Smart Grids and Micro-Grids. Umashankar Subramaniam
Читать онлайн книгу.
cell parameters”. Optik, 223, 165277.
8. Abdulrazzaq, A. K., Bognár, G., & Plesz, B. (2020). “Evaluation of different methods for solar cells/modules parameters extraction”. Solar Energy, 196, 183-195.
9. Humada, A. M., Hojabri, M., Mekhilef, S., & Hamada, H. M. (2016). Solar cell parameters extraction based on single and double-diode models: A review. Renewable and Sustainable Energy Reviews, 56, 494-509.
10. Et-Torabi, K., Nassar-Eddine, I., Obbadi, A., Errami, Y., Rmaily, R., Sahnoun, S., & Agunaou, M. (2017). “Parameters estimation of the single and double diode photovoltaic models using a Gauss–Seidel algorithm and analytical method: A comparative study”. Energy Conversion and Management, 148, 1041-1054.
11. Alam, D. F., Yousri, D. A., & Eteiba, M. B. (2015). “Flower pollination algorithm based solar PV parameter estimation”. Energy Conversion and Management, 101, 410-422.
12. Celik, A. N., & Acikgoz, N. (2007). “Modelling and experimental verification of the operating current of mono-crystalline photovoltaic modules using four-and five-parameter models”. Applied energy, 84(1), 1-15.
13. Abdulrazzaq, A. K., Bognár, G., & Plesz, B. (2020). “Evaluation of different methods for solar cells/modules parameters extraction”. Solar Energy, 196, 183-195.
14. Jadli, U., Thakur, P., & Shukla, R. D. (2017). “A new parameter estimation method of solar photovoltaic”. IEEE Journal of Photovoltaics, 8(1), 239-247.
15. KAREEM, M. S. A., & Saravanan, M. (2016). “A new method for accurate estimation of PV module parameters and extraction of maximum power point under varying environmental conditions”. Turkish Journal of Electrical Engineering & Computer Sciences, 24(4), 2028-2041.
16. Shongwe, S., & Hanif, M. (2015, October). “Gauss-Seidel iteration based parameter estimation for a single diode model of a PV module”. In 2015 IEEE Electrical Power and Energy Conference (EPEC) (pp. 278-284). IEEE.
17. Carrero, C., Ramírez, D., Rodríguez, J., & Platero, C. A. (2011). Accurate and fast convergence method for parameter estimation of PV generators based on three main points of the I–V curve. Renewable Energy, 36(11), 2972-2977.
18. Kulaksiz, A. A. (2013). ANFIS-based estimation of PV module equivalent parameters: application to a stand-alone PV system with MPPT controller. Turkish Journal of Electrical Engineering & Computer Sciences, 21(Sup. 2), 2127-2140.
19. De Soto, W., Klein, S. A., & Beckman, W. A. (2006). Improvement and validation of a model for photovoltaic array performance. Solar energy, 80(1), 78-88.
20. Chatterjee, A., Keyhani, A., & Kapoor, D. (2011). Identification of photovoltaic source models. IEEE Transactions on Energy conversion, 26(3), 883-889.
21. Phillips, R. L. (1985). Computing solutions to generalized equilibrium models by successive under-relaxation. In Economic Equilibrium: Model Formulation and Solution (pp. 192-209). Springer, Berlin, Heidelberg.
22. King, D. L. (2000). Sandia’s PV module electrical performance model (version, 2000). Sandia National Laboratories, Albuquerque, NM.
*Corresponding author: [email protected]
2
Energy Storage System in Microgrid
Md Waseem Ahmad* and Ravi Raushan
National Institute of Technology Karnataka, Surathkal, India
Abstract
The energy storage systems (ESS) integrated microgrid have grown attention and acceptance because it has power reliability and sustainable energy utilization capability. Several ESS has been introduced with significant characteristics such as performance, size, life cycle, charging/discharging, safety, reliability, capacity, and cost. This chapter comprehensively reviews the types of ESS technologies, configurations, classifications, features, energy conversion, life cycle, and advantages and disadvantages. Moreover, the power electronics converter interfacing the microgrid has also been briefly studied. The present review critically demonstrates the interfacing circuits of ESS to microgrids. The mathematical modeling of bidirectional DC-DC converter interfacing the ESS to DC microgrid is presented developed. Moreover, the modeling and control of VSI interfacing the BESS to a three-phase grid is also demonstrated. The simulation model for both systems is also developed in MATLAB-Simulink. A critical review of the obtained simulation results is presented to show the ability of the DC-DC converter and VSI system for charging the BESS and delivering the power to the microgrid as per the requirement assigned by the higher-level controller of the microgrid.
Keywords: Energy storage system, microgrid, VSI, bi-directional D-DC converter
2.1 Introduction
Intermittency and fluctuation of renewable energy sources coupled with increased penetration pose a challenging problem for microgrid (MG) from the perspective of maintaining grid stability and delivering reliable power. Distributed energy storage (DES) is the best option to mitigate the uncertain power generation challenge posed by renewable energy while maintaining grid reliability with reduced microgrid operational cost. The excess renewable generation is stored by DES and is used when it is useful from either a technical perspective (e.g., voltage and frequency regulation) or an economic perspective (e.g., energy arbitrage). From the perspective of improving power quality and frequency regulation, energy storage systems (ESS) having high power density and fast response is required. For load levelling as well as peak shaving requirements in the microgrid, ESS (Energy Storage Systems) having high energy density and long discharge time is required. This chapter intends to explore the need and application of ESSs to deliver the electric power to costumers that meet the reliability and quality standard. Characteristics of different ESS technologies and their relative pros and cons are discussed, which is the key to select ESSs for a particular application in a microgrid. An overview of interfacing circuit for integrating ESS to microgrids such as DC-DC converter and DC-AC converter is also discussed. The development of simulation model of a popular bidirectional DC-DC converter which is used for controlling the charging and discharging of the ESS to microgrid is discussed as an example of application of ESS in microgrid. To control real and reactive power flow to the grid, modelling and control of voltage source inverter (VSI) based grid tried converter that interfaces ESS and grid is provided. Discussion on simulation results of the developed model in MATLAB-Simulink is provided to show the ability of VSI system for charging the battery or providing power for microgrid as per the requirement mandated by higher level controller of the microgrid.
2.2 Need of ESS (Energy Storage Systems)
The power management of renewable energy source based microgrid is complicated by virtue of the intermittencies and unpredictability issues of renewable distributed generators. The flexibility in a microgrid can be established with Energy Storage Systems (ESS) having the ability to operate as a load or generator, which can eventually balance the fluctuation in the microgrid and significantly improves the microgrid stability. Depending on the requirement of the microgrid, ESS is required to fulfil the objectives of maintaining grid reliability with reduced microgrid operation costs. Some of the function that may be required to be performed by ESS is listed as follows:
1. Load-levelling and Peak-shifting: The renewable systems produce energy only during the availability of the natural source regardless of the demand during peak hour. Thus, this difference in energy may lead to