Optimal Modeling for Dynamic Response of Energy Storage Systems
Source abstract
Abstract
Using energy storage systems with solar and wind energy can overcome the intermittence of these types of renewable energy. According to the regulations made by the utilities in each country, facilities that are connected to the power grid should be assessed on how they influence the power grid. Power system simulation software such as PSS/E, DIgSILENT, and DSATools are widely used by utilities. The default models in these kinds of software are defined by the Western Electricity Coordinating Council (WECC). Improper parameters will produce estimation results that are not informative, and the utilities may make wrong decisions. To avoid this problem, this study designed the process to find suitable parameters for real energy storage systems. Using models created by the WECC and reducing it according to the application condition decreased the burden of the optimization process. We used two algorithms and their improved versions to search for an appropriate value of variables that can represent a real energy storage system. We also compared the results between the BESS simplified model that we built and the original model from PSS/E.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Power Systems and Renewable Energy · Microgrid Control and Optimization · Optimal Power Flow Distribution
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Electrical Engineering, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
Graduate Institute of Energy and Sustainability Technology, National Taiwan University of Science and Technology, Taipei 10607, Taiwan
References (23)
Show source-provided references
1. (2021, June 02). International Renewable Energy Development Trends and Policies. Available online: https://www.re.org.tw/knowledge/more.aspx?cid=201&id=3966.
2. Taipower Company Renewable Energy Power Generation System Parallel Technology Guidelines, Taipower Company.
3. Sparacino, A.R., Reed, G.F., Kerestes, R.J., Grainger, B.M., and Smith, Z.T. (2012, January 22–26). Survey of battery energy storage systems and modeling techniques. Proceedings of the 2012 IEEE Power and Energy Society General Meeting, San Diego, CA, USA.10.1109/PESGM.2012.6345071 ↗
4. Application and modeling of battery energy storage in power systems10.17775/CSEEJPES.2016.00039 ↗
5. Modeling and validation of battery energy storage systems using simple generic models for power system stability studies
6. Placement and sizing of battery energy storage for primary frequency control in an isolated section of the Mexican power system10.1016/j.epsr.2018.02.013 ↗
7. A Paretian Approach to Optimal Design with Uncertainties: Application in Induction Heating10.1109/TMAG.2013.2280377 ↗
8. Design Sensitivity Analysis for Shape Optimization of Nonlinear Magnetostatic Systems10.1109/TMAG.2015.2478196 ↗
9. Lykas, P., Georgousis, N., Kitsopoulou, A., Korres, D.N., Bellos, E., and Tzivanidis, C. (2023). A Detailed Parametric Analysis of a Solar-Powered Cogeneration System for Electricity and Hydrogen Production. Appl. Sci., 13.10.3390/app13010433 ↗
10. Colangelo, A., Guelpa, E., Lanzini, A., Mancò, G., and Verda, V. (2020). Compact Model of Latent Heat Thermal Storage for Its Integration in Multi-Energy Systems. Appl. Sci., 10.10.3390/app10248970 ↗
11. Multiobjective Evolutionary Optimization of a Surface Mounted PM Actuator with Fractional Slot Winding for Aerospace Applications10.1109/TMAG.2013.2285497 ↗
12. Stochastic Nondestructive Testing Simulation: Sensitivity Analysis Applied to Material Properties in Clogging of Nuclear Powerplant Steam Generators10.1109/TMAG.2013.2243409 ↗
13. Evaluation of inductance coil and fluxgate magnetometer under harmonic and pulsed excitations in ECT10.3233/JAE-2012-1471 ↗
14. Trajectory sensitivity analysis of first order and second order on position control system of highly integrated valve-controlled cylinder10.1007/s12206-015-0944-x ↗
15. Cari, E.P.T., Alberto, L.F.C., and Bretas, N.G. (2006, January 18–22). A methodology for parameter estimation of synchronous generators based on trajectory sensitivity and synchronization technique. Proceedings of the 2006 IEEE Power Engineering Society General Meeting, Montreal, QC, Canada.10.1109/PES.2006.1709492 ↗
16. How to avoid a perfunctory sensitivity analysis10.1016/j.envsoft.2010.04.012 ↗
17. Dynamic Equivalent Model Development to Improve the Operation Efficiency of Wind Farm10.1109/TIA.2016.2537778 ↗
18. Robustness Analysis of Dynamic Equivalent Model of DFIG Wind Farm for Stability Study10.1109/TIA.2018.2858738 ↗
19. A Hybrid Optimization Algorithm and Its Application for Conformal Array Pattern Synthesis10.1109/TAP.2010.2050425 ↗
20. Bangyal, W.H., Nisar, K., Soomro, T.R., Ibrahim, A.A.A., Mallah, G.A., Hassan, N.U., and Rehman, N.U. (2023). An Improved Particle Swarm Optimization Algorithm for Data Classification. Appl. Sci., 13.10.3390/app13010283 ↗
21. Gupta, J., Hussain, A., Singla, M.K., Nijhawan, P., Haider, W., Kotb, H., and AboRas, K.M. (2023). Parameter Estimation of Different Photovoltaic Models Using Hybrid Particle Swarm Optimization and Gravitational Search Algorithm. Appl. Sci., 13.10.3390/app13010249 ↗
22. A New Improved GA and PSO Combined Hybrid Algorithm (HIGAPSO) for Solving Optimal Reactive Power Dispatch Problem
23. Zhu, Z., Liu, Y., He, Y., Wu, W., Wang, H., Huang, C., and Ye, B. (2022). Fuzzy PID Control of the Three-Degree-of-Freedom Parallel Mechanism Based on Genetic Algorithm. Appl. Sci., 12.10.3390/app122111128 ↗