Abstract
One of the main challenges in microgrid system energy management is dealing with uncertainties such as the power output from renewable energy sources. The classic two-stage robust optimization (C-TSRO) method was proposed to cope with these uncertainties. However, this method is oriented to the worst-case scenario and is therefore somewhat conservative. In this study, focusing on the energy management of a typical islanded microgrid and considering uncertainties such as the power output of renewable energy sources and the power demand of loads, an expected-scenario-oriented two-stage robust optimization (E-TSRO) method is proposed to alleviate the conservative tendency of the C-TSRO method because the E-TSRO method chooses to optimize the system cost according to the expected scenario instead, while ensuring the feasibility of the first-stage variables for all possible scenarios, including the worst case. According to the structural characteristics of the proposed model based on the E-TSRO method, a column-and-constraint generation (C & CG) algorithm is utilized to solve the proposed model. Finally, the effectiveness of the E-TSRO model and the solution algorithm are analysed and validated through a series of experiments, thus obtaining some important conclusions, i.e., the economic efficiency of system operation can be improved at about 6.7% in comparison with the C-TSRO results.
Highlights
Microgrids are small power generation and distribution systems composed of distributed power supplies, energy storage systems (ESSs), user loads, energy conversion devices, and protective devices. ey are important for the effective utilization of renewable energy resources and to improve the reliability of the energy supply under various loads
Targeting on the drawback in adopting the classic two-stage robust optimization (C-TSRO) method, an expected-scenario-oriented two-stage robust optimization (E-TSRO) model is proposed for microgrid energy management of typical islanded microgrid systems composed of renewable energy equipment, ESSs, diesel generators, and various types of loads. e model accounts for uncertainties in factors such as the power output from renewable energy sources and the load demand
Equations (16) and (17) show that the prescheduling result is affected by the two BoUs used to describe an uncertain parameter, that is, ΓT, which is related to the number of periods, and ΓS, which is related to the number of uncertain parameters
Summary
Microgrids are small power generation and distribution systems composed of distributed power supplies, energy storage systems (ESSs), user loads, energy conversion devices, and protective devices. ey are important for the effective utilization of renewable energy resources and to improve the reliability of the energy supply under various loads. Researchers have proposed two main types of uncertainty modelling methods for microgrid energy management, namely, stochastic programming and robust optimization [1]. Researchers [2,3,4,5,6] have developed stochastic programming models for the energy management of grid-connected microgrids to minimize the overall cost under uncertainties in single or multiple factors (e.g., electricity transaction price, power output from renewable energy sources, and loads). Targeting on the drawback in adopting the C-TSRO method, an expected-scenario-oriented two-stage robust optimization (E-TSRO) model is proposed for microgrid energy management of typical islanded microgrid systems composed of renewable energy equipment (wind and solar), ESSs, diesel generators, and various types of loads. E main constraints and optimization objectives of the basic model for islanded microgrid energy management are described below
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