is to use a BIM (Building Information Model) to deliver better buildings on-time and under budget. BIM trades higher design costs for much lower construction costs and reduced risk. We use BIM to generate energy models, essential to green certifications for buildings. Until recently, BIM hasn’t had much to do with the operations of a building, or with systems inside a building. This month, I am writing about how this is starting to change.

In traditional CAD, we have used libraries of templates supplied by product vendors for years. Suppliers of plumbing and lighting equipment have wanted it to be easy to design with their products, and they have wanted their products to look good in design renderings. Specifiers Property information exchange (SPie) is a project that encourages this approach applied to the more detailed requirements of BIM. SPie objects are cross-referenced with Omniclass and can include hookup and connection information. The National Electrical Manufacturing Association (NEMA) and is one of the associations participating. SPie brings the things we install in buildings into BIM.

Two technologies dominate the generation of building energy models. GBXML has wide support not only in energy modeling, but also in the design of HVAC and control systems. Information built on GBXML has had no path pack into BIM. EnergyPlus is purported to generate more accurate energy models, and has a well-defined model view for re-entry into BIM. ENERGie, (the ie is again for information exchange) is an effort to merge the two to provide a single model coordinating system design with building design and supporting full system detail. It is likely that ENERGie will soon be required for General Service Administration (GSA) and Department of Defense (DOD ) work. GSA and DOD are the two biggest landlords in North America, so their wants can drive the industry.

In information technology, we again and again see the technology we develop for the most advanced systems flowing down through normal business and all the way to the consumer. ISO 15926 is an information framework developed to express the relations between systems and components in the largest chemical processing plants. Today, ISO 15926 being adapted for a variety of tasks, from the esoteric mapping between ontologies to the automated mapping between form and function to operate smaller systems. ELie is a project to hand over the Equipment Layout in buildings to the owner by mapping from BIM to ISO 15926. ELie connects a static design to a runnable model.

Management of live electrical load in buildings is the largest challenge in smart energy. Plug load is almost unknowable in any automatic way. It will be some time before smart energy-communicating systems will outnumber legacy dumb-load equipment. Smart electrical panels that expose energy use per circuit have not found wide use; they follow no standards, and it is unclear what space they support. PLie standardizes the description of Panel Layout and brings it into the BIM of electrical wiring. PLie can provide automate the mapping of building wiring into the spaces and equipment it supports.

The EIS Alliance is developing models to support autonomous load management and shaping in buildings. One of their concepts is that the buildings electrical meter should be an information appliance for the building EMS. New building equipment and appliances could support the same interface to report their own energy use. Web services (WS) aware electrical panels could use the same interface to standardize their load reporting. Combining this interface and PLie brings the buildings dumb load under management with minimal integration.

Everything above is talking about plans and designs. New systems present ongoing integration costs. WS-DD and WS-DP are new standards to enable the automatic discovery of systems. These standards enhance the value of the energy information appliances by describing what each meter is tracking.

This laundry list of energy-related specifications are the answer to high integration costs and provide a path to sustained re-integration of systems. The flow of information through Model Views into smart energy is the key to continued understanding of building performance. These specifications will move the markets in energy management systems into improved interfaces, for users, for enterprises, and for energy marketeers.

Microgrids Big and Small

Last summer, we used the call “Every end node is a microgrid” to focus smart energy standards activities. Like the regional grids, a microgrid is responsible for running its own operations, and for supporting its own needs. Like the regional grids, a microgrid uses market operations to acquire what it cannot make itself, and what it can buy more economically than it can make itself. Like the regional grids, a microgrid can contain microgrids that are responsible for their own operations.

Last week, a board member of NAESB asked me to define microgrids. I was invited to speak to NAESB to explain what interest natural gas suppliers might have in smart grid standards. I was surprised that an idea so central to national smart grid efforts needed to be described to one of the most significant energy market and business practices groups. There is so much going on so fast right now, and the pressures to accelerate are so strong, that some of us get used to ideas before we ever have to explain them.

The list of end nodes that might be microgrids starts with homes, commercial buildings, and industrial sites. Within an end node, different subsystems can interact much as they do within the larger grid. Building systems could bid for access to site-based power. Microgrid events can trigger demand response (DR) behaviors from the building systems or building zones. Microgrids can contain and be contained by other microgrids.

