Due to the variable nature of wind resources, the increasing penetration level of wind power will have a significant impact on the operation and planning of the electric power system. Energy storage systems are considered an effective way to compensate for the variability of wind generation. This paper presents a detailed production cost simulation model to evaluate the economic value of compressed air energy storage (CAES) in systems with large-scale wind power generation. The co-optimization of energy and ancillary services markets is implemented in order to analyze the impacts of CAES, not only on energy supply, but also on system operating reserves. Both hourly and 5-minute simulations are considered to capture the economic performance of CAES in the day-ahead (DA) and real-time (RT) markets. The generalized network flow formulation is used to model the characteristics of CAES in detail. The proposed model is applied on a modified IEEE 24-bus reliability test system. The numerical example shows that besides the economic benefits gained through energy arbitrage in the DA market, CAES can also generate significant profits by providing reserves, compensating for wind forecast errors and intra-hour fluctuation, and participating in the RT market.
Y. Gu et al., "Economic Modeling of Compressed Air Energy Storage," Energies, vol. 6, no. 4, pp. 2221-2241, MDPI, Apr 2013.
The definitive version is available at https://doi.org/10.3390/en6042221
Electrical and Computer Engineering
Keywords and Phrases
Commerce; Compressed Air; Economic Analysis; Economics; Electric Load Dispatching; Electric Power Generation; Electric Power System Planning; Electric Power Systems; Energy Storage; Pressure Vessels; Scheduling; Weather Forecasting; Wind Power; Ancillary Services Markets; Co-Optimization; Compressed air Energy Storages (CAES); Economic Dispatch; Energy Storage Systems; Large-Scale Wind Power Generations; Reliability Test System; Unit-Commitment; Compressed Air Energy Storage; Unit Commitment; Wind Energy
International Standard Serial Number (ISSN)
Article - Journal
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01 Apr 2013