To be effective, energy management must be given the same emphasis as management of any other cost/profit center. Top management should

It is common for a facility to allocate 3 to 10% of the annual energy cost for administration of an energy management program. The budget should include funds for continuing education of the energy manager and staff.

The functions of an energy manager fall into four broad categories: technical, policy-related, planning and purchasing, and public relations. A list of specific tasks and a plan for their implementation must be clearly documented and communicated to building occupants. An energy manager in a large commercial complex may perform most of the following functions; one in a smaller facility may have only a few from each category to consider.

If it is not possible to add a full-time manager, an existing employee with a technical background should be considered and trained. Energy management should not be a collateral duty of an employee who is already fully occupied. Another option is to hire a professional energy management consultant. Energy services companies (ESCOs) provide energy services as part of a contract, with payments based on realized savings. Other companies charge a fee to perform a variety of energy management functions.

The energy manager establishes procedures for meter reading, monitoring, and tabulating facility energy use and profiles. The energy manager also periodically reviews utility rates, rate structures, and trends, and should subscribe to free utility mailing lists to track changes in their rate tariffs. The energy manager provides periodic reports to top management, summarizing the work accomplished, its cost-effectiveness, plans for future work, and projections of utility costs. Utility bill analysis software can be used to track avoided costs. If energy-efficiency measures are to be cost-effective, continued monitoring and periodic reauditing are necessary to ensure persistence. The procedures in ASHRAE Guideline 14 can be used for measurement and verification of energy savings.

Energy accounting means tracking utility bill data on a monthly basis to provide a current picture of building energy performance and to identify trends and instances of excess use. An Internet search for “energy accounting” will produce web sites for the major commercial providers. In some cases software is sold for computer installation, or the accounting system is web-based and the user has a subscription. For many users, a simple spreadsheet is all that is needed. A comparison of the features of many available energy accounting software packages can be found at http://www.betterbricks.com/DetailPage.aspx?ID=518. Portfolio Manager, from the ENERGY STAR web site, allows users to enter monthly energy usage, in kWh, therms, etc. The Portfolio Manager simultaneously calculates the facility’s EUI and develops a normalized ENERGY STAR score (http://www.energystar.gov/benchmark). Portfolio Manager facilitates comparison of multiple buildings and goal setting, is useful for numerous building types, and is normalized by building type for weather.

Because most energy management activities are dictated by economics, the energy manager must understand the utility rates that apply to each facility. Electric rates are more complex than gas or water rates and some rate structures make cost calculations difficult. In addition to general commercial or institutional electric rates, special rates may exist such as time of day, interruptible service, on peak/off peak, summer/winter, and peak demand. Electric rate schedules vary widely in North America; Chapters 37 and 56 discuss these in detail. Energy managers should work with local utility companies to identify the most favorable rates for their buildings, and must understand how demand is computed as well as the distinction between marginal and average costs (see the section on Improving Discretionary Operations). The utility representative can help develop the most cost-effective methods of metering and billing.

Opportunities for savings come in reducing (1) the cost per unit of energy, and then (2) energy consumption. Historically, energy users had little choice in selecting energy suppliers, and regulated tariffs applied based on certain customer characteristics. In recent years there has been a move in North America and other parts of the world to deregulate energy markets. and there is more flexibility in supply and pricing. Electric rate structures vary widely in North America; Chapter 37 discusses these in detail.

Electric utilities commonly meter both consumption and demand. Demand is the peak rate of consumption, typically averaged over a 15 or 30 min period. Electric utilities may also use a ratchet billing procedure for demand. Contact the local electric utility to fully understand the demand component.

Some utilities use real-time pricing (RTP), in which the utility calculates the marginal cost of power per hour for the next day, determines the price, and sends this hourly price to customers. The customer can then determine the power consumption at different times of the day. A variation on RTP was introduced in some areas: demand exchange and active load management pays customers to shed loads during periods of high utility demand. Also called demand reduction or demand response, the utilities ask participating customers to reduce their consumption for a period of time on as little as a few hours’ notice.

