Process Efficiency

Identifying High-Value CHP Candidates

Quantifying the Statewide Potential for CHP Using an Optimized Low-Cost Methodology

Sue Haselhorst with David Larson for Zondits, November 1, 2013

In an effort to achieve greater greenhouse gas reductions and energy efficiency, program planners are turning to combined heat and power (CHP) technologies. A properly sized, thermal-following CHP system can exceed the combined efficiency of a standard boiler and electrical grid in meeting a customer’s heat and power requirements. In contrast, CHP systems that are either oversized or operated to strictly follow electric requirements can increase greenhouse gases or fail to be cost-effective for the customer. Further, planners are challenged with attempting to identify appropriate program goals and markets for this complex technology.

Addressing this need for a statewide program located in the Northeast, the evaluation team developed a straightforward and inexpensive methodology for robust estimation of statewide and sector level (by both building application type and CHP equipment type) CHP economic potential. The model also accounts for some of the achievement potential factors such as regions with restrictive interconnect requirements.

The estimation methodology utilizes individual commercial and industrial (CI) gas-customer billing-usage data as a proxy for thermal loading. Customer-by-customer monthly gas usage is analyzed to estimate base and weather-sensitive loading. Hourly weather data is analyzed to determine the full-load hours of operation of the weather-sensitive load; typical base-load profiles, mapped by SIC code, are used to determine the base-load full-load hours. An optimization algorithm selects a CHP size that meets a payback threshold. Units deemed feasible must meet a minimum size requirement, which represents the smallest commercially available units.

The end product is a rich, “bottoms-up” estimate of CHP technical and economic potential by capacity range, sector, community, and program administrator. Sensitivity analysis can examine the impact of spark-spread, base-usage hourly profiles, and building balance points on the potential.

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