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Integrated energy scheduling under uncertainty in a micro energy grid

Integrated energy scheduling under uncertainty in a micro energy grid

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It is expected that different energy infrastructures and resources to be operated and planned simultaneously in the future smart energy systems. Recently, the concept of energy hub and its corresponding management systems has been proposed in multi-carrier energy systems. The presented study develops a two-stage stochastic mixed-integer linear programming model for a day-ahead energy scheduling of a multi-carrier energy system, considering the time-varying energy price signals and volatility feature of renewable energy resources. In the framework of the proposed method, the objective is set to minimise the energy hub's total cost, while finding the optimal values for decision variables. A set of valid scenarios is considered for the uncertainties of loads and solar energy resources. Finally, the proposed stochastic day-ahead optimisation is tested in a case study situation. In the process of minimising the operational cost, an energy hub operator is able to fix some decisions such as energy exchange with the main grid and unit commitment, before the actual realisation of the uncertain parameters is observed. The unit commitment results also are compared with those produced by a deterministic model for the case in which the electricity flow is bidirectional.

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