Designing, updating buildings for the Smart Grid

Here’s how to achieve maximum operational benefits and increased energy savings by making a building Smart Grid compatible.

08/16/2012


Over the past several years, electric utility companies and the federal government have been spending billions of dollars on sophisticated “smart” meters and advanced metering infrastructure (AMI) as part of an overall effort to modernize the U.S. power grid. However, in many cases, the full value of this investment has yet to be realized by these utilities and their customers.

Figure 1: Prototypical hourly power market pricing for a summer day in California is shown. Notice that market prices often increase three to four times during the middle of the day compared to the off-peak hours earlier and later in the day. Courtesy: ArPart of the reason for this is that most building owners and managers have not optimized their facilities and systems for the new electric rate structures and Smart Grid load management programs that are intended to reduce operational costs for both the utilities and their customers. This article summarizes the basic concepts of the Smart Grid; explains how it applies to smart building designers, owners, and managers; and describes new applications for customers to achieve maximum operational benefits and increased energy savings by making their buildings Smart Grid compatible.

Rationale for the Smart Grid

One of the fundamental premises of the Smart Grid is to enhance the interaction and “connectivity” among the various parts and pieces of the electric supply and distribution systems. At the end-use customer level, this usually focuses on the smart meter and related AMI components. Along with potential labor cost saving (compared to manual meter reading) for the utilities that own them, AMI systems typically provide improved communication and data transfer that will allow the following attributes to be realized:

  • Two-way communications between the customer and the utility
  • More granular, time interval data—typically 5-, 15-, or 30-min increments instead of monthly aggregated data
  • Real-time data acquisition and presentation for the utility and customer
  • Utility outage alerts, event notification, price discovery, and reliability/condition signaling to customer system interfaces
  • The utility or grid operators’ ability to directly trigger load control operations of customer equipment and systems and verify performance/compliance
  • Allowing two-way, metered flow of power, including backfeeding of power from various distributed generation resources such as renewables and electric vehicles, and providing a net-metering solution
  • Theft detection and prepaid metering solutions. 

A key feature of the Smart Grid is to provide more dynamic and time-responsive power grid operations and retail pricing schema, which are better aligned with the bulk (wholesale) power markets and technologies that are being used to generate power. One reason for this is that some of the newer central and distributed generation resources, such as renewables, tend to be more variable and less predictable than conventional thermal power generation. This increase in the intermittency and randomness of generation assets creates power flow, generator dispatch and scheduling issues for the grid operators. As some states increase the requirements for the percentage of power generation coming from renewable resources, it can be expected that these scheduling and coordination issues will become more relevant and have a greater impact on grid operations and power costs.

How much does electricity cost?

Historically, retail power rates considered both the amount of energy consumed (kWh) and the rate at which it was used (kW). In very general terms, the energy (kWh) component includes the variable fuel and generator operating costs, and the demand (kW) component considers the fixed capital costs of generation, transmission, and distribution equipment required to serve the customer. However, these components of energy rate can be significantly affected by the type of generation because renewables tend to have higher initial capital costs and lower operating costs, and fossil/thermal plants tend to be the opposite. And because renewable generation is somewhat variable and typically needs to be supplemented with thermal generation, these operational and scheduling requirements will impact the total cost of delivered power and the relative costs of these energy and demand components on an hourly basis.

Another driver is the variability and uncertainty of the customer’s loads themselves. And because generation output must closely match the loads, the achievement of this continuous equilibrium typically requires near real-time grid control in intervals of a little as 4 sec. Since this ongoing balancing act occurs with a strict requirement for very high reliability, the one operational element that is not fixed is the cost of providing and balancing this power.

Therefore, market prices are subject to the basic laws of supply/demand economics and are greatly influenced by both the fluctuating customer loads and the effective generation mix at that time. As a result, we find that the hourly bulk power market price will vary significantly and occasionally by a couple orders of magnitude (see Figure 1).