Caution is advised in designing or installing systems that take advantage of utility rate provisions, because the structure or provisions of utility rates cannot be guaranteed for the life of the system. Provisions that change include on-peak times, declining block rates, and demand ratchets. Chapter 56 has additional information on billing rates.

Any reliable utility data should be examined. Utilities often provide metered data with measurement intervals as short as 15 min. Data from shorter time intervals make anomalies more apparent. High consumption at certain periods may reveal opportunities for cost reduction (Haberl and Komor 1990a, 1990b). If monthly data are used, they should be analyzed over several years.

A base year should be established as a reference point. Record the dates of meter readings so that energy use can be normalized for the number of days in a billing period. Any periods in which consumption was estimated rather than measured should be noted.

If energy data are available for more than one building or department, each should be tabulated separately. Initial tabulations should include both energy and cost per unit area (in an industrial facility, this may be energy and cost per unit of goods produced). Document variables such as heating or cooling degree-days, percent occupancy, quantity of goods produced, building occupancy, hours of operation, or daily weather conditions (see Chapter 14 in the 2017 ASHRAE Handbook—Fundamentals). Because these variables may not be directly proportional to energy use, it is best to plot information separately or to superimpose one plot over another. Examples of ways to normalize energy consumption for temperature and other variations are provided in ASHRAE Guideline 14.

Potential savings areas can be identified by separating base energy consumption from weather-dependent energy consumption. Base-load energy use is the amount of energy consumed independent of weather, such as for lighting, motors, domestic hot water, and miscellaneous office equipment. When a building has electric cooling and no electric heating, the base-load electric energy use is normally the energy consumed during the winter. The annual base-load energy use may also be estimated by taking the average monthly use during nonheating or noncooling months and multiplying by 12. For many buildings, subtracting the base-load energy use from total annual energy use yields a good estimate of heating or cooling energy consumption. This approach is not valid when building operation differs from summer to winter, when cooling operates year-round, or when space heating is used during summer (e.g., for reheat). Base-load analysis can be improved by using hourly load data. Electric load factors (ELFs) and occupancy factors can also be used instead of hourly energy profiles (Haberl and Komor 1990a, 1990b).

Although it can be difficult to relate heating and cooling energy directly to weather, several authors, including Fels (1986) and Spielvogel (1984), suggest that this is possible using a curve-fitting method to calculate the balance point of a building (discussed in Chapter 19 of the 2017 ASHRAE Handbook—Fundamentals). For this method, building use must be regular, and actual rather than estimated data must be used, along with accurate dates and weather data.

More detailed breakdown of energy use requires that some metered data be collected daily (winter versus summer days, weekdays versus weekends) and that some hourly information be collected to develop profiles for night (unoccupied), morning warm-up, day (occupied), and shutdown. Submetering of energy end uses is recommended for optimal energy management. For more information, see Chapter 41.

An example spreadsheet using three years of electricity bill data for a two-story office building in Atlanta, Georgia, is presented in Table 1. (See Chapter 18 of the 2017 ASHRAE Handbook—Fundamentals for floor plans and elevations of the building.)

The electrical use profile (EUP) report, shown in Figure 2, divides electrical consumption into base and weather-dependent consumption. The average daily consumption for each month appears in the daily use column in Table 1, and is plotted in the EUP graph. The average daily consumption is calculated by dividing the consumption for a particular month by its billing days.

Figure 2. Electrical Use Profile for Atlanta Example Building

The lowest value in the daily-use column is used to plot the facility’s base electrical consumption (shown as the base use line) in Figure 2. Where a facility uses electricity only for cooling or heating, or in an all-electric facility where there is no overlap between cooling and heating, the difference between these two lines represents the weather-dependent electrical consumption.

