This article presents a novel mixed-integer second-order cone programming model to increase the photovoltaic (PV) hosting capacity and optimize the operation of distribution networks. The problem considers voltage and reactive (Volt/VAr) control through the optimal operation of capacitors banks, substations’ on-load tap changers, voltage regulators, and network reconfiguration with radial and closed-loop operation topologies. The proposed formulation considers voltage-dependent models for loads and capacitor banks. The objective function maximizes the PV hosting capacity of the network. Numerical experiments are carried out using the 33-node and the 85-node networks. Results demonstrate the effectiveness of the proposed formulation to increase the penetration of PV sources, especially when the closed-loop operation is allowed, together with network reconfiguration and Volt/VAr control.

This article presents a restoration approach for improving the resilience of electric distribution systems (EDSs) by taking advantage of several operational resources. In the proposed approach, the restoration process combines dynamic network reconfiguration, islanding operation of dispatchable distributed generation units, and the prepositioning and displacement of mobile emergency generation (MEG) units. The benefit of exploring a demand response (DR) program to improve the recoverability of the system is also taken into account. The proposed approach aims to separate the in-service and out-of-service parts of the system while maintaining the radiality of the grid. To assist the distribution system planner, the problem is formulated as a stochastic-scenario-based mixed-integer linear programming model, where uncertainties associated with PV-based generation and demand are captured. The objective function of the problem minimizes the amount of energy load shedding after a fault event as well as PV-based generating curtailment. To validate the proposed approach, adapted 33-bus and 83-bus EDSs are analyzed under different test conditions. Numerical results demonstrate the benefits of coordinating the dynamic network reconfiguration, the prepositioning and displacement of MEG units, and a DR program to improve the restoration process.

This article presents a new mixed-integer second-order cone programming model for solving the restoration problem in active distribution systems considering the optimal control of distributed generators (DGs), voltage regulators (VRs), on-load tap changers (OLTCs), and capacitor banks (CBs). In contrast to most of the works found in the literature, temporary loops may be formed in the network during the restorative operation state. This operating condition allows restoring the service to more loads. In this way, the objective function of the problem minimizes (i) the total load not supplied, (ii) the number of switching operations, (iii) the changes in the statuses of the voltage control devices and in the dispatch of the DGs, and (iv) the number of basic loops formed in the system. Several tests are carried out using a 53-node system for single-fault and multiple-fault scenarios. The results obtained with the proposed approach outperform the solutions achieved when only radial configurations are allowed in the problem. Moreover, it is also verified that the voltage control allows for more efficient restoration schemes.