A Robust-Stochastic Approach for Energy Transaction in Energy Hub Under Uncertainty
The global enhancement in gas-fired units has increased the rate of interdependency between electricity and natural gas networks. Nowadays, electrical systems heavily depend on reliability of gas suppliers to ramp up/ramp down during the on-peak hours and intermittent renewable generation and contingencies. Because of interdependency between electricity and natural gas system, it is imperative to co-optimize such two systems in an integrated scheme for improving the overall efficiency of the whole system and minimizing total investment and operation costs. This work proposes a hybrid robust-stochastic approach, which focuses on coordinated optimal scheduling of natural gas and electricity co-generation by considering market price contingencies. It should be noted that in proposed work, the methodology only considers purchasing power from market. The proposed model minimizes total costs of these two systems simultaneously, where both electrical and natural gas demand uncertainties are considered. On the other hand, a real-time demand response (DR) program is also considered in order to make load profile smoother to avoid technical and operational issues during on-peak hours in the system. In addition, the proposed method is applied on IEEE 24-bus RTS combined with natural gas network, and the simulation results are reported to evaluate the performance of the proposed model. The obtained results show that the proposed hybrid model has more economic efficiency and takes benefits of gas-electricity coordinated scheduling.
KeywordsHybrid robust-stochastic programming Electricity market Demand response Gas/electricity co-generation
- 2.Geidl, M., Koeppel, G., & Favre-Perrod, P. (2007, March). The energy hub–A powerful concept for future energy systems. Third annual Carnegie mellon conference on the electricity industry, pp. 13–14.Google Scholar
- 10.Wen, Y., Qu, X., Li, W., Liu, X., & Ye, X. (2017). Synergistic operation of electricity and natural gas networks via ADMM. IEEE Transactions on Smart Grid, 1–1.Google Scholar
- 13.Dolatabadi, A., Jadidbonab, M., & Mohammadi-Ivatloo, B. (2017). Short-term scheduling strategy for wind-based energy hub: A hybrid stochastic/IGDT approach. IEEE Transactions on Sustainable Energy, 99, 1.Google Scholar
- 21.Soroudi, A., & Keane, A. (2015). Risk averse energy hub management considering plug-in electric vehicles using information gap decision theory. In Power systems (Vol. 89, pp. 107–127). Singapore: Springer.Google Scholar
- 26.Bahrami, S., Toulabi, M., Ranjbar, S., Moeini-Aghtaie, M., & Ranjbar, A. M., (2017). A decentralized energy management framework for energy hubs in dynamic pricing markets. Ieeexplore.Ieee.Org
- 33.CONOPT. [Online]. Available: https://www.gams.com/latest/docs/S_CONOPT.html. Accessed 20 May 2018.