Risk‐averse energy management system for isolated microgrids considering generation and demand uncertainties based on information gap decision theory

• DOI: 10.1049/iet-rpg.2018.5856
• Publication Date: 2019-01-08T15:52:31Z
• Authors: Mohamad‐Amin Nasr; Ehsan Nasr‐Azadani; Abbas Rabiee; Seyed Hossein Hos...
• Keywords: Demand Response; energy demand; Decision theory

There are many technical challenges for integration of renewable energy sources (RESs) in the context microgrids. Among these challenges, spinning reserve management should be accurately considered microgrid scheduling system a better operation. This study presents methodology to model and analyse novel scheme integrate RESs, particularly photovoltaic (PV) systems, diesel generation‐based isolated The proposed approach considers uncertainties PV power generation demand, simultaneously, by solving bi‐level multi‐objective optimisation problem using information gap decision theory (IGDT). is formulated considering constraints associated with load, unit commitment problem. method, non‐probabilistic approach, does not require probability density function uncertain parameters provides robust framework understand potential savings due integration. In order test perform analysis, realistic data from 20 MW hybrid project used as case study. Furthermore, method compared probabilistic techniques, such Monte Carlo simulations scenario‐based stochastic programming technique. presented studies demonstrate applicability real