Optimal multi-layer economical schedule for coordinated multiple mode operation of wind–solar microgrids with hybrid energy storage systems

Abdelghany, Muhammad Bakr; Al-Durra, Ahmed; Daming, Zhou; Gao, Fei

doi:10.1016/j.jpowsour.2023.233844

Cited by 24 publications

(3 citation statements)

References 57 publications

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“…The datadriven energy management system was reported in Wen and Aziz 42 for the flexible operation of energy hubs and MCMGs, while hydrogen ammonia technologies were studied. Abdelghany et al 43,44 reported a new strategy according to the hierarchical rolling horizon control and model predictive control (MPC) to efficiently manage an HSS-based MG. Abdelghany et al 45 reported the control platform architecture of a real HSS-based energy system paired with WTs located in north Norway.…”

Section: Literature Reviewmentioning

confidence: 99%

Optimal technoeconomic reliability‐oriented design of islanded multicarrier microgrids with electrical and hydrogen energy storage systems considering emission concerns

Imanloozadeh,

Nazififard,

Hashemi‐Dezaki

2024

Energy Science & Engineering

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Although several studies have been performed on energy systems, there is a gap in examining the impact of energy storage systems (ESSs) technologies on the technoeconomic design of optimal multicarrier microgrids (MCMGs), considering environmental concerns. This paper aims to address this research gap by developing an optimal technoeconomic reliability‐oriented design of MCMGs, specifically focusing on battery storage systems (BSSs) and hydrogen storage systems (HSSs). The study was applied to MCMG at an actual MCMG, using HOMER Pro software. Additionally, a reliability‐oriented sensitivity analysis is conducted to understand the effects of reliability constraints, such as desired maximum capacity shortage, on the performance of various ESS technologies. One of the main contributions is analyzing the HSS and BSS from different viewpoints, such as cost, emission, and other technical–economic features for MCMGs. The comparative test results show that if a highly reliable MCMG is desired, the BSS‐based MCMG is the more practical option in terms of technoeconomic indices. However, regardless of reliability constraints, the HSS‐based MCMGs offer better environmental conditions. The total net present cost of the HSS‐based MCMG is 1.68% higher than the BSS‐based one, while it has 17.99% less CO2 emissions, while the HSS one has 17.99% less CO2 emissions.

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Section: Literature Reviewmentioning

confidence: 99%

Optimal technoeconomic reliability‐oriented design of islanded multicarrier microgrids with electrical and hydrogen energy storage systems considering emission concerns

Imanloozadeh,

Nazififard,

Hashemi‐Dezaki

2024

Energy Science & Engineering

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“…Authors in [12] present a model predictive control (MPC) process for dealing with forecast deviations, and this work considers an islanded microgrid in which hydrogen is used for long-term storage. Two control layers, one for day-ahead and one for the real-time market, are proposed in [13] for a microgrid that also considers hydrogen consumers. On the other hand, this work is focused on a plant connected to a large electrical system.…”

Section: Introductionmentioning

confidence: 99%

Optimal Operation and Market Integration of a Hybrid Farm with Green Hydrogen and Energy Storage: A Stochastic Approach Considering Wind and Electricity Price Uncertainties

García-Miguel,

Zarilli,

Alonso-Martinez

et al. 2024

Sustainability

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In recent years, growing interest has emerged in investigating the integration of energy storage and green hydrogen production systems with renewable energy generators. These integrated systems address uncertainties related to renewable resource availability and electricity prices, mitigating profit loss caused by forecasting errors. This paper focuses on the operation of a hybrid farm (HF), combining an alkaline electrolyzer (AEL) and a battery energy storage system (BESS) with a wind turbine to form a comprehensive HF. The HF operates in both hydrogen and day-ahead electricity markets. A linear mathematical model is proposed to optimize energy management, considering electrolyzer operation at partial loads and accounting for degradation costs while maintaining a straightforward formulation for power system optimization. Day-ahead market scheduling and real-time operation are formulated as a progressive mixed-integer linear program (MILP), extended to address uncertainties in wind speed and electricity prices through a two-stage stochastic optimization model. A bootstrap sampling strategy is introduced to enhance the stochastic model’s performance using the same sampled data. Results demonstrate how the strategies outperform traditional Monte Carlo and deterministic approaches in handling uncertainties, increasing profits up to 4% per year. Additionally, a simulation framework has been developed for validating this approach and conducting different case studies.

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“…Due to the variability of the energy produced during the day/night cycle and the seasonality in the summer/winter cycles, hydrogen cannot be produced just by using the green energy from the sun [102]. The required energy must be supplemented by the energy from the wind, which also blows at night, i.e., when the sun is not shining [103]. The most stable of the renewable energy sources are hydroelectric power plants.…”

Section: Introductionmentioning

confidence: 99%

Strategic Model for Yellow Hydrogen Production Using the Metalog Family of Probability Distributions

Małek,

Dudziak,

Caban

et al. 2024

Energies

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Storing energy in hydrogen has been recognized by scientists as one of the most effective ways of storing energy for many reasons. The first of these reasons is the availability of technology for producing hydrogen from water using electrolytic methods. Another aspect is the availability of relatively cheap energy from renewable energy sources. Moreover, you can count on the availability of large amounts of this energy. The aim of this article is to support the decision-making processes related to the production of yellow hydrogen using a strategic model which exploits the metalog family of probability distributions. This model allows us to calculate, with accuracy regarding the probability distribution, the amount of energy produced by photovoltaic systems with a specific peak power. Using the model in question, it is possible to calculate the expected amount of electricity produced daily from the photovoltaic system and the corresponding amount of yellow hydrogen produced. Such a strategic model may be appropriate for renewable energy developers who build photovoltaic systems intended specifically for the production of yellow and green hydrogen. Based on our model, they can estimate the size of the photovoltaic system needed to produce the assumed hydrogen volume. The strategic model can also be adopted by producers of green and yellow hydrogen. Due to precise calculations, up to the probability distribution, the model allows us to calculate the probability of providing the required energy from a specific part of the energy mix.

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Optimal multi-layer economical schedule for coordinated multiple mode operation of wind–solar microgrids with hybrid energy storage systems

Cited by 24 publications

References 57 publications

Optimal technoeconomic reliability‐oriented design of islanded multicarrier microgrids with electrical and hydrogen energy storage systems considering emission concerns

Optimal technoeconomic reliability‐oriented design of islanded multicarrier microgrids with electrical and hydrogen energy storage systems considering emission concerns

Optimal Operation and Market Integration of a Hybrid Farm with Green Hydrogen and Energy Storage: A Stochastic Approach Considering Wind and Electricity Price Uncertainties

Strategic Model for Yellow Hydrogen Production Using the Metalog Family of Probability Distributions

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