Optimal Planning of Nuclear-Renewable Micro-Hybrid Energy System by Particle Swarm Optimization

Abdussami, Muhammad R.; Adham, Md. Ibrahim

doi:10.1109/access.2020.3027524

Cited by 35 publications

(13 citation statements)

References 43 publications

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“…For utility companies, it is necessary to optimize power production so that the maximum amount of energy is utilized from these renewable sources so as to reduce cost to the user while also maintaining the quality of service. The authors in [47][48][49][50][51][52][53][54][55][56][57][58][59][60] provide a management scheme for DERs to minimize cost. In this regard, the authors in [47,48,[50][51][52]55,[58][59][60] all formulate the problem of distributed energy resource management as a single objective problem where the cost incurred is minimized.…”

Section: Smart Gridmentioning

confidence: 99%

Making Cities Smarter—Optimization Problems for the IoT Enabled Smart City Development: A Mapping of Applications, Objectives, Constraints

Syed

Sierra-Sosa

Kumar

et al. 2022

Sensors

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One of the prime aims of smart cities has been to optimally manage the available resources and systems that are used in the city. With an increase in urban population that is set to grow even faster in the future, smart city development has been the main goal for governments worldwide. In this regard, while the useage of Artificial Intelligence (AI) techniques covering the areas of Machine and Deep Learning have garnered much attention for Smart Cities, less attention has focused towards the use of combinatorial optimization schemes. To help with this, the current review presents a coverage of optimization methods and applications from a smart city perspective enabled by the Internet of Things (IoT). A mapping is provided for the most encountered applications of computational optimization within IoT smart cities for five popular optimization methods, ant colony optimization, genetic algorithm, particle swarm optimization, artificial bee colony optimization and differential evolution. For each application identified, the algorithms used, objectives considered, the nature of the formulation and constraints taken in to account have been specified and discussed. Lastly, the data setup used by each covered work is also mentioned and directions for future work have been identified. This review will help researchers by providing them a consolidated starting point for research in the domain of smart city application optimization.

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Section: Smart Gridmentioning

confidence: 99%

Making Cities Smarter—Optimization Problems for the IoT Enabled Smart City Development: A Mapping of Applications, Objectives, Constraints

Syed

Sierra-Sosa

Kumar

et al. 2022

Sensors

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“…The Generator Size, Capital Cost, Replacement Cost, Fixed O & M cost, Lifetime, CO 2 emission, and Fuel cost of diesel generator are 1000 (kW), 800 (USD/kW), 800 (USD/kW), 35 (USD/kW/Year), 2.5 (Years), 700 (kg/MWh), and 202 (USD/MWh), respectively [14], [20].…”

Section: Diesel Generatormentioning

confidence: 99%

“…P gen (t) = P pv (t) + P w (t) + P GNRT (t) ∀t ∈ t total (14) where, BAT inm (t), BAT outm (t), P genm (t), P L (t), P pv (t), P w (t), P vSMR (t), P GNRT (t) is the amount of energy that can be given to the battery bank, the amount of energy that is needed from the battery bank, the total electric energy generation, the total electric load, the total electric energy from the solar panel, the total electric energy from the wind turbine, the total electric energy from MR, and the total electric energy from diesel generator at the time step (t), respectively. The amount of energy that the battery bank can take and give at any time step can be formulated by the below equations.…”

Section: Electrochemical Energy Storagementioning

confidence: 99%

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Optimal Planning of Integrated Nuclear-Renewable Energy System for Marine Ships Using Artificial Intelligence Algorithm

Adham

Abdussami

2021

Energies

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Ocean-going ships are one of the primary sources of Greenhouse Gas (GHG) emissions. Several actions are being taken to reduce the GHG emissions from maritime vessels, and integration of Renewable Energy Sources (RESs) is one of them. Ocean-going marine ships need a large amount of reliable energy to support the propulsive load. Intermittency is one of the drawbacks of RESs, and penetration of RESs in maritime vessels is limited by the cargo carrying capacity and usable area of that ship. Other types of reliable energy sources need to be incorporated in ships to overcome these shortcomings of RESs. Some researchers proposed to integrate fossil fuel-based generators like diesel generators and renewable energy in marine vessels to reduce GHG emissions. As the penetration of RESs in marine ships is limited, fossil fuel-based generators provide most of the energy. Therefore, renewable and fossil fuel-based hybrid energy systems in maritime vessels can not reduce GHG emissions to the desired level. Fossil fuel-based generators need to be replaced by emissions-free energy sources to make marine ships free from emissions. Nuclear energy is emissions-free energy, and small-scale nuclear reactors like Microreactors (MRs) are competent to replace fossil fuel-based generators. In this paper, the technical, environmental, and economic competitiveness of Nuclear-Renewable Hybrid Energy Systems (N-R HES) in marine ships are assessed. The lifecycle cost of MR, reliability of the proposed system, and limitations of integrating renewable energy in maritime vessels are considered in this study. The proposed N-R HES is compared with three different energy systems, namely ‘Standalone Fossil Fuel-based Energy Systems’, ‘Renewable and Fossil Fuel-based Hybrid Energy Systems’, and ‘Standalone Nuclear Energy System’. The cost modeling of each energy system is carried out in MATLAB simulator. Each energy system is optimized by using the Differential Evolution Algorithm (DEA), an artificial intelligence algorithm, to find out the optimal configuration of the system components in terms of Net Present Cost (NPC). The results determine that N-R HES has the lowest NPC compared to the other three energy systems. The performance of the DE algorithm is compared with another widely accepted artificial intelligence optimization technique called ‘Particle Swarm Optimization (PSO)’ to validate the findings of the DE algorithm. The impact of control parameters in the DE algorithm is assessed by employing the Adaptive Differential Evolution (ADE) algorithm. A sensitivity analysis is carried out to assess the impact of different system parameters on this study’s findings.

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“…[9] EENS, LOLE [47] EENS, Energy index of reliability [56] EENS, EIR [12] LPSP, LEP [65] LOLP, LOEP [66] LPSP, Total energy loss [44] ENS [55] LOLE, LOLF,EENS [67] LOLP [49] EENS [68] LPSP [69] LPSP, LOEE, LOLE Probabilistic Subcategory: Frequency and duration based indices [43] SAIFI, SAIDI  Information regarding type of outage  Provides information regarding frequency and duration of outage.  Useful for customer or load point evaluation.…”

Section: Probabilistic Criteriamentioning

confidence: 99%

A Technical Review on Reliability and Economic Assessment Framework of Hybrid Power System with Solar and Wind Based Distributed Generators

Paliwal

2021

IJIE

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Recent years have witnessed an upsurge in the penetration of solar and wind power. This can be chiefly attributed to worldwide climate concern and inclination towards low carbon sources. Owing to their abundant availability, solar and wind sources are projected to play a key part in de-carbonization of power sector. However, the variability of these sources and high initial cost pose a major challenge in their deployment. Thus, reliability and economic assessment is imperative to hybrid power system(HPS) with solar and wind integration. This paper tenders a survey on different aspects involved in reliability and economic assessment of HPS. Various techniques employed in uncertainty modelling of climatological parameters like solar irradiance and wind velocity have been deliberated. A detailed discussion on reliability evaluation parameters as well as techniques along with their merits and demerits has been carried out. In order to impart a sense of extensiveness to review, a discussion on economic evaluation metrics has also been presented. Further, author’s critical comments on review along with suggestions for possible research avenues has also been presented. The review presented in this paper is envisioned to facilitate a comprehensive guide towards evaluation of solar and wind energy based HPS.

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Optimal Planning of Nuclear-Renewable Micro-Hybrid Energy System by Particle Swarm Optimization

Cited by 35 publications

References 43 publications

Making Cities Smarter—Optimization Problems for the IoT Enabled Smart City Development: A Mapping of Applications, Objectives, Constraints

Making Cities Smarter—Optimization Problems for the IoT Enabled Smart City Development: A Mapping of Applications, Objectives, Constraints

Optimal Planning of Integrated Nuclear-Renewable Energy System for Marine Ships Using Artificial Intelligence Algorithm

A Technical Review on Reliability and Economic Assessment Framework of Hybrid Power System with Solar and Wind Based Distributed Generators

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