Last year we explored the truism that “we only manage what we measure.” With energy and greenhouse gas emissions, this is only part of the truth. The adjusted version probably should read “we only manage what we see.” More important is the relevance of the selected data and how it’s presented to key decision makers accountable for energy-related decisions. Having good energy data is a prerequisite for effective energy management; knowing how to use it is a skill that needs to be developed.
This was highlighted recently in the experience of a global manufacturer at a plant in Asia. Many Asian regions are struggling to keep up with growth in electricity demand. Curtailment of supply is sometimes the only option the local utility has to meet all customers’ needs equitably. In this case, regional and national policy recognizes the systemic challenge and encourages good energy practices and efficiency through both incentives and regulation. There also is added pressure to slow the growth of greenhouse gas emissions, most coming from electricity.
In the real world, curtailment through efficiency usually takes much longer than curtailment through restricted supply, the latter often disrupting production volume and potentially threatening product quality. The plant in question was threatened by a significant curtailment action costing millions of dollars of lost production and reduced productivity. However, the plant also was part of a company that had put in place first-class energy management practices over many years. As a result, it had excellent data and management practices. It also had leadership that understood how to use it to their best advantage.
Plant management sat down with the utility and showed how the plant’s energy management not only met their needs, but also contributed to the region’s efficiency. Management also was able to state, with a high degree of confidence, that future demand targets would be met based on the combination of historic performance and management disciplines. As a result, the plant was excluded from the curtailment and avoided significant production disturbance.
This is a striking example of capturing major energy-related economic benefits through effective energy management. The value of maintaining production levels is as much an avoided energy cost as any utility discount or cost reduction derived from efficiency. This team not only had the right energy data readily available, it also knew how to use it.
Similarly, I’ve been struck by the power of presenting complex energy data in an understandable way with some community work in the Washington, D.C., area. Communities around the world are recognizing the need to develop strong local energy plans to ensure the energy supply’s reliability, environmental performance and competitiveness. Like all good plans, an essential step is to understand the current use of energy in homes, commercial and public buildings, industry and transport in the community. This is a daunting, complex task. Even for a single community, this took many weeks of painstaking work.
Layers of spreadsheets were reduced to a couple of pie charts for the discussion with the business, political and community leadership. These clearly showed that about half of all the energy the community consumed, and paid for, was used to convert fuel to electricity and, therefore, had no direct value. This even included the diesel and gasoline sold in the community. This simple graphic was a real eye-opener for many, and it was a short step to the realization that, even in this single suburb of Washington, D.C., the cost of this conversion was hundreds of millions of dollars.
This immediately raised the obvious question: How can the non-productive half of the energy costs be reduced? The same pie charts suggested two strategies. The first, unsurprisingly, was to get serious about efficient building construction, renovation and operation. The second was to turn into useful energy the heat that making electricity wasted. The next logical step was for the leadership to see how others had tackled the same questions. This led to global benchmarking and the realization that some cities in Europe and Asia not only had much higher efficiency levels, but also made widespread use of district energy for heating and cooling buildings of every type.
These simple visualizations of highly complex data triggered the healthy discussion currently underway in that community. This discussion is focused on two questions. The first is how deep and how fast they can double the efficiency of the building stock. The second is about the feasibility of widespread deployment of district heating and cooling, supplied by distributed combined heat and power. Both are complex questions with implications that go far beyond simple thermodynamics. They’ll ultimately be answered by predominantly non-technical decision makers.
The right data, when presented clearly and relevantly, helps decision makers make better long-term energy decisions. Are those of us in the energy business helping or hindering key decisions through our selection and presentation of data?
Peter Garforth is principal of Garforth International LLC, Toledo, Ohio. He can be reached at firstname.lastname@example.org.