Weather-dependent energy consumption (either electric or other fuels) may then be compared to the cooling degree-days (CDD) or heating degree-days (HDD) totals for the same time period (see Chapter 14 of the 2017 ASHRAE Handbook—Fundamentals). This comparison shows how the building performs from month to month or year to year. The HDDs stop and CDDs start at the balance point, defined as the outdoor temperature at which, for a specified interior temperature, the total heat loss is equal to the heat gain from the sun, occupants, lights, etc. Note that all-electric buildings may have periods of overlap between heating and cooling, causing the base load to be overestimated and the heating and cooling estimates to be conservative.

Examine the average daily use line to see whether it follows the expected seasonal curve. For example, the shoulders of the curve for an electrically cooled, gas-heated hospital should closely follow the base electrical use line in the winter. As summer approaches, this curve should rise steadily to reflect the increased cooling load. Errors in meter readings, reading dates, or consumption variances appear as unusual peaks or valleys. Reexamine the data and correct errors as necessary.

If an unusual profile remains after correcting any errors, an area of potential energy savings may exist. For example, if the average daily use line for the facility is running near summer levels during March, April, May, October, and November, simultaneous heating and cooling may be occurring. This situation is illustrated in Figure 2, and often occurs with dual-duct systems.

Simultaneous heating and cooling is also indicated in the percent excess use column of Table 1. The values show the percent difference between the value appearing in the monthly base use column and the billed consumption for the month. In Figure 2, note how the excess consumption for spring and fall months runs close to the summer percentages. The monthly base use is the lowest value from the daily use column multiplied by the number of billing days for each month.

For electrically cooled, gas-heated facilities, weather-dependent consumption is the difference between the totals of the monthly base use column and the billed use column.

For an all-electric facility, subtract the total monthly consumption from total billed use for the cooling months, then do the same calculations for heating months to determine the electric cooling and heating loads, respectively.

Another method for detecting potential energy savings is to compare the facility’s electrical load factor to its occupancy factor. An ELF exceeding its occupancy factor indicates a higher-than-expected electric use occurring outside normal occupancy (e.g., lights or fans are left on or air conditioning is not shut off as early in the day as possible in summer). Setback thermostats, direct digital control (DDC) strategies, time-of-day scheduling, and lighting controls can address this.

The ELF is the ratio between the average daily use and the maximum possible use if peak demand operated for a 24 h period. The occupancy factor is the ratio between the hours a building actually is occupied and 24 h/day occupancy.

To calculate the ELF, find the month with the lowest demand on the utility data analysis spreadsheet. This value represents the base monthly peak demand, and is usually found in the same or adjacent month as the month with the lowest consumption. From the EUP report, find the lowest value in the daily use column. For example, the lowest average daily use for the office building in Table 1 is 1704 kWh (in November 2003), and the lowest monthly demand from the spreadsheet is 122 kW (in October 2003). The ELF is calculated as follows:

The office is normally occupied from 7:30 am to 6:30 pm, Monday to Friday. Therefore, the occupancy factor is calculated as

ELFs can also be calculated for cooling and heating seasons. Typical defaults are May to August as cooling months, and the rest of the year as heating months, but these change based on climate.

The steps for calculating a seasonal ELF are as follows:

For example, because the electrically cooled Atlanta example building operates year-round, the summer ELF must also be calculated. The daily base consumption (1089) is determined by subtracting the lowest value (1665) from the highest cooling-season value (2754) in the daily use column of the EUP report.

From the spreadsheet, take the demand from September 2002 (the month with the peak cooling-season actual demand) and subtract the lowest monthly demand from the spreadsheet (195 – 140) to determine the cooling-season base demand (55). Thus, the summer ELF is

These calculations show that the cooling equipment is operating beyond building occupancy (82% versus 33%) Therefore, excessive equipment run times should be investigated. Note that comparing the ELF to the occupancy factor is meaningless for buildings occupied 24 h a day, such as hospitals.

Figure 3. Comparison Between Actual and Billed Demand for Atlanta Example Building

Similar tables and charts may be created for natural gas, water, and other utilities.

The Atlanta example building has a ratchet-type demand rate (see Chapter 56), and billed demand is determined as a percentage of actual demand in the summer months. The ratchet is illustrated in Figure 3, where billed demand is the greater of the measured demand or 95% of the highest measured demand within the past 12 months. The billed demand for January of year 3 was 171 kW (171 = 0.95 × 180), or 95% of the actual demand from July of year 2.