How electric rates are evolving

Because the bulk market price for power varies throughout the day, and because utilities have to pay the current price for the power when they deliver it—or the lost opportunity to sell their own power into the market during those times—it seems obvious that utilities would want to “share” these time-dependent costs with their customers and recover them through pricing designs that appropriately reflect them. Several different billing solutions and rate tariffs have been created by utilities to deal with the time element of varying power costs. These rate designs deviate from a flat rate (i.e., constant $/kWh) and incorporate some time-sensitive metric to bill the customer. The following are a few examples of these time-based electric rates.

Interruptible rates: Under this option, the utility charges lower rates in exchange for the ability to interrupt service or reduce consumption to a predefined level, called the Firm Service Level, within a defined amount of time, for a limited number of times per year.

Time of use (TOU): A TOU rate charges a customer for energy based on the time of day, day of week, and/or month of the year that the energy is used. The rates are established based on the expected wholesale energy costs during various “tiers” throughout the day, which might include different pricing for peak, shoulder, and off-peak hours during the summer and winter.

Figure 2: This provides some examples or how hourly energy rates vary under the RTP rate. While the average cost of power may be lower than under a fixed rate, the peak prices are substantially greater. Courtesy: Southern California EdisonReal-time pricing (RTP): Under a RTP rate, customers are billed hourly electricity prices that vary based on the time of day, season, and/or temperature. For the latter element, the utility may use temperatures based on data as provided by the National Weather Service. Customers participating in RTP may receive courtesy notification of temperature-based price changes, but there are no specific requirements for customers to reduce energy consumption (see Figure 2).

Critical peak pricing (CPP): CPP offers benefits to customers for shifting or reducing electricity use during critical peak events in the summer season. During summertime peak demand periods when CPP events occur (generally between 9 and 15 times per summer) the utility will contact its customers the day before the event to ask them to reduce energy usage. During CPP events, the energy charges will increase significantly. By reducing electricity usage during each 4-h CPP event, customers can avoid these higher prices and may benefit from lower overall monthly electricity bills.

Figure 3: In this case, the energy use impact of a temporary load curtailment occurs during a demand response event. The red line is the baseline energy consumption of the building without load management and the blue line shows the actual usage with loadDemand response (DR): DR can take many forms and may include year-round, flexible, Internet-based bidding programs whereby customers sell their available load reductions back to the utility or grid operator in exchange for billing credits or payments. Other programs involve a predetermined load reduction that’s provided by a customer when a DR event is called by the utility or grid operator. The customer typically receives a monthly payment for agreeing to provide this kW of load reduction when called.

The DR event may be caused by power supply emergencies or may be based on unusually high power market prices, though these conditions are typically correlated. Customers may reduce power consumption by curtailing loads and equipment in their facility, or in locations that permit it, use a backup/emergency generator or other on-site power generation to shift their power loads off the grid. In many circumstances this DR action can be automated through the programming and use of the building’s direct digital control (DDC) building management system.

Smart energy management

Improving the use and consumption of energy in buildings has taken several different approaches over the past 40 years. Building designers and operators have increasingly implemented various strategies and technologies to reduce and manage the energy use in buildings by improving the energy use of the building envelope, controls, and mechanical and electrical systems. We’ll look at three different techniques for energy management, which are generally compatible and synergistic.

The first wave: energy efficiency. We begin with a “static” view of energy use that accounts for the savings that could be achieved by simply using a smaller amount of energy to do the same function. Most types of building equipment, including lights, chillers, and motors, have continued to become more efficient and longer lasting. By installing and controlling this equipment and the buildings systems in an efficient manner, the building owner/operator will save energy and costs. Increasing the energy efficiency of building equipment and systems, and thereby reducing the annual energy use (and related reductions in carbon and greenhouse gases), will nearly always reduce the cost of operating and maintaining a building and is a primary goal of building energy engineering.

