Power-electronics-based Medium-Voltage Direct Current (MVDC) shipboard power systems consist of several interconnected feedback-controlled switching converters. Such systems suffer from stability degradation owing to the negative incremental resistance of the Constant-Power Loads (CPLs). To tackle the stability problem, system-level stabilizing control methods were proposed acting on either the load-side or the source-side converters. In this paper, the three-phase dual-active bridge (DAB3) dc-dc converter is considered to realize the MVDC bus. A master-slave control approach is introduced which not only ensures system-level stability but also optimizes the load-sharing among the DAB3 converters. A nonlinear control technique for the master controller is compared with the PI controller with linearized feed-forward compensation. The comparison is performed through simulations in Matlab/PLECS.

The design of intelligent strategies for grid management is a cost-effective solution to increase the hosting capacity of distribution grids without investing in the reinforcement of the grid assets. This paper presents a distributed voltage control algorithm to coordinate Energy Storage Systems (ESSs) and Distributed Generation (DG) in a scenario of high renewable penetration. The proposed control algorithm relies on a dual decomposition approach and aims at mitigating possible voltage rise events occurring in the Low Voltage (LV) grid by solving an optimization problem of power minimization. Instead of using local control strategies, in the proposed solution, the voltage control burden is distributed among all the available resources in the grid, which cooperate to resolve the existing voltage violations. The performance of the developed voltage control has been tested under realistic distribution grid scenarios, using stochastic load profiles together with photovoltaic generation profiles obtained in the presence of both clear sky and cloudy sky conditions. The algorithm is also compared to a strategy that considers only DG management, highlighting the benefits associated to the proposed coordination of DG and Energy Storage Systems (ESSs).

Modern distribution grids are transforming due to the increasing amount of load and generation based on DC technologies, whose interconnection is facilitated by the upcoming AC-DC distribution networks. Their fault management is challenged by new issues related to the power transferred among AC and DC sub-networks. In light of this, the present paper proposes a novel Service Restoration (SR) algorithm, specifically tailored for AC-DC distribution grids, that optimizes the re-energization by establishing priorities of disconnected bus groups and computing, as candidate solutions, hierarchical combinations of normally open and normally closed switches. To overcome the limitations of existing approaches, a Multiple Criteria Decision Analysis (MCDA) is proposed to combine and objectively prioritize different SR goals (i.e., the use of telecontrolled switches, the minimization of power losses, and the applicability of the proposed solutions in a defined time horizon), and ultimately make the grid operator benefit from the possibility to flexibly tune different operational objectives. The proposed algorithm allows to effectively discriminating competing solutions, i.e. whence and how to re-energize disconnected buses, and complies with the time requirements for field implementation. The results prove the crucial role of DC sub-networks, associated to the control of power injection from AC-DC converters, in enhancing the SR by improving its targets and increasing the number of re-energized loads. Ultimately, the effect of MCDA comparison parameters on the SR outcomes is quantitatively investigated via global sensitivity analysis, whose adoption is recommended for supporting the grid operator in the algorithm implementation.

To support the transition to a more sustainable energy supply, interest in Multi-energy Systems (MESs) is increasing due to their ability to enhance overall system flexibility and reliability. Within this framework, control approaches play a key role, as they must address the challenges associated with the different dynamics of various energy domains and the balance between loads and the availability of energy resources. Controller Hardware-in-the-Loop (CHIL) allows for the safe testing of control applications for MESs but it is inevitably challenged by the complexity of those systems. This paper presents the CHIL set-up designed for MESs. The peculiarities of the setup are described, and its capabilities are evaluated considering a multi-timescale control architecture.

The development of strategies for distribution network management is an essential element for increasing network performance and reducing the upgrade of physical assets. This paper analyzes a multi-timescale framework to control the voltage of distribution grids characterized by a high penetration of renewables. The multi-timescale solution is based on three levels that coordinate Distributed Generation (DG) and Energy Storage Systems (ESSs), but differs in terms of the timescales and objectives of the control levels. Realistic load and photovoltaic generation profiles were created for cloudy and clean sky conditions to evaluate the performance features of the multi-timescale framework. The proposed solution was also compared with different frameworks featuring two of the three levels, to highlight the contribution of the combination of the three levels in achieving the best performance.

Modern distribution grids require the development of advanced control solutions to solve voltage issues by coordinating distributed generators and storage systems. In particular, distributed control solutions represent innovative and flexible approaches to control the voltage by means of a communication network. This paper presents the implementation of a distributed voltage control with containers, which allow a faster and more versatile implementation of the control along with the ability to model the distributed control as if it were implemented in the field. The scalability of the distributed control implemented with the containers has been demonstrated in terms of nodes activation and data exchanged by means of numerical simulations.