Hybrid Energy Storage System (HESS) have the potential to offer better flexibility to a grid than any single energy storage solution. However, sizing a HESS is challenging, as the required capacity, power and ramp rates for a given application are difficult to derive. This paper proposes a method for splitting a given load profile into several storage technology independent sub-profiles, such that each of the sub-profiles leads to its own requirements. This method can be used to gain preliminary insight into HESS requirements before a choice is made for specific storage technologies. To test the method, a household case is investigated using the derived methodology, and storage requirements are found, which can then be used to derive concrete storage technologies for the HESS of the household. Adding a HESS to the household case reduces the maximum import power from the connected grid by approximately 7000 W and the maximum exported power to the connected grid by approximately 1000 W. It is concluded that the method is particularly suitable for data sets with a high granularity and many data points.
MULTIFILE
SEEV4-City is an innovation project funded by the European Union Interreg North Sea Region Programme. Its main objective is to demonstrate smart electric mobility and integration of renewable energy solutions and share the learnings gained. The project reports on the results of six Operational Pilots (OPs) which have different scales and are located in five different cities in four different countries in the North Sea Region.Loughborough OP (United Kingdom) is the smallest pilot, being a household with a bi-directional EV charging unit for the Nissan Leaf, a stationary battery, and a PV system. In the Kortrijk OP (Belgium), a battery system and a bi-directional charging unit for the delivery van (as well as a smart charging station for ebikes) were added to the energy system. In Leicester (United Kingdom), five unidirectional charging units were to be accompanied by four bi-directional charging units. The Johan Cruyff Arena OP is a larger pilot in Amsterdam, with a 2.8 MWh (partly) second life stationary battery storage for Frequency Control Regulation services and back-up power, 14 fast chargers and one bi-directional charger. Integrated into the existing energy system is a 1 MW PV system that is already installed on the roof. In the Oslo OP, 102 chargers were installed, of which two are fast chargers. A stationary battery energy storage system (BESS) supports the charging infrastructure and is used for peak shaving. The FlexPower OP in Amsterdam is the largest OP with over 900 EV charging outlets across the city, providing smart charging capable of reducing the energy peak demand in the evening.Before the start of the project, three Key Performance Indicators (KPIs) were determined:A. Estimated CO2 reductionB. Estimated increase in energy autonomyC. Estimated Savings from Grid Investment Deferral
Electric vehicles and renewable energy sources are collectively being developed as a synergetic implementation for smart grids. In this context, smart charging of electric vehicles and vehicle-to-grid technologies are seen as a way forward to achieve economic, technical and environmental benefits. The implementation of these technologies requires the cooperation of the end-electricity user, the electric vehicle owner, the system operator and policy makers. These stakeholders pursue different and sometime conflicting objectives. In this paper, the concept of multi-objective-techno-economic-environmental optimisation is proposed for scheduling electric vehicle charging/discharging. End user energy cost, battery degradation, grid interaction and CO2 emissions in the home micro-grid context are modelled and concurrently optimised for the first time while providing frequency regulation. The results from three case studies show that the proposed method reduces the energy cost, battery degradation, CO2 emissions and grid utilisation by 88.2%, 67%, 34% and 90% respectively, when compared to uncontrolled electric vehicle charging. Furthermore, with multiple optimal solutions, in order to achieve a 41.8% improvement in grid utilisation, the system operator needs to compensate the end electricity user and the electric vehicle owner for their incurred benefit loss of 27.34% and 9.7% respectively, to stimulate participation in energy services.
As electric loads in residential areas increase as a result of developments in the areas of electric vehicles, heat pumps and solar panels, among others, it is becoming increasingly likely that problems will develop in the electricity distribution grid. This research will analyse different solutions to such problems to determine Using a model developed as part of this project, we will simulate various cases to determine under which circumstances load balancing at a community-level is more (cost) effective than alternative solutions (e.g. grid reinforcement and/or household batteries).
