This paper focus on optimal scheduling of microgrid including thermal and electrical loads, renewable energy sources (solar and wind), combined heat and power (CHP), conventional energy sources (boiler and micro turbine), energy storage systems (thermal and electrical storages), and series flexible alternating current transmission system (FACTS) devices. Dynamic Voltage Restorer (DVR) is included in the line between the main network and the microgrid in order to achieve a higher power transfer to the upstream grid. In the proposed method, wind speed, solar radiation, and loads are modelled as uncertain parameters based on a stochastic approach. The problem is modelled as a linear, mixed integer, constrained, and multi objective optimization one aiming at minimizing cost and pollution at the same time. Also, a sensitivity analysis is proposed for studying the sensitive parameters in microgrid management. The proposed multi objective and stochastic problem is solved by using the augmented Epsilon-constraint method. All results and calculations are obtained by using GAMS24.1.3/CPLEX12.5.1. Finally, in order to confirm the results of the proposed method, final results are compared to the genetic algorithm method. Simulation results demonstrate the viability and effectiveness of the proposed scheduling method for microgrid.

Multi objective stochastic microgrid scheduling incorporating dynamic voltage restorer

Siano, Pierluigi
2017-01-01

Abstract

This paper focus on optimal scheduling of microgrid including thermal and electrical loads, renewable energy sources (solar and wind), combined heat and power (CHP), conventional energy sources (boiler and micro turbine), energy storage systems (thermal and electrical storages), and series flexible alternating current transmission system (FACTS) devices. Dynamic Voltage Restorer (DVR) is included in the line between the main network and the microgrid in order to achieve a higher power transfer to the upstream grid. In the proposed method, wind speed, solar radiation, and loads are modelled as uncertain parameters based on a stochastic approach. The problem is modelled as a linear, mixed integer, constrained, and multi objective optimization one aiming at minimizing cost and pollution at the same time. Also, a sensitivity analysis is proposed for studying the sensitive parameters in microgrid management. The proposed multi objective and stochastic problem is solved by using the augmented Epsilon-constraint method. All results and calculations are obtained by using GAMS24.1.3/CPLEX12.5.1. Finally, in order to confirm the results of the proposed method, final results are compared to the genetic algorithm method. Simulation results demonstrate the viability and effectiveness of the proposed scheduling method for microgrid.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11386/4702256
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