This report describes the creation and use of a database for energy storage technologies which was developed in conjunction with Netbeheer Nederland and the Hanze University of Applied Sciences. This database can be used to make comparisons between a selection of storage technologies and will provide a method for ranking energy storage technology suitability based on the desired application requirements. In addition, this document describes the creation of the energy storage label which contains detailed characteristics for specific storage systems. The layout of the storage labels enables the analysis of different storage technologies in a comprehensive, understandable and comparative manner. A sampling of storage technology labels are stored in an excel spreadsheet and are also compiled in Appendix I of this report; the storage technologies represented here were found to be well suited to enable flexibility in energy supply and to potentially provide support for renewable energy integration [37] [36]. The data in the labels is presented on a series of graphs to allow comparisons of the technologies. Finally, the use and limitations of energy storage technologies are discussed. The results of this research can be used to support the Dutch enewable Energy Transition by providing important information regarding energy storage in both technically detailed and general terms. This information can be useful for energy market parties in order to analyze the role of storage in future energy scenarios and to develop appropriate strategies to ensure energy supply.
MULTIFILE
The intermittency of renewable energy technologies requires adequate storage technologies. Hydrogen systems consisting of electrolysers, storage tanks, and fuel cells can be implemented as well as batteries. The requirements of the hydrogen purification unit is missing from literature. We measured the same for a 4.5 kW PEM electrolyser to be 0.8 kW for 10 min.A simulation to hybridize the hydrogen system, including its purification unit, with lithium-ion batteries for energy storage is presented; the batteries also support the electrolyser. We simulated a scenario for operating a Dutch household off-electric-grid using solar and wind electricity to find the capacities and costs of the components of the system.Although the energy use of the purification unit is small, it influences the operation of the system, affecting the sizing of the components. The battery as a fast response efficient secondary storage system increases the ability of the electrolyser to start up.
Battery energy storage (BES) can provide many grid services, such as power flow management to reduce distribution grid overloading. It is desirable to minimise BES storage capacities to reduce investment costs. However, it is not always clear how battery sizing is affected by battery siting and power flow simultaneity (PFS). This paper describes a method to compare the battery capacity required to provide grid services for different battery siting configurations and variable PFSs. The method was implemented by modelling a standard test grid with artificial power flow patterns and different battery siting configurations. The storage capacity of each configuration was minimised to determine how these variables affect the minimum storage capacity required to maintain power flows below a given threshold. In this case, a battery located at the transformer required 10–20% more capacity than a battery located centrally on the grid, or several batteries distributed throughout the grid, depending on PFS. The differences in capacity requirements were largely attributed to the ability of a BES configuration to mitigate network losses. The method presented in this paper can be used to compare BES capacity requirements for different battery siting configurations, power flow patterns, grid services, and grid characteristics.
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
Thermal batteries, which store and release energy by hydrating and dehydrating salt crystals, hold great promise for domestic heating. Such batteries can be charged from waste heat from industrial processes, and discharged to provide neighbourhood heating. Unlike hot water storage systems, the energy is stored at room temperature, so the thermal losses are very low, making a salt battery highly efficient. However, the electrochemical change of the salt due to hydration and dehydration is very small, making it difficult to measure how much energy is stored in a battery. One promising technique is to measure the absolute humidity of the inlet and outlet air flow. The difference in humidity, combined with a rate equation model allows the total mass of water stored in the battery to be calculated, which can then be used to calculate the energy storage and battery power flow. However, there are several uncertainties in this approach. Commercially available sensors age over time, sometimes quite suddenly. It is not yet known if software can be used to compensate for sensor aging, or if a different sensor type is required. In addition to aging, each measurement is subject to random noise, which will be integrated into the model used to calculate the charge of the battery. It is not yet known how the noise will influence charge estimates. On the other hand, the sensor system must be as durable as domestic heating systems (decades). Hence, it is required to understand sensor aging in order to validate the sensor system for its intended use.
