@Article{ee.2024.053130,
AUTHOR = {Guo Zhao, Chi Zhang, Qiyuan Ren},
TITLE = {A Two-Layer Optimal Scheduling Strategy for Rural Microgrids Accounting for Flexible Loads},
JOURNAL = {Energy Engineering},
VOLUME = {121},
YEAR = {2024},
NUMBER = {11},
PAGES = {3355--3379},
URL = {http://www.techscience.com/energy/v121n11/58402},
ISSN = {1546-0118},
ABSTRACT = {In the context of China’s “double carbon” goals and rural revitalization strategy, the energy transition promotes the large-scale integration of distributed renewable energy into rural power grids. Considering the operational characteristics of rural microgrids and their impact on users, this paper establishes a two-layer scheduling model incorporating flexible loads. The upper-layer aims to minimize the comprehensive operating cost of the rural microgrid, while the lower-layer aims to minimize the total electricity cost for rural users. An Improved Adaptive Genetic Algorithm (IAGA) is proposed to solve the model. Results show that the two-layer scheduling model with flexible loads can effectively smooth load fluctuations, enhance microgrid stability, increase clean energy consumption, and balance microgrid operating costs with user benefits.},
DOI = {10.32604/ee.2024.053130}
}