Moving beyond Demand Response (DR) – Pricing Services

Utilities and Regulatory commissions are obsessed with demand response (DR). All want to know how to get more of it. I could, with little effort, attend a national conference on DR every week. A large share of the standards priorities of the National Institute of Standards and Technology (NIST) to support smart grids support DR. And yet, almost everyone recognizes that DR is a short-term solution. Plans are just now underway to move beyond DR.

The most expensive electricity comes from the dirtiest generating facilities used for only a few hours a year. If consumers would use less energy, i.e., reduce demand, in just those few periods, then those expensive dirty plants could be turned off permanently. To do this, electricity suppliers need to anticipate when those moments are coming and take steps to reduce demand. We call this Demand Response.

At its simplest, DR is just turning things off. Rolling black-outs are the simplest form of DR. They make consumers very unhappy. Utilities have worked for years to improve on this model through direct load control. They have been installing remote switches on home heat pumps since the ‘70s. Today, they are developing SEP to control homes device by device using software installed in smart meters. Consumers like it in off-months, when they get a bill reduction and the utilities do nothing. In summer months, when the utilities do something, things get turned off in the home. They make consumers very unhappy.

In the commercial building world, utilities pay per incident. The energy use is greater, the number and complexity of systems on the premises are bigger, and the possible DR per incident is larger. In the most expensive markets, this pays for the custom integrations needed to respond to price signals. This is probably good enough for today’s grid. Tomorrow’s grid will be much less predictable, and the need for more participants will be greater.

Just as there are times when there is a shortage of electricity, there are times when there is a superabundance. Buildings that take responsibility for storing energy in advance are better able to manage demand reductions when asked. If the markets offer fixed prices except for the peaks, then it will be cheaper to ignore storage and DR. Sooner or later Markets must follow availability. The most important feature of smart grids will be to recognize scarcity and abundance faster, and to thereby price better.

In the future, then, a Pricing Service will be the essential load management service that operates the grid. A grid pricing service must be able several questions:

1. What is the price of Electricity now?
2. What will it be in 5 minutes?
3. What was the highest price for electricity in the last day? Month? Year?
4. What was the lowest price for electricity in the last day? Month? Year?
5. What price will electricity have for each hour of the day tomorrow?
6. What was the high price for the day the last time it was this hot?

The answer to each of these questions has another component “How sure are you?” Those prices may be fixed tariffs absolutely locked down. Those prices may be fixed tariffs, “unless a DR event is called.” Those prices may be wild guesses about free markets.

At its core, OpenADR must have price services in the future.

Privacy Mosaic: Tiling over the Fourth Amendment Piece by Piece

Regular readers know that I am concerned that the accumulation of many small legal actions can create a violation of privacy that exceeds the sum of the observations. This week, the DC Circuit Court ruled that prolonged recurring legal acts can become an illegal search, or one that requires a specific warrant. If it stands on appeal, this theory may be one of the most important decisions to protect individuals and restrain the modern state ever.

The ruling defines a new "mosaic" theory of the Fourth Amendment under which individual law enforcement actions that are not searches to become a search when collected together. This is an important new theory. Noted fourth amendment scholar Orin Kerr has written how this throws decades of decisions on their head. Lawyers, though, worry about clear predictability of the law more than about theory and justice and the proper balance between the individual and society.

In the case United States v. Maynard, the court ruled that the long term use of a GPS device to monitor a car required a warrant. The government argued that roads are public, and that it could have had a watched public acts on public roads if it wanted; automating that information gathering was no big deal. According to the court, "[T]hat whole reveals far more than the individual movements it comprises. The difference is not one of degree but of kind, for no single journey reveals the habits and patterns that mark the distinction between a day in the life and a way of life." Exactly.

One purpose of constitutional law is to provide a basis for understanding bodies of law as well as individual laws. Law is made up primarily by decisions accumulated over time, in response to uncomfortable circumstances. A small bad decision supports another slightly worse decision until the law is firmly behind something few would choose. Plessey vs. Ferguson, the famous case that defined separate but equal as the law of the land was uncontroversial when passed, unexamined for 50 years, and supported by precedent and cemented by rulings that followed. It was good that we overturned that body of law.

In a similar way, we have been building a series of decisions about the use of technology and surveillance that must be overturned. The law has been willfully ignorant about technology and change. Perhaps it is because judges are older when appointed, and isolated from wider business. Perhaps it is because judges are discouraged from speculating on their thoughts and motives in public. Perhaps they are simply overly deferential to congress and police.

Judges have ruled that the information on personal computers are neither personal “papers or effects”. The current administration is arguing that searches of cell phones, including modern smart phones with call logging, email, documents, and passwords for accessing personal and business web sites, do not require a warrant. For whatever reason, judges have not given sufficient respect to digital papers and digital effects.

