Maximization of Distribution Network Hosting Capacity through Optimal Grid Reconfiguration and Distributed Generation Capacity Allocation/Control

Abstract

High penetration of small-scale distributed energy sources into the distribution network increase negative impacts related to power quality causing adverse conditions. This paper presents a mathematical model that maximizes distribution network hosting capacity through optimal distributed generation capacity allocation and control and grid reconfiguration. In addition to this, the model includes on-load tap changer control for stabilization of grid voltage conditions primarily in grid operating conditions related to voltage rise problems, which can limit grid hosting capacity. Moreover, the objective function allows the possibility of energy transfer between distribution and transmission grids. The proposed model considers alternative grid connection points for distributed generation and determines optimal connection points as well as install capacity while considering network operating limits. The model is cast as a multiperiod second-order cone linear program and involves aspects of active power management. The model is tested on a modified IEEE 33 bus test network.

Hosting capacity enhancement of hybrid AC/DC distribution network based on static and dynamic reconfiguration

“…Case 2: The DC line is connected to two AC buses via two VSCs. Equation (5) shows the active power flow through the DC line, while (6) shows the reactive power injection to bus i, which is connected to VSC. It should be noted that P i j in (5) is the active power flow through the VSC.…”

“…Two types of NR are dynamic, that is, grid reconfiguration using remotely controlled switches as an Active Network Management (ANM) scheme, and static, that is, grid reconfiguration at the planning stage. Static NR for the HC enhancement based on a multi-period Second-Order Cone Programming (SOCP) is proposed in [6]. A multi-period non-linear and non-differentiable integer optimization problem is proposed in [7], which uses a hybrid Particle Swarm Optimization (PSO) algorithm to solve the problem in order to increase the HC considering dynamic NR.…”

Maximization Approach of Hosting Capacity Based on Uncertain Renewable Energy Resources Using Network Reconfiguration and Soft Open Points

“…In [24], a graphical-based method was introduced to optimally reconfigure the distribution system to minimize the system power losses without the need to check the system radiality, where the introduced method was tested on different scales of distribution systems. In [25], the combination between the optimal placement of DGs and optimal NR was presented as an effective technique for maximizing the HC, where a multiperiod linear programming was utilized to solve the optimization problem. Authors in [23,26] presented various heuristic techniques to get the optimal network topology using NR to enhance the integration of the RERs.…”

Optimal DG Integration in Power Distribution Systems Using Coronavirus Herd Immunity Optimizer

“…This is done in an effort to further enhance the DS's performance, not only in terms of improving voltage stability and reducing system loss but also in terms of MDHC. For instance, different researchers offered methods to simultaneously determine the best network reconfiguration and DG integration in order to maximize the MDHC and reduce system losses [14,15]. Furthermore, some approaches were employed to maximize MDHC and improve overall system performance via well-known promising strategies using, mathematical, heuristic, and metaheuristic optimization techniques.…”