Transactive Energy in Deep and Shallow Markets

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.

One of the most contentious areas of the CTS is how much information market participants and market makers should have about one another. The premises pit functionality vs. scalability, echo the arguments of stateless vs stateful communications, and have ramifications for personal fulfillment and personal privacy.

In any truly transactive market, all transactions are committed. Agents that buy too much power, or power at the wrong time must find separate partners to buy or sell the difference. If your agent purchases for normal power consumption for the week you are on vacation, you pay for the power whether you use it or not. Alternately, a solar producer who commits to power sales on a rainy day must buy power on the spot market to make good on his contracts. The Star Wars character Yoda could have been describing transactive energy when he famously said “Do or Do not; there is no try.’

The minimal market information side is epitomized by TEMIX (Transactive Energy Market Information Exchange). TEMIX uses the most restrictive profile of the CTS. EMIX Agents share no information about capabilities or effects or purposes. Much as a web server can services thousands of clients because it maintains no state information, a TEMIX market can scale to high speed and high volume because of the simplicity of interaction. An idealized TEMIX market is based on peer-to-peer trading.

Many of the most fluid financial markets rely on market makers. A Market Maker may use its own portfolio to complete transactions, or assemble several purchases to enable one sale. Market Makers can maintain knowledge of market participants beyond the capabilities of a single participant. In a deep market, the most significant knowledge is where to find counterparties. Some device capabilities offer services to the Market Maker that are unique to transactive resource markets. These are touched on below.

The purpose of an end node in a transactive resource market is to support the owner or inhabitant of that end node. A commercial facility participates in resource markets to better support the business that is based in that facility. A house participates in a resource market to support the needs and interests of the homeowner. These purposes are private, as are the operation of the systems within the end node.

The systems within an end node can themselves be organized using the CTS, creating a microgrid operated by a micromarket. This market is inherently shallow. There is a limited pool of counterparties at each moment. In a trivial but concrete example, who can sell power to the smart toaster when the occupant pushes down the lever?  If a generator must be idle for twenty minutes before being tuned on again, how will the home plan? The specification that defines the CTS also describes how to communicate capabilities, or resource descriptions, using the same semantics as the CTS.

There is no universally correct answer for whether to use resource descriptions or not. Resource descriptions were developed on the models used for bidding into North American bulk power markets. The systems that run these markets are at the limit of their capabilities to handle complexity. They rely on day-ahead markets to allow pre-planning. They will not support a dynamic market with widespread deployment of distributed energy suppliers and purchasers. The deeper the market grows, the more the exchange of resource capabilities are a hindrance to dynamic balance.

A better case can be made for resource descriptions in a shallow market, that of the home and neighborhood, of the commercial building and the office park. For the near future, many systems participating in these microgrids will not natively understand transactive energy. Many systems will still be managed by direct control. Resource capabilities may enable better coordination of a limited number of market participants, i.e. systems that can buy or sell power moment to moment.

The benefits of the simpler “TEMIX” model predominate quickly as systems scale. If there are enough participants in the market, the wisdom of markets produces better results than any central planning. In an unpublished paper, Frank Wolak and Akshaya Jha show that even pure financial participants in day-ahead markets improve overall system efficiency and reduce energy costs by improving forecast quality. Financial participants do not fit into the resource description model, but can integrate seamlessly into the abstract TEMIX model.

Local Markets and the Common Transactive Services

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 Common Transactive Services (CTS) simplify integration of a facility into the grid, managing the interactions between facilities and the larger market. CTS can work within a Facility, using the market to smooth and shape the external load curve. This potentially reduces the integration costs of bringing new equipment and technology into a facility that is participating in larger markets.

In proposed regulation on Distributed Energy Resource Aggregates (DERA), directs each state to promulgate rules to allow DERAs full participation in power markets. But what does this mean? One came easily manage the market within the distribution loop, driven by the LMP, and residing under a single injection point from Transmission to Distribution, but what does this mean? We are all waiting for the regulators in each state to tell us.

The Common Transactive Services were defined in the OASIS Energy Interoperation Technical Committee.

There are numerous groups studying the internal market design for agent-based markets, including market rules, and anti-gaming, and … The CTS messages include the means to advertise parameterized market rules for machine understanding. The rule set was defined so as to be extensible. New rules and new rule types is the portion of the CTS most likely to see change.

Fractal Energy: Galvin Perfect Power Updated

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.

One of the most influential insights into smart energy was defined by Robert Galvin in his vision for Perfect Power. Perfect Power turned the vision for the grid upside down, with each facility and each home responsible for its own power, acting as microgrids. These building-based microgrids would interact with their nearby peers, to gain resilience in operation and quality of supply across a neighborhood. Groups of neighborhoods would then interact at a larger scale. The Galvin Project promulgated the vision of Perfect Power, reliable, efficient, without single points of failure—and eventually the best way to incorporate distributed energy resources (DER) into the power supply.

