Operations of a microgrid with renewable energy integration and line switching
- 122 Downloads
With the development of new technologies and their integration to the conventional power grid, the smart grid with the capacity of satisfying power demand by large amount of renewable energy is emerging. Microgrid, a small-scale power system with clearly defined electrical boundaries and ability of self-supply, especially by distributed renewable energy, plays a big role in this process. In this paper, we study the operations of a microgrid with solar photovoltaic generators, energy storage system, and power exchanges with main power grid. More specifically, a mixed integer programming model is formulated for decision-making, such as scheduling of generators within the microgrid, islanding operations through line switching and power trades between microgrid and the main grid, charging and discharging operations of storage system, and also line switching within the microgrid, by robust optimization for capturing the uncertainties of solar power generation. To solve the robust optimization formulation, we formulate our model in order to apply the column-and-constraint generation algorithm, and perform numerical experiments on several test cases to validate the proposed model and algorithm.
KeywordsMicrogrid Renewable energy sources Strorage systems Line switching Robust optimization Column-and-constraint generation algorithm
J.L. Ruiz Duarte is supported by the Mexican National Council of Science and Technology (CONACYT) and the Mexican Department of Energy (SENER) for his PhD program. N. Fan is supported by University of Arizona Faculty Seed Grant (2016–2017).
- 11.Siddiqui, J., Hittinger, E.: Forecasting price parity for stand-alone hybrid solar microgrids: an international comparison. Energy Syst. (2017). https://doi.org/10.1007/s12667-017-0237-9
- 16.Guo, Y., Zhao, C.: Islanding-aware robust energy management for microgrids. IEEE Trans. Smart Grid (2016). https://doi.org/10.1109/TSG.2016.2585092
- 20.Heymann, B., et al.: Continuous optimal control approaches to microgrid energy management. Energy Syst. (2017). https://doi.org/10.1007/s12667-016-0228-2
- 21.Wang, H., Huang, J.: Joint investment and operation of microgrid. IEEE Trans. Smart Grid 8(2), 833–845 (2017)Google Scholar
- 25.Kazemzadeh, N., Ryan, S.M., Hamzeei, M.: Robust optimization vs. stochastic programming incorporating risk measures for unit commitment with uncertain variable renewable generation. Energy Syst. (2017). https://doi.org/10.1007/s12667-017-0265-5
- 27.Melgar Dominguez, O.D., et al.: Optimal siting and sizing of renewable energy sources, storage devices, and reactive support devices to obtain a sustainable electrical distribution systems. Energy Syst. (2017). https://doi.org/10.1007/s12667-017-0254-8
- 29.TEP. Tucson Electricity Power. Demand time-of-use (2017). https://www.tep.com/demand-tou/. Accessed 26 Apr 2017
- 30.TEP. Tucson Electricity Power. 2017 Integrated resource plan (2017). https://www.tep.com/wp-content/uploads/2016/04/TEP-2017-Integrated-Resource-FINAL-Low-Resolution.pdf. Accessed 26 Apr 2017
- 31.NREL. National Renewable Energy Laboratory. National solar radiation data base 1991–2010 update (2010). http://rredc.nrel.gov/solar/old_data/nsrdb/1991-2010/statistics/hsf/722740_2010.hsf. Accessed 26 Apr 2017