Laminar Control and Transactive Energy

Laminar control is drawing a lot of attention from utilities today, and it may just clear the way be the basis for distributed transactive energy (TE).

The problem of smart grids boils down to adapting to intermittent power sources while reducing the operating margin. In power distribution, the operating margin is the amount of “extra” power available at any time. It is the operating margin that protects power delivery from unanticipated power consumption. This causes a volatility of power supply even while it reduces the ability of the traditional grid to adapt to consumers.

The intermittent power sources are distributed, meaning that they cannot supply any consumer not within the local distribution line unless that power travels between lines. For some users, these power sources will be local, and using them locally may not require permission from the grid. Some smart microgrids will not even be attached to the larger grid, so the model cannot rely on central control.

The power utilities have made heroic efforts to try to build a central control system that can manage this growing complexity and volatility with less margin for error. They still have little ability to provide an optimum solution to the knowledge problem of diverse technologies serving diverse purposes to support diverse activities. We are now seeing the beginning of a top-down re-architecting of the grid. 

Laminar Control manes an approach that layers the operation of power distribution. A lamina names a discrete adjacent layer, a term usually used for tissues in biology or for layers in rocks across a geological area. Laminar Control delegates decision-making to the Laminar Control Nodes within each lamina. Upper layers provide guidance based on strategic surveillance and offer situation awareness. Laminar Control nodes respond as best they can and provide telemetry up. Each node may itself have lamina underneath, with its own control nodes. At the lowest level, decision-making may use mechanisms such as traditional demand response (DR). This model pushes decision-making pushed down to the lowest layer, also referred to as the Edge. The Edge is where the local situation can be more clearly perceived and rapidly acted on. Even if there are disruptions in communications or power supplies from above, the elements at the edge can continue in semi-autonomy to complete the mission at hand.

Bottom-up re-architecting of the grid is getting to the same place. A FSGIM-aware facility is a facility ready to act as a Laminar Control Node. A FSGIM-aware node is also ready to negotiate with its peer nodes even in the absence of the higher lamina. A vehicle, then, acts as a mobile control node. Whether it is a peer node to the building systems, or it is a member of a lamina below the building or facility is an implementation decision.

Some early adopters of this edge-based decision-making are those interested in cybersecurity for their systems. For some, it is not enough to hide the internal mechanisms of their power generation and power management, but they want power cloaking as well. They have no interest in sharing any information of the internal workings of their FSGIM-aware facilities. They view the inside of a facility as a discrete security realm. The growing expectations are that a microgrid should cloak power signatures as well as controls. Clearly this model is not accepting of third party monitoring, let alone third party control.

Circling back to the electric vehicle, as a simple cartoon of these issues…

As a mobile control node it needs to understand, about itself, in information model conformant with FSGIM, or the CTS at least. As the EV drives around, it parks within different microgrids, which may opt to not share any information about this control node with the others. We can also imagine a charging station connected directly to the substation, allowing the car to act as a peer control node to the distribution microgrids.

Throughout, this car should be a car as any other. The V2B interactions and the V2G interactions should be the same. In either case, it should be laminar control node, acting autonomously with other nodes, to achieve directives from the lamina above….

The purpose of the Facility Smart Grid Information Model (FSGIM) (ASHRAE/NEMA/ANSI 201) is to prepare building-based systems to talk to the grid. Traditionally, such systems ignored power supply and demand, and simply assume it was there for them. It does not dictate what such a system does with that information. If could be merely to share its upcoming plans with its supplier, or it could negotiate changes to those plans.

The important part is the power *effects* of the activity, and not the details of the activity. There is far too much diversity in building systems and the business activities they support to expose direct control. One of the Regulated Environment facilities that Jim Butler’s company is known for could incur huge losses in dollars, and possible large health and safety risks by simply accepting a HVAC “nudge” from a far-away system operator.

This is exactly the information that an electric vehicle should have about itself. It should internally know those things that FSGIM describes, and use that information to share its upcoming plans with its supplier, or it could negotiate changes to those plans. That negotiation is properly with the facility it is plugged into, and we should not assume that is “the grid.” A car may be in an urban parking lot during the day a home at night, and at charging in an off-grid wilderness retreat on the weekend.

Architectural Principals of Transactive Energy

This post is part of the continuing Paths to Transactive Energy series. You can find them all listed by clicking on the matching metatag at the bottom of each post.

Transactive energy describes a pattern of integration where parties exchange the value or a commodity resource [power] over time and make forward commitments to sell or purchase that commodity. The Common Transactive Services (CTS) can be used in central auction-type systems, where a single entity announces or broadcasts prices or in markets were two or more parties come to a mutual agreement on price and delivery.

All forward transactions are committed, that is one party commits to delivering the service or commodity, one commits to buying it. If a provider wishes not to deliver, or if a purchaser wishes not to take delivery, they can participate in a separate negotiation, with a separate price, that can be netted against the original committed transaction. Such a buy-back resembles today’s Demand Response.

If one purchaser wishes to acquire more power at the last minute, and one wishes to acquire less, they can negotiate an exchange on the spot market. Different market structures and market rules will change the format, but not the substance of this transaction.

The CTS are essentially identical for any commodity resource or service. CTS works for transmission rights and ancillary services, as well as for other resource markets such as transactive water or transactive thermal markets. In each case, the product is delivery of the commodity at the designated time at the designated rate.

The CTS can work in many market structures. CTS can be used with a single (for the microgrid / micromarket) brokered trading floor or with peer-to-peer transactions. Compound transactions can link multiple simple transactions, such as paired transmission and delivery. Different circumstances will work best with different market structures, but in all cases, the communications can use the CTS.

