Stochastic Optimization of Renewable-Based Microgrid Operation Incorporating Battery Operating Cost
Abstract
Integration of renewable energy resources in microgrids has been increasing in recent decades. Due to the randomness in renewable resources such as solar and wind, the power generated can deviate from forecasted values. This variation may cause increased operating costs for committing costly reserve units or penalty costs for shedding load. In addition, it is often desired to charge/discharge and coordinate the energy storage units in an efficient and economical way. To address these problems, a novel battery operation cost model is proposed which considers a battery as an equivalent fuel-run generator to enable it to be incorporated into a unit commitment problem. A probabilistic constrained approach is used to incorporate the uncertainties of the renewable sources and load demands into the unit commitment (UC) and economic dispatch problems.
Recommended Citation
T. A. Nguyen and M. Crow, "Stochastic Optimization of Renewable-Based Microgrid Operation Incorporating Battery Operating Cost," IEEE Transactions on Power Systems, vol. 31, no. 3, pp. 2289 - 2296, Institute of Electrical and Electronics Engineers (IEEE), May 2016.
The definitive version is available at https://doi.org/10.1109/TPWRS.2015.2455491
Department(s)
Electrical and Computer Engineering
Sponsor(s)
United States. Department of Energy
National Science Foundation (U.S.)
Keywords and Phrases
Costs; Electric batteries; Electric power distribution; Energy resources; Operating costs; Optimization; Renewable energy resources; Scheduling; Secondary batteries; Battery operation; Economic dispatch problems; Energy storage unit; Integration of renewable energies; Microgrid operations; Renewable resource; Stochastic optimizations; Unit commitment problem; Electric load dispatching; Energy storage; Microgrids; Renewable energy; Unit commitment
International Standard Serial Number (ISSN)
0885-8950
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2016 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.
Publication Date
01 May 2016
Comments
This work has been supported in part by the Department of Energy SunShot program under DE-0006341 and in part by the National Science Foundation FREEDM ERC program.