Impact of uncertainty and correlation on operation of micro-integrated energy system. (November 2019)

• Record Type: Journal Article
• Authors: Qiao, Xuebo; Zou, Yao; Li, Yong; Chen, Yuanyang; Liu, Fang; Jiang, Li; Cao, Yijia
• Is Part Of: International journal of electrical power & energy systems. Volume 112(2019)
• Page Start: 262
• Page End: 271
• Publication Date: 2019-11
• Subjects: Combined scenario and Monte-Carlo method -- Correlation -- Day-ahead scheduling -- Micro-integrated energy system -- Uncertainty; Electrical engineering -- Periodicals; Electric power systems -- Periodicals; Électrotechnique -- Périodiques; Réseaux électriques (Énergie) -- Périodiques; Electric power systems; Electrical engineering; Periodicals; 621.3
• DOI: 10.1016/j.ijepes.2019.03.066
• Languages: English
• ISSNs: 0142-0615

Abstract

Highlights: A combined scenario and MC method is proposed to handle the uncertainty and correlation between electricity and heat loads. The uncertainty and the correlation, affected by the MC and scenario reduction number, can accurately evaluate the operating cost of MIES. Abstract: The uncertainty and correlation of energy sources and loads bring challenges to the operation of integrated energy system (IES). In this article, a two-stage stochastic day-ahead scheduling problem on a micro-IES (MIES) is analyzed, and the correlation model of electricity and heat loads is presented as a constraint. Most importantly, for the new MIES with less or no historical data, a combined scenario and Monte-Carlo (MC) method is presented to manage the uncertainties of solar photovoltaic (PV) generation, electricity and heat loads, as well as the correlation between stochastic electricity and heat loads. The impact of uncertainty and correlation on the performance and optimal operation of the MIES are investigated under a two-stage stochastic day-ahead scheduling model. Case studies show that the proposed combined scenario and MC method is suitable for scenario generation with the consideration of uncertainty and correlation in the new MIES. The varying range of the total cost of the MIES is influenced by the MC sampling and scenario reduction number, which reflect the impact of various uncertainties. It is also demonstrated that considering correlation between the electricity and the heat loads can evaluate various cost in the MIES more accurately.