scholarly journals Hybrid Intelligent Modelling in Renewable Energy Sources-Based Microgrid. A Variable Estimation of the Hydrogen Subsystem Oriented to the Energy Management Strategy

2020 ◽  
Vol 12 (24) ◽  
pp. 10566
Author(s):  
José-Luis Casteleiro-Roca ◽  
Francisco José Vivas ◽  
Francisca Segura ◽  
Antonio Javier Barragán ◽  
Jose Luis Calvo-Rolle ◽  
...  
Keyword(s):  
Intelligent System ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Absolute Error ◽  
Energy Storage System ◽  
Nonlinear Behaviour ◽  
Hydrogen Energy ◽  
Energy Management Strategy ◽  
Regression Methods ◽  
Hydrogen Level

This work deals with the prediction of variables for a hydrogen energy storage system integrated into a microgrid. Due to the fact that this kind of system has a nonlinear behaviour, the use of traditional techniques is not accurate enough to generate good models of the system under study. Then, a hybrid intelligent system, based on clustering and regression techniques, has been developed and implemented to predict the power, the hydrogen level and the hydrogen system degradation. In this research, a hybrid intelligent model was created and validated over a dataset from a lab-size migrogrid. The achieved results show a better performance than other well-known classical regression methods, allowing us to predict the hydrogen consumption/generation with a mean absolute error of 0.63% with the test dataset respect to the maximum power of the system.

scholarly journals Bioinspired Hybrid Model to Predict the Hydrogen Inlet Fuel Cell Flow Change of an Energy Storage System

Processes ◽  
2019 ◽  
Vol 7 (11) ◽  
pp. 825 ◽  
Author(s):  
Héctor Alaiz-Moretón ◽  
Esteban Jove ◽  
José-Luis Casteleiro-Roca ◽  
Héctor Quintián ◽  
Hilario López García ◽  
...  
Keyword(s):  
Energy Storage ◽  
Fuel Cell ◽  
Intelligent System ◽  
Storage System ◽  
Research Work ◽  
Energy Storage System ◽  
Parametric Models ◽  
Validation Dataset ◽  
Nonlinear Behaviour ◽  
Hydrogen Consumption

The present research work deals with prediction of hydrogen consumption of a fuel cell in an energy storage system. Due to the fact that these kind of systems have a very nonlinear behaviour, the use of traditional techniques based on parametric models and other more sophisticated techniques such as soft computing methods, seems not to be accurate enough to generate good models of the system under study. Due to that, a hybrid intelligent system, based on clustering and regression techniques, has been developed and implemented to predict the necessary variation of the hydrogen flow consumption to satisfy the variation of demanded power to the fuel cell. In this research, a hybrid intelligent model was created and validated over a dataset from a fuel cell energy storage system. Obtained results validate the proposal, achieving better performance than other well-known classical regression methods, allowing us to predict the hydrogen consumption with a Mean Absolute Error (MAE) of 3.73 with the validation dataset.

Modeling an Energy Storage System Based on a Hybrid Renewable Energy System in Stand-alone Applications

2017 ◽  
Vol 68 (11) ◽  
pp. 2641-2645
Author(s):  
Alexandru Ciocan ◽  
Ovidiu Mihai Balan ◽  
Mihaela Ramona Buga ◽  
Tudor Prisecaru ◽  
Mohand Tazerout
Keyword(s):  
Renewable Energy ◽  
Energy Storage ◽  
Storage Systems ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Energy Storage System ◽  
Compressed Air ◽  
Energy Sources ◽  
Energy Storage Systems ◽  
Hybrid Renewable Energy System

The current paper presents an energy storage system that stores the excessive energy, provided by a hybrid system of renewable energy sources, in the form of compressed air and thermal heat. Using energy storage systems together with renewable energy sources represents a major challenge that could ensure the transition to a viable economic future and a decarbonized economy. Thermodynamic calculations are conducted to investigate the performance of such systems by using Matlab simulation tools. The results indicate the values of primary and global efficiencies for various operating scenarios for the energy storage systems which use compressed air as medium storage, and shows that these could be very effective systems, proving the possibility to supply to the final user three types of energy: electricity, heat and cold function of his needs.

