Turning interval meter data into analytics to improve program performance for demand-side management.
Planning for Efficiency
Forecasting the geographic distribution of demand reductions. Copyright © 2011 Consolidated Edison Company of New York, Inc.
As new energy efficiency programs proliferate, regulators increasingly will seek to use the associated demand reductions to reduce capital expenditures on new transmission and distribution assets. However, forecasting the expected geographic distribution of these demand reductions within the grid and integrating this information into a utility’s capital planning process is a challenging task.
Con Edison has included the effects of demand side management (DSM) in its capital planning process since 2003. Con Edison developed a methodology to forecast the geographic distribution—down to the network level—of expected peak load reductions from non-targeted energy efficiency programs. Our approach uses historical energy consumption patterns and demographic data, by service class and by network, to allocate the energy savings expected from the various efficiency programs operating in our service territory to individual networks. Then, composite load curves for each efficiency program are applied to calculate the coincident demand reductions at each network’s local peak.
Importantly, the forecasting approach accounts for the uncertainty (risk) introduced by the inherent geographic variability in the market penetration of efficiency programs from year to year. The inclusion of DSM in the company’s 10-year peak demand forecast has reduced projected capital expenditures for load relief projects by more than $1 billion.
With the creation of its energy efficiency portfolio standard (EEPS) in 2008, the New York State Public Service Commission voiced the hope that reducing energy consumption would also potentially reduce—or at least defer—the construction of new transmission and distribution (T&D) facilities. The commission expected that, in its words, “Establishing program targets on a utility service territory specific basis will allow utilities to factor the demand reductions from the efficiency programs into their infrastructure planning.” 1
While it’s obvious that successful energy efficiency programs can reduce peak demand, the practical task of leveraging these expected demand reductions through a utility’s infrastructure planning process is fraught with many underappreciated challenges. In particular, if utility planners are to rely on energy efficiency gains to eliminate projected peak capacity shortfalls on specific distribution circuits, utilities must be able to forecast the future geographic distribution of energy efficiency gains down the level of these circuits. This task is complicated by the fact that efficiency programs are typically designed to target specific market segments (residential, commercial, industrial, etc.), and few utility service territories have uniform demographics with regard to such segments.
For Con Edison, the forecasting challenge is very real, because the utility made a decision many years ago to only plan and build its system to supply the net forecasted demand— i.e., peak load forecast minus expected efficiency gains. Utility veterans will appreciate the magnitude of culture change implied by this decision. Convincing grid planning engineers—a profession conditioned to focus obsessively on reliability—to forego