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Abstract
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Energy hubs as a multi-carrier energy system with various energy carriers and conversions have been integrated
with smart grids to increase the efficiency, flexibility, and reliability of the network. Today, scheduling multienergy hubs (MEH) is one of the challenging issues in smart grids. In this paper, the optimal schedule of
interconnected MEHs based on the robust optimization in the presence of electric vehicles (EVs) is proposed. A
robust optimization approach is considered to deal with uncertainties of electrical price, renewable energy resources (RESs) generations, and electrical loads. In this paper, MEHs network include commercial, industrial, and
residential energy hubs. The energy consumption of MEHs consist of electrical, water, gas, and heat. RESs, demand response (DR) programs, heat and electrical energy storage devices are used to supply the energy demand.
The aim of the proposed model is reducing the total cost of operation and carbon emission. The price-based
demand response program is applied to shift the power consumption from on-peak to off-peak times in
response to the price signal. Finally, the problem is solved for the three cases with CPLEX under YALMIP
MATLAB. The results illustrate the effectiveness of the proposed model to achieve optimal scheduling of MEHs.
The proposed problem is organized in three scenarios, among which the scenario I determines optimal scheduling of MEHs, using robust optimization method. The scenario II investigates the problem with deterministic
model. The scenario III evaluates the problem applying robust optimization method without DR program and
energy storage device consideration in autonomous EHs. The numerical results show that the total operation cost
is increased 15.46% in scenario I compared with the scenario II due to applying the worst-case of uncertainties in
robust optimization approach.
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