Optimal scheduling modelling for wind power accommodation with compressed air energy storage and price-based demand response

2018 International Conference on New Energy and Future Energy System

Xu, C.L.^1 ; Li, L.X.^2 ; Li, Y.W.^2 ; Liu, J.Y.^2 ; Miao, S.H.^2 ; Tu, Q.Y.^2

Jiangsu Electric Power Dispatch Center, Nanjing

210000, China^1

State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Hubei Electric Power Security and High Efficiency Key Laboratory, School of Electrical and Electronic Engineering, Huazhong University of Science and Technology, Wuhan

430074, China^2

关键词: Compressed air energy storages (CAES);    Development trends;    Electricity demands;    Fuzzy chance constrains;    Optimal scheduling;    Simulation studies;    Thermal power units;    Wind power accommodations;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/188/1/012095/pdf
DOI  :  10.1088/1755-1315/188/1/012095

来源: IOP

【 摘 要 】

Nowadays, price-based demand response (PDR) programs with compressed air energy storage (CAES) systems have been rapidly developed in China for wind power generation propagation. Based on this development trend, an optimal scheduling model considering thermal power units (TUs), wind power plants, PDR mechanisms and CAES plants is studied in this paper. Considering the factors of uncertainties in PDR, wind power output and electricity demand, a fuzzy power system optimal scheduling model for minimizing the sum of TUs operation cost, CAES plants cost and wind curtailment penalty is proposed. According to the fuzzy scheduling theory, the fuzzy chance constrains are converted into their clear equivalent forms. The simulation study is implemented with using the data from the Huntorf CAES plant, which can verify the feasibility and effectiveness of the optimal scheduling model. It is found that the use of CAES and PDR results in 11.1% reduction in thermal power units operation cost and 71.6% reduction in the penalty of wind curtailment.