Optimal sizing of autonomous hybrid energy system using supply‐demand‐based optimization algorithm

Alturki, Fahd A.; Al-Shamma’a, Abdullrahman A.; Farh, Hassan M. H.; AlSharabi, Khalil

doi:10.1002/er.5766

Cited by 51 publications

(27 citation statements)

References 58 publications

(62 reference statements)

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“…where P r is the PV rated power; G T,STC and G T are the solar PV radiation for standard test conditions (STCs) and normal conditions, respectively; T c,STC and T c are the temperatures under STCs and normal conditions, respectively; and α P and f PV are the power temperature coefficient and derating coefficient, respectively. The PV steady-state temperature is formulated as shown below [50].…”

Section: Modeling Of Pv Generation Sourcementioning

confidence: 99%

“…The diesel generator is considered the secondary standby generation source, which is utilized to cover the load if the renewables (WT and PV) and the batteries are not capable of covering the load demand. The annual fuel cost depends on the diesel rated power and output power generated, which can be formulated as follows [50]:…”

Section: Modeling Of the Diesel Generatormentioning

confidence: 99%

“…The ASC equals the annualized capital costs (C Cap. ), plus the O&M cost (C O&M ) and annualized replacement costs (C Rep. ), as follows [50]:…”

Section: Lpspmentioning

confidence: 99%

“…, and C Diesel are the capital costs of the renewable resources, battery bank, and diesel, respectively. The annualized replacement cost can be formulated as shown below [50].…”

Section: Lpspmentioning

confidence: 99%

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Technical and Economic Evaluation for Off-Grid Hybrid Renewable Energy System Using Novel Bonobo Optimizer

et al. 2022

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In this study, a novel bonobo optimizer (BO) technique is applied to find the optimal design for an off-grid hybrid renewable energy system (HRES) that contains a diesel generator, photovoltaics (PV), a wind turbine (WT), and batteries as a storage system. The proposed HRES aims to electrify a remote region in northern Saudi Arabia based on annualized system cost (ASC) minimization and power system reliability enhancement. To differentiate and evaluate the performance, the BO was compared to four recent metaheuristic algorithms, called big-bang–big-crunch (BBBC), crow search (CS), the genetic algorithm (GA), and the butterfly optimization algorithm (BOA), to find the optimal design for the proposed off-grid HRES in terms of optimal and worst solutions captured, mean, convergence rate, and standard deviation. The obtained results reveal the efficacy of BO compared to the other four metaheuristic algorithms where it achieved the optimal solution of the proposed off-grid HRES with the lowest ASC (USD 149,977.2), quick convergence time, and fewer oscillations, followed by BOA (USD 150,236.4). Both the BBBC and GA algorithms failed to capture the global solution and had high convergence time. In addition, they had high standard deviation, which revealed that their solutions were more dispersed with obvious oscillations. These simulation results proved the supremacy of BO in comparison to the other four metaheuristic algorithms.

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Section: Modeling Of Pv Generation Sourcementioning

confidence: 99%

Section: Modeling Of the Diesel Generatormentioning

confidence: 99%

“…The ASC equals the annualized capital costs (C Cap. ), plus the O&M cost (C O&M ) and annualized replacement costs (C Rep. ), as follows [50]:…”

Section: Lpspmentioning

confidence: 99%

“…, and C Diesel are the capital costs of the renewable resources, battery bank, and diesel, respectively. The annualized replacement cost can be formulated as shown below [50].…”

Section: Lpspmentioning

confidence: 99%

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Technical and Economic Evaluation for Off-Grid Hybrid Renewable Energy System Using Novel Bonobo Optimizer

et al. 2022

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“…It leaves 15% of the world's population without electricity [1]. Especially in remote areas, due to economic and geographic reasons, people face so many challenges related to energy supply [2]. In the current era, the usage of electricity in all countries is increasing day by day.…”

Section: Introductionmentioning

confidence: 99%

Consumer-Driven Demand-Side Management Using K-Mean Clustering and Integer Programming in Standalone Renewable Grid

et al. 2022

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Many countries have larger land areas and scattered communities. Therefore, to electrify them, small standalone power systems are the more preferred and cost-efficient solution as compared to utility grid extensions. The main objective of a standalone power system is to supply cleaner, cheaper, and uninterrupted electricity. However, for standalone power systems, demand-side management always remains a challenging task. In this paper, a load scheduling algorithm driven by K-mean clustering and linear integer programming to schedule consumers’ appliances for the upcoming day is proposed. In addition, the basic power to run the necessary appliances is kept available in the system all the time. Furthermore, to assist the consumer in every situation, the battery storage system and the overall system size reduction are also taken into consideration. Consumer input is also used in scheduling the appliances. The proposed method is evaluated on the publicly available real-world dataset; the simulation results demonstrate that the proposed approach performs better, due to which the reliability and continuity of the system are increased.

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Amulti‐objectiveapproach for the optimal design of a standalone hybrid renewable energy system

Anilkumar

Kollu

Rayapudi

et al. 2021

Intl J of Energy Research

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Dependency on alternative energy sources has increased due to the depletion of fossil fuel and their costs. Even though the usage of renewable energy sources (RESs) has significantly reduced these problems, there are quite a few challenges like reliability, lower efficiency, and high cost which can be overcome by the integration of multiple RES to meet the energy demand. In this study, a multi-objective approach is proposed to get the best optimal sizing configuration of a standalone hybrid renewable energy system (HRES) by choosing the minimization of the total cost of the system and loss of power supply probability. In this regard, wind turbines, solar photovoltaic (PV), battery storage systems, biomass, and diesel generators are used to design HRES. The proposed approach deals with the intermittent nature of wind and solar PV power generation using Weibull distribution to model wind speed and solar irradiance. The normal distribution is used to model the load demand. The backtracking search algorithm capable of solving single-objective optimization problems is modified to handle the multi-objective optimization problem and to find the optimal sizes of wind turbines, solar PV, battery storage system, diesel, and biomass generators for efficient HRES performance.

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Optimal sizing of autonomous hybrid energy system using supply‐demand‐based optimization algorithm

Cited by 51 publications

References 58 publications

Technical and Economic Evaluation for Off-Grid Hybrid Renewable Energy System Using Novel Bonobo Optimizer

Technical and Economic Evaluation for Off-Grid Hybrid Renewable Energy System Using Novel