Scarcity events analysis in adequacy studies using CN2 rule mining  

作　　者：Fabian Heymann Ricardo Bessa Mario Liebensteiner Konstantinos Parginos Juan Carlos Martin Hinojar Pablo Duenas 

机构地区：[1]Center for Power and Energy Systems INESC TEC Porto,Portugal [2]School of Business,Economics and Society Friedrich-Alexander-Universitat Erlangen-Nuremberg Nuremberg,Germany [3]System Development ENTSO-E Brussels,Belgium [4]MIT Energy Initiative Massachusetts Institute of Technology Cambridge(MA),United States [5]PERSEE,Mines ParisTech

出　　处：《Energy and AI》2022年第2期116-123,共8页能源与人工智能（英文）

摘　　要：Dealing with scarcity events is nowadays gaining relevance in electricity market studies, as traditionally predictable generation and consumption patterns are fading. Policymakers and system planners use therefore adequacy studies to a) understand if the current market design will attract sufficient generation capacity to meet electricity demand in the future and b) to comprehend what drives system inadequacy or resource scarcity when future scenarios lack adequate capacity. This work addressed the latter and showcases a first in-its-kind rulebased methodology that filters scarcity events from a large set of electricity market simulations. In this proof-of-concept, a rule-mining algorithm is applied to outputs from ENTSO-E’s Pan-European electricity market model, which is run for 700 model scenarios, each covering 8760 time steps. The developed methodology shows how to unveil potential reasons behind scarcity events in an automated, interpretable, and scalable manner.

关 键 词：Electricity markets Data mining Security of supply Renewable energy INTERPRETABILITY 

分 类 号：F426.61[经济管理—产业经济]