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
As the Dutch electric vehicle (EV) fleet continues to expand, so will the amount of charging sessions increase. This expanding demand for energy will add on to the already existing strain on the grid, primarily during peak hours on workdays in the early morning and evening. This growing energy demand requires new methods to handle the charging of EVs, to distribute the available energy in the most effective way. Therefore, a large number of ‘smart charging’ initiatives have recently been developed, whereby the charging session of the EV is based on the conditions of the energy grid. However, the term smart charging is used for a variety of smart charging initiatives, often involving different optimization strategies and charging processes. For most practitioners, as well as academics, it is hard to distinguish the large range of smart charging initiatives initiated in recent years, how they differentiate from each other and how they contribute to a smarter charging infrastructure. This paper has the objective to provide an overview of smart charging initiatives in the Netherlands and develop a categorization of smart charging initiatives regarding objectives, proposed measures and intended contributions. We will do so by looking at initiatives that focus on smart charging at a household level, investigating the smart charging possibilities for EV owners who either make use of a private or (semi-)public charging point. The different smart charging initiatives will be analyzed and explicated in combination with a literature study, focusing on the different optimization strategies and requirements to smart charge an electric vehicle.
Bij ‘Tolling Agreements’ blijven overheden eigenaar van energie-infrastructuur en wordt de capaciteit verhuurd. Deze oplossing uit de Verenigde Staten biedt volgens Martien Visser efficiency en zekerheid aan marktpartijen in een onzekere energiemarkt.
LINK
Based on the model outcomes, Houtlaan’s energy transition will likely result in congestion and curtailmentproblems on the local electricity grid within the next 5-7 years, possibly sooner if load imbalance between phasesis not properly addressed.During simulations, the issue of curtailment was observed in significant quantities on one cable, resulting in aloss of 8.292 kWh of PV production per year in 2030. This issue could be addressed by moving some of thehouses on the affects cable to a neighboring under-utilized cable, or by installing a battery system near the end ofthe affected cable. Due to the layout of the grid, moving the last 7 houses on the affected cable to the neighboringcable should be relatively simple and cost-effective, and help to alleviate issues of curtailment.During simulations, the issue of grid overloading occurred largely as a result of EV charging. This issue can bestbe addressed by regulating EV charging. Based on current statistics, the bulk of EV charging is expected to occurin the early evening. By prolonging these charge cycles into the night and early morning, grid overloading canlikely be prevented for the coming decade. However, such a control system will require some sort of infrastructureto coordinate the different EV charge cycles or will require smart EV chargers which will charge preferentiallywhen the grid voltage is above a certain threshold (i.e., has more capacity available).A community battery system can be used to increase the local consumption of produced electricity within theneighborhood. Such a system can also be complemented by charging EV during surplus production hours.However, due to the relatively high cost of batteries at present, and losses due to inefficiencies, such a systemwill not be financially feasible without some form of subsidy and/or unless it can provide an energy service whichthe grid operator is willing to pay for (e.g. regulating power quality or line voltage, prolonging the lifetime of gridinfrastructure, etc.).A community battery may be most useful as a temporary solution when problems on the grid begin to occur, untila more cost-effective solution can be implemented (e.g. reinforcing the grid, implementing an EV charge controlsystem). Once a more permanent solution is implemented, the battery could then be re-used elsewhere.The neighborhood of Houtlaan in Assen, the Netherlands, has ambitious targets for reducing the neighborhood’scarbon emissions and increasing their production of their own, sustainable energy. Specifically, they wish toincrease the percentage of houses with a heat pump, electric vehicle (EV) and solar panels (PV) to 60%, 70%and 80%, respectively, by the year 2030. However, it was unclear what the impacts of this transition would be onthe electricity grid, and what limitations or problems might be encountered along the way.Therefore, a study was carried out to model the future energy load and production patterns in Houtlaan. Thepurpose of the model was to identify and quantify the problems which could be encountered if no steps are takento prevent these problems. In addition, the model was used to simulate the effectiveness of various proposedsolutions to reduce or eliminate the problems which were identified
