Grid Coordination
A new goal for zero net energy projects

Zero Net Energy Buildings are all the rage these days. These buildings have on-site renewable energy assets that, over the course of a calendar year, generate at least as much energy as is consumed by and within the building over that period of time.

According to New Buildings Institute, 58¹ buildings have achieved Certified or Verified Net-Zero status, which means that a third party has reviewed actual operating data for at least one full year that demonstrates net-zero energy operation. While this feat may seem sufficiently challenging that building owner and designers can say “mission accomplished,” others have pointed out that in some cases, the performance of the whole is less than the sum of its parts.


The Problem

The problem for net-zero buildings is that they use the electrical utility grid as a battery. They export energy to the grid when their on-site generation assets create a surplus and they draw energy from the grid when their on-site assets fall short. This role presents a problem for the utility in that it must provide service infrastructure to support the building during peak import and provide infrastructure for peak export. The electrical utility grid, furthermore, must maintain a very precise instantaneous balance between load (users) and supply (generators). Failure to maintain this balance with small fractions of a percent results in poor power quality, reduced supply voltage and poor control of the frequency of the alternating current supply. This task is made more difficult because, typically, the grid manager has control only over the supply (generation) side of the equation. Users draw what they will, when they will and the manager has to juggle supply assets to maintain the balance. Net-zero buildings, furthermore, will tend to import energy from the grid when other users have maximum demand from the grid and, sometimes, will be in export mode when demand from other users is low.


Utilities meet their demand requirements with three general types of generation assets:


  1. Base load generation – large generation plants that modulate output slowly and run constantly. These include large coal-fired steam generation plants and nuclear power plants.
  2. Peaking generation – typically smaller generation assets that can be modulated precisely to track loads, and which can be kept on “hot stand-by” status to be dispatched instantaneously to meet a sudden spike in demand or a sudden loss of supply from other generation assets.
  3. Renewable generation – Most renewable generation assets, with the exception of some hydro-electric assets, have the confounding characteristic that their generation capacity is determined by environmental conditions, rather than by the operator, to the extent that they are referred to as VRE (Variable Renewable Assets). Wind generators depend upon the wind speed that varies from second to second. Photovoltaic systems have an overall diurnal generation pattern (they don’t generate at night when there is no sun), but cloud conditions, which can change rapidly, add another uncontrolled variable that determines their output. Utilities striving for a high renewable energy content in the delivered electrical supply must use their peaking generation to offset precisely the output of their renewable generation assets to the varying demand seen by the system.


As is mentioned above, electric utilities are striving to reduce their carbon footprint by increasing the renewably generated fraction of their delivered power. Most of their renewable generation assets are likely to be of the same type as those that Zero Net Energy facilities utilize for on-site generation, so that these two sets of renewable assets track one another for generation output. The net result is that the building may be in export mode precisely when the carbon content of the offset grid electricity has the lowest carbon footprint, while it may be in import mode when utility renewable energy assets are at lower generation levels. Figure 1 shows the daily schedule of marginal carbon emissions per unit of electric generation for four different power pools, for four different renewable energy generation output levels. The net result of the match between renewable generation profiles on-site and utility scale is less carbon reduction overall than might have been expected.

Figure 1. Diurnal Marginal Carbon Emissions Profiles (Mean) for Weekdays in Four Regions - Southwest Power Pool (SPP), New York (NYISO), California (CAISO) and Texas (ERCOT)²

This problem is, in fact, becoming more severe as utilities add more VRE assets. Figure 2 below shows the historical and project levels for non-VRE generation for the California utility grid on a typical spring day. Note that as the sun goes down and photovoltaic generation drops off, both for on-site building and utility scale assets, the utility must dispatch peaking generation very rapidly to offset this drop off. Failure of the incoming peaking generation to keep pace with the VRE decline can result in system-wide instability and brown-outs, or, even worse, black-outs. The resultant curve is referred to as “the Duck Curve,” with the duck’s tail in the morning hours, and the head during the evening, when photovoltaic generation is rapidly dropped off.

Figure 2. The “Duck Curve,” showing historical and projected net “non-renewable” load for the California utility grid on a typical spring day.³

The problem is demonstrated very simply by comparing the load and energy generation schedules of a typical Zero Net Energy Building, as shown in Figure 3. Note that the building has its highest energy export precisely at the time when required peaking generation is lowest. Because baseline generation has relatively high minimum part-load generation levels, and because maximum VRE asset output is a primarily a function of the weather, as the VRE fraction of overall generation capacity increases, the utility may be forced to curtail some of its VRE capacity on sunny or windy days in order to match generation capacity with the load.

Figure 3. Typical demand, production and net demand curve for a net zero energy office building for a high solar weekday.