I have written before that accumulating data creates something that is of a different quality than each datum, and that quality is more dangerous as the points accumulate. I have written that there is danger to the citizenry even in gathering data required to operate a business, when it is shared outside the purposes of that business. I now know to call this the mosaic theory.

The government will certainly appeal United States v. Maynard. It may be overturned. If it is not, it creates a legal theory that may be held not only against police actions of the government, but against the misuse and re-sale of information gathered in e-commerce. It establishes a legal theory for discussing the repurposing of operational data.

It might help change to direction of the smart grid. Direct load control of homes and commercial buildings collects millions of data points that create their own mosaic. These mosaics will combine with mosaics from the internet and e-commerce. If every market is the sum of the participants knowledge problems, then not only privacy, bit all markets are changed, as one set of participants accumulates an immense imbalance of knowledge about the other.

Economic signals in smart energy collect less personally identifiable details than do direct load control models. We should all prefer them, rather than contribute more to the mosaic owned by others, and created to achieve advantage over each of us as individuals.

Underpinnings for standardizing Demand Response (DR)

For decades, regulated electricity markets have struggled to deal with volatile energy markets providing to support un-caring customers. Customer’s real-time purchases, called load by the electricity industry, vary throughout the day, and more to the point, co-vary with external events. These issues are not limited to electricity. The “Super-Bowl flush”, which has reached the status of urban legend, names the stresses placed on urban waste water systems as external events synchronize demand.

Public Utilities Commissions defined tariffs to prevent the Super-Bowl flush for decades. Peak use can increase prices for a year. Tiered pricing increases the bill for any amount above a pre-set usage during a month. These approaches pre-date any discussion of smart grid—often they have effects contrary to those desired by the smart grid. The smart grid is smart in that it detects at any time whether there is too little or too much power available, and uses market signals to decrease or increase demand to match supply.

Early efforts at the smart grid focus solely on reduction. When the signal goes out to certain buildings, they reduce their load, or use of electricity, in a pre-defined way. We call this process demand response, and pre-eminent specification for this signal is called Open Automated Demand Response (OpenADR).

Demand response must be more than load reduction. The great wind farms of west Texas, the most successful farms in North America, are, I’m told, able to sell less than 40% of the electricity they generate. The wind generates electricity at times when no one is planning to use it. Even the most inefficient energy storage would be preferable to simply wasting the electricity.

The challenge now is to define signals that common across North America and the world, and that that handle energy surplus as well as deficit. This effort is underway in the OASIS Energy Interoperation Technical Committee.

One problem is that energy market operations have been restricted and confined, both by technology limitations and by public policy decisions. We have discussed DR as a one-way interaction, from utilities to customers. We have tied DR to special tariffs and to direct control systems. Each of these restricts the participants and innovation in DR.

On the Committee, we tried to place electricity in a normal market context. We identified four essential market activities, or services:

1. There is an indication of interest (trying to flush out offers), when a market operator is seeking partners for a demand response or energy source.
2. There is an offer of a service whether megawatts or “nega-watts”
3. There is an execution of a contract (agreement to purchase / supply (b))
4. There is a call for performance of the contract (c) at the price agreed upon.

We are defining these services so they can be combined to meet today’s tariffs. For example, one of today’s tariffs for interruptible power may offer a lower price all year in return for the right to shed load automatically up to six times a year. Under the Energy Interoperation model, this would be standing contract with 6 time-limited pre-executed response contracts. Automated Demand Response is merely a call for performance on existing contracts at the agreed upon price.

Another model, coming into use, is Price-based ADR. If we assume the traditional utility-centric model, we would see the utility publishing an indication of interest in buying DR at a given price. Business and buildings willing to respond would simultaneously offer and execute a contract to shed load. The performance could be called at the same time or later as contracted.

Emergency or "Grid Reliability" events could look left out by this approach. Grid Reliability events require mandatory participation in today’s markets. These could be set up as standing pre-executed options. A grid operator then need merely call for performance as in any other demand-limiting event.

In this way, we can build all the tariffs and markets out of a few low-level services.

Sometime soon, I will write about the requirements for a pricing service.

Smart Buildings & Smart Energy: the Integration Challenge

Last week, twenty of us gathered in DC for a two-day charrette on the standards needed to apply BIM to the problems of dynamic energy management. The work-shop, entitled “Smart Buildings, Smart Energy”, was put on by the Corps of Engineers Research Lab (CERL) at the National Institute for Building Science (NIBS). The meeting was a fascinating, and occasionally heated conversation that brought together academic and government researchers, building system practitioners from industry leading companies, and participants in standards committees from ASHRAE to OASIS. It was a fascinating meeting, filled with bright, deeply focused individuals who as a group had not yet recognized the profound changes in their goals required by smart energy.

