Search for: All records

The interconnection of distributed energy resources (DERs) in microgrids (MGs) operating in both islanded and grid-connected modes require coordinated control strategies. DERs are interfaced with voltage source inverters (VSIs) enabling interconnection. This paper proposes a load demand sharing scheme for the parallel operation of VSIs in an islanded voltage source inverter-based microgrid (VSI-MG). The ride-through capability of a heavily loaded VSI-MG, where some of the VSIs are fully loaded due to the occurrence of an event is investigated. In developing analytical equations to model the VSI, the concept of virtual synchronous machines (VSM) is applied to enable the VSI mimic the inertia effect of synchronous machines. A power frame transformation (PFT) that takes the line ratios of the MG network into account is also incorporated to yield satisfactory transient responses of both network frequency and bus voltages in the MG network. A Jacobian-based method is then developed to take into account the operational capacity of each VSI in the VSI-MG. The resulting amendable droop control constrains the VSIs within their power capabilities when an event occurs. Simulation results presented within demonstrate the effectiveness of the proposed procedure which has great potential to facilitate efforts in maintaining system reliability and resiliency. 

Microgrids (MGs) comprising multiple interconnected distributed energy resources (DERs) with coordinated control strategies can operate in both grid-connected and islanded modes. In the grid-connected mode, the frequency and bus voltages are maintained by the utility grid. In the islanded mode, the DERs maintain the frequency and bus voltages in the MG. This paper presents a load demand sharing strategy in an islanded voltage source inverter-based microgrid (VSI-MG). The survivability of the interconnected MG in the presence of a single fully loaded VSI in an islanded VSI-MG is investigated. The concept of virtual synchronous machines (VSM) that enables the modeling of the VSI to emulate the inertia effect of synchronous machines is applied and then a Jacobian-based approach is formulated that takes into account, the capacity of the VSI. Simulation results are presented to verify the effectiveness of the approach. 

This paper develops an ensemble learning-based linearization approach for power flow with reactive power modeled, where the polynomial regression (PR) is first used as a basic learner to capture the linear relationships between the bus voltages as the independent variables and the active or reactive power as the dependent variable in rectangular coordinates. Then, gradient boosting (GB) and bagging as ensemble learning methods are introduced to combine all basic learners to boost the model performance. The inferred linear power flow model is applied to solve the well-known optimal power flow (OPF) problem. The simulation results on IEEE standard power systems indicate that (1) ensemble learning methods can significantly improve the efficiency of PR, and GB works better than bagging; (2) as for solving OPF, the data-driven model outperforms the DC model and the SDP relaxation in both accuracy, and computational efficiency.