The second wave: peak load demand management. The next approach looks at the rate of power use, which is defined as the quantity of energy used over a specific amount of time, typically 15 min for most electric utilities. This rate of power usage, also known as demand, will impact the size of electrical service equipment and the corresponding infrastructure cost required to serve this load. So, several decades ago, utilities began to bill customers for the peak rate at which power was consumed during a month or the entire year, and this became known as a “peak demand charge.” Some of these tariffs even included “ratchet” provisions whereby the measured peak created a minimum billing for the next 11 months. Many building operators seek to actively limit and even shift equipment loads to reduce the monthly demand peak and thereby reduce these charges.

The third wave: dynamic load control and demand response. More recently, utilities have begun to look at not only how much energy a customer used (kWh) and what the peak demand was (kW), but also when during the day that power was consumed. This close linkage between the utilities’ energy costs and their customers’ rates has placed end users in the interesting position of having to pay for these variable costs, usually without having sufficient real-time information and appropriate tools to do so. We’ll examine some of the tools and methods that buildings can use to their advantage under this paradigm.

Modifying, managing a facility for the Smart Grid

Figure 4: This shows the general evolution of the smart building’s capability and value in terms of reducing operating costs and increasing operational flexibility. Courtesy: ArupUltimately what is a building designer, engineer, or manager expected (and able) to do to reduce operating and energy costs, make their buildings more Smart Grid friendly, and achieve a smart building that is more compatible with both utilities’ needs and tenants’ desires to receive benefits from this new technology?

The first answer is to acquire and use building energy and operational information in a more structured and proactive manner. There are several systems and techniques for accomplishing this goal, and there are an ever-increasing number of information technology and controls vendors and energy consultants that can assist in implementing these tools. We will examine each step in roughly the order that most will want to follow.

1. Instrument and interconnect

Establish an energy information dashboard: You will need some type of user interface through which you can receive information about, and ultimately control, your building. Typically this will be your BAS front-end computer, but we are beginning to see tablet-type device (and even smartphone) applications performing some level of building status and operations support. There are even incredibly simple “orbs” that merely change color to indicate a change in status of some important energy metric. The selection of format and device is up to you, but it needs to be capable of accurately informing you about the building’s condition and energy use, the fluctuating external factors such as weather/temperature and energy prices, and provide a suitable platform for adjusting and enabling programming scripts and macros when necessary. Even if most of your facility is automated, knowing the condition and settings of your systems is strongly advised.

Figure 5: This is a representative Energy Information Dashboard that provides near-real time data on energy usage, site generation and costs/savings. Courtesy: Viridity Energy LLCReal-time energy data acquisition: The old saying about “you can’t manage what you don’t measure” definitely applies to Smart Grid-enabled buildings. What you will need to do first is to get near real-time energy use data flowing into your energy information dashboard (Figure 5). This will require a data feed from either the utility meter or the power distribution equipment. A typical approach is to install a “shadow” device on the utility’s revenue meter using a KYZ pulse or other technology. This will give -you the same energy data that the utility gets and ultimately provides to you a month later, but will now allow you to actually do something with it as you are getting it.

Distributed generation and microgrids: Distributed generation (DG), also known as on-site power, includes generation technologies such as backup diesel generators, renewable sources, cogeneration, and fuel cells. DG can provide opportunities to manage the amount of power consumed by the end user. Through DG, the end user is able to control several key aspects of energy costs, reliability, and even power quality.

The deployment of a “microgrid,” whereby several smart buildings and DG can interact with the Smart Grid based on continually changing economic and reliability conditions, takes this concept even further. The microgrid can be operated in several power exchange modes, such as import and export (i.e., directional flow), as well as “islanding,” which allows the microgrid to achieve operational energy independence from the grid. This flexibility and redundancy provides a huge increase in capability for how and when energy is consumed and purchased from, or sold to, the wholesale energy and capacity markets. The microgrid concept can scale from a single smart building, to a campus, to a community, with a corresponding increase in complexity and economic opportunity. A microgrid or smart building control architecture is essential for achieving real-time adjustments to the various components of the facility and to optimize the benefits and savings potential.

