A proposal of energy management strategy on hybrid renewable system with hydrogen backup

Vivas, F.J.; Heras, A. De las; Segura, F.; Andújar, José Manuel

doi:10.1109/irec.2016.7478902

Cited by 7 publications

(7 citation statements)

References 14 publications

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“…In this case the different authors have eliminated the hysteresis bandwidth of the fuel cell operation (Table 4), maintaining the same SOCmin value and the rest of the simulation parameters similar to Case I. According to the results obtained from Case I and Case II, Tables 3 and 5 respectively, we can state that the use of the hysteresis band mode can reduce the startestop cycles of the fuel cell [45,46]. Besides, it requires higher operation time to reach the SOCfcmax value [45,46].…”

Section: Case II Sensitivity Analysis Examplementioning

confidence: 89%

“…The system configuration, cost and degradation parameters as well as the weather and the load profile (Fig. 10), are based on a real prototype implementation developed by different authors [45,46].…”

Section: Case Imentioning

confidence: 99%

“…According to the results obtained from Case I and Case II, Tables 3 and 5 respectively, we can state that the use of the hysteresis band mode can reduce the startestop cycles of the fuel cell [45,46]. Besides, it requires higher operation time to reach the SOCfcmax value [45,46]. Depending on the hydrogen storage capacity, the difference between the fuel cell degradation of both strategies can be determined by one of the previous parameters.…”

Section: Case II Sensitivity Analysis Examplementioning

confidence: 99%

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H2RES2 simulator. A new solution for hydrogen hybridization with renewable energy sources-based systems

Vivas

Heras

Segura

et al. 2017

International Journal of Hydrogen Energy

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This paper presents a new simulator for Hydrogen hybridization with Renewable Energy based Systems. The aim of this simulator is to provide a new solution for testing different energy management strategies of hydrogen hybridization based on renewable systems, in order to optimize them for implementation. The simulator uses the open architecture philosophy and has been developed in MATLAB ® -SIMULINK environment. Its main feature is calculating technical and economical parameters for a deepened analysis of influences on energy management strategies. It considers each element of the hybrid system and the whole system function. A simulation case shows the proper functioning of the simulator.

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Section: Case II Sensitivity Analysis Examplementioning

confidence: 89%

Section: Case Imentioning

confidence: 99%

Section: Case II Sensitivity Analysis Examplementioning

confidence: 99%

See 1 more Smart Citation

H2RES2 simulator. A new solution for hydrogen hybridization with renewable energy sources-based systems

Vivas

Heras

Segura

et al. 2017

International Journal of Hydrogen Energy

Self Cite

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show abstract

“…The common practice is to set the dispatch model prior to size optimisation process or test different dispatch strategies to obtain best possible output of an optimal size of HRES [5][6][7][8]. For instance, PV-Diesel-Battery and Wind-PV-Battery-Diesel of HRES configurations presented in [9] and [10] respectively, battery discharging is given the priority to meet the demand level when primary energy supply falls short.…”

Section: Introductionmentioning

confidence: 99%

Dispatch Strategy as a Design Variable in Hybrid Renewable Energy System Optimisation

Althani

Maheri

2021

2021 6th International Symposium on Environment-Friendly Energies and Applications (EFEA)

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In hybrid renewable energy system (HRES) with multiple storage and auxiliary/backup components different dispatch strategies can be defined based on the usage and charging order of these components. This paper presents a new formulation for size and configuration optimisation of HRES by including the dispatch strategy as a design variable. The new formulation is implemented in the optimisation tool MOHRES and is used to conduct three case studies with various scenarios. It is shown that compared to traditional method of predefining the dispatch strategy prior to size optimisation, inclusion of the dispatch strategy in size optimisation leads to superior solutions.

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“…The production of clean energy, with zero CO 2 emissions, and the microgrid concept are closely related. A microgrid is responsible for managing energy flows from renewable production to and from storage systems and consumers [23,24].…”

Section: Introductionmentioning

confidence: 99%

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

et al. 2020

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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.

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A proposal of energy management strategy on hybrid renewable system with hydrogen backup

Cited by 7 publications

References 14 publications

H2RES2 simulator. A new solution for hydrogen hybridization with renewable energy sources-based systems

H2RES2 simulator. A new solution for hydrogen hybridization with renewable energy sources-based systems

Dispatch Strategy as a Design Variable in Hybrid Renewable Energy System Optimisation

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

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