Techno-economic analysis of a heat and power combination system based on hybrid photovoltaic-fuel cell systems using hydrogen as an energy vector

Peláez-Peláez, Sofía; Colmenar‐Santos, Antonio; Pérez-Molina, Clara; Rosales, Ana-Esther; Rosales-Asensio, Enrique

doi:10.1016/j.energy.2021.120110

Cited by 72 publications

(19 citation statements)

References 31 publications

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“…Research into investing in renewable energy sources in Serbia [45] suggests public-private partnership as a promising funding mechanism. Using this mechanism for solar capacities would require greater involvement of the state and local governments, which should recognize special challenges in solar energy production projects and dynamics of change [46].…”

Section: Discussionmentioning

confidence: 99%

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Artificial Intelligence and Nature-Inspired Optimization on Integrative Capacity of Renewable Energy in the Western Balkan

Stevović¹,

Kirin²,

Bozic³

2021

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Two artificial intelligence models for the integration of renewable energy sources are developed within this research to contribute to the European Green Plan realization. The review of renewable energy natural potential, on one hand, and installed capacity, on the other hand, in the Western Balkans and twenty-eight European countries is done within this research, as well as emissions. The analyses show that the European countries, sometimes even with lower natural potential in renewables, have installed much more renewable capacities than the Balkans countries with much higher natural potential. According to this, the first artificial intelligence model is developed based on multi-criteria linear regression analysis. This model relies on the correlation between the relevant regressors, i.e. relevant input variables for twenty-eight European countries and the same regressors for a particular Balkans country. Its goal is to find the maximum possible integrative renewable capacity in a Balkans’s country within the real socio-economic environment. The second artificial intelligence model is developed based on multi-criteria evolution genetic algorithms. Its goal is to find the maximum possible integrative renewable capacity within a real electric power system. Nature-inspired optimization is applied. From the framework of a given large number of generations, technical combinations of the degree of renewable energy sources integration, the best populations, i.e. combinations are selected. As nature selects from many generations and allows the best to survive and punishes the „weakˮ, in our case, „weak” combinations are those failing to meet the given conditions and limitations of the real electric power system. A new methodology is offered. Theoretical general formulas are given for both models. Developed models are tested on a numerical experiment of solar energy integration in the Serbia case study. Analyses of sensitivity prove that both models are applicable for all renewable energy sources and countries or regions.

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Section: Discussionmentioning

confidence: 99%

“…Other approaches facilitate and harmonize the integration of SPPs. In the literature, they are referred to as "energy to heat" [44], "energy to electricity [45]" and "energy to hydrogen" [46]. All of them represent different methods of solar energy storage.…”

Section: Discussionmentioning

confidence: 99%

Artificial Intelligence and Nature-Inspired Optimization on Integrative Capacity of Renewable Energy in the Western Balkan

Stevović¹,

Kirin²,

Bozic³

2021

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“…The optimal method based on simulation and multi-core parallel computing can quickly obtain the optimal solution in the design space and can perform sensitivity analysis on the specified parameters. The interface with Matlab/Simulink also enables the software to design better energy scheduling strategies [17].…”

Section: Capacity Planning Of Energy Storagementioning

confidence: 99%

A Study for a Hybrid Wind-Solar-Battery System for Hydrogen Production in an Islanded MVDC Network

Lin

2022

IEEE Access

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Renewable energy hydrogen production technology is an effective way to improve the utilization of renewable energy and alleviate the problem of wind and light abandonment. However, there are many challenges in the system structure design and "Source-Load-Storage" coordination control strategy for large-scale, megawatt-scale renewable energy hydrogen production. In this paper, a hybrid wind-solar-energy storage hydrogen production system based on Medium Voltage Direct Current (MVDC) structure is proposed. HOMER software is used to plan and study the storage capacity to achieve longterm power balance and matching of the system. In addition, A decentralized coordinated control energy management system with active power following and state of charge (SOC) recovery capability is proposed and implemented for transient power regulation. An electromagnetic transient simulation was established in PSCAD/EMTDC, and semi-physical experiments were designed using StarSim to verify the effectiveness of the control strategy. Theoretical analysis and experiments show that the island MVDC network with decentralized coordinated control has technical feasibility in realizing hydrogen production from renewable energy in the 20MW level class. In addition, the power consumed by the load can realize the seconds level tracking of the output power of renewable energy.

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“…e ESS costs include the cost of maintaining ESS according to the charging/discharging power transmitted in the IMG. e penalty of load shedding is accounted for in the third part in equations ( 1) and (7). It should be mentioned that the load demand of the critical facilities must be satisfied so it is feasible to cut the proportional energy supply to meet the need of the critical loads.…”

Section: Mathematical Formulationmentioning

confidence: 99%

“…Lorestani et al [6] introduced a rule-based energy management system to administrate the stand-alone multicarrier microgrid operation and maximize RERs utilization. Peláez-Peláez et al [7] proposed a techno-economic assessment for a hybrid combined generation system based on renewable storage technologies. Maulik and Das [8] presented a method for determining optimal droop settings of dispatchable distributed generation units in an IMG aiming at minimizing the operational cost and the emission with the consideration of the uncertainties of load and renewable generation forecasting.…”

Section: Introductionmentioning

confidence: 99%

Robust Model Predictive Control for Energy Management of Isolated Microgrids Based on Interval Prediction

Huang

Liu

et al. 2021

Discrete Dynamics in Nature and Society

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With the integration of Renewable Energy Resources (RERs), the Day-Ahead (DA) scheduling for the optimal operation of the integrated Isolated Microgrids (IMGs) may not be economically optimal in real time due to the prediction errors of multiple uncertainty sources. To compensate for prediction error, this paper proposes a Robust Model Predictive Control (RMPC) based on an interval prediction approach to optimize the real-time operation of the IMGs, which diminishes the influence from prediction error. The rolling optimization model in RMPC is formulated into the robust model to schedule operation with the consideration of the price of robustness. In addition, an Online Learning (OL) method for interval prediction is utilized in RMPC to predict the future information of the uncertainties of RERs and load, thereby limiting the uncertainty. A case study demonstrates the effectiveness of the proposed with the better matching between demand and supply compared with the traditional Model Predictive Control (MPC) method and Hard Charging (HC) method.

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Techno-economic analysis of a heat and power combination system based on hybrid photovoltaic-fuel cell systems using hydrogen as an energy vector

Cited by 72 publications

References 31 publications

Artificial Intelligence and Nature-Inspired Optimization on Integrative Capacity of Renewable Energy in the Western Balkan

Artificial Intelligence and Nature-Inspired Optimization on Integrative Capacity of Renewable Energy in the Western Balkan

A Study for a Hybrid Wind-Solar-Battery System for Hydrogen Production in an Islanded MVDC Network

Robust Model Predictive Control for Energy Management of Isolated Microgrids Based on Interval Prediction

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