The topic of this thesis is the development of a tool for an optimal energy management strategy (EMS) of the generators and energy storage systems constituent microgrids, both grid-connected or isolated (stand-alone power system) powered by Renewable Energy Sources (RES). In particular, a novel control system is designed based on the resolution of the unit commitment problem. For each time step, the proposed control system compares the expected power produced by the renewable generators with the expected load demand and determines the scheduling of the different energy storage devices and generators for the next few hours, which minimizes the operating cost of the overall microgrid. To take into account for forecasting uncertainties, the generation of the different scenarios is carried out through a discretization of the probability distribution function of the forecasting errors for wind speed, solar radiation and load requests by a set of finite states. A set of various scenarios are therefore analyzed and compared by the control system to find the minimum operating costs. The proposed algorithm is firstly applied to a microgrid at LABH2FER (Sardegna Ricerche, Italy). Since the microgrid is under construction, the expected performance is evaluated through a simulation modeling, implemented in Matlab-Simulink. Furthermore, in order to highlight the benefits of including weather forecasts and operating costs in the EMS, a comparative analysis with a simpler EMS based on control states of storage devices is carried out. The results of the comparative study demonstrate that a reduction of almost 5-10% in the annual operating costs and energy losses is achieved thanks to the implementation of the proposed control system. Moreover, the proposed control strategy is implemented and tested to a microgrid present at the University of Seville. Experimental results demonstrate the feasibility and the actual functionality of the control system. Additional benefits are also observed, such as the reduction in power exchanged with the upstream grid thanks to a better management of the storage systems.
Optimal generation scheduling for renewable microgrids using hydrogen storage systems
PETROLLESE, MARIO
2015-03-26
Abstract
The topic of this thesis is the development of a tool for an optimal energy management strategy (EMS) of the generators and energy storage systems constituent microgrids, both grid-connected or isolated (stand-alone power system) powered by Renewable Energy Sources (RES). In particular, a novel control system is designed based on the resolution of the unit commitment problem. For each time step, the proposed control system compares the expected power produced by the renewable generators with the expected load demand and determines the scheduling of the different energy storage devices and generators for the next few hours, which minimizes the operating cost of the overall microgrid. To take into account for forecasting uncertainties, the generation of the different scenarios is carried out through a discretization of the probability distribution function of the forecasting errors for wind speed, solar radiation and load requests by a set of finite states. A set of various scenarios are therefore analyzed and compared by the control system to find the minimum operating costs. The proposed algorithm is firstly applied to a microgrid at LABH2FER (Sardegna Ricerche, Italy). Since the microgrid is under construction, the expected performance is evaluated through a simulation modeling, implemented in Matlab-Simulink. Furthermore, in order to highlight the benefits of including weather forecasts and operating costs in the EMS, a comparative analysis with a simpler EMS based on control states of storage devices is carried out. The results of the comparative study demonstrate that a reduction of almost 5-10% in the annual operating costs and energy losses is achieved thanks to the implementation of the proposed control system. Moreover, the proposed control strategy is implemented and tested to a microgrid present at the University of Seville. Experimental results demonstrate the feasibility and the actual functionality of the control system. Additional benefits are also observed, such as the reduction in power exchanged with the upstream grid thanks to a better management of the storage systems.
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