There are two sides to a company’s energy profile – consumption of energy by its facility assets (HVAC, lighting, etc.) and it’s purchase of utility services (electricity, gas, etc.) In practice energy engineering teams (including ours) spend most of their time identifying opportunities for energy efficient equipment upgrades or behavior changes. Purchased utility services are usually taken as a given, with utility bills being studied for historical inflation rates, usage patterns and demand charges.
But the Enterprise Smart Grid framework highlights that to operate most efficiently companies need Visibility, Control and Management Integration for both of these elements. And here there’s a useful lesson to be taken from the information technology industry.
In the 1970′s corporations used time-sharing to access mainframe computing, paying on a per-minute, per-job basis – call it computing as a service. A decade later, microprocessor advances made it financially practical to bring PC and server computing in-house. By the late 90′s software as a service, using low cost Ethernet connected servers, made it equally attractive for companies to move their computing back out to the network, this time the Internet.
So over a thirty year period technology advances shifted the best economics for corporate IT from pay-for-service, to owning and back to pay-for-service.
Power stations (electricity as a service) predate corporate IT by almost a century, first being delivered in the late 1880′s. Like the mainframe model, utility providers centrally manage a high capital cost system (a generator) and deliver the service (electrons) over the network (the electrical grid) with customers paying as they go for what they consume. Generally they’ve had few alternatives to buying their electricity in this local utility pay-for-service model. Only a handful of the largest industrials have been able to cost justify installing and operating their own on-site primary generators. Also, in the last decade companies in deregulated markets have been able to hedge a portion of their electricity costs by purchasing third-party power generation.
With the latest solar PV technology advances (and renewable incentives) some have considered bringing a portion of their electricity generation back in-house. But with today’s average US cost of $0.11kWh, the math still points to pay-for-service (i.e. solar PPAs) and that only in four to five states in the country.
Steam as a service (Saas) is less well known, but has also been in existence for almost a century. The industry’s trade association (International District Energy Association) started in 1909. Universities and hospitals have run their own steam systems for a long time; with Harvard’s Blackstone plant having been in service since the late 1800′s. NYC’s ConEd network, operating since 1882, is the largest in the US.
As with electric utilities, the Saas model runs a centrally managed high capital cost system (a boiler or cogen plant) to deliver the service (Btus) over the network (physical steam piping.) Technology has not changed so rapidly in steam generation, with the latest large boilers moving from @ 70 to 80 percent efficient over the last 50 years. While 90% efficient systems are in development, their high cost likely make them impractical for quite some time.
The corporate alternative to Saas involves installing a large on-site steam boiler and retrofitting a building’s mechanical system. Where PV is renewable, solid state and overproduction can be sold back to the grid, financially modeling on-site steam is more complicated, including estimating future gas prices, a total maintainance cost for a lot of moving parts and a less clear excess steam utility sell back model. (For an reference point on the cost of running a 100-mile steam pipe network check out ConEd’s 2010 long-term investment plan)
Recently we performed an energy assessment on a 20-story New York City commercial building still using district steam from ConEd. Our analysis confirmed a three-year 40% increase in our customer’s cost of steam, this coming principally through newly assessed demand charges. So the bring it in-house payback model needed to forecast the future cost of ConEd steam versus the new boiler and retrofit cost, the future cost of gas at a 20% premium to ConEd’s high volume cost, the on-going maintenance costs, with the ConEd incentives which supported this retrofit. (Another reminder of why utility incentives needed to be decoupled)
The simple payback was 5 years. Which means NYC steam as a service has officially priced itself out of the market and we’ll be working with this customer to bring their “mainframe” in-house.
Another alternative for the largest corporate users is a pay-for-service delivered by a non-utility third party. Like solar PPAs for electricity, these vendors specialize in owning, operating and maintaining large traditional boilers, chillers, cogen and electric generator systems for single or multiple tenants, selling chilled/heated water, electricity or heat with long term purchase contracts. But these agreements do have their challenges – and don’t lend themselves towards a customer changing their mind after a few years.
In a world where utility rates and incentives are dynamic, energy costs are likely to be accelerating (after a three-year hiatus) and new energy technology development is being introduced, our engineers should expect to be performing more of this in-house vs. pay-for-service tradeoff analysis.
Top business schools Harvard, Kellogg and University of Chicago have entire departments studying Organizational Behavior (OB). Wharton even has an annual conference called OB. The OB curriculums are cross-disciplinary, combining psychology, anthropology, economics and political science, as they consider how organizations work and how managers can best drive posititve change.
How money can be used as a motivational tool is a long-standing OB research topic. While even healthcare firms consider how to pay people to take better care of themselves, McKinsey’s post crash research highlights that financial reward is less effective than providing employees the opportunity to lead and recognition by management for strong performance.