The challenge of smart energy to buildings is dynamic change. The goal of smart buildings has always been superior performance—usually defined as energy efficiency. Energy from external sources will all become dynamic and intermittent. Some will be available under rapidly changing prices. The most efficient system may not be the one that is most able to respond to these changing conditions. Perhaps the goal of smart buildings is to defend its occupants from the degraded conditions of the smart grid. The game is changing.

The use of Building Information Models (BIM) is only now becoming common enough to change business processes. BIM lets us design buildings the way we design cars and planes, with full simulation and testing before the contractor turns over the first shovel full of dirt. BIM furthermore provides the contractor with accurate materials requirements and each trade with accurate measurements. With better knowledge and a dramatic reduction in re-work, the cost of construction can come way down while the quality goes up.

Most of the cost of a building is incurred in operations, during the long period between construction and demolition. For the last five years, led by NASA and CERL, there has been a project to define how to hand over information from design and construction for use in operations. The Construction Operations Building Information Exchange (COBIE) defines how to hand over information from the BIM to maintenance and operations.

The information in COBIE seems almost trivial—unless you don’t have it. COBIE defines a standard exchange for equipment information including spare parts lists and preventive maintenance schedules. COBIE exchanges are defined as a series of simple spreadsheets, which can be generated from BIM or filled in by hand. A growing number of maintenance management systems are now able to import COBIE directly into their databases. Whether or not a building was built using BIM, whether a building is old or new, the owner can request COBIE formatted information for handover from the builder, commissioning agent, or seller.

Francois Grobler gathered us together to discuss how to extend COBIE to reduce the cost of building system integration. Building systems are classically islands of automation, communicating only with a single proprietary console. The cost and time required for integration is a barrier both to better integration, and to system upgrades. Occult system tags and poor documentation prevent the timely value-based upgrades that drive innovation in the IT world.

This last point is critical of we are ever to get to a highly innovative green-tech. Cost-based upgrades look to historical cost and to growing maintenance problems to decide when to upgrade. Systems are not replaced until they fail or have been completely depreciated. As IT merged with telecommunications, we moved to value-based upgrades. Lap-tops and PDAs are upgraded when they give the sales force a competitive edge. Work-stations are upgraded to increase engineering productivity. This dynamic has driven these worlds to innovate to drive shorter sales and replacement cycles. The difference is the one between the old black hand-set we used to lease from the phone company, often for decades, and the new market of cell-phones and the latest functions.

A key component of this new COBIE will be control system tags and metadata. Today, a retro-commissioning agent spends the first days or even on site in low-value discovery of this information from blue prints and the current control system. Only after this work is complete, can the more high-value and useful work begin. When a project such as completed, those working notes are thrown away, or stored where they see no further use. A standard for the exchange of this information would reduce the costs of each commissioning and perhaps stimulate a market for third party discovery tools.

Space is the most important class of metadata. People in buildings inhabit and interact with spaces. Building systems affect those spaces, and secure those spaces, but the relation between systems and space is often occult. BIM can provide the mapping, but we don’t need all the BIM for that. We need something small and lightweight, describes the three dimensional space, but leaves out the details that add complexity.

The most significant use of BIM will be in buildings that built without using BIM. Most buildings next year are not new; most new buildings next year will be built without using BIM. Even if we were to imagine that in five years, all buildings will be built using BIM, most buildings still would not have a full BIM, with an intelligent structure, for a very long time. Fortunately, we do not need a full BIM to describe the space in buildings, and to provide a light framework integrating system information with that space.

Retro-BIM is the work for taking one of today’s buildings and creating a BIM for a portion, usually during a renovation. These BIMs tend to be descriptive, and lack the full engineering detail that would come with design through BIM. There is a growing set of tools and practices to cost effectively create a three-dimensional BIM during a renovation. Retro-BIM can provide as good a foundation for a light integration framework as can a full design BIM.

Green Building XML (GBXML) was designed to provide a “good enough” description of building space and building systems to support energy models that are “good enough”. GBXML is based on the IFC data models that underlie design BIM. Because GBXML already includes information on space and systems in a light-weight model, GBXML would need only a little extension to map system tags and related system metadata to space. Retro-BIM datasets, design to map to the IFCs, should be able to expose information as GBXML with little trouble.

The new challenge of smart energy is dynamic decision-making. Volatile energy availability and energy prices will make the grid  an unpredictable supplier. The availability of on-site energy sources, both generation and storage, enable self-reliance. Smart energy will require energy use decisions on a minute by minute basis. Buildings must be able to accept the complexity of new systems and new technologies without bearing the additional cost of complex integrations. GBXML might be the shim between systems, space, and the people that occupy that space that lets us put it all together.