Search

• Dynamically reconfiguring the structure of multi-microgrid systems to enhance the penetration of distributed energy resources. • Vehicle-to-grid concept is deployed to capture the intermittency of renewable resources and load demand. • To make the model more accurate, the uncertainty of loads and renewables is handled by using stochastic programming. • A mathematical-based convex optimization model is established to reap the benefits of CPLEX and GUROBI as solvers. • Results illustrate that both technical and economic aspects of multi-microgrid system improved significantly. On the one hand, the inherent intermittency in demands and renewable energy sources (RES) frequently bring challenges such as overload or surplus generation within microgrids. On the other hand, electric vehicle aggregations (EVAs) have garnered substantial attention as a pivotal strategy to address climate change and serve as a sustainable substitute for petroleum-based vehicles. However, the uncoordinated deployment of EVAs within microgrids, especially in the face of the intermittent nature of RES, poses a potential threat to the secure operation of microgrid systems. To tackle the mentioned issues, this research concentrates on interconnecting a group of scattered microgrids to create a multi-microgrid system. In more detail, by developing an energy management strategy to reconfigure the interconnections among microgrids, the efficient exchange of power among these multi-microgrid systems is facilitated, addressing the variability in load demands amidst the stochastic generation patterns of RESs. Besides, grid-to-vehicle (G2V) and vehicle-to-grid (V2G) concepts of EVAs are synchronized within the reconfigurable microgrid structure to enhance the flexibility of the model. To evaluate the model under realistic situations, a scenario-based method is also employed to reflect the effects of uncertainties on the model. The proposed approach, characterized by its mathematical convexity, allows for employing efficient solvers like CPLEX, ensuring the attainment of a feasible global solution within a finite timeframe. The effectiveness of the proposed method is demonstrated through its implementation on a modified 33-bus test system operated as multi-microgrid system. The results show the effectiveness of the proposed approach as a promising tool for optimizing the operation of reconfigurable multi-microgrid systems in the presence of EVAs, leading to operational cost reduction and voltage profile enhancement. [ABSTRACT FROM AUTHOR]

Distribution network reconfiguration is one of the well-known and effective strategies in the distribution networks which performs by the status management of the network switches in order to obtain a new optimal configuration for the feeders. This study formulates multi-objective distribution feeder reconfiguration along with optimal sizing of distributed generators and capacitors. The prevalent objective functions in the network reconfiguration studies comprise of power loss and voltage deviations that are considered as the main objectives for traditional distribution systems, however, less attention has been paid to the objective functions of reliability and network voltage security in the previous literatures. Therefore, the main objective of this study is to improve the reliability and network voltage security by solving the distribution network reconfiguration problem. To this end, the energy not supplied and voltage stability index are defined as the objective functions of reliability and voltage security. A modified gravitational search algorithm is suggested to solve the complex and non-convex optimization problem. Ultimately, to demonstrate the efficiency of the proposed method; it has been tested on two 33 and 70-bus test systems, and the results are compared with the results of using other evolutionary algorithms, such as particle swarm optimization and shuffled frog leaping. [ABSTRACT FROM AUTHOR]

• Coordinating conventional Volt-VAr devices with distributed energy resources. • Incorporating demand response program into the Volt-VAr control problem. • Utilizing ε-constraint approach to generate Pareto optimal solutions. • Using IGDT to develop a robust decision-making approach. • Developing a mixed-integer linear programing framework. Distributed energy resources (DERs), such as renewable energy sources (RESs) and energy storage systems (ESSs), are inevitable parts of future power grids. However, the high penetration of RESs may cause voltage violation issues in distribution levels. To this end, the application of the Volt-VAr management (VVM) scheme is highlighted. This paper aims to maintain voltage levels within standard ranges with optimal coordination of different resources at minimum operational costs and voltage deviation. In more detail, this article develops a new VVM in distribution networks to effectively coordinate novel smart grid technologies such as PV inverters, time of use demand response program (TOU-DRP), energy storage systems (ESSs) with traditional devices, including on-line tap changer transformer (OLTC) and switchable capacitor banks (SCBs). Because the coordinated VVM is a bi-objective model that minimizes both operating cost and voltage deviation, it is proposed to use the ε-constraint technique to identify optimal Pareto solutions. To handle the uncertainty related to RESs and load demands, a robust technique based on information gap decision theory (IGDT) is also utilized. The formulation is configured as a mixed-integer linear program (MILP) and solved by CPLEX. It was implemented on the 118-bus distribution network under various conditions. The simulation results clearly show that the coordination of DERs and traditional devices has a significant impact on maintaining voltage levels within permissible ranges while minimizing operational costs. A higher degree of uncertainty radius can also be obtained if DRP participates in the VVM scheme. [ABSTRACT FROM AUTHOR]