Buildings and sites can be participants in local area microgrids. Campuses, and military bases present existing business models for microgrids. Rather than as integrated control systems, these contained building microgrids grids can participate collection of autonomous entities. Each building / microgrid could then bid for and obtain energy supply and reliability from larger microgrid.

The models propagated by the District Energy Association can inform microgrid thinking. The defining characteristic of District Energy is cogeneration, in which a single plant may make electricity, steam, and hot water. Because steam can be used to power cooling, cogeneration systems often produce chilled water was well. Each of these products can find a market within the microgrid. The district energy plant then becomes the market maker, shifting modes of energy delivery to match the bids from the autonomous buildings it contains.

Microgrids can opt to be more intimate, and to communicate more frequently than does the larger grid today. Buildings may choose to negotiate available load shapes, sharing planned energy use and backing-off of planned energy-using processes to maintain overall market conditions within the local microgrid. Microgrids can maintain their own cybersecurity regimes, tighter or looser than those in the wider grid as befits their needs.

These local area microgrids will require regulatory reform to flourish. Industrial parks must avoid these business models today lest they become regulated as a public utility. Commodity home builders are exploring providing turnkey district energy and management, turned over to the turnkey homeowner’s association (HOA) they provide today. When combined with the new package solar thermal systems, shipped in a single container, and installed on-site, neighborhood microgrids may be the future of distributed energy.

Today, in many states, an energy supplier becomes a regulated utility when the energy delivery crosses a public road. In new neighborhoods, the homebuilder finishes a neighborhood and turns the rods over to the city. Green builders are already considering turning title for the roads over to the HOA instead, to avoid such regulation. Future regulatory changes could open up existing neighborhoods to this kind of energy management.

Microgrids can extend down as well. Each tenant in a commercial building could operate its own microgrid, existing within the environment of the buildings microgrid. One could argue that green leases are beginning to move in this direction. I find it fascinating to think of intra-building market opportunities. Can we use intra-building markets to re-use what is today waste energy? Does the data center in the basement defray costs by selling its waste heat to the other tenants? Would some tenants pay a premium for site-generated energy? By hiding the complexity of interoperation behind an economic veneer, can we improve performance and reduce integration costs?

Microgrids, whether virtual or real, are an important organizing concept of smart energy.

Risky Business – Removing barriers to Free Energy

It is no secret to readers that I think we can best balance energy supply and demand using pure economic transactions. Whatever you feel about flash trading, those markets with millions of 14 millisecond transactions prove that we know how to run markets fast enough to manage even the most demanding decision making on smart grids. Free energy, that is energy markets unencumbered price and reliability arbitrage, is certainly the fastest path to the technologies we need to balance supply with the increasingly volatile supple we foresee. But today’s utilities serve a social justice purpose that I have been unable to reconcile in my mind with free energy until now.

We need free energy because we need to unbundle two of the most significant services provided alongside today’s energy delivery; availability risk arbitrage and price risk arbitrage. These services create a moral hazard we can no longer afford. Availability risk arbitrage removes performance incentives for end nodes to install systems for energy storage and generation. Price risk arbitrage reserves all economic incentives for energy storage and generation to the grid, where it is too expensive and innovation adoption is, of necessity, to slow to support the type of venture creation we have seen in high tech.

The basic problem is that our electric grid operates with lower margins for error than it ever has before, and current policy is to reduce them further. No community is clamoring for more power lines in its back yard even as our houses are filled with ever more energy consuming equipment for computing, telecommunications, and entertainment. It is becoming too expensive, in generation costs, infrastructure capacity, and social will to maintain constant oversupply of traditional energy. We wish to use new energy sources that are unpredictable and episodic. Attempts to smooth out supply volatility at the grid re too expensive or too few. (Ask me some time why natural gas sales went up when gas generation was replaced by wind in Colorado.) The ability of the grid to supply availability arbitrage is failing.

With fixed prices, the economic incentives for end nodes to participate in energy generation and storage are non-existent. The most basic market rule is buy low and sell high. Without dynamic pricing, the rule for homes and commercial buildings is sell low (wholesale) and buy high (retail). Efforts by local regulators to repeal that rule are as artificial as efforts to repeal gravity.

Dynamic pricing changes all that. With the volatility of energy supply fully exposed, end nodes will buy technologies to manage their risk. With the volatility of energy prices fully exposed, end nodes will find the business case to manage their power purchases. Bottlenecks in the power grid will result in local congestion pricing, letting the true costs neighborhood infrastructure decisions to be seen by the public.

