As dictated by the Energy Independence and Security Act of 2007, the National Institute of Standards and Technology, through an organization called the Smart Grid Interoperability Panel (SGIP), is coordinating the development of the Smart Grid. This technology will result in new features and capabilities in commercial building automation systems.
Although Smart Grid operations involving building automation systems are envisioned to be automatic, facility managers (fms) will need to participate in configuring and maintaining these system operations. Exactly what these operations will encompass is not clear. Therefore, an effort with more than 400 participating organizations (ranging from power producers through transmission grid operators to appliance manufacturers and residential, industrial, and commercial buildings, distributed among 22 stakeholder categories) is likely to be a bit chaotic at first.
In an attempt to organize these efforts, the Energy Information Standards Alliance (EIS Alliance) is developing a set of use cases and data models for Smart Grid communications with buildings. [For additional innovations that will have an impact on fms and building automation, see the accompanying sidebar below by Terry Reynolds entitled, “Cloud Based Energy Services And Open Automation Systems.”]
Although the use cases are initial drafts, they demonstrate the various ways in which buildings will interact with the Smart Grid. These are as follows, arbitrarily categorized.
Several use cases (or case study examples) are related to varying energy prices, whether by time or source. In the “Manage Power Demand to Minimize Cost” example, these energy costs vary over time. The pricing information is conveyed to the building, which responds by reducing or turning off loads defined by the fm as sheddable (as opposed to critical loads which could include production processes). There are many factors that could enter into the determination of which loads could be shed, including production schedules and their flexibility, minimum load cycle times, personnel safety and comfort, and so on.
The production element is the focus of another use case, “Manage Production Needs with Power and Energy Management,” in which energy pricing and energy provider demand shed requests are factors in optimizing productions.
And in a similar case study, “Balance Power Purchases Between Utility and On-site Generation,” the decision to be made based on utility energy pricing is whether to switch to on-site generation or to use stored energy instead of consuming from the grid. A variation of this occurs in yet another use case, “Buy or Sell Electric Power,” wherein an additional decision can be made to generate electricity for the grid.
In another example, “Balance Power Purchases between Multiple Utilities,” multiple energy suppliers are available and the user selects a less expensive source over a more expensive one.
Energy Consumption Forecasts
Forecasting one’s own energy consumption is the focus of one use case. In “Forecast Power Usage,” based on usage history and a number of other factors, customers forecast their power usage hours, days, or even months ahead to manage their power costs and production schedules better. When this information is shared with the energy utilities, the latter are better able to plan and manage their capacity.
In fact, many of the use cases are centered on actually measuring consumption. Two similar examples are “Measure Plug Load to Calculate Cost and Consumption” and “Measure Equipment Power to Calculate Cost and Consumption.” One case measures the energy consumption through electrical outlets, by power circuits and at the panel level using a sub-meter, and in the other case, consumption by specific devices is measured. In both cases, the goal is to determine the consumption cost.
Another example, “Allocating Energy Costs,” uses the energy management system or meters or sub-meters to measure the energy consumption in selected areas for the purpose of tenant billing and cost accounting or reports (e.g. monthly energy consumption reports).
The use case “Measure Present Demand, Energy Cost, Emissions, and Consumption for Display” measures the energy consumption and calculates costs and greenhouse gas emissions for display in a report or on a screen. A similar one, “Measuring Energy Cost, Emissions, and Consumption to Compare Against Building Portfolio for Benchmarking Purposes,” makes similar measurements and calculations for the purpose of benchmarking the building or production site. This benchmarking may be used for Energy Star or LEED purposes.
The example, “Measuring Energy Cost, Emissions, and Consumption to Compare against Similar Buildings for Benchmarking Purposes,” builds on the prior use case. Meanwhile, the case study entitled “Measure Energy to Validate Energy Consumption,” uses temporary measurement equipment to verify an energy efficiency upgrade, in a time of use pricing or demand response environment.
Grid Maintenance And Planning
Two case studies exchange information related to grid maintenance. “Communicate Generation for Grid Maintenance and Planning” passes the status of the building’s internal for grid generation capability to the utility, especially important when the utility is planning maintenance of the electrical distribution system.
“Receive Grid Maintenance Planning Information” conveys grid maintenance plans from the utility to the building to warn of possible resultant power outages or lower quality power.
A couple of case studies center on shedding and restoring loads. In “Choose Response to Price Signal,” the energy management system sheds (or restores) loads per signals from the utility. In “Load(s) Controlled by External Source,” on the other hand, the loads react directly to signals from the utility (under the assumption that there is no master control capability on-site, unlike the previous use case; the loads might or might not provide feedback to the utility or other source).
