Open AccessDynamic reserve demand estimation model and cost‐effectivity oriented reserve allocation strategy for multi‐area system integrated with wind power
Author(s) -
Jiang Haiyan,
Xu Jian,
Sun Yuanzhang,
Liao Siyang,
Ke Deping,
Jiang Yibo,
Tang Bowen
Publication year - 2018
Publication title -
iet generation, transmission and distribution
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.92
H-Index - 110
eISSN - 1751-8695
pISSN - 1751-8687
DOI - 10.1049/iet-gtd.2017.0868
Subject(s) - electric power system , wind power , contingency , reserve requirement , reliability (semiconductor) , estimation , computer science , mode (computer interface) , economic dispatch , reliability engineering , power (physics) , engineering , economics , physics , quantum mechanics , electrical engineering , monetary policy , linguistics , philosophy , central bank , systems engineering , monetary economics , operating system
Optimisation of reserve purchased in advance becomes increasingly essential to hedge against the growing level of power unbalance brought by the integration of large‐scale wind power. Moreover, due to the centralised integration mode of wind farms, cross‐region reserve sharing strategy becomes quite imperative. Therefore, this study presents a dynamic reserve demand estimation (DRDE) model, which synthetically considers N − 1 contingency along with load and wind forecast error. In the proposed approach, historical data is rearranged by a two‐dimensional binning technique and fitted by the versatile probability distribution model, which assisting the model reacts to different prediction level in each dispatch period dynamically. Furthermore, a cost‐effectivity oriented reserve allocation strategy for the multi‐area system is developed based on the DRDE model. The efficiency of the proposed method is tested in both 6‐bus test system and IEEE 118‐bus test system. The results show that, whether in the scenario of self‐sufficient reserve supplying or cross‐region reserve sharing strategy, the proposed estimation model effectively reduces the expectation of both load shedding and wind curtailment. Moreover, the proposed strategy improves the economy of system operation on the premise of ensuring system reliability.