OpenDSM (formerly OpenEEmeter) is an open-source library used to measure the impacts of demand-side programs by using historical data to fit models and then create predictions (counterfactuals) to compare to post-intervention, observed energy usage.

Energy efficiency programs have traditionally focused on addressing long-term load growth and reducing customer energy bills rather than serving as reliable grid resources. However, as utilities work to decarbonize power generation, buildings, and transportation, demand-side programs (e.g. energy efficiency, load shifting, electrification, and demand response programs) must evolve into dependable, scalable grid assets. Ultimately, decarbonizing the power grid will require both supply and demand-side solutions. While supply-side production is easily quantified, measuring the impacts of demand-side programs has historically been challenging due to inconsistent and opaque measurement methodologies.

OpenDSM solves these problems with accurate, efficient, and transparent models designed to measure demand-side program impacts. OpenDSM gives all stakeholders full visibility and confidence in the results.

OpenDSM hosts a suite of modules that work together through a clear and consistent pipeline:

• EEweather pulls weather station data critical for building models.
• EEmeter creates long-term, building-level energy consumption models using billing, daily, or hourly resolution data. 
  • EEmeter is often used to measure the load impact of energy efficiency, load shifting and other programs or factors that cause an ongoing change to energy consumption.
• DRmeter (Demand Response) creates short-term, building-level models with hourly resolution data.
  • DRmeter is commonly used to measure demand response programs
• GRIDmeter uses data from non-participating customers to remove model errors in energy efficiency and demand response measurements. Errors can be due to improperly applying a linear function to a non-linear response or complex and dynamic external factors such as natural disasters, economic shifts, and public health events that would otherwise skew results.

Since 2016, the OpenDSM has been used to measure hundreds of energy efficiency, load shifting, electrification, and demand response programs. It has even been used to measure the variable impact of the COVID-19 pandemic on diverse building stock and different business sectors.

OpenDSM evolved from OpenEEmeter, which itself is a product of a decade of expert collaboration and open working groups through the CalTRACK specifications. Recurve originally developed OpenEEmeter and contributed it to LF Energy in 2019.