Robust operation of a multicarrier energy system considering EVs and CHP units

• Published in: Energy (Oxford) Vol. 192; p. 116703
• Main Authors: Zafarani, Hamidreza, Taher, Seyed Abbas, Shahidehpour, Mohammad
• Format: Journal Article
• Language: English
• Published: Oxford Elsevier Ltd 01.02.2020; Elsevier BV
• Subjects: Bounded uncertainty based robust optimization; Case studies; Cogeneration; Combined heat and power systems; Compensators; computer software; Constraint modelling; Demand; deterministic models; electric potential difference; electric power; Electric vehicles; electricity; Electricity consumption; Energy; Energy costs; equations; Flow equations; heat; Heating; Linear programming; Multicarrier energy system; Nodes; Nonlinear programming; Optimization; Parameter uncertainty; Peak load; Power flow; Reactive power; Robustness (mathematics); temperature; Uncertain parameters; uncertainty; Electric vehicles; Linear programming; Bounded uncertainty based robust optimization; Combined heat and power systems; Multicarrier energy system; Uncertain parameters
• ISSN: 0360-5442; 1873-6785
• DOI: 10.1016/j.energy.2019.116703

This paper presents the issue of robust operation of a multicarrier energy system (MES) or an energy hub in the presence of electric vehicles (EVs) and combined heat and power (CHP) units. Electrical and gas energies are considered as the inputs of the energy hub whereas electrical and heating energies are the outputs of the MES. In the first step, a deterministic model is developed in the MES that minimizes the energy cost of the energy hub subject to the power flow equation and limits of technical indexes in the MES, EVs parking lots, and CHP constraints. This model is similar to non-linear programming that does not obtain the global optimal point. Hence, in the next step, a linear programming method is used to obtain the global optimal point. In addition, the parameters of electricity, gas, and heating demand, electrical energy price, and EVs parameters are considered as uncertainty sources. This paper presents the bounded uncertainty-based robust optimization for an original deterministic formulation. The case study used in this paper considers 9electrical buses, 4gas nodes, and 7 heating nodes, simultaneously. Finally, the proposed method is implemented in the case study using the GAMS software. Based on numerical results, the linear programming model solves the proposed method with lower calculation time and error. Moreover, the values of parameters including demands, electrical energy, and EVs demand (EVs capacity and charge rate) increase (decrease) in the worst-case scenario (robust model) in comparison to the scenario run with the deterministic method. Additionally, the demand for power decreases at peak load times in the grid with the presence of energy hub units consisting of CHPs and EVs. Finally, because of using energy hub units as reactive power compensators and controlling power, parameters such as pressure, temperature and voltage profiles improve. •This paper presents the issue of robust operation of a multicarrier energy system (MES) or an energy hub.•Electrical and gas energies are the inputs of the energy hub whereas electrical and heating energies are the outputs.•Parameters of electricity, gas and heating demand, electricity energy price and EVs parameters are as uncertainty.•This work presents the bounded uncertainty-based robust optimization for MES.•Results were indicated, that demand of power decreases at peak load times in grid with the presence of energy hub units.