Teitl: Hierarchical Microgrid Energy Management in an Office Building


Dyfyniad
Jin X, Wu J, Mu Y, et al. (2017). Hierarchical Microgrid Energy Management in an Office Building. Cardiff University. https://doi.org/10.17035/d.2017.0041619600



Hawliau Mynediad: Dim ond yn amodol ar rai telerau cytundebol y gall data fod ar gael

Dull Mynediad: I anfon cais i gael y data hwn, ebostiwch opendata@caerdydd.ac.uk


Crewyr y Set Ddata o Brifysgol Caerdydd


Manylion y Set Ddata

Cyhoeddwr: Cardiff University

Dyddiad (y flwyddyn) pryd y daeth y data ar gael i'r cyhoedd: 2017

Fformat y data: .docx, .xlsx

Amcangyfrif o gyfanswm maint storio'r set ddata: Llai na 100 megabeit

Nifer y ffeiliau yn y set ddata: 2

DOI : 10.17035/d.2017.0041619600

DOI URL: http://doi.org/10.17035/d.2017.0041619600


Disgrifiad

A two-stage hierarchical Microgrid energy management method in an office building is proposed, which considers uncertainties from renewable generation, electric load demand, outdoor temperature and solar radiation. In stage 1, a day-ahead optimal economic dispatch method is proposed to minimize the daily Microgrid operating cost, with the virtual energy storage system being dispatched as a flexible resource. In stage 2, a two-layer intra-hour adjustment methodology is proposed to smooth the power exchanges at the point of common coupling by coordinating the virtual energy storage system and the electric vehicles at two different time scales. A Vehicle-to-Building control strategy was developed to dispatch the electric vehicles as a flexible resource. Numerical studies demonstrated that the proposed method is able to reduce the daily operating cost at the day-ahead dispatch stage and smooth the fluctuations of the electric power exchanges at the intra-hour adjustment stage.

The dataset contains details of the test office building with electric vehicles integrated (thermal parameters, volume, outdoor temperature data, solar radiation data, electrical load, internal heat gain data and real-time electricity purchasing price, etc). It also contains the optimal dispatch results of the virtual energy storage system and the electric vehicles at both day-ahead and intra-hour stages.

Research results based upon these data are published at http://dx.doi.org/10.1016/j.apenergy.2017.10.002


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