In this paper, a novel distributed active power control method for interlinking converters (ICs) in an islanded hybrid ac/dc microgrid (IHMG) is proposed. The goal is to implement power sharing among all distributed generators (DGs) in an IHMG and among the ICs in a distributed manner, without the need for additional proportional-integral controllers. A mathematical formula for the active power references of the ICs is derived to achieve these objectives. Then, an estimator providing the data required for the reference calculation is proposed based on the modified dynamic consensus algorithm. In addition, a unified state-space model is derived for the entire IHMG, including the cyber-physical interactions, and a design method is presented for the parameters of the estimator. Finally, the effectiveness of the proposed method is verified by performing small-signal analysis and controller-hardware-in-the-loop verification. Compared to a previous distributed control method, the proposed method significantly improves the robustness in terms of communication delay and variation in the status of DGs while achieving the objectives.

We propose a new local controller to determine the active power reference for an interlinking converter (IC) of an islanded hybrid ac/dc microgrid (IHMG). The main objective of the proposed method is to improve the accuracy of global power sharing (GPS) between distributed generators throughout an IHMG to enhance the reliability and stability. Based on our analysis of the required active power of ICs for GPS, a local IC controller is proposed to enable parallel IC operation and improve GPS. The effects of the proposed controller on the system stability and GPS accuracy are also analyzed using a small-signal model. Furthermore, we provide guidelines on how to determine an appropriate control parameter for the proposed controller based on the desired GPS accuracy and the stability margin. Finally, the proposed method is verified by Simulink/MATLAB and hardware-in-the-loop experimental platform.

The grid-forming distributed generators (GFM-DGs) have attracted much attention as a key technology for realizing 100% renewable energy grids. This paper presents a novel control strategy to ensure the reliable operation of a renewable energy source (RES)-based GFM-DG even during weather variations. The GFM-DG connects a RES to the grid via source- and grid-side converters, with the converters’ common DC-link voltage $V_{DC}$ indicating the power balance between the RES and the grid. We begin by identifying the limitation of conventional strategies in maintaining $V_{DC}$ against severe weather. To address the limitation, we propose a coordinated strategy for both source- and grid-side converters to regulate $V_{DC}$ cooperatively, ensuring GFM-DG stability even in adverse weather conditions while also achieving decentralized power sharing and contributions to frequency inertia and damping. The proposed strategy is applicable to photovoltaic- and wind turbine-based generators, as well as energy storage systems. A guideline for control parameter design and stability margin analysis for weather conditions are also provided. The effectiveness of the proposed strategy is validated via small-signal analysis and simulation case studies under various conditions of 100% renewable energy grids, characterized by severe weather, load demand changes, actual line impedances, and a grid fault.

Voltage-to-power sensitivities play a key role in the control and operation of distribution networks. To estimate these sensitivities without network information, data-driven estimation methods have been studied. However, conventional methods do not consider mutual dependency (MD) of the sensitivities and thus the estimation can be inaccurate. Thus, this paper proposes a new data-driven estimation method of the sensitivities, which considers MD of the sensitivities in medium voltage distribution networks. In the proposed method, via MD analysis, the sensitivities are estimated by solving nonlinear least square problems and thus the accurate estimation can be achieved. The effectiveness of the proposed method is verified using the real-time platform.

Energy storage systems are an effective solution to manage the intermittency of renewable energies, balance supply, and demand. Numerous studies recommend adopting a shared energy storage system (ESS) as opposed to multiple single ESSs because of their high prices and inefficiency. Thus, this study examines a shared storage system in a grid-connected microgrid. By modifying the power outputs of the energy resources, this work intends to implement an economic dispatch of a shared ESS in order to satisfy the power balance and lower the overall cost of electricity. In this context, an optimization problem was formulated and developed using a mixed-integer linear programming (MILP) model. Furthermore, a pilot project (the Solar Decathlon Africa Village) in the Green & Smart Building Park (GSBP), Benguerir, Morocco, was employed to evaluate and verify the proposed approach. Some comparable scenarios were therefore run in a MATLAB environment. The collected findings demonstrate the efficacy of the developed algorithm in terms of optimizing energy cost reductions and enhancing the integration of renewable resources into the Moroccan energy mix.

In an islanded hybrid ac/dc microgrid (IHMG), ac and dc subgrids are connected via interlinking converters (ICs). For reliable operation of an IHMG, achieving distributed generators’ power sharing (DGPS) throughout the entire IHMG and ICs’ power sharing (IPS) is the main objective in an IHMG. To improve efficiency of an IHMG, minimizing operating costs of DGs is required and thus cost-minimized DGPS needs to be achieved. Similarly, when multiple ICs operate in an IHMG, efficiency-maximized IPS can further improve the efficiency of an IHMG, as total loss of ICs can vary by the IPS ratios. Thus, this paper proposes a distributed power sharing strategy to achieve cost-minimized DGPS and efficiency-maximized IPS simultaneously, without any communication lines for DGs. Incremental cost-based droop controlled DGs and distributed controlled ICs are coordinated for cost-minimized DGPS and a distributed optimal power sharing method of ICs is proposed to achieve efficiency-maximized IPS. The proposed strategy secures both cost-minimized DGPS and efficiency-maximized IPS, with only sparse communication lines among ICs, thus resulting in a significant improvement in IHMG efficiency and reliability.