The Galvin Perfect Power Model was abstracted into fractal microgrids, and demonstrated in the Camp Pendleton Fractal Microgrid Project. Fractal patterns are self-referential and self-similar.

A fractal system is one in which each part of has the same statistical character as the whole. Fractals are useful in modeling structures in which similar patterns recur at progressively smaller scales, and in describing partly random or chaotic phenomena such as crystal growth, fluid turbulence, and galaxy formation. In biological systems, simple genetic rules can create complex systems through re-application of simple genetic processes. There are no inherent limits to scaling fractal patterns up or scaling them down.

Transactive microgrids abstract complex components into self-similar systems that interact through common patterns of economic competition for resources. Whether the smallest system or the largest aggregate of systems that consumes, generates, or stores power, common interaction patterns define how each interacts with its peers.

Within each system of systems, these interaction patterns support efficient allocation and coordination of energy use within and among the smallest systems to create larger system or microgrid. These microgrids act as components that allocate and coordinate of energy use within and among their peers to operate still more complex systems. At each level, complexity and diversity, diversity of technology, of purpose, and of mission, is contained locally and managed locally.

Fractal system integration is inherently resilient. Systems command and control is managed locally, and only the information necessary to exchange services is shared. New systems can be integrated as components without increasing overall complexity. Larger systems can respond to degraded or damaged components by creating new spontaneous order.

Each node interacts with its peer nodes only in terms of the services, buying and supplying energy, consuming or curtailing use, and not in terms of process. Inside the box, which might be the BAS, is an algorithm or many that is outside the scope of the service interactions.

More than a decade ago, there was discussion on the smart toaster, the theoretical minimal system that could interact with the smart grid. Prices to devices was often discussed. The notion is that the grid does not need or want to understand a toaster, but only the toaster’s use or non-use of energy over a load curve. Transactive Energy, expressed as what we now call the common transactive services, defines the interaction patterns between systems that buy and sell power over time.

In this model, each integration, each customer gets to decide when transactive services stops and more traditional integration begins. So long as a system can participate in the containing grid with the common transactive services, the contents of the system are a black box; internal technology and algorithm are out of scope.

The Common Transactive Services (CTS) simplify define the interactions between and system and the microgrid it is participating in. CTS handles resources other than power, such as transport costs, congestion management, and ancillary services. Only the scale facto changes as we move up and down the fractal.

Independence of Services provided by Transactive Energy Nodes

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.

Grid operators cannot know the purpose of each system attached to the grid. On a college campus, very similar sets of components: fans, ducts, temperature sensors, could provide environmental conditioning for a classroom whose windows can be opened, for office space, or for document archive which requires constant temperature and humidity.  The most important attribute of animal quarters might be constant high-volume ventilation, while for a biohazard lab it might be maintaining a negative air pressure in the room. Humidity and temperature changes might make a basketball court slippery, and environmental management is focused on making sure that the All-American is not injured before the NCAA tournament.

Direct control for demand response requires that all parties know these issues and agree on their import. A central operator cannot know this.

If we look at pure DER, we will see more hybrid systems in the future. Solar will be paired with power storage. Power storage will be hybrid systems blending fast response and slow draw technologies. The best chemical battery systems are starting to come with internal intelligence to extend battery life. Power flows are optimized over time to manage dendrite growth, or to recondition one cell among many. Unless the grid operator understands the intelligence imbued within the storage system, then they can damage expensive assets by interrupting these processes in mid cycle.

Some of the earliest DR was based on refrigeration management. The purpose of such a system may be for food safety during shipping and storage. Such a system may be able to time shift chilling, or even skip a cycle without harm. After repeated shifts within a short period, the next cooling cycle becomes more critical to maintain biological safety of food, or the integrity if a chemical or pharmaceutical manufacturing process. As we look to more complex systems in the future, this tension between local purpose and remote direct control strengthens.

As we scale down, we might get to the refrigerator in the home. The ice-maker is a pre-consumption agent, which could time-shift ice production to the cheapest prices on the power market internal to the facility. On the other hand, as we get closer to the planned weekend party, the goal of a full ice bin may become more important…

Many early adopters of behind-the-meter power storage are concerned first about reliability. Their facilities may be able to perform a mix of pre-consumption, DR cycle skipping, internal generation, and battery storage management. By intelligent internal management, such a facility may be able to act as a DERA—but be completely unwilling to turn over direct monitoring and control.

Power use in a facility should always be driven by the local or personal needs