Pol Olivella-Rosell

Architecture definition and operation testing of local electricity markets. The EMPOWER project

This article describes the results of the European Project Empower. This project is about the creation of a trading platform for local energy exchange in local markets. To do so, a system architecture is proposed, based on the Smart Grid Architecture Model (SGAM). The implementation of the developed platform has been tested in the Prosumer Lab environment. The Prosumer Lab is an installation at the UPC that permits to emulate different use cases by the means of power electronics. The tests showed a successful integration of the software and hardware for the project purpose.

Performance analysis of an electric vehicle fleet for commercial purposes

This article presents a Knowledge Discovery in Databases (KDD) process to analyze data obtained by monitoring a fleet of eight electric vehicles with ZEBRA batteries during the years 2012 and 2013. Over 4,000 journeys and 2,000 charging events have been detected. The analysis of such events shows the consumption of the battery and its aging, and how the electric vehicles are used.

Assessment of impact of charging infrastructure for electric vehicles on distribution networks

Charging infrastructure for electric vehicles can impact significantly on distribution systems. Normal charging will be the usual way while fast charging has to be considered as a complement to this. Both charging processes represent a new load for distribution networks. The effect of both normal and fast charging are assesses. Management strategies are proposed for reducing the impact and the results are presented.

Impact Evaluation of Plug-in Electric Vehicles on Power System

The aim of this chapter is to expose the probabilistic Plug-in electric vehicle (PEV) charging model and to apply it in a distribution grid to evaluate the PEV impact. The model is based on agent-based techniques, has probabilistic variables, includes queuing theory, and applies Monte Carlo methodology. The PEV user’s charging needs can be divided in two categories: private charging points and public charging points. Regarding private charging points, the PEV charging demand depends strongly on private user’s mobility needs and it includes variables as number of trips per day, driving distance, and arrival time. Also, the user’s profile can be modelled with probabilistic variables as the PEV model and the charging connection point. All these variables can be modelled with probabilistic distributions functions to obtain a probabilistic model with data from different sources. Additionally, public charging points are made available for PEV users that need to plug-in the vehicle between trips to extend the vehicle autonomy. After that, the model is applied to a case study to analyze the impact to the power network. Probabilistic grid impact includes the probability to exceed a maximum voltage drop, and transformer and current saturations. The main impact is on saturations of lines and they can be reduced controlling private points but it does not make sense to control the public points. Fast chargers present some challenges for grid integration because they are public charging points of 50 kW power rate per charger. In this chapter, a stochastic arrivals model is applied to analyze the public fast charging stations, the PEV user’s charging needs and their grid impact. Fast charging stations are designed to extend the autonomy of PEV and their arrivals to the station have a certain stochastic behavior. The probabilistic arrivals for the fast charger impact evaluation are based on queuing theory and the corresponding electricity demand is evaluated. The case study analyzed includes three fast chargers installed in the same grid and they provoke saturations in lines.

Assessment of the impact of Electric vehicles on iberian day-ahead electricity market

Electric vehicles (EVs) could become a controllable grid load by using demand side management techniques, but this requires an information and communications technology (ICT) infrastructure and aggregator agents, to coordinate the EV charging process. To determine the opportunity cost of aggregators, it is necessary to analyze the extra charges in the electricity market, due to the EV charging demand. The EV energy consumption is modeled following agent-based techniques, and the data used corresponds to the Iberian day-ahead market and Spanish mobility needs in 2012. The simulation results show that EVs would significantly influence the electricity price on the day-ahead market, depending on the EV charging behavior.