scholarly journals Optimal Placement and Sizing of an Energy Storage System Using a Power Sensitivity Analysis in a Practical Stand-Alone Microgrid

Electronics ◽  
2021 ◽  
Vol 10 (13) ◽  
pp. 1598
Author(s):  
Dongmin Kim ◽  
Kipo Yoon ◽  
Soo Hyoung Lee ◽  
Jung-Wook Park
Keyword(s):  
Sensitivity Analysis ◽  
Energy Storage ◽  
Power System ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Energy Storage System ◽  
Optimization Techniques ◽  
Optimal Placement ◽  
Stable Operation ◽  
Analytical Approaches

The energy storage system (ESS) is developing into a very important element for the stable operation of power systems. An ESS is characterized by rapid control, free charging, and discharging. Because of these characteristics, it can efficiently respond to sudden events that affect the power system and can help to resolve congested lines caused by the excessive output of distributed generators (DGs) using renewable energy sources (RESs). In order to efficiently and economically install new ESSs in the power system, the following two factors must be considered: the optimal installation placements and the optimal sizes of ESSs. Many studies have explored the optimal installation placement and the sizing of ESSs by using analytical approaches, mathematical optimization techniques, and artificial intelligence. This paper presents an algorithm to determine the optimal installation placement and sizing of ESSs for a virtual multi-slack (VMS) operation based on a power sensitivity analysis in a stand-alone microgrid. Through the proposed algorithm, the optimal installation placement can be determined by a simple calculation based on a power sensitivity matrix, and the optimal sizing of the ESS for the determined placement can be obtained at the same time. The algorithm is verified through several case studies in a stand-alone microgrid based on practical power system data. The results of the proposed algorithm show that installing ESSs in the optimal placement could improve the voltage stability of the microgrid. The sizing of the newly installed ESS was also properly determined.

scholarly journals The cost-effectiveness of an energy storage system using hydrogen and underground gas storage

2019 ◽  
Vol 137 ◽  
pp. 01007 ◽  
Author(s):  
Sebastian Lepszy
Keyword(s):  
Cost Effectiveness ◽  
Energy Storage ◽  
Historical Data ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Energy Storage System ◽  
Electricity Production ◽  
Energy Market ◽  
The Cost ◽  
Random Nature

Due to the random nature of the production, the use of renewable energy sources requires the use of technologies that allow adjustment of electricity production to demand. One of the ways that enable this task is the use of energy storage systems. The article focuses on the analysis of the cost-effectiveness of energy storage from the grid. In particular, the technology was evaluated using underground hydrogen storage generated in electrolysers. Economic analyzes use historical data from the Polish energy market. The obtained results illustrate, among other things, the proportions between the main technology modules selected optimally in technical and economic terms.

scholarly journals Adequacy Assessment of Wind Integrated Generating Systems Incorporating Demand Response and Battery Energy Storage System

Energies ◽  
2018 ◽  
Vol 11 (10) ◽  
pp. 2649 ◽  
Author(s):  
Jiashen Teh
Keyword(s):  
Energy Storage ◽  
Demand Response ◽  
Renewable Energy Sources ◽  
Storage System ◽  
Peak Load ◽  
Energy Storage System ◽  
Battery Energy Storage System ◽  
Battery Energy Storage ◽  
Battery Energy ◽  
Generating System

The demand response and battery energy storage system (BESS) will play a key role in the future of low carbon networks, coupled with new developments of battery technology driven mainly by the integration of renewable energy sources. However, studies that investigate the impacts of BESS and its demand response on the adequacy of a power supply are lacking. Thus, a need exists to address this important gap. Hence, this paper investigates the adequacy of a generating system that is highly integrated with wind power in meeting load demand. In adequacy studies, the impacts of demand response and battery energy storage system are considered. The demand response program is applied using the peak clipping and valley filling techniques at various percentages of the peak load. Three practical strategies of the BESS operation model are described in this paper, and all their impacts on the adequacy of the generating system are evaluated. The reliability impacts of various wind penetration levels on the generating system are also explored. Finally, different charging and discharging rates and capacities of the BESS are considered when evaluating their impacts on the adequacy of the generating system.

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