1. Each party represents a node that acts in its own interests to support its own purposes.
2. The internal mechanisms and systems of a node are not communicated as part of the CTS.
3. The system of systems that make up a node may choose to organize some or part of their internal operations using transactive energy / transactive agents.
4. Actors inside a node interact with the internal market, not the external; there is no direct market interaction with things / markets / prices external to the node.
5. The purpose of an transactive node is to support the purposes of its owners and occupants, and not to support the things outside the node.
6. Economic signals or availability from outside the node might influence the market, if any, inside the node, but only as the market interface on the node relays that information. This may include markups, smoothing, discounts or any other means or mechanism that the owner of the node chooses to use (or that the maker of the system that operates the node chooses to use so that the owner of the node box will choose that system).
7. Parties external to the node should not use the possible existence of an economic entity inside the box as an excuse to penetrate the veil of the black box.

The Human Side of Energy Micromarkets

This post is part of the continuing Paths to Transactive Energy series. You can find them all listed by clicking on the matching metatag at the bottom of each post.

The Human Beings must have a say, or any model for transactive energy is doomed to failure. No model based on satisfying The Computers or The Grid will acheive prominence in the market. If optional, people will opt out. If mandatory, people will work around. The market is not a model for decision making, it is a pattern for interactions. In the abstract, semiotics does not determine meaning, only how meaning is conveyed. The interaction patterns do not determine the value of energy used at a particular place and time, they only determine how it is negotiated and conveyed.

Decision making must be local, driven by internal needs. Those decisions take place in the context of a larger market, but the larger market is not determinative of particular actions. People, whether at home or at work, will participate to the extent that it enhances their own satisfaction in some way, and transactive energy is, and must be, thoroughly agnostic about which layer of the Maslovian cake is driving decisions.

The occupants of the house, or of the business facility, determine the values of those systems that they use and how they negotiate. No one outside the house can know whether that spare refrigerator is deep storage or beer refrigerator, and if this weekend’s party makes the beer refrigerator and the ice-maker priority uses. (Note that I am not discussing the human interface that might make it useful or desirable to interact with the priorities of these systems—because these interfaces are outside the scope of transactive energy).

One system keeps things cool, within a range determined by biological safety or by personal preference, with limited flexibility over time of operation. One manages ice production, a pre-consumer that wants to acquire when power is cheap. Those two agents may have the same locus of interaction, let’s call it an IP address. They may be expressions of a single control system, of no open standard. They may not choose to share any temperature information with the EMS/BMS. The EMS/BMS does not care what protocols are used inside the refrigerator. In a similar way, a BACnet network with 5 AHUs may choose to represent itself as any number of agents (likely 1-5, but ventilation may come to market as a separate service than cooling) but not as a collection of BACnet points.

Transactive integration is the way to solve the problem of diversity of systems in the home. Developers of small microgrids aim to waste no energy, but struggle to develop drivers for every system. Energy device drivers for every CPAP? Every stereo system and television? Plate warming drawers? Expresso machines? In my home, the biggest energy user might be my well. The diversity of home systems is daunting. Each of them is valued for the service it provides, but each can have an economic profile, a meta-model, a prototypical pattern for its energy use.

This simplicity and abstraction is a benefit for the maker of the system or device as well as of the EMS/BMS. The owner can look at a device profile in a store or on-line and can say “yes, that is the way this device uses/stores/generates energy”. We can imagine heuristics, such as “you need some more pre-consumption devices to smooth your load.” The economic actor profiles become a way to discuss the systems as well as how they will interact when sharing resources.

Profiles for the Economic Actors in Distributed Energy

This post is part of the continuing Paths to Transactive Energy series. You can find them all listed by clicking on the matching metatag at the bottom of each post.

As this series continues its survey of Transactive Energy, we get, at last to what I see are the essential agent personalities. The Agent Personalities are a mid-level abstraction that makes it easier for the appliance supplier and the EMS/BMS maker to know what is being attached. Every appliance at the local store could be a pluripotent transactive agent, but this does not aid the brain-developer in understanding what you just bought. A wine cellar may not be on the list of known appliances, but it is useful to know that it is similar to the refrigerator and to an air conditioner in how it approaches the in-home energy market.

http://www.theenergymashuplab.org/blog/8agents 

These agent types interact based on the principals of transactive energy. The non-power services provided and mechanisms used by each system are not known to the energy market. The precise mechanism of each system is not known to the market. Each system uses the market to achieve its own goals.

The creator of a system can identify which economic best suits the system. Some systems may be most easily represented by aggregate roles, wherein each role remain simple.

For example, an air conditioning system and a refrigerator may each act as intermittent consumers. When in the same market, each system can optimize its own costs by buying when the other does not. The air conditioner produces an equilibrium of comfort, the refrigerator produces an equilibrium of the conditions to store food safely, and the market achieves a punctuated equilibrium of power use with lower peaks. An ice maker may act as a pre-consumer, buying power when it is cheap to have a supply of ice at the target time. A pre-consumer buys when others do not, so long as its delivery time and product (ice) can be met. These two agent types may coexist in a single interface just as the two roles coexist in the same refrigerator.

These agent profiles indicate patterns for market interaction. But the market doesn’t care what kind of agent you are. User interfaces, which is to say human interfaces, that want to augment information beyond market summaries, will need to look for another means to discover that information.

The ASHRAE Facility Smart Grid Info Model (FSGIM) allows for communication of expected forward load curves, I think. A controller needs to know more than a partner’s present state. The partners trading position is Inflexible until when? Shiftable until when, then available for how long? How adjustable (shed levels)? Etc. These are all things that higher-level controllers need to get from lower-level controllers. A higher level controller could pass DR-related signals to lower level controllers: it may choose to alter them for its own purposes.