Utilities today must play not to lose rather than to win. They cannot adapt new technologies quickly because they must always be reliable. Market actors that cannot accept risk, cannot afford to innovate. End nodes can voluntarily accept risk, and so can afford to adopt new technology. If Denver, where we met this month to form the Smart Grid Interoperability Panel (SGIP), is plunged into darkness for a week, it is a dire outcome; if my home fails for a week, is provides entertainment to my neighbors. The difference between grid-level innovation and end-node innovation is the difference between tragedy and comedy.

Smart grids will transfer risk to their end nodes. Economic agents which assume risk will expect to be paid for it. These payments will be the fertilizer for an untold number of new technologies. The best way to transfer risk and payments together is self-balancing, self organizing free markets in energy. Systems that can participate in these markets for us as well as systems that can store or generate energy on-site, will be the reward.

Energy Collisions and Autonomous Appliances

Appliance manufacturers are moving beyond energy pain points to energy collisions. Utility-based energy standards are stuck on energy pain. Energy collisions can offer much more benefits to smart grids than can pain points; they can offer still more to the off-grid or near grid building. Collisions are part of a wide variety of autonomous energy behaviors we will see in the near future—if only the energy suppliers will stop blocking them.

Too many energy suppliers are stuck on models of direct control. When they accept using prices, they want to use them to create direct control. (There is a name for this in Economics—drop me a line or comment if you know what it is…). To use a cartoon version of this approach, if I knew that when the yellow light comes on, I will be charged $1000 / minute to run the air conditioning, that yellow light is as good as an on / off switch. This mechanistic approach, seeking only for the right price that will achieve direct control, will not get any better results than the direct control of the 1980’s

The appliance manufacturers have a more engaging vision, in which they can compete as to how well they engage the consumer in better energy decisions. Most appliances can run in high and in low energy modes. The low energy mode may use half the energy but take three times as long. If time is money, this approach asks the question, “But how much?” Do you want that shirt clean and ready in 30 minutes [high energy mode]? Is it OK if it takes 90 minutes [low energy mode]? Is it OK to wait for 10 minutes until the energy price drops? How about 45 minutes? How about seven hours to get the overnight energy prices—or the wind-sourced energy?

The appliance manufacturers know how to do this already. They are starved for information. They want not only information about the price now, but predictions about price in the future. They want to compete on how well they can communicate energy decisions to the consumer.

This model of autonomous response can reach past the relatively low energy appliances. The intelligent thermostat may want to cool more now to in anticipation of higher prices later. The Plug-In Electric Vehicle (PEV) must support the household schedule while deciding when to charge.

There is renewed focus within the autonomous appliance community on energy profiles to support this model. Energy profiles as defined by Open Smart Grid efforts or by ZigBee have a simple model of energy use, low energy mode, turn off mode and ramp time. Building systems and appliances have a more complex mode. That washing machine may use no energy while filling, and then plenty while agitating the clothes. If an appliance understands its own energy profile, it may start filling its tank five minutes before the price drops—and time its final spin to complete before energy prices step up.

And then they began talking about systems working together to avoid energy spikes…

One of the foundational approaches in networking is collision sensing and detection (CSMA/CD) on a shared bus. Nodes on a network can transmit message whenever they want. Each is responsible for detecting when another node is transmitting at the same time, called a collision. When a collision is detected, each node waits a random period of time and then re-transmits. You may recognize this pattern as what humans do in conversation.

Today’s appliance manufacturers are talking about comparing energy profiles avoid the spin cycle and the refrigerator’s compressor cycle from running at the same time. With almost no degradation of performance, these autonomous systems can begin to shape the overall load profile of a building—or of the green neighborhood.

This approach can provide a smoother, more predictable load to the utilities. When combined with price responsiveness. It could produce a very predictable market. It really becomes interesting, however, when it applies to off grid buildings, and something that I call near-grid buildings.

If a building is running on site-generated energy, it has very distinct energy budget. That budget is not merely aggregate energy over 15 minutes, but hard, clear limits on maximum energy use at any moment. That upper limit may be continuously varying as, say, the speed of the wind changes. Continuous autonomous load shaping, based upon detailed energy profiles, may be critical to a distributed energy future.

To get there, we must get beyond price as a proxy for direct control. To paraphrase General Honore, don’t get stuck on pain.