A load duration curve shows the number of hours per year that the utility is operating at or above a certain capacity. The current load duration curve and load duration curves for various scenarios of customer energy efficiency and on-site VRE deployment are shown, for the U.K., in Figure 4. The graph for “Recent Averages” shows that the minimum load is about 18 GW because 8,760 hours (all of the hours in the year) have an equal or greater demand. The graph also shows that the top 20% of capacity is only required for 10% of the hours and that infrequent utilization of capacity is likely to get much worse in the future, with the top 30% of capacity required only 5% of the time. The negative values in the projected 2035 curve indicate that, because of distributed generation, the utility will be forced to curtail some of its VRE generation assets. Those peak capacity assets (required for less than 5% of the hours of the year), furthermore, determine the required capital emplacement to meet the demand. Utility revenue, conventionally, is a function of the total number of kWh sold, the area under the curve. Distributed energy systems (required for net-zero energy buildings) dramatically reduce the area under the curve (total kWh sold), while having only a small impact on the peak system demand. Recovering the cost of servicing a net-zero building that nominally consumes no energy but may have significant peak demand becomes problematic. The direct implications of this relationship are that, for the utility to remain solvent, the average cost of electricity per kWh must rise significantly, and that the utility must levy significant charges on Net-Zero buildings for their use of the utility as an annual energy storage medium.

Figure 4. Projected impact of distributed generation on utility load duration curves. (Note that negative values in the above graph indicate that the utility will be forced to curtail some of its photovoltaic capacity because it is not needed.)

Technical Strategies to Address the Utility Problem in Zero Net Energy Buildings.

The U.S. Department of Energy’s definition of a Net Zero Building is “an energy-efficient building where, on a source energy basis, the actual annual delivered energy is less than or equal to the on-site renewable exported

Energy,” so their annual load factor is less than zero. Yet the buildings rely upon the utility to be a storage mechanism to facilitate the non-coincidence of their energy production and consumption. Arguably, net-zero energy buildings should coordinate with the utility by to reduce the magnitude of their import peak demand during periods of low VRE production, or they should pay for the storage capacity provided by the utility. To achieve this goal, real-time communication is necessary between the building and the utility so that the building can control its operation to conform to available utility VRE capacity. This communication could be in the form of direct control of electric storage assets, or real-time pricing signals that are received by the building and are used to trigger demand response protocols.


The strategy for a grid-friendly net-zero building is to alter the profile of energy balance with the grid, reducing its energy export operation when utility VRE generation is highest, and reducing its import when utility VRE is lowest. As can be seen in Figure 1, the time of day or year for these situations can vary, so communication from the utility to the building is necessary. Multiple technologies exist to help net-zero buildings reduce their peak import demand from the utility. As mentioned before, they can generally be categorized into passive load reduction strategies and active load management strategies. Passive load reduction strategies are typically incorporated into net-zero energy buildings, but for buildings that are intended to be more grid-friendly, their intent is more specific: to minimize electric demand at the “head of the duck” between 5:00 p.m. and 9:00 p.m. when cooling loads are still high, but PV generation is fading. These strategies would include drastic minimization of solar heat gain from west exposures, while optimizing electric lighting reduction from daylight penetration -- two seemingly conflicting but reconcilable goals. One favored strategy, pre-cooling with night ventilation, will have reduced effectiveness for demand limiting at the “head of the duck” because the target period is much later in the day, probably long after any pre-cooling effect has been depleted. Another strategy, applicable in areas with predominantly solar utility VRE generation assets, such as California, is orientation of on-site photovoltaic arrays toward the east or the west, reducing their generation during the period when utility VRE generation peaks and moving it into more favorable periods of the day.


The most direct technology for active load management is electrical storage, now most commonly in the form of batteries, but first cost, which is dropping but still high, precludes their use for dramatic load shifting for long duration. In order to get the most beneficial impact out of the battery, it should be charged during periods when the utility has excess capacity for renewable energy generation and should be discharged, to offset building electrical import during periods when the utility’s renewable resources are contributing little to its generation capacity. Batteries, of course, have the inefficiencies of charging and discharging, resulting in what is called a “round-trip” efficiency of between 80% and 90%, depending upon technology. Arguably, however, 0.8 kWh of renewable energy exported to the grid at 7:00 p.m. is worth far more for overall carbon reduction than is 1.0 kWh delivered at 2:00 p.m. This intelligent dispatch of a building’s energy storage assets requires communication from the utility to the building on the current and projected immediate future disposition of renewable energy generation by the utility. Precise scheduling of the dispatch of these storage assets, either through direct utility control or through on-site algorithms responding to real-time pricing signals, will maximize the impact of their capital cost and minimize required storage capacity.


Thermal storage can also be very effective in reducing electrical load at the “head of the duck.” The operating strategy, however, would be slightly different from conventional methods of reducing peak demand through thermal storage operation. Conventionally, cooling assets are operated overnight or in the early morning to charge thermal storage that is typically discharged to offset the electric demand for cooling production over the course of the afternoon peak demand window, in order to reduce the peak electrical billing demand. Grid-coordinated operation of a thermal storage system would entail charging the thermal storage during periods of high VRE generation (both utility and on-site) in anticipation of thermal loads during periods of low output for VRE assets. Plants that utilize the same refrigeration assets for baseline building cooling and thermal storage charging may require additional capacity in order simultaneously to meet the peak cooling demand and demand for thermal storage charging during the midday “back of the duck.” Full load hours required for thermal storage capacity may vary significantly from current practice depending upon whether the local utility is wind or solar dominant.


