Developing a holistic fuzzy hierarchy-cloud assessment model for the connection risk of renewable energy microgrid

Abstract

Grid-connection of renewable energy microgrids (GCREM) is an important form of promoting the use of clean and renewable energy (RE). However, GCREM will bring huge risks to the power grid. Accurate evaluation and control of risks are critical to the development of GCREM. The existing research is not deep and comprehensive enough to make a reliable evaluation on the risks. The current study proposes a new evaluation framework based on the unit decomposition of the system of GCREM, and then builds a holistic fuzzy hierarchy-cloud assessment model for the risks. The main contributions of this paper are as follows: (1) decomposes GCREM risks to each functional unit of the system, and clarifies the risk transmission between the units within the system; (2) improves the accuracy of weighting risk variables based on interval type-2 fuzzy method; (3) realizes the visibility of risk evaluation and a prior judgment on its effectiveness; (4) establishes a 5-dimensional risk evaluation system of GCREM for the first time, which achieved full coverage of risk variables without the overlap between dimensions. The empirical analyses show that our model can not only assess the overall risk level of GCREM, but also identify key risk sources.