K-means Clustering-based Energy Efficiency Measurement of PV-Storage-Charge-Inspection-integrated Smart Stations
PV output has strong uncertainty and stochasticity,which reduces the energy efficiency measurement and de-tection performance of the PV-storage-charge-inspection integration.Therefore under the randomized sampling mode,the energy efficiency measurement and detection method of PV-storage-charge-inspection-integrated stations was proposed in this paper.First the topological structure of the PV-storage-charge-inspection-integrated station was analyzed.Second the photovoltaic output data were clustered by K-means algorithm,and the photovoltaic output scenario was generated accord-ing to the topology of power station through Beta distribution,which provided relevant data for energy efficiency measure-ment and detection.Finally the power station energy efficiency detection was modeled and the measurement and detection of energy efficiency was realized.The proposed method was indicated by experimental results accurate in detecting supply and charge/discharge powers of the PV-storage-charge-inspection-integrated station with small relative deviation of energy efficiency detection.
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