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

Small Transactions and Smart Energy

The problem of smart energy is distributed intermittent generation laid across unmanageable power use and a fixed distribution grid. Central operators will never be able to keep pace with controlling new technologies that generate, store, and use power. Privacy demands that central operators not track and predict every activity in our homes and buildings. In economic terms, this is a knowledge problem

Markets are a proven means to balance supply and demand without central control. In 1992, Huberman & Clearwater demonstrated that a market in data center cooling better optimized allocation and reduced energy use than the best control strategies. The technique they used in data center at XEROX PARC was to add an agent to each server and have each agent bid for cooling.

The best place to manage the changing technology mix for power and changing demands on systems is locally, in a microgrid. Within a microgrid, each system can bid to buy or sell power over time, aligning demand with supply, smoothing load, and managing storage—each microgrid can be operated by a micromarket. Each system and application can be represented by a market agent. Each market agent represents the needs of its system and the preferences of tis owner. Smart energy is an emergent behavior of the IoT market.

Every microgrid can participate as a node in a containing grid. Each microgrid shares only its aggregate market position with the containing grid. Microgrids gain resilience through buying and selling power to and from their peers. This model is fractal, as the term microgrid can refer to the city, the neighborhood, the street, the building, or even to systems within a building.

Microgrid markets are markets based on time of delivery. Power is a resource whose value is determined by time of delivery. The information models for resource markets are already defined in OASIS. WS-Calendar defines a semantic model for M2M schedule negotiation services. EMIX (Energy Market Information Exchange) defines semantics for describing time-based products. (Energy Interoperation) defines eight services, each with just a few methods—the building blocks to construct markets in transactive energy.

Building markets is not enough without a means to create identities, to register contracts, and to settle transactions. The largest power markets, dealing with long-running purchases of centrally managed power, use traditional banking. Several projects are using expensive centrally authorized blockchain methods to operate microgrid-to-microgrid exchanges (see Brooklyn Microgrid Project, or the company Grid Singularity)

But to actually operate a microgrid, to balance power in real time, requires thousands of small transactions. To operate off-grid, or after grid failure, requires cryptocurrency that does not rely on permission from a server in the cloud. It must be local, and permissionless, and free. At the edges, transactive energy requires technology like the tangle-based IoTa. Individual transactions will be for a half cent or less. Systems must be able to establish identity and record contracts.

The Energy Mashup Lab is an open source project to create the software infrastructure for smart energy. The first step is to complete definition of the Common Transactive Services of smart energy. We are updating reference implementations of software to wrap a physical system and abstract its operation into power services. System developers will then be able to choose from the transactive agent personalities to match how their system acquires or disposes of power. All software will be available for download under an Apache 2.0 License.

Working, interoperable sets of code will be periodically donated to the various IoT framework consortia. For example, the AllSeen Alliance will want to modify code to support its own message formats and security profiles. Specific implementations will include ledger integration, i.e., IoTa or other cryptocurrency. Eventually, working profiles will move to microcode, and from microcode to ASICs. A system or application that supports a given framework and ledger will be able to discover the local micromarket, and self-integrate into the local microgrid.

Just-In-Time Infrastructure and Watergy

The future of infrastructure is just-in time. Just-in-time delivery of structures, ready to support people and business, customizable to the site, long lasting, ready for smart energy and water. Just in time delivery of distributed energy, ready to support structures, the people who live and work in them, and the services they need, and ready for smart grids. Just in time delivery of pure water, ready to support people and agriculture, able to work alongside smart power and smart grids.

Consider a simple building with only a refrigerator, air conditioning, a solar panel (PV) and a power storage system (battery). Each is represented by an autonomous market agent.

The refrigerator and the air conditioner are similar: each runs episodically to support some private purpose, prefers to run an entire cycle or not at all, can shift any cycle forward or back in time while still providing its service. To coexist within the power supplied by the PV, they must not run at the same time lest they exceed the power available. Each determines when it cycles by submitting time-based tenders, finding the minimum price, i.e., buying power when the other is not.

The PV is represented by an agent acting as a seller, able to make commitments based on its internal predictions of weather. When it is unable to meet commitments, say when a cloud passes over, it must go to the more expensive aftermarket, and buy power from the battery.

The battery is represented by a merchant actor, buying power low and selling high. In another model, it could operate as the “market specialist”, brokering market transactions and improving market liquidity through trading on its own account.

