Abstract

This paper gives information about Renewable Energy Generation and its impacts on E-Mobility. By 2050, the two pillars of modern transformation are E-Mobility and Renewable Energy. This transformation requires adaptation to meet demographic and economic growth without increasing pollution and congestion. The modern world needs affordable, secure and inclusive, sustainable and integrated with customer-centric infrastructure and services. There is a great fundamental change needed in road transportation sector, which is to achieve its objective of a long term transition to a low-carbon economy. Electric Vehicles when charged with the electricity generated from Renewable Energy Sources can reduce future emissions of greenhouse gases and air pollutants from road transport. Electric Vehicles combined with renewable energy paint a different picture from the oversimplification of gas miles versus electric miles.Smart Mobility and Smart Grid technologies make people live more sustainable and efficiently.

Abstract

This paper presents a reference architecture for interoperability testing of electric vehicles as well as their support equipment with the smart grid and the e-Mobility environment. Pan-European Electric Vehicle (EV)-charging is currently problematic as there are compliance and interoperability issues on different communication levels and among the different domains comprising the eMobility system. The discussed reference architecture is composed out of three layers that enable addressing a direct mapping of interfaces, functions and services, as well as real world actors and/or laboratory equipment. Utilizing this architecture enables cross-domain co-simulation for interoperability within the electric mobility and the smart grid environment. Given the future challenges that rise to interoperability testing and the fact that certain aspects are yet unknown or rarely defined, the discussed architecture presents a very modular and extendable approach. © 2015 IEEE.

Abstract

ggregated demand response for smart grid services is a growing field of interest especially for market participation. A growing trend in research is to utilize aggregated demand response for multiple smart grid services. This could be multi-market trading (day ahead, intraday and imbalance) or a combination of market and ancillary services such offering reserve power or congestion management. However, there is a potential conflict of interest when offering the same resource for simultaneous services. This work investigates the impact, both from a monetary and network stability perspective, of applying a predictive control trading strategy which actively offers aggregated flexibility of electric vehicles on both the German EPEX day ahead and intraday markets. An artificial neural network was used to forecast the available ramp up and down capacity of a Virtual Power Plant (VPP) of 1000 electric vehicles. Using this information, the available flexibility is traded to ramp up in one quarter and down in the next depending on the price delta seen in the intraday market. A number of simulation runs are done, each with different levels of flexibility traded. In every run, one week of realistic VPP behaviour is simulated. The total earnings on the intraday market are calculated as well as imbalance cost and imbalance power generated over this period. It was seen that with an increased offer of available flexibility, there was an increase in both total revenues up to ∼4200 euros for one week of trade as well as imbalance generated, ∼1.6 MWh. Therefore, there is a clear need for effective regulation that limits imbalance without losing the future grid-stabilising effects of the flexibility aggregator.