Accelerated hierarchical optimization method for emergency energy management of microgrids with energy storage systems

Abstract

When failures occur in microgrids (MGs), the energy management for emergencies is required. To respond to emergencies in MGs rapidly, an accelerated hierarchical optimization method has been proposed, where the outputs of energy storage systems (ESSs) are controlled to provide urgent supports, before the MG reconfiguration starts. However, it is time-consuming to find the optimal schemes for MG reconfiguration. To reduce the time of reconfiguration, an optimization method based on deep neural networks (DNNs) for MG reconfiguration is presented, which consists of three levels. First, the combinational optimization for load shedding amounts is solved to determine the loads that have to be cut off.Second, a DNN is used to find the parameters of reconfiguration instead of the time-consuming calculation of power flow, which is a good way to reduce time of reconfiguration. Third, according to these parameters, the optimal scheme for reconfiguration is selected by a comprehensive evaluation method, where the Delphi method (DM) is employed to adjust the weights of preferences in a comprehensive evaluation function, so it offers the diversity of decisions for the MG reconfiguration. Finally, to test our method, a modified IEEE 33-bus system is built in MATLAB for simulations. Compared to traditional methods, our method can obtain the same reconfiguration scheme under different on/off states of load switches, but the time of reconfiguration is only one-sixty-seventh of that of other methods. Furthermore, in terms of our comprehensive evaluation method, reconfiguration schemes can be selected under different preferences.

Neuro-Fuzzy Based High-Voltage DC Model to Optimize Frequency Stability of an Offshore Wind Farm

“…It is anticipated that the generation of wind energy using OWFs can be nearly 54 GW in the United States [5]. The technical complexities associated with the implementation of offshore platforms and the process of transferring power from OWF to onshore power grids needs significant attention [6][7][8]. Previous studies have shown that the HVDC transmission is superior to HVAC transmission in terms of improved technical and economic feasibility, sustainability, and flexibility of integration with larger wind farms located at greater distances [9,10].…”

Joint scheduling optimization of a microgrid with integration of renewable energy sources and electric vehicles considering energy and reserve minimization

“…As a result, MGs have the potential to facilitate the widespread adoption of renewable energy sources and plug-in electric vehicles (PEVs), therefore alleviating global ecological and climate-change issues. 1,2 In addition to improving power quality and decreasing operational costs, MGs would provide additional benefits to power systems, such as decreasing power losses owing to the close proximity of the load and the generating. It is possible for MGs to operate either in synchrony with the grid or independently of it.…”

“…Microgrids (MGs) are characterized as localized power systems that use distributed generation (DG) and active consumers with upstream system connectivity. As a result, MGs have the potential to facilitate the widespread adoption of renewable energy sources and plug‐in electric vehicles (PEVs), therefore alleviating global ecological and climate‐change issues 1,2 . In addition to improving power quality and decreasing operational costs, MGs would provide additional benefits to power systems, such as decreasing power losses owing to the close proximity of the load and the generating.…”

Emergency Energy Management of Microgrid in Industrial Park Based on Robust Optimization

“…Reference [1] firstly established a naturally determined and systematic control of multiple decision variables as a robust optimal game for game players. Reference [2] introduced a robust optimal planning algorithm considering wind speed uncertainty.…”