Open AccessA multi-sequence method for monthly unit combination optimization using flexible resources
Author(s) -
Cui Dai,
Fei Xu,
Weichun Ge,
Yong Min,
YongWu Zhou,
Xiao Chen,
Peng Zhao
Publication year - 2020
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/512/1/012143
Subject(s) - computer science , mathematical optimization , scheduling (production processes) , renewable energy , grid , integer programming , power system simulation , electric power system , power (physics) , engineering , algorithm , mathematics , physics , geometry , electrical engineering , quantum mechanics
In order to solve the problem of renewable power curtailment, the authors put forward a multi-sequence monthly unit combination optimization method using flexible resources. In addition, an algorithm is proposed to estimate the capacity of peak load shifting of flexible resources in day-ahead or intraday scheduling. By optimizing various types of flexible resource scheduling in day-ahead or intraday scheduling, the maximum load of the system is lessened, and the limit on the capacity of thermal power units is reduced to improve the system’s ability to accommodate renewable power. In the monthly unit combination optimization model, the total minimum output of thermal power units is introduced into the objective function, which can further reduce the thermal power start-up capacity in the monthly plan to increase the system’s spinning reserve and to expand the renewable power accommodation capacity of the system. Various practical constraints are taken into account. The mixed integer programming and software GLPK are used to program and solve the model. Finally, an example of a provincial grid in north China is given to verify the effectiveness of the proposed method.