eCite Digital Repository
Tri-stage optimal scheduling for an islanded microgrid based on a quantum adaptive sparrow search algorithm
Citation
Li, B and Wang, H and Wang, X and Negnevitsky, M and Li, C, Tri-stage optimal scheduling for an islanded microgrid based on a quantum adaptive sparrow search algorithm, Energy Conversion and Management, 261 pp. 115639. ISSN 0196-8904 (2022) [Refereed Article]
 | PDF Pending copyright assessment - Request a copy 11Mb |
DOI: doi:10.1016/j.enconman.2022.115639
Abstract
An islanded microgrid includes a combined heating and power system as well as electric vehicles. It is a key method for increasing energy efficiency, reducing pollution, and achieving carbon neutrality. Considering the uncertainties caused by renewable energy, load, and electric vehicles, this study presents a modified tri-stage scheduling method to realise the real-time dispatch of the islanded microgrid. The novel tri-stage scheduling method incorporates an information feedback mechanism into the traditional tri-stage scheduling method to address the problem of the sub-optimal solution obtained by the traditional method, which results from the significant errors between the day-ahead forecast data and intraday forecast data. In addition, users are guided by the tri-stage real-time price to charge/discharge electric vehicles orderly to fill in the valley and shave the peak of the electric load. In this study, a quantum adaptive sparrow search algorithm is proposed based on the characteristics of the tri-stage scheduling optimisation model and the limitation that the original algorithm easily falls into a local optimum. In the case study, the superiority of the novel tri-stage scheduling method, modified algorithm, and orderly charging/discharging of electric vehicles proposed in this paper are evaluated in different seasons. In the vehicle-to-grid mode, the influence of different numbers of electric vehicles on the real-time dispatch of the islanded microgrid is analyzed and discussed.
Item Details
| Item Type: | Refereed Article |
|---|---|
| Keywords: | islanded microgrid, electric vehicles, real-time price, tri-stage scheduling method, quantum adaptive sparrow search algorithm |
| Research Division: | Engineering |
| Research Group: | Mechanical engineering |
| Research Field: | Energy generation, conversion and storage (excl. chemical and electrical) |
| Objective Division: | Energy |
| Objective Group: | Energy storage, distribution and supply |
| Objective Field: | Energy systems and analysis |
| UTAS Author: | Wang, X (Professor Xiaolin Wang) |
| UTAS Author: | Negnevitsky, M (Professor Michael Negnevitsky) |
| UTAS Author: | Li, C (Mr Chengjiang Li) |
| ID Code: | 149941 |
| Year Published: | 2022 |
| Deposited By: | Engineering |
| Deposited On: | 2022-05-02 |
| Last Modified: | 2022-05-03 |
| Downloads: | 0 |
Repository Staff Only: item control page