Optimal Operation of Combined Photovoltaic Electrolyzer Systems

Khalilnejad, Arash; Sundararajan, Aditya; Abbaspour, Alireza

doi:10.3390/en9050332

Cited by 16 publications

(7 citation statements)

References 34 publications

(38 reference statements)

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“…The power produced from PV is available during the day when solar irradiance is available to be exploited, and the power produced from WT is at the peak when the wind blows favorably to the blades. Hence, for increasing the reliability of the power generation, the combination of these two systems is a feasible proposition [4][5][6][7][8][9][10][11]. Moreover, typically, the irradiance and wind complement each other [12][13][14][15].…”

Section: Introductionmentioning

confidence: 99%

Optimal design of hybrid wind/photovoltaic electrolyzer for maximum hydrogen production using imperialist competitive algorithm

Khalilnejad

Sundararajan

2017

J. Mod. Power Syst. Clean Energy

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The rising demand for high-density power storage systems such as hydrogen, combined with renewable power production systems, has led to the design of optimal power production and storage systems. In this study, a wind and photovoltaic (PV) hybrid electrolyzer system, which maximizes the hydrogen production for a diurnal operation of the system, is designed and simulated. The operation of the system is optimized using imperialist competitive algorithm (ICA). The objective of this optimization is to combine the PV array and wind turbine (WT) in a way that, for minimized average excess power generation, maximum hydrogen would be produced. Actual meteorological data of Miami is used for simulations. A framework of the advanced alkaline electrolyzer with the detailed electrochemical model is used. This optimal system comprises a PV module with a power of 7.9 kW and a WT module with a power of 11 kW. The rate of hydrogen production is 0.0192 mol/s; an average Faraday efficiency of 86.9 percent. The electrolyzer works with 53.7 percent of its nominal power. The availability of the wind for longer periods of time reflects the greater contribution of WT in comparison with PV towards the overall throughput of the system.

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Section: Introductionmentioning

confidence: 99%

Optimal design of hybrid wind/photovoltaic electrolyzer for maximum hydrogen production using imperialist competitive algorithm

Khalilnejad

Sundararajan

2017

J. Mod. Power Syst. Clean Energy

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“…These distributed computing "big data" analytical approaches to building research have been applied to processing and analyzing building energy datasets, to building population studies, and to the use of machine learning methods [22]. Generally, the development of data-driven analysis methods has lead to the introduction of new savings opportunities on the energy consumption side, whereas the innovations on savings in energy generation such as renewable energy implementation and storage has already been discussed in several research studies [23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Automated pipeline framework for processing of large-scale building energy time series data

et al. 2020

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Commercial buildings account for one third of the total electricity consumption in the United States and a significant amount of this energy is wasted. Therefore, there is a need for “virtual” energy audits, to identify energy inefficiencies and their associated savings opportunities using methods that can be non-intrusive and automated for application to large populations of buildings. Here we demonstrate virtual energy audits applied to large populations of buildings’ time-series smart-meter data using a systematic approach and a fully automated Building Energy Analytics (BEA) Pipeline that unifies, cleans, stores and analyzes building energy datasets in a non-relational data warehouse for efficient insights and results. This BEA pipeline is based on a custom compute job scheduler for a high performance computing cluster to enable parallel processing of Slurm jobs. Within the analytics pipeline, we introduced a data qualification tool that enhances data quality by fixing common errors, while also detecting abnormalities in a building’s daily operation using hierarchical clustering. We analyze the HVAC scheduling of a population of 816 buildings, using this analytics pipeline, as part of a cross-sectional study. With our approach, this sample of 816 buildings is improved in data quality and is efficiently analyzed in 34 minutes, which is 85 times faster than the time taken by a sequential processing. The analytical results for the HVAC operational hours of these buildings show that among 10 building use types, food sales buildings with 17.75 hours of daily HVAC cooling operation are decent targets for HVAC savings. Overall, this analytics pipeline enables the identification of statistically significant results from population based studies of large numbers of building energy time-series datasets with robust results. These types of BEA studies can explore numerous factors impacting building energy efficiency and virtual building energy audits. This approach enables a new generation of data-driven buildings energy analysis at scale.

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“…It proposes that the operating parameters of the electrolyzer, namely the temperature and the pressure, have a great impact on the overall efficiency. In Khalilnejad et al, the operation of a combined PV‐electrolyzer system to produce hydrogen as a fuel is designed and simulated, and the maximum hydrogen production and minimum average excess power are considered as the optimization indices in this study.…”

Section: Introductionmentioning

confidence: 99%

Experimental study on the external electrical thermal and dynamic power characteristics of alkaline water electrolyzer

Shen

Zhang

et al. 2018

Int J Energy Res

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Summary As hydrogen production with a water electrolyzer is an effective way for renewable energy consumption, understanding the external electrical characteristics of water electrolyzer is of great significance for the modeling and simulation, system configuration, and control strategy of the system for hydrogen production by renewable energy. However, there are relatively fewer studies in this area. This paper presents the establishment of an experimental platform to conduct an experimental study on the static and dynamic voltage‐current characteristics and analyze the adjustability of the electric power of the traditional alkaline water electrolyzer, the relationship between the electrical characteristics and the electrolyte temperature, and operating point of the alkaline water electrolyzer. In addition, the mathematical fitting problem of the electrical characteristics of the alkaline water electrolyzer is discussed. The work could supply a reference to alkaline water electrolyzer intergrated application in renewable energy.

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Optimal Operation of Combined Photovoltaic Electrolyzer Systems

Cited by 16 publications

References 34 publications

Optimal design of hybrid wind/photovoltaic electrolyzer for maximum hydrogen production using imperialist competitive algorithm

Optimal design of hybrid wind/photovoltaic electrolyzer for maximum hydrogen production using imperialist competitive algorithm

Automated pipeline framework for processing of large-scale building energy time series data

Experimental study on the external electrical thermal and dynamic power characteristics of alkaline water electrolyzer

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