Energy storage systems are an integral part of Germany’s Energy Transition (Energiewende). While the need for energy storage is growing across Europe, Germany remains the lead target market and the first choice for companies seeking to enter this developing industry. It stands out as a unique market, development platform and export hub. Germany Trade & Invest helps open up a vista of opportunities for companies looking to cooperate with German part­ ners, become involved in demonstration projects, and expand through direct investment. Video: Energy Storage in Germany

Energy Storage I

State-of-charge (SoC) estimation is of great importance for electric vehicles (EVs) optimum operation, while highly dynamic operation environment makes this task extremely thorny. By far, considerable researches have been done in modeling and approaches to accurately estimate SoC for lithium-ion batteries (LiBs) used in EVs. Nevertheless, existing reviews are either ambiguous in classifications or incomplete in methodologies, especially lack of detailed evaluation. To solve these issues, this work undertakes a comprehensive survey on various models and methods utilized in LiBs SoC estimation, which aims to more specifically guide automobile engineers and researchers utilize these techniques in an effective manner and facilitate future research works. Enumeration method is used for review screening to select the most representative papers in an application-oriented manner. Firstly, five modeling techniques are outlined, which are significant in improving estimation precision. Then, six categories along with twenty-one evaluation criteria are summarized for quantitative performance verification. Moreover, various SoC estimation methods in six categories are thoroughly discussed, among which ninety-three methods are carefully elaborated in table for a systematic evaluation and fair comparison. Meanwhile, this work gives insight to SoC estimation methods with emphasis on their major benefits/limitations and application conditions. Lastly, important recommendations of future researches are disclosed in the hope of providing some inspirations to propel EVs applications. All in all, this work provides a state-of-the-art one-stop handbook of LiBs SoC estimation used in EVs.

Classification, summarization and perspectives on state-of-charge estimation of lithium-ion batteries used in electric vehicles: A critical comprehensive survey

Optimal parameter estimation strategy of PEM fuel cell using gradient-based optimizer

Peak shaving benefit assessment considering the joint operation of nuclear and battery energy storage power stations: Hainan case study

This paper presents an optimal sizing and allocation of a renewable energy resource (RES) based distribution generation (DG) units with gravity energy storage (GES) in the radial distribution network (DN). The optimization technique Constriction Coefficient Particle Swarm Optimization (CPSO) is utilized to reduce the total energy loss, which is subjected to equality and inequality constraints. Different DG parameters are considered and evaluated to reduce energy losses in electricity DN. To reduce search space and computational burden, a sensitivity analysis is performed to determine the candidate buses for the placement of DGs. The stochastic nature of RES (solar and wind), load, and storage unit has been handle using the probabilistic technique. The suitable penetration level is so adjusted as to restrict RES output on a certain fraction of the system load for stability consideration. The load flow analysis is performed using a backward-forward sweep algorithm embedded in the probability framework. The proposed approach has been examined on four different cases on DN consisting of 33 buses and it has been found that a notable reduction in losses with improved voltage profile is obtained by optimal sizing and placing DG units at an appropriate location. Results obtained using the CPSO technique has been validated by comparing it with the Simple Genetic Algorithm (SGA) technique. Further, the results obtained in case 3 using GES technology have compared with the battery storage system.

Optimal sizing and allocation of renewable based distribution generation with gravity energy storage considering stochastic nature using particle swarm optimization in radial distribution network

Robust Fractional-order PID Control of Supercapacitor Energy Storage Systems for Distribution Network Applications: A Perturbation Compensation based Approach

Danyang Li

Papers

Robust Fractional-order PID Control of Supercapacitor Energy Storage Systems for Distribution Network Applications: A Perturbation Compensation based Approach

Levenberg-Marquardt backpropagation algorithm for parameter identification of solid oxide fuel cells