In it's purest form, Load Research refers to collecting hourly electric usage data for a randomly-selected sample of customers. In 1978, the Public Utility Regulatory Policies Act (PURPA) was passed by the United States Congress as part of the National Energy Act. PURPA required that utilities collect hourly data for a sample of customers in each rate class. It was difficult and expensive at that time to do hourly metering, so a great deal of effort went into designing non-proportional stratified random samples that would minimize the number of meters needed to get valid results. The objective of the sample was to accurately determine how much that rate class contributed to the system peak use of electricity. The contribution to system peak is a significant allocator of capacity costs to each rate class.

Because of PURPA, every large utility has a Load Research sample and they know average daily load curves for each season and daytype for each customer class. In recent years, the installation of Automated Metering Information (AMI) systems has given some utilities the opportunity to greatly expand their Load Research sample at a low cost. As more utilities move to AMI systems, the sample design issue will likely become less important as sample sizes increase. In fact, there may be the opportunity to know and charge capacity allocators that are unique to each customer. For these reasons and many more, Load Research continues to be an important area of study for all utilities.

Load Forecasting builds off of Load Research data coupled with an understanding of how customers use energy to predict what annual energy use and system peak hour consumption will be in future years. Load Forecasting also benefits from understanding economic conditions and how they affect energy consumption, as well as tracking new developments in the enduses of energy. New technologies, like electric cars, bring new uses that will change existing load shapes. Energy efficiency, demand response and dynamic pricing also affect forecasts of future load requirements.

Integrated Resource Planning looks at the various ways that future load requirements can be met and determines the most cost-effective plan for moving forward. The Integrated Resource Plan commonly includes a combination of traditional generation, renewables, energy efficiency, demand response and dynamic pricing. The benefits and costs of the Demand-side Management options come directly from the results of evaluation work, effectively looping through the plan-do-check cycle.

20-year Hourly DSM Forecast. Mary created long-term hourly forecast of Demand-side Management Plan impacts for Tucson Electric Power and Unitil for the Arizona Integrated Resource Planning process. Daniel combined enduse load shapes with details of DSM plans to support the creation of an enduse-based 20-year hourly DSM forecast.(2010)

Energy Efficiency Market Penetration Study. Mary and Daniel completed a data-mining analysis of energy efficiency market penetration for the Small Commercial and Industrial customer sector at MidAmerican Energy. (2007)

Customer Segment Contributions to System Peak. Mary initiated and presented analytical information to successfully complete a collaborative ordered by the Public Service Commission of Wisconsin between WPSC and intervenors regarding the value of avoided costs in Demand Response programs. As part of this work, she supplied customer segment hourly load curves to a public intervenor for use in calculating net benefits with the DSMore model. (2005)

Integrated Resource Planning. Mary worked with Wisconsin Public Service Corporation (WPSC) generation planners on incorporation of Demand-side Management Plans into Integrated Resource Planning model (EGEAS). They used the net present value of revenue requirements method to collaborate on optimization of plan. (2004)

Appliance Saturation Survey. Mary managed the WPSC Home Energy Survey to collect saturation rates and other planning inputs from a statistically valid sample of Residential customers. She combined incentives, multiple mailings and follow-up phone calls to achieve a 70% response rate and minimize sample bias. (2003 to 2004)

Cost-of-Service for Customer Segments. Mary pioneered data-mining techniques at WPSC to estimate cost-of-service for different customer segments. The data-mining was based on a combination of survey data which identified customer characteristics and enduses with hourly meter data and hourly market prices. (2003)

New Product Development for Small Business. Mary helped develop the best new product options for the WPSC Small Business Customer strategic marketing plan using conjoint analysis. (2001)

Developing Solar Resources. Mary facilitated a “green energy” initiative and worked with WPSC staff, regulators and intervenors to develop the innovative Solarwise for Schools program which was recognized by the Department of Energy's National Renewable Energy Laboratory (NREL) as one of the best programs in the country for developing use of renewable energy. (1994)

Demand-side Management Planning. Mary combined her experience with rate design, energy markets and customer energy use to serve as Market Planning Administrator for WPSC. She led the development of a portfolio of new demand-side management programs that benefited both the utility and customers. She did this as the supervisor of a team of six professionals tasked with strategic market planning, new program and product development, department-wide budgeting, sales tracking systems, technical product research, competitive intelligence and quality improvement processes. This included monthly regulatory reporting on the net benefits of all existing demand-side management programs, as well as evaluation of net benefits for planned programs. (1992 to 1994)

Testifying in Public Hearings. Mary prepared and presented testimony on load forecasts in rate hearings and integrated resource planning hearings. She represented both WPSC and the statewide forecast. (1990 to 1994)

Statewide Load Forecast Coordination. Mary chaired the Wisconsin Load Forecast Task Force during Advance Plan proceedings. She led a group of utilities, regulators and intervenors in the collaborative development of statewide standards for reporting peak and energy forecasts, naturally-occuring conservation, and demand-side management impacts. (1985 to 1992)

Long-term Electric and Gas Load Forecasts. Mary served as a Load Forecast Analyst and later as Load Forecast Supervisor within the Rates department at WPSC. She was responsible for creating electric and gas forecasting models and contributing to the Integrated Resource Planning process. The work included creation and collection of extensive detail on customer end-use activities, modeling of naturally-occurring and program-induced demand-side management impacts, and probability-based risk analysis. She worked with generation planners using ProSim and EGEAS and contributed long-term hourly forecasts to their effort. (1982 to 1992)