With ESG Visibility and Control, companies can use real energy use/cost data as the basis for both types of motivational tools, financial and non-financial. The most significant energy efficiency behavior changes will come when companies integrate all of them, empowering managers with authority (lead), recognizing their impact (energy savings) and using the savings as a quantifiable financial incentive (financial reward).
Depending on the type of business we see a few different ways to make this happen:
We’ve already commented on how line managers can use ESG energy data from their production lines as a new metric – energy cost per unit of product produced. These managers already have the authority and incentive to act, but have lacked the management system to enable them to make the best decisions. Once given this new data, behavior change can be driven by the motivation to direclty impact their P&L, a very quantifiable and measureable metric. Obviously managment incentives are regularly tied to P&L, coupling incentive to behavior change.
In Commercial Office buildings:
Office environment facility managers, responsible for a BMS controlling all HVAC and other major systems, typically have the capacity, but not the authority nor financial incentive to reduce energy consumption in their buildings. These managers are trained to avoid any complaints by a building occupant – their implicit management metric is how few complaints they receive.
But they also know that by shutting down systems during low traffic or unoccupied periods they can save energy. Simple activities such as turning off the escalators at night, alternating elevators, or dialing down the A/C when less that a dozen people are in the cafeteria can save real money. These can even be programmed into the BMS schedule. But these facility managers need the authority to act and to be relieved of the misleading complaint metric.
How about providing them instead a direct financial reward for taking these actions and a company green team sign saying ”these escalators are off now, reducing our energy use by X annual kWh”?
In Retail Stores:
Many store managers already have direct incentive to manage floor sales teams using sales results as their measureable management metric. Their activies are often geared around driving sales through effective promotions, the customer in-store experience and having the right products in stock.
By providing energy consumption and cost visibility tools to these store managers, a company can apply a new goal which, like sales, has a compensation impact. During our research we’re learned of one large retailer who conducted energy usage competitions between stores posting results on the store’s backroom bulletin board.
By their very nature distribution centers are rarely occupied by large staffs. While DC managers are in the position to understand their facility’s regular traffic patterns, they’ll now see how much can be saved by shutting down systems. But they too need the management incentive to act.
With the right financial incentive, these managers can “micro-zone” their facilities, shutting down systems in low traffic areas, time-shifting fork lift charging stations, or reducing conditioning costs where dock doors are left open unnecessarily.
But in each of the above examples someone “higher up” needs to lead a new managment approach. Authority and incentives get defined at the top – and that is where real Organizational Behavior change occurs.
Today’s hype around Smart Grid 2.0 continues to be focused on utilities and the homeowner.
Policy makers predict intelligent networks of electrons flowing in and out of the home. The theory is that during peak-pricing, high-demand periods, utilities will save homeowners money by automatically slowing down their air conditioners and refrigerators and buying electricity from their solar array and the electric vehicles plugged into their garage. And consumers, receiving continuous electricity usage & cost updates via web, email, text, Facebook and Nintendo, will change their behavior.
This last point is the trickiest. Our engineers can model energy savings from intelligent systems based on past operating history, but predicting savings from behavior change is more challenging. We’ve seen $4 gasoline drive behavior change. At some price, consumers will choose to dry their clothes at 11pm instead of 4pm. But for now we’re still guessing on how significantly electricity cost signaling can drive consumer behavior change.
Recently we installed an energy monitoring and control system for a large industrial customer. Like the utility Smart Grid, this Enterprise Smart Grid provides our customer with visibility, intelligent control and integration into their business.
The system monitors facility-wide consumption of gas, electricity and water. Instead of monthly utility bills sitting in boxes in the purchasing department, current and historical usage is continuously reported, visible across the corporate intranet, with alarming for extraordinary events enabled.
The business rules around controlling demand, integrating with OpenADR and participating in Demand Response events can now be built into the system.
But the system’s most powerful effect comes from its integration with the company’s accounting system.
Previously energy costs were considered general overhead, assigned pro-rata to each department or product line based on an annual management estimate. As line managers couldn’t change this overhead allocation, they had limited motivation to reduce energy consumption. Participating in Demand Response events was an annoyance. And when our team installed an energy-saving retrofit project somewhere in the plant it didn’t show up on that manager’s radar screen.
With sub-meters on pumps, presses and furnaces actual product line energy usage and costs are now reported into the P&L, giving line managers a new metric: cost of energy per product produced. Which means it matters. Demand Response dollars can now flow back into their business as contribution margin. All of a sudden shutting down a large gas-fired furnace for the weekend during a quiet period has a direct impact on their bottom line. And all this affects that manager’s performance bonus.
Now that intelligence really has the chance to drive behavior change.