Emerging Transactive Energy Technology for Future Modern Energy Networks - Chapter 9: A case study in the hybrid energy network with 100 percent renewable energy resources and future directions

Elsevier, Mohammadreza Daneshvar, Behnam Mohammadi-Ivatloo, Kazem Zare, 'Chapter 9 - A case study in the hybrid energy network with 100 percent renewable energy resources and future directions', Editor(s): Mohammadreza Daneshvar, Behnam Mohammadi-Ivatloo, Kazem Zare, Emerging Transactive Energy Technology for Future Modern Energy Networks, Academic Press, 2023, Pages 135-149, ISBN 9780323911337
Authors: 
Mohammadreza Daneshvar, Behnam Mohammadi-Ivatloo, Kazem Zare

Renewable energy sources (RESs) have been taken into account as the main source of energy for future energy grids due to their tremendous benefits to the system. Ambitious recent endeavors have clarified the possibility of high RESs utilization in the grid to gain clean energy production benefits. This trend has led to the consideration of a 100 percent RESs target for the future modern energy grid. Given the necessity for appropriate models for the realization of this goal, this chapter uses transactive energy for offering an energy sharing model for the optimal scheduling of microgrids that contain 100 percent RESs for energy generation. Herein, the hydrogen storage system is also deployed to support the system against RESs uncertainties for a dynamic energy supply. An autoregressive integrated moving average technique is intended to generate scenarios for uncertain parameters while their most applicable ones are selected using a fast forward selection approach. In this study, the energy sharing possibility provided by the transactive energy has enabled the system to have flexible behaviors in the system's energy management. For covering the energy structure with fully RESs, the energy management schemes are applied, in which the price and load response plans are considered for the demand-side energy management. The modified IEEE 24-bus test system is selected to be used for verifying the applicability of the studied model. The cost-effective achievements are reached according to the extracted results from the stochastic day-ahead scheduling problem.