In Table 1, the actual demand in the first six months of 2003 had no effect on the billed demand, and therefore no effect on the dollar amount of the bill; the same is true for the last three months of the year. Because of the demand ratchet, the billed demand in January 2004 (171 kW) was set in July 2003. This means that any conservation measures that reduce peak demand will not affect billed demand until the following summer (e.g., June to September 2004); however, consumption savings begin at the next billing cycle. The effect of demand ratchet rates is that any conservation measures implemented have a longer initial payback period simply because of the utility rate structure. The energy manager should investigate other rate structures, such as a time-of-use (TOU) or seasonal rates. Rate structures for smaller buildings may not include demand charges.

Benchmarking (comparing a building’s normalized energy consumption to that of similar buildings) can be a useful first measure of energy efficiency. Relative energy use is commonly expressed in energy utilization index (EUI; energy use per unit area per year) and cost utilization index (CUI; energy cost per unit area per year). The Atlanta example building is 30,700 ft² in size, so its 2004 EUI is 76,200 Btu/ft² and its CUI is $1.47/ft².

Two sources of benchmarking data for U.S. buildings are ENERGY STAR (www.energystar.gov) and the U.S. Department of Energy’s Energy Information Administration (DOE/EIA). Data on U.S. buildings in all sectors are summarized in periodic reports by the DOE/EIA. Tables 2 to 4 present DOE/EIA CBECS data in a combined format. Table 2 lists EUI input data and EUI distributions for the buildings surveyed in 2003. Table 3 lists the 2003 Commercial Buildings Energy Consumption Survey (CBECS) electricity per unit of floor area, and Table 4 shows CUI distributions. More complete and up-to-date information on the CBECS is available at www.eia.doe.gov/emeu/cbecs. When referring to these tables, keep in mind the facility’s operating or occupied hours of facility and current utility rates.

Databases. Compiling a database of past energy use and cost is important. All reliable utility data should be examined. ASHRAE Standard 105 contains information that allows uniform, consistent expressions of energy consumption in new and existing buildings.

The energy use database for a new building may consist solely of typical data for similar buildings, as in Table 2. This may be supplemented by energy simulation data developed during design. A new building should be commissioned to ensure proper operation of all systems, including any energy-efficiency features (see ASHRAE Guideline 1.1 and Chapter 43).

All the data presented in these tables come from detailed reports of consumption patterns, and it is important to understand how they were derived. When using the data, verify correct use with the original EIA documents.

Mazzucchi (1992) lists data elements useful for normalizing and comparing utility billing information. Metered energy consumption and cost data are also published by trade associations, such as the Building Owners and Managers Association International (BOMA), the National Restaurant Association (NRA), and the American Hotel and Lodging Association (AH&LA). In some cases, local energy consumption data may be available from local utility companies or state or provincial energy offices.

Additional energy use information for homes and commercial buildings in Canada can be found at the Office of Energy Efficiency at http://www.oee.nrcan.gc.ca/corporate/statistics/neud/dpa/data_e/publications.cfm. In Europe, benchmarking data are defined on a national basis in the frame of the European Directive on the Energy Performance of Buildings (EPBD) (EC 2010). Balaras et al. (2007) provides an overview of relevant data for residential buildings, although detailed data for commercial buildings are rather limited (Gaglia et al 2007).

The objective of an energy audit is to identify opportunities to reduce energy use and/or cost. The results should provide the information needed by an owner/operator to decide which recommendations to implement. Energy audits may include the following:

ASHRAE (2004) identifies the following four levels of effort in the audit process.

Preliminary Energy Use Analysis. This involves analysis of historic utility use and cost and development of the energy utilization index (EUI) of the building. Compare the building’s EUI to similar buildings to determine if further engineering study and analysis are likely to produce significant energy savings.