As we add more systems to the building, each represented in the internal power market by an agent, we do not need to add complexity to the control systems; we merely add participants to the market. The knowledge problem of specific system operations and controls is simplified through abstraction to the common transactions. If the building is able to connect to a grid of some kind, it does not expose its inner workings; the building exposes only the aggregate market position of the interior market.

In this model buildings may trade with each other using the same market services and interactions unused to manage the internal supply and demand. A community energy resource such as an independent wind generator or larger power storage system acts as a peer node within the neighborhood. A non-building entity such as a wastewater pumping station may participate in the local building-to-building (B2B) market.

In a similar way, the local B2B market can participate in a larger neighborhood market. Where transactions between particular market participants are limited by transmission capabilities, a parallel transport or congestion market can be introduced.

Inside any building, any system can potentially operate an internal market. For example, a multi-story building may choose to have its multiple air conditioning (HVAC) zones operating as their own market, with only the aggregate HVAC market participating in the building market. The underpinning for in-building markets in power are described in detail in the recently published ANSI/ASHRAE/NEMA Standard 201-2016, the Facility Smart Grid Information Model.

This pattern of integration is sometimes referred to as fractal microgrids. With transactive integration, the market negotiations and transactions are identical at each level, and the underlying complexity of each market participant is hidden. Inside a building with a single owner, the complexity of block-chain as a transaction monitor may be unnecessary. At the largest scale, in the bulk power markets, transactions may require traditional financial instruments. In-between, where the transactions many and small, where resources are flowing between systems with different owners, and where local settlement may be desired to achieve resilience goals, blockchain is of most use. Within any microgrid, systems may use blockchain to create and manage identity, to record contracts, and to settle transactions.

Blockchain is in essence a means to create a distributed database, with information shared between participants, so no one participant can change the information. Blockchain is in growing use from early power trading in the Brooklyn Microgrids project, to world-wide logistics management. Some codebases such as Open Ledger, look to bankable blockchain, wherein the net of transactions can easily flow into the world banking system. Others, such as IOTA, aim at lightweight models that are cost-effective for transactions a tenth of a cent and smaller, and that can run on very small chipsets.

New initiatives are extending the principles of transactive energy to water distribution. These models make sense today where there are tight restrictions on aquifer pumping shared between farms. Since water must be pumped, and pumped water can generate electricity, markets in transactive power and transactive water can work together. This scenario is particularly interesting in communities that are off the water grid and may be using energy intensive technologies such as Atmospheric Water Generation (AWG) to provide water for homes and hydroponics.

Transactive power and transactive water work together to create what soem of us are starting to call watergy.

The End of Net Metering

Net metering can never be more than a fantasy that dissolves once the level of distributed power generation rises beyond the level of noise. This is as true as water is wet.

If any neighborhood were all generating, all houses would produce more than they need at the same time. The only “target” for the power would be a use different than the houses, which means somewhere else. The distribution infrastructure must be in place to get there.

Assuming you could solve the physical problem of power transport, you are still left with the market problem. Each house wants to sell power at the same time as all the others do. In any realistic scenario that must reduce price.

This problem is dealt with today by enabling the [Utility] to disable the inverter to support system stability. This means that as the owner of home solar, a third party can decide whether you come to market, and what price you must take. By any economic definition, this means you do not own your solar power system.

Distribution itself brings other problems. Maintenance of the network is expensive. An actual net zero house is free-riding on all others. Middle income power hobbyists are subsidized by the poor. Transporting power is like driving a pickup truck filled with water, there is always splashing (line loss) and the further you travel, the less is left at the end.

The best place to use distributed generation is where you generate it, with no line loss, and no restriction on your use. The second best use is to store it, for later use on site. The third best use is to sell it when it fits your needs and you receive a price you accept. Perhaps the price you receive is from your neighbor. Perhaps you must discount your price because your customer is far away and much of your “product” is lost.  Home (and business) storage is an essential part of this.

It is inevitable that charges for the distribution network will eventually be unbundled from power. Per-kWh prices will drop. We must continue to innovate so that distributed generation and distributed storage fit within those future prices when the time is ripe.

For widely deployed distributed energy to work, we must adopt business models that encourage full use of all the power generated at the edges. To use power at the edges, we must manage power at the edges, and this includes power storage at the edges. It will require shared signals of scarcity and abundance within homes and commercial buildings, and between those homes and commercial buildings.

The supply of distributed energy varies over time and that supply is always local. Local usage is inherently more volatile than usage combined and averaged over a wide area. Local supply and local demand for power must be solved locally, with local transactive integration of systems.