J. García-Villalobos

Co-simulation with DIgSILENT PowerFactory and Matlab: Optimal integration of plug-in electric vehicles in distribution networks

Smart grid concept is gaining more and more importance in electric power systems. In near term, electric grids will be more intelligent, interconnected and decentralised. Dealing with a significant number of distributed resources in a smart way frequently requires the use of optimal control techniques, which find the best solution according to a defined objective function. Taking into account all these aspects, the simulation of these types of problems is characterised by having a great number of controlled resources and the use of advanced control techniques. In this context, DIgSILENT PowerFactory provides useful tools to simulate complex systems. On the one hand, the DIgSILENT Programming Language (DPL) can be used for multiple purposes such as automation of simulations, automatic generation of simulation scenarios, analysis of results. On the other hand, the DIgSILENT Simulation Language (DSL) and the digexfun interface allow the implementation of advanced control techniques. Using the digexfun interface, DIgSILENT PowerFactory can send and receive data from other mathematical software APIs such as MATLAB. This chapter presents a co-simulation framework developed to test optimal control methods for root mean square (RMS) simulations on DIgSILENT PowerFactory. As an example, the implementation of a smart charging control for plug-in electric vehicles in electric distribution networks is explained.

Testing and analysis of a fuel cell based stand-alone power system for residential use

Nowadays, there are residential buildings which cannot be connected to a distribution network, due to the lack of electric infrastructure. Also, there are other electric applications where it is necessary to have a back-up system, i.e. hospitals, hotels, etc. Additionally, there are users who just want to be off-grid. In all these cases, a dedicated stand-alone generation system can provide a valuable service. In this context, this paper is focused on testing and analysis of a real small stand-alone generation system composed by two proton membrane exchange fuel cells (PEMFC) and a micro wind generator (WG). The key feature of this configuration is to be an on-site zero-emission system. Additionally, quality of supply and energy efficiency of this microgrid in islanded mode are analyzed. Furthermore, possible optimization methods and future enlargements of the system are proposed, in order to improve the overall efficiency of the proposed microgrid.

Decentralized controltechniques for plug-in electric vehicles in MV/LV distribution networks

Decentralized control techniques are acquiring more and more importance to efficiently manage a large number of distributed energy resources (DER). It is expected that, in the future, plug-in electric vehicles (PEVs) will act as DERs providing valued services to power grids. In addition, it has been proven that uncontrolled charging of PEVs will have a significant impact on the operation of MV/LV distribution networks. In this context, this paper presents a review on decentralized control approaches to adequately integrate PEVs in MV/LV distribution networks. Among these decentralized control techniques, optimal and droop based controls are the most common. Both have strengths and weaknesses, so, more research about mixing both methods is needed.

Control optimization of an electric traction bus powered by PEMFC and PV

This paper focuses on the design and optimization of the electrical system operation in an electric drive bus, powered by a PEM fuel cell and photovoltaic modules. Through the optimization developed, an improved performance and reduced operating costs for the system, in normal operation, is pursued. Aiming that objective, models of all components (fuel cell, solar modules, electric motors, batteries, controllers, etc.) involved in the system have been developed using the software MATLAB. Results obtained with these models have allowed the designing of an optimized control system.