Level I: Walk-Through Analysis. This assesses a building’s current energy cost and efficiency by analyzing energy bills and briefly surveying the building. The auditor should be accompanied by the building operator. Level I analysis identifies low-cost/no-cost measures and capital improvements that merit further consideration, along with an initial estimate of costs and savings. The level of detail depends on the experience of the auditor and the client’s specifications. The Level I audit is most applicable when there is some doubt about the energy savings potential of a building, or when an owner wishes to establish which buildings in a portfolio have the greatest potential savings. The results can be used to develop a priority list for a Level II or III audit.

Level II: Energy Survey and Analysis. This includes a more detailed building survey and energy analysis, including a breakdown of energy use in the building, a savings and cost analysis of all practical measures that meet the owner’s constraints, and a discussion of any effect on operation and maintenance procedures. It also lists potential capital-intensive improvements that require more thorough data collection and analysis, along with an initial judgment of potential costs and savings. This level of analysis is adequate for most buildings.

Level III: Detailed Analysis of Capital-Intensive Modifications. This focuses on potential capital-intensive projects identified during Level II and involves more detailed field data gathering and engineering analysis. It provides detailed project cost and savings information with a level of confidence high enough for major capital investment decisions.

The levels of energy audits do not have sharp boundaries. They are general categories for identifying the type of information that can be expected and an indication of the level of confidence in the results. In a complete energy management program, Level II audits should be performed on all facilities.

A thorough systems approach produces the best results. This approach has been described as starting at the end rather than at the beginning. For example, consider a factory with steam boilers in constant operation. An expedient (and often cost-effective) approach is to measure the combustion efficiency of each boiler and to improve boiler efficiency. Beginning at the end requires finding all or most of the end uses of steam in the plant, which could reveal considerable waste by venting to the atmosphere, defective steam traps, uninsulated lines, and lines through unused heat exchangers. Eliminating end-use waste can produce greater savings than improving boiler efficiency.

A detailed process for conducting audits is outlined in ASHRAE (2004).

Control Energy System Use. The most effective method to reduce energy costs is through discretionary operations, such as turning off equipment when not needed. Ways to conserve energy include the following:

Purchase Lower-Cost Energy. This is the second most effective method for reducing energy costs. Building operators and managers must understand all the options in purchasing energy and design systems to take advantage of changing energy costs. The following options should be considered:

Optimize Energy Systems Operation. The third most effective method for reducing energy costs is to tune energy systems to optimal performance, an ongoing process combining training, preventive maintenance, and system adjustment. Tasks for optimizing performance include

Purchase Efficient Replacement Systems. This method is more expensive than the other three, presents energy managers with the greatest liability, and may be less cost-effective. It is critical to ensure that possible equipment or system replacements are objectively evaluated to confirm both the replacement costs and benefits to the owner. The optimum time for replacing less-efficient equipment is near the end of its expected life or when major repairs are needed. Systems commonly replaced include

As the complexity of building systems increases, additional strategies are needed to optimize energy systems. According to ASHRAE Guideline 0-2005, approaches include recommissioning (applied to a project that has been delivered using the commissioning process), retrocommissioning (applied to an existing facility that was not previously commissioned), and ongoing commissioning (continuation of the commissioning process well into the occupancy and operations phase to verify that a project continues to meet current and evolving owner’s project requirements). See Chapter 43 for more information.

These approaches typically require a strong team effort of the facility staff and third-party consultants to identify and fix comfort problems as well as aggressively optimize HVAC operation and control. Some important measures typically implemented include

Implementing these measures has been found to reduce energy use by an average of about 20% (Claridge et al. 1998). Approaches to commissioning and optimizing operation of existing buildings can be found in ASHRAE Guideline 1.1-2007, Claridge and Liu (2000), Haasl and Sharp (1999), Kurt et al. (2003), Liu et al. (1997), Poulos (2007), and Tseng (2005).

Various energy-efficiency measures (EEMs) can be quantitatively evaluated from end-use energy profiles. Important considerations in this process are as follows:

Accurate energy savings calculations can be made only if system interaction is allowed for and fully understood. Annual simulation models may be necessary to accurately estimate the interactions between various EEMs.

