A realistic model for battery state of charge prediction in energy management simulation tools

In this paper, a comprehensive model for the prediction of the state of charge of a battery is presented. This model has been specifically designed to be used in simulation tools for energy management in (smart) grids. Hence, this model is a compromise between simplicity, accuracy and broad applicability. The model is verified using measurements on three types of Lead-acid (Pb-acid) batteries, a Lithium-ion Polymer (Li-Poly) battery and a Lithium Iron-phosphate (LiFePo) battery. For the Pb-acid batteries the state of charge is predicted for typical scenarios, and these predictions are compared to measurements on the Pb-acid batteries and to predictions made using the KiBaM model. The results show that it is possible to accurately model the state of charge of these batteries, where the difference between the model and the state of charge calculated from measurements is less than 5%. Similarly the model is used to predict the state of charge of Li-Poly and LiFePo batteries in typical scenarios. These predictions are compared to the state of charge calculated from measurements, and it is shown that it is also possible to accurately model the state of charge of both Li-Poly and LiFePo batteries. In the case of the Li-Poly battery the difference between the measured and predicted state of charge is less than 5% and in the case of the LiFePo battery this difference is less than 3%

A comprehensive model for battery State of Charge prediction

In this paper the relatively simple model for State of Charge prediction, based on energy conservation, introduced in [1] is improved and verified. The model as introduced in [1] is verified for Pb-acid, Li-ion and Seasalt batteries. The model is further improved to accommodate the rate capacity effect and the capacity recovery effect, the improvements are verified with lead-acid batteries. For further verification the model is applied on a realistic situation and compared to measurements on the behavior of a real battery in that situation. Furthermore the results are compared to results of the well-established KiBaM model. Predictions on the SoC over time done using the proposed model closely follow the SoC over time calculated from measured data. The resulting improved model is both simple and effective, making it specially useful as part of smart control, and energy usage simulations

The Role of Off-Grid Houses in the Energy Transition with a Case Study in the Netherlands

Off-grid houses can be considered an important concept to increase the access to electricity throughout the world. Although there are quite some initiatives in place to improve the access to electricity, the implementation rate of practical solutions is far below the UN Sustainable Development Goal 7: Energy (SDG 7) + for 2030. This situation is most apparent in Sub-Saharan Africa, where the current trends of electricity access calculated by the World Bank indicate that this region will not be able to achieve the SDG 7 target. Another worldwide trend which may help to increase electricity access is that currently, a lot of renewable energy generation is realized locally in houses (especially Solar Photovoltaics (PV)). This paper reviews the recent developments to increase the access to electricity in the world and the implementation of off-grid houses in different scenarios. The focus here is on the different efforts to create off-grid houses considering their challenges on a macro and micro level. Moreover, potential research directions for technologies in off-grid houses are presented in more detail. For this, a case description of a possible off-grid house in the Netherlands is presented together with some initial simulations results for this case using solar PV, the Sea-Salt battery, and a Glycerol Fuel Cell. The simulations use the DEMkit software and the analysis is performed using measured house load data for a period in winter and in summer

Influence of co-depositor materials and modification of substrate on the formation of dendrites on the anode of a zinc-based secondary battery

Dendrite formation poses serious problems in the operation of zinc-based batteries. Electrode material and electrolyte composition are known to have an influence on the dendrite formation. In this paper possible solutions for the reduction of dendrite formation at the anode of a zinc-based battery are studied. The electrochemical behaviour of various electrode materials and electrolyte compositions is researched. It is observed that the tested electrode materials have no significant impact on the reaction at the anode. However, significant reduction in dendrite formation are observed at various electrode materials. The largest reduction in dendrite formation is observed when SGL bipolar graphite is used as electrode material. Furthermore, using several analysis methods (CV, EIS, SEM) it is observed that the addition of low concentrations (around 10% of the main component concentration) of certain additives (MgBr2, MnSO4) to the electrolyte has no significant impact on the electrolyte reaction at the anode, but prevents the formation of dendrites. Finally, the changes in substrate material and electrolyte additive do not have significant influence on the over-all performance of the battery

Characterization of Storage Sizing for an Off-Grid House in the US and the Netherlands

This work uses experimental data to estimate the size of storage needed for an isolated off-grid household in two different regions (Austin, Texas, US, and Nunspeet, NL). In our study, an off-grid house is considered to be supplied with 100% renewable energy during the summer period, in which cooling demand is neglected, and a solar photovoltaic (PV) system and batteries are the main electrical energy providers. Based on results achieved with the DEMkit simulation package we can conclude that, in both cases, using a solar PV system and a Sea-Salt battery would have been sufficient to provide the necessary electricity without showing a blackout during the summer of 2016. The Austin household needs a solar PV system of 38 kWp and storage of 452 kWh; in the case of Nunspeet, a solar PV system of 11.5 kWp and storage of 90 kWh is sufficient. Furthermore, using the DEMkit model, it is possible to determine an optimal value for the size of storage to half of the initial battery capacity (226 kWh for Austin and 45 kWh for Nunspeet) and still be able to provide enough power to cover the load demand of the households during the summer. In a second part, data of the solar PV system and load from Austin for one specific week was used to create data of a ‘typical’ but downscaled day. This day was used to determine the fluctuation of electricity for a real Sea-Salt battery for the considered off-grid scenario in Austin. The downscaling of the data was needed in order to have load values that fit to the size of the real battery. The tests show that the Sea-Salt battery under real electricity fluctuations is possibly adequate for off-grid scenario