Conventional demand response strategies can also be effective in reducing electrical import during the “head of the duck.” These include a slight reduction in baseline light-level set-points for daylight responsive lighting controls, slight elevation of dry bulb thermostat set-points and, for systems that allocate all dehumidification duties to a Dedicated Outdoor Air System (DOAS), slight increase in the room’s relative humidity set-point by raising the air temperature off the coil of the DOAS.


The simplest strategy for active load management involves manipulation of the building operating schedule, shifting the hours of operation from 8:00 a.m. to 6:00 p.m. to an earlier schedule of 6:00 a.m. to 4:00 p.m. While this strategy is very effective on the face, it might not be popular with workers, and would require massive commercial and cultural re-orientation. Another active load management strategy would take advantage of the provisions of ASHRAE Standard 62.1-2016, paragraph 6.2.6.2, for intermittent interruption of ventilation air. For an office space with 200 ft2 per person (19.5 m2/person) and a ceiling height of 9 ft. (2.7 m), the averaging period is 318 minutes. According to the letter of the standard, the ventilation air rate could be maintained at double the required rate for the first half of this period and reduced to zero during the second half. While application of the strategy according to the letter of the standard might not be optimal, over-ventilating prior to 4:00 p.m. and closing outdoor air intakes for the remainder of the workday would be an effective strategy for reducing load during this most challenging period for the utility grid. Depending upon the building, other opportunities for electric load shifting out of the critical period may also exist. No load is too small for consideration. De-energizing ice-making in ice machines, turning off pumps in water features, de-energizing electric water heaters, partially de-energizing decorative lighting, disabling dishwashers in office building break-rooms all can contribute to this goal. Although these strategies require significant levels of communication with diverse pieces of equipment and appliances, rapidly proliferating Internet-of-things (IoT) technology enables this level of control.


As mentioned previously, real-time communication between utility and building is necessary to coordinate these activities. In order to facilitate this communication, utilities should distill the myriad parameters of their system dynamic into a simple structure. Retail real-time pricing signals are one universal language. Curtailment requests with associated incentives are another, and previously agreed curtailment protocols with direct utility control are another. In whatever form, two-way communication allows the building to become a much more informed and collaborative customer.


Conclusion

The current enthusiasm for Net-zero energy buildings often neglects the necessity for coordination with the utility grid to maximize the desired goal of carbon reduction. Coordination requires adjusting both fixed strategies and operating procedures to minimize electrical export during times when the utility has excess renewable energy capacity and decrease electrical import during periods when the utility has reduced renewable capacity. Because these may vary across the day and across the year, utility status has to be communicated to the building. This will enable building operators, either human or electronic, to make intelligent decisions about how to adapt building operation to lessen the strain on the utility generation system.


Systems that are included in the building design should have the capability to shift loads from periods of deficit in utility renewable generation to periods when the utility has surplus renewable capacity. These systems should have flexibility to respond to the availability of renewable energy at any time and for projections for near term availability. Implementation of these strategies may complicate the achievement of the net-zero goal, but the result will be more beneficial than attaining a one-dimensional status for an individual building. Only when this capability is incorporated into building design do net-zero energy buildings fulfill their full capability for moving the world toward energy sustainability. Building owners and designers must realize that the ultimate goal of Zero Energy Buildings is an overall reduction in carbon emissions, and that goal may require some compromise of the individual building energy bottom line.


References

1. NBI, 2019 Getting to Zero Project List: Zero Energy Certified Buildings, New Buildings Institute, May, 2018.

2. J. Seel, A. Mills, R. Wiser, S. Deb, A. Asokkumar, M. Hassanzadeh, A. Aarabali, Impacts of High Variable Renewable Energy (VRE) Futures on Wholesale Electrical Prices, and on Electric-Sector Decision Making, Technical Report, Lawrence Berkeley National Laboratory, Berkeley, CA, May, 2018.

3. Image courtesy of California Independent System Operator (CAISO), public image.

4. R. Grubbs, A. Smith, “Hinkley Point C and Other third Generation Nuclear in the Context of the UK’s Future Energy System”. CEE Briefing Note 20160915, RCUK Centre for Energy Epidemiology. 2016.

5. K. Fowler, I. Demirkanli, D. Hostick, K. McMordie-Stoughton, A. Solana, R. Sullivan, Federal New Buildings Handbook for Net Zero Energy, Water and Waste, U.S. Department of Energy Federal Energy Management System, Washington, DC, August, 2017, p. 1.

6. D. Lew, G. Brinkman, E. Ibanez, A. Florita, M. Heaney, B.-M. Hodge, M. Hummon, and G. Stark. The Western Wind and Solar Integration Study Phase 2, NREL 2013 (general background information).

Daniel H. Nall PE, FAIA, FASHRAE, LEED Fellow, BEMP, HBDP, CPHC