A Real-World Test Distribution System With Appliance-Level Load Data for Demand Response and Transactive Energy Studies
Research on demand response and transactive energy systems often require granular, appliance-level demand data. However, there is no existing test system with such appliance-level data with proper temporospatial diversity in a realistic distribution system. This paper develops a 240-node real distri...
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| Autores principales: | , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
IEEE
2021
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/473fdc574c6e403eb621f9afb4a6aedc |
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| Sumario: | Research on demand response and transactive energy systems often require granular, appliance-level demand data. However, there is no existing test system with such appliance-level data with proper temporospatial diversity in a realistic distribution system. This paper develops a 240-node real distribution test system with appliance-level demand data for responsive loads. The residential appliance-level demand data are derived from smart meters connected to 1,120 homes in a real distribution system from Iowa State, hereafter called Midwest 240-Node test distribution system. A queueing load model was used to derive the appliance-level data from the smart meter data. The Midwest 240-Node test distribution system provides granular appliance-level information for all homes in the distribution system (i.e., individual appliances that constitute the home load), and the aggregate of all customer load emulates the actual smart meter data. The performance of the Midwest 240-Node test distribution system is evaluated by comparing the aggregated appliance-level demand with the actual measured smart meter data from the utility. The one-year appliance data has a mean absolute percentage error of 2.58% compared to the measured smart meter data. The test system is modeled in OpenDSS and GridLAB-D and is openly available to researchers to enable demand response and transactive energy studies with active end-users. |
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