Title :
Meter data management for the electricity market
Author :
Matheson, Don ; Jing, Chaoyang ; Monforte, Frank
Author_Institution :
Bonneville Power Adm., Vancouver, WA
Abstract :
The quality of the meter data for billing and analysis is very important in the electricity market. The meter data is used primarily in billing & settlement for industrial customers and bulk trading partners who have direct access to data, and used secondarily in trading, transmission operations & planning, and load forecasting & scheduling who don´t have direct access to data. A software system called the metering data management (MDM) system has been developed using the web service technology to support the meter usage data collection, validation, estimation, versioning, and publishing at Bonneville Power Administration (BPA), a US Federal Power Marketing Agency. One of its key features is the validation and estimation of the meter usage data based on statistical models. The paper presents the infrastructure and implementation details of MDM. It also addresses a novel approach to validating the meter data and estimating missing values in the meter data. The key performance criteria of MDM are scalability, collaboration, integration, in addition to good data acquisition and data persistence capabilities. Further more, use of the meter data with weather information for more accurate validation and estimation is also discussed
Keywords :
data acquisition; invoicing; load forecasting; power markets; power meters; power system analysis computing; power transmission planning; regression analysis; Bonneville Power Administration; US Federal Power Marketing Agency; bulk trading partners; data acquisition; data persistence capabilities; electricity billing; electricity market; industrial customers; load forecasting; load scheduling; meter data management; meter data quality; meter usage data collection; regression analysis; software system; statistical models; transmission operations; transmission planning; weather information; web service technology; Electricity supply industry; Energy management; Job shop scheduling; Load forecasting; Marketing management; Power system management; Power system planning; Software development management; Software systems; Technology management;
Conference_Titel :
Probabilistic Methods Applied to Power Systems, 2004 International Conference on
Print_ISBN :
0-9761319-1-9