Social, Environment And Regulatory Aspects
The use case “Social, Environmental and Regulatory Aspects of Energy Consumed” is provided for those who wish to include these aspects of consumed energy into the business models to track, communicate, and/or provide better control of these aspects. This involves acquisition of energy related emissions, inclusion of on-site generation, information regarding on-site energy storage (in whatever form), and data regarding periodic historical usage.
The examples described here are those proposed and drafted by the EIS Alliance. The work is in its early stages and will pass through a number of review stages before final approval, but it still provides a rough idea of the new building automation system features and capabilities that will be needed for the Smart Grid. In order to stay ahead of these developments, fms should be aware of the work being done by the EIS Alliance and other organizations involved in this project.
Swan is buildings standards initiatives leader for Alerton, an SGIP member representing ASHRAE. He is also a member of the EIS Alliance’s commercial buildings working group. For more information on the use cases, visit this link.
Cloud Based Energy Services And Open Automation Systems
By Terry Reynolds, PE, CEM, CDSM, LEED AP
In the early 90s, open systems—with interoperable communications standards at their core—began to appear. Early market perception was that the age of the proprietary relationship was at an end. However, this was only partially true. The use of open systems technology alone did not obviate the economic problem associated with the proprietary relationship of the past.
Today, it is understood that open technology must be coupled with disciplined application and oversight in order for a facility manager (fm) to retain his or her ability to bid system additions, modifications, and service competitively. It is safe to say that open system technology has gained significant market share, and the two dominant communications standards, LonWorks and BACnet, are now designed into most of the DDC systems being delivered worldwide.
In fact, the more analytics promised by a vendor, the more critical the need for transparent access to the DDC data stream. The equipment operating parameters and status, and the current value of associated environmental parameters resident in the site DDC system’s database will be mined by cloud based services. Analytics in the cloud will determine optimal equipment set points and determine whether equipment is operating efficiently.
The financial impact of neglecting to cure the problems which are discovered will be determined and reported, resulting in prioritization of work schedules based on payback. Work orders will automatically be generated, managed, and closed out using services in the cloud. Maintenance history will be recorded, archived, and available with financial tools to assist in equipment purchasing decisions. Just in time material supply strategies will be employed using M2M (machine-to-machine) connectivity between cloud based services, minimizing site inventories.
The benefits that are possible with cloud based services are manifest; thus, the transition to them is inevitable. The fm’s ability to leverage these new services competitively will be influenced significantly by the same economic dynamic at work in the aforementioned proprietary relationship scenario; so if a facility’s DDC system is proprietary, the company that controls the pricing for a facility’s DDC system additions and service is the same company that controls the cost of access to the cloud. This intermediary is empowered while the fm is not.
A conceptual analogy that is becoming popular with respect to cloud based services is the “pipeline.” The “pipeline” (aka Internet) connects the cloud to the fm’s site; the point of “connection” is the DDC system. In order to facilitate access and use of the data necessary to realize the benefits of energy services, the fm must control the pipeline.
While many of today’s energy services require only one way flow of information (from the site to the cloud), in the very near future, supervisory control in the form of optimized set point signals and start-stop override commands (similar in concept to the old SSP systems of the 70s) will also be part of energy service strategies. The cost of the system and network programming changes and possible additional monitoring and control points required to maximize the benefits of cloud based energy services will no doubt be influenced by the relative openness of the site DDC system, from an economic perspective as well as a technical perspective.
It makes more sense than ever for today’s fms to make purchasing decisions that yield open systems, and if their facilities use proprietary DDC system technology, to develop a transition plan that moves them away from the proprietary relationship that controls the“pipeline.”
The simplest way to formulate such a plan is to look at existing DDC system layers—devices, supervisory controllers, gateways, IP gateways/routers, and management and configuration software. At each layer, the simple questions to ask are:
- “Can I upgrade this product with a better one from a different company?”
- “Is this the only software I can use to manage this product?”
- “If I make a change, can I hire someone other than my original vendor to do the work?”
The answers to these questions will help determine how much power fms leave on the table. If they can’t upgrade, have no choices in software, and can’t switch service providers, the chances are they won’t be in a position to control the pipeline either. On the other hand, if they can do all that, then the pipeline belongs to the fm.
At the end of the day, cloud based services are coming. Whether in the form of energy information and analytics or full service energy analytics and management, the role of fms is changing. The fact is that if they want to deliver the highest possible level of benefits, they should get started on their transition plans as soon as possible.
Reynolds, an expert in process and environmental control systems applications, data communications, system integrations, and open communications protocols, is a partner with Control Technologies and also serves on the board of directors for Lonmark Americas.