2. Inform and analyze

Now that we have an energy information and control infrastructure in place, and perhaps some DG, we can conduct an analysis and make some informed decisions about how best to manage our smart building or campus. In many situations, we can audit, trend, and calculate a range of control sequences that might improve our building’s performance. Examples could include demand response strategies such as zone temperature resets, pre/sub-cooling, dimming of lights, and duty cycling of equipment. These operational modification strategies generally fall into one of the following generic concepts for dynamic building management:

  • Operational flexibility: Although most buildings are controlled to maintain certain conditions (e.g., temperature, humidity, outside air, etc.), there may be some ability to temporarily and occasionally modify these setpoints to achieve substantial energy, demand, and cost savings. Several studies have shown that humans can tolerate, and may not even notice, a deviation in temperature if it occurs over time. There are cases where tenants may be willing and motivated to support DR programs where the building raises cooling setpoints in exchange for some of the savings related to reduced energy costs. And there are many noninvasive opportunities to dim lights, turn off equipment, and initiate or delay an energy-intensive process to a time when energy is cheaper. If these efforts can be automated, there may be little or no negative impact on the building occupants.
  • Storage and inventory: This concept uses the physical properties of the building, systems, or products produced to achieve a lower cost of energy or reduced demand through some type of storage. An example might be to pre/sub-cool a building prior to a time of day when energy costs increase. So, rather than using a dedicated thermal storage system that uses ice or cold water, we may be able to employ the building and its contents to perform a similar function, though generally to a lesser level. Another example would be in a production facility where a product can be inventoried so that during a DR event the production can be slowed down—and energy use curtailed—without impacting the shipping of the product. When combined with the operational flexibility (e.g., a zone temperature reset) approach, we can get a synergistic result that may create very little occupant discomfort for a 4-h DR event.

Once we have estimated the performance potential for these measures to modify electric demand, we will usually want to test the concept in the building to see the actual results. Because the dynamic control of building energy use is affected by a large number of building-specific factors including thermal mass, system and control response times, and human reaction to changing environmental conditions, it is very difficult to accurately estimate what level and duration of load modification will be achieved. So, empirical testing and results are usually a critical step in establishing effective smart building operational process and protocols.

3. Automate and transact

Through our information systems and the capability to functionally optimize our building’s operations and performance through a dynamic and continuous control strategy, the smart building can effectively transact with the Smart Grid. The energy information dashboard will keep us aware of situational conditions and our BAS will execute our predesigned routines in response to a range of changing hourly energy pricing, environmental conditions (temperature, humidity, solar gain, etc.), and internal building loads variations such as start-up, end-of-day, and even lunch hour occupancy levels.

The objective of these systems is to have your smart building work with the Smart Grid to reduce your costs and permit you to understand how these various operations influence each other. Just like many of the other smart device technologies in our modern life, the smart building should simplify what we do—while also allowing us to do more and perform better.

Conclusions

By achieving greater overall connectivity between the supply side (generators, utilities, and grid operators) and the demand side (smart building customer), the Smart Grid is expected to provide the superior communication and active control necessary to achieve the required grid reliability at minimum costs for everyone.

While smart building/Smart Grid technology can help to inform, automate, and execute the operational strategies necessary for an optimized building, there is no substitute for a skilled and knowledgeable building manager or engineer to establish the parameters and criteria for this operation. As building engineers, consultants, and operators, we need to sufficiently understand and integrate these concepts of improved real-time energy information into our smart building systems design. Doing so will improve the operation of our buildings at the lowest cost, highest reliability, and maximum operational performance.

 


Nordham is an associate principal at Arup. He manages the energy consulting group and works primarily in improving the energy performance of existing commercial and industrial buildings. Nordham’s 35 years of energy industry experience includes a wide range of roles related to alternative and distributed generation technology, energy management business development, automated demand response, and energy business advisory.



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