A model for balance responsible distribution systems with energy storage to achieve coordinated load shifting and uncertainty mitigation. (15th June 2022)

• Record Type: Journal Article
• Authors: Lu, Xi; Xia, Shiwei; Gu, Wei; Chan, Ka Wing
• Is Part Of: Energy. Volume 249(2022)
• Publication Date: 2022-06-15
• Subjects: Power distribution system -- Balance responsible party -- Energy storage -- Flexibility -- Uncertainty -- Load shifting; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2022.123749
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: An operation model is established in this paper to fully utilize the flexibility of energy storage to reduce the operation costs of balance responsible distribution systems, which are responsible for their energy balance. Depending on whether uncertainties in outputs of renewable energy sources are involved, energy storage operation is classified into load shifting and uncertainty mitigation. Such classification enables separate analysis of the two types of energy storage operation and also facilitates their coordination to achieve optimal overall costs. To handle the computational difficulty that is brought by temporal sequences of uncertainties and track uncertainties that are mitigated by energy storage, linear decision rules are adopted to model the process of uncertainty mitigation. As a flexible device, energy storage is distinct because using its flexibility influences its state of charge and eliminating such influence is essential for recovering its flexibility. Based on these features of energy storage, keys of using energy storage to mitigate uncertainties in balance responsible distribution systems are revealed, which are aggregating uncertainties from different times and thus letting them offset each other. Through case studies, it is shown that uncertainties are better mitigated when they are better aggregated, and the aggregation level of uncertainties is limited by energy storage parameters including its maximum charging and discharging power and its capacity. Besides, it is demonstrated that the cooperation between the two kinds of energy storage operation, i.e., load shifting and uncertainty mitigation, achieves better outcomes because of more efficient use of energy storage flexibility in some cases, but it is also possible that they compete for the limited flexibility of energy storage and thus need to be coordinated in other cases. Highlights: Operation costs of distribution systems are reduced by using energy storage. Energy storage operation is classified into load shifting and uncertainty mitigation. Linear decision rules are used to track uncertainties and reduce model complexity. Keys of uncertainty mitigation are revealed to be aggregating uncertainties. Optimal costs are achieved by coordinating load shifting and uncertainty mitigation.