Using average costs per unit of energy in calculating the energy cost avoidance of a particular measure is likely to result in incorrect energy costs and cost avoidance, because actual energy cost avoidance may not be proportional to the energy saved, depending on the billing method for energy used.

PNNL (1990) discusses 118 EEMs, including the following:

In addition, previously implemented energy-efficiency measures should be evaluated to (1) ensure that devices are in good working order and measures are still effective, and (2) consider revising them to reflect changes in technology, building use, and/or energy cost.

In establishing EEM priorities, the capital cost, cost-effectiveness, effect on indoor environment, and resources available must be considered. Factors involved in evaluating the desirability of energy-efficiency measures are as follows:

Project success also depends on the availability of

Some owners are reluctant to implement EEMs because of bad experiences with energy projects. To reduce the risk of failure, documented performance of EEMs in similar situations should be obtained and evaluated. One common problem is that energy consumption for individual end uses is overestimated, and the predicted savings are not achieved. When doubt exists about energy consumption, temporary monitoring or spot measurements should be made and evaluated.

Electrical equipment and appliances, from lighting systems and office equipment to motors and water heaters, provide useful services; however, the electrical energy they use eventually appears as heat within the building, which can either be useful or detrimental, depending on the season. In cold weather, heat produced by electrical equipment can help reduce the load on the building’s heating system. In contrast, during warm weather, it adds to the air-conditioning load.

Energy-efficient equipment and appliances consume less energy to produce the same useful work, but they also produce less heat. As a result, efficient electrical equipment increases the load on heating systems in winter and reduces the load on air-conditioning systems in summer. Effects of energy-efficient equipment and appliances on energy use for building heating and air conditioning systems are commonly called interactive effects or cross effects.

When considering the overall net savings of an energy-efficiency measure, it is important to consider its interactive effects on building heating, cooling, and refrigeration systems. Weighing the interactive effects results in better-informed decisions and realistic expectations of savings.

The percentage of heat that is useful in a specific building or room depends on several factors, including the following:

Unfortunately, interactive effects are often quite complex and may require assessment by a specialist; for details, see Rundquist et al. (1993).

Financing alternatives also need to be considered. When evaluating proposed energy management projects, particularly those with a significant capital cost, it is important to include a life-cycle cost analysis. This not only provides good information about the financial attractiveness (or otherwise) of a project, but also assures management that the project has been carefully considered and evaluated before presentation.

Several life-cycle cost procedures are available. Chapter 37 contains details on these and other factors that should be considered in such an analysis.

Capital for energy-efficiency improvements is available from various public and private sources, and can be accessed through a wide and flexible range of financing instruments. There are variations and combinations, but the five general mechanisms for financing investments in energy efficiency are the following:

An organization may use several of these financing mechanisms in various combinations. The most appropriate set of options depends on the type of organization (public or private), size and complexity of a project, internal capital constraints, in-house expertise, and other factors (Turner 2001).

It is important to determine performance factors of the energy management program. These are expressed in terms of key performance indicators (KPIs). The definition of key performance indicators determines what data need to be collected, how often to collect it, and how to present it to senior management. Suggested basic key performance indicators are

Energy Policy Act. The Energy Policy Act (EPAct 2005) set goals for federal buildings to decrease their energy consumption by 2% per year between 2006 and 2015, compared to a baseline of 2004 consumption. Thus, by 2010, for example, the target percentage reduction from 2004 values was 10%. For this initiative, the following sample KPI definitions could be used:

Executive Order 13514 October 2009. Executive Order 13514 further set goals for U.S. federal agencies to develop and implement strategic energy sustainability plans for 2011 through 2021 to reduce buildings’ energy use intensity (EUI), increase renewable energy use, obtain net-zero-energy buildings by 2030, and ensure that all products and services are ENERGY STAR or Federal Energy Management Program (FEMP) designated.

ENERGY STAR Tools. The U.S. Environmental Protection Agency’s (EPA) ENERGY STAR web site offers the free online benchmarking tool, Target Finder (I-P units only; accessible from https://portfoliomanager.energystar.gov/pm/targetFinder). This tool compares actual building performance to target values, and to other similar buildings. Figure 4 shows sample results for the Atlanta example building’s general office space (omitting the computer center’s floor space and electricity use). ENERGY STAR also offers an online Portfolio Manager (https://portfoliomanager.energystar.gov/pm), which provides secure performance data management and benchmarking for multiple buildings. Annual benchmarking with these (or similar) tools helps track improvements, both over time and in comparison with other buildings.

The ASHRAE Building Energy Quotient (beQ) labeling program rates new and existing buildings (Jarnagin 2009). Like the EPA’s ENERGY STAR program, beQ focuses solely on energy, but provides additional features, including potential side-by-side comparison of operational and asset (as-designed) ratings; peak-demand reduction and demand management opportunities; on-site renewable energy; indoor environmental quality indicators; and a list of operational features, including commissioning activities, energy-efficiency improvements, and information on improving performance. The beQ scale allows differentiation among buildings at the highest levels of performance and encourages the design and operation of net-zero-energy buildings.

Figure 4. ENERGY STAR Rating for Atlanta Building

The beQ program provides an easily understood scale to convey a building’s energy use to the public. Through an on-site assessment, the building owner is provided with building-specific information that can be used to improve the building. Documentation on previous energy-efficiency upgrades and commissioned systems is also included. With procedures for both an asset and operational rating, building owners can make side-by-side comparisons that could further reconcile differences between designed and measured energy use.

The label itself is the most visible aspect of the program (Figure 5). It is simple to understand and is targeted at the general public. It could be posted in a building lobby and could satisfy compliance with many of the programs being developed at the state and local level requiring display of energy use. The certificate contains technical information that explains the score on the label and provides information useful to the building owner, prospective owners and tenants, and operations and maintenance personnel. This includes many of the value-added features described previously. The documentation accompanying the label and certificate provides background information useful for engineers, architects, and technically savvy building owners or prospective owners in determining the current state of the building and opportunities for improving its energy use. More information is available at http://buildingeq.com/.

Figure 5. ASHRAE beQ Label

Throughout the European Union, the European Commission’s directive on the energy performance of buildings (EPBD) has been in effect since January 4, 2006. Despite difficulties, all EU member states have brought into force national laws, regulations, and administrative provisions for setting minimum requirements on the energy performance of new buildings and for existing buildings that are being renovated, as well as energy performance certification of buildings. Additional requirements include regular inspection of building systems and installations, assessment of existing facilities, and provision of advice on possible improvements and alternative solutions. The objective is to properly design new buildings and renovate existing buildings in a manner that will use the minimum nonrenewable energy, produce minimum air pollution as a result of the building operating systems, and minimize construction waste, all with acceptable investment and operating costs, while improving the indoor environment for comfort, health, and safety.

An energy performance certificate (EPC) is issued when buildings are constructed, sold, or rented out. The EPC documents the energy performance of the building, expressed as a numeric indicator that allows benchmarking. The certificate includes recommendations for cost-effective improvement of the energy performance, and it is valid for up to 10 years.

According to the EPBD, minimum energy performance requirements are set for new buildings and for major renovations of large existing buildings in each EU member state. Energy performance should be upgraded to meet minimum requirements that are technically, functionally, and economically feasible. In the case of large new buildings, alternative energy supply systems should be considered (e.g., decentralized energy supply systems based on renewable energy, combined heat and power, district or block heating or cooling, heat pumps). The concerted action (CA) EPBD that was launched by the European Commission provides updated information on the implementation status in the various European countries (www.epbd-ca.eu).

The next step is to create a tracking mechanism to provide high-level KPI views, giving an overall indication of energy performance. Daily monitoring can be a valuable, proactive tool. Most DDC systems can monitor energy performance and notify the energy engineer when energy usage is off track.

For example, using the data presented in Table 1, a daily target usage/day could be determined based on outside air temperature and building occupancy schedule. If the daily use rises above the target use by a predetermined amount, the DDC system can indicate an alarm and send a notification. The energy manager can then investigate the cause of the discrepancy and correct any operational errors before long-term performance is affected. When implementing this type of performance-monitoring strategy, it is important that the measurement and verification plan provide standard operating procedures (SOPs) to facilitate troubleshooting of energy performance alarms. Procedures are discussed in ANSI/ASHRAE Standard 105.

Implementing the baseline model is a three-step process: (1) the baseline period is selected, (2) the baseline model is created, and (3) one or more target models are identified to track energy performance. The baseline period should most closely reflect the current or expected building use and occupancy. Utility bill data can be used to create a steady-state baseline model of energy consumption for each building. Steady-state models are useful when using monthly, weekly, or daily data. Utility bills for an entire year are collected and used for baseline development. Many energy managers use spreadsheets to compile and compare the data. For more information on energy estimating using steady-state, data-driven models, see Chapter 19 of the 2017 ASHRAE Handbook—Fundamentals.

Cooling degree-days and heating degree-days are commonly used to track successes compared to EEM targets with respect to weather-dependent energy consumption. Local CDD and HDD information is traditionally based on a balance point of 65°F, which is not typically the actual balance point for any commercial or residential building; therefore, regional or local HDD values are only a general reference point. A building’s weather-affected energy consumption may be calculated by using spreadsheets, regression analysis, or building energy modeling software.

For larger, more complex facilities, regression analysis can be used to analyze energy consumption if the energy manager has the analytical expertise. Through linear regression, utility bills are normalized to their daily average values. Repeated regression is done until the regression data represent the best fit to the utility bill data. Figure 6 shows the scatter plot of a best-fit baseline and target models. In this example, cooling degree-days significantly affected building energy consumption, with a best fit for a base temperature (balance point) of 54°F (Sonderegger 1998). Reducing the slope and intercept constants of the baseline by 20% creates a straight-line model equation that represents a target goal for a 20% energy reduction.

The utility bill data steady-state model is also referred to as whole-building measurement and verification. More information about this process can be found in ASHRAE Guideline 14 and EVO (2002).

When developing presentation materials to document energy performance, make sure that report content shows performance as related to key performance indicators (KPIs) used by the organization. Reports should be pertinent to the audience. Whereas a report to the company’s administration would show how the energy management program affects operating and maintenance costs, a separate report to the operations staff might show how their daily decisions and actions change daily load profiles.

Figure 7 shows progress toward energy reduction goals for federal buildings presented to the U.S. Congress for fiscal year 2001 (DOE 2004). The figure compares energy performance against energy goals established in 1999.

Reports must be easy to understand by their readers. Keep management aware of the progress of changes to resource consumption, utility costs, and any effects (positive or negative) on the indoor environment as perceived by staff. Provide information on any major activities, savings to date, and future planned activities. Provide narrative reports with pie charts or bar graphs of cost per resource. Figure 8 shows an example of monthly gas use in a facility from year to year.

Figure 6. Scatter Plot, Showing Best-Fit Baseline Model and Target Models

Figure 7. Progress Toward Energy Reduction Goals for Federal Standard Buildings

Figure 8. Monthly Comparison of Natural Gas Use by Year

Each building manager or operator should use the energy team approach and identify an individual with the necessary authority and knowledge to review and fit recommendations into a building energy management plan. Because energy reduction requirements may occur with little or no advance notice, contingency plans should be developed and reviewed by the energy team. Each type of energy emergency requires a specific plan to reduce building energy use and still maintain the best possible building environment. The plan should include measures to reduce specific types of energy use in the building, as well as provisions for both slight and major energy use reduction. In some cases, existing building energy management systems can be used to implement demand shedding. The plan should be tested regularly. The following steps should be taken in developing a building emergency energy use reduction plan:

Some measures can be implemented permanently. Depending on the level of energy emergency and the building priority, the following actions may be considered in developing the plan for emergency energy reduction: