Optimal sizing and distribution system reconfiguration of hybrid FC/WT/PV system using cluster computing based on harmony search algorithm

Brinda, M. Deva; Suresh, A.; Rashmi, M. R.

doi:10.1007/s10586-017-1605-x

Cited by 14 publications

(6 citation statements)

References 15 publications

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“…Maleki [62] utilized the discrete simulated annealing algorithm to optimize the size of a solar/wind/fuel cell HRES. Based on the maximum voltage stability index and minimum power loss, Brinda et al [63] applied the harmony search algorithm to optimize a solar/wind/fuel cell HRES in terms of the size and configuration of the system. With the premise of meeting load requirements, Ahmadi et al [64] proposed an effective optimization approach based on a hybrid big bang-big crunch (HBB-BC) algorithm to optimize the size of a stand-alone HRES.…”

Section: Artificial Intelligence Methods Of Optimization For Hybrid R...mentioning

confidence: 99%

A review of hydrogen-based hybrid renewable energy systems: Simulation and optimization with artificial intelligence

Cai

Agbossou

et al. 2022

J. Phys.: Conf. Ser.

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With the massive use of traditional fossil fuels, greenhouse gas emissions are increasing, and environmental pollution is becoming an increasingly serious problem, which led to an imminent energy transition. Therefore, the development and application of renewable energy are particularly important. This paper reviews a wide range of issues associated with hybrid renewable energy systems (HRESs). The issues concerning system configurations, energy storage options, simulation and optimization with artificial intelligence are discussed in detail. Storage technology options are introduced for stand-alone (off-grid) and grid-connected (on-grid) HRESs. Different optimization methodologies, including classical techniques, intelligent techniques, hybrid techniques and software tools for sizing system components, are presented. Besides, the artificial intelligence methods for optimizing the solar/wind HRESs are discussed in detail.

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Section: Artificial Intelligence Methods Of Optimization For Hybrid R...mentioning

confidence: 99%

A review of hydrogen-based hybrid renewable energy systems: Simulation and optimization with artificial intelligence

Cai

Agbossou

et al. 2022

J. Phys.: Conf. Ser.

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“…By reviewing the literature, some studies [33][34][35][36][37] have been identified to optimize the RES by physical or chemical heuristic algorithms, such as simulated annealing algorithm, harmony search algorithm, discrete harmony search algorithm, mine blast algorithm.…”

Section: Physical or Chemical Biological Heuristic Algorithms For Opt...mentioning

confidence: 99%

“…The results showed that the PV/WT/FC/diesel HRES was the best choice for decreasing emissions and wastes, and the PV/FC/diesel HRES was the most cost-effective power generation system as diesel HEET-2021 Journal of Physics: Conference Series 2208 (2022) 012013 price rose. Brinda et al [35] applied a harmony search algorithm (HS) to optimize the size and distribution system reconfiguration of FC/WT/PV HRES for maximizing voltage stability index (VSI) and minimizing the cost, power loss and pollution. Maliki et al [36] used a discrete harmony search algorithm (DHS) to optimize the size of independent PV/WT/diesel systems with batteries or fuel cell storage devices to achieve minimum cost.…”

Section: Physical or Chemical Biological Heuristic Algorithms For Opt...mentioning

confidence: 99%

Artificial intelligence for hydrogen-based hybrid renewable energy systems: A review with case study

Yan

Agbossou

et al. 2022

J. Phys.: Conf. Ser.

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In recent years, with the progress of computer technology, artificial intelligence has been rapidly developed and begun to be applied in industry, economy and other aspects. Besides, with the pursuit of green hydrogen, hydrogen-based hybrid renewable energy systems have become the focus of the development of the hydrogen industry. This paper compares different artificial intelligence applications in hydrogen-based hybrid renewable energy systems and carries out a case study in a typical area. Firstly, this paper summarizes important works in literature, which use artificial intelligence methods to predict the supply chain of the renewable energy system, including the prediction of renewable energy system resources, output power, load demand and terminal electricity price. Secondly, main articles about artificial intelligence optimization algorithms used in renewable energy systems are also summarized, including swarm and non-swarm biological heuristics, physical or chemical heuristics and hybrid optimization algorithms. Finally, a case study is carried out in Tikanlik, Xinjiang, China. Tikanlik’s weather and load data train the artificial neural network to predict system output power. It shows that 99.32% of the relative error of the test set is less than 3%, which proves that this model can achieve good prediction results.

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“…According to the recent reviews, it is analyzed that the optimal sizing of equipment in hybrid systems 23,24 still remains one of the most challenging and crucial task. The key contribution of this work is to present the comprehensive analysis between GA and PSO techniques based on the objective functions of optimal sizing of components and minimizing the total net cost of hybrid energy storage systems.…”

Section: Introductionmentioning

confidence: 99%

“…According to the recent reviews, it is analyzed that the optimal sizing of equipment in hybrid systems 23,24 still remains one of the most challenging and crucial task.…”

Section: Introductionmentioning

confidence: 99%

A hybrid energy storage system using GA and PSO for an islanded microgrid applications

Firdouse¹,

Reddy²

2023

Energy Storage

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The renewable‐based hybrid energy storage systems have gained significant attention in recent times, due to their increased power extraction efficiency, cost‐effectiveness, and eco‐friendly nature. But, the power management, optimal sizing of components, economic cost of energy, and system reliability are considered as the major problems of hybrid energy storage systems. For this purpose, the different types of optimization methodologies are developed in the conventional works for optimizing the size and cost of hybrid energy systems. The main contribution of this work is to design an efficient and reliable hybrid energy storage system based on the combination of solar, wind, biomass, batteries, and generators with optimal sizing of components, and reduced system cost. Hence, two different types of meta‐heuristics optimization techniques such as genetic algorithm (GA), and particle swarm optimization (PSO) are validated and compared with select the most suitable one for the reliable hybrid energy systems. Here, the mathematical modeling of a hybrid energy sources are presented for generating the electricity. It also discussed about the operating principles, working nature, flow of modeling, advantages, and disadvantages of GA and PSO techniques. During simulation, the performance of these algorithms is evaluated and compared by using various measures. Due to the increased convergence rate, reduced overfitting, and local optimum the performance of PSO is highly improved, when compared with the GA. Also, the PSO is discovered to perform better than the GA because it concurrently executes global and local searches, whereas the GA focuses primarily on the global search. The total excess energy for the entire year is estimated to be 5139 kWh/yr based on the findings. The PSO algorithm accurately predicts solar PV, wind turbines, batteries, and biomass gasifier with an ASC of 63 006$/yr and an LCOE of 0.173$/kWh. Hence, the results of PSO are superior than the standard GA mechanism. Moreover, the obtained results indicate that the PSO algorithm provides the better results compared with GA and HOMER.

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Optimal sizing and distribution system reconfiguration of hybrid FC/WT/PV system using cluster computing based on harmony search algorithm

Cited by 14 publications

References 15 publications

A review of hydrogen-based hybrid renewable energy systems: Simulation and optimization with artificial intelligence

A review of hydrogen-based hybrid renewable energy systems: Simulation and optimization with artificial intelligence

Artificial intelligence for hydrogen-based hybrid renewable energy systems: A review with case study

A hybrid energy storage system using GA and PSO for an islanded microgrid applications

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