University of Tehran. Tehran (Iran)
August 9th, 2020
Summary:
This thesis focuses on the joint planning and operation of hub energy systems integrated with renewable energy sources. Three different two-stage models are presented, with two of them linking meta-heuristic algorithms in MATLAB with the CPLEX/GUROBI solver in GAMS. The third model applies Bander's decomposition approach to solve the joint planning and operation problem of the energy hub. In all three proposed models, the Monte Carlo simulation method is utilized to account for short-term uncertainties arising from electrical, heating, and cooling load demands, as well as fluctuations in renewable energy source output power. Backward scenario reduction and SCENRED methods are used to reduce scenarios. The effects of implementing various demand response programs, the presence of different energy storage systems, carbon footprint, and different installation candidates are investigated through more than 15 case studies on hub planning and operation. The results of this thesis demonstrate that the proposed models: a) significantly enhance computational efficiency, b) ensure hub stability under diverse operating conditions, and c) yield economically feasible solutions.
Keywords: Energy hub; Stochastic optimization; Demand response programs; Monte-Carlo simulation; Backward scenario reduction; Bender’s decomposition approach; Meta-heuristic algorithms.
Citation:
S.A. Mansouri (2020), Optimal planning and operation of an energy hub considering the consumers’ contribution. University of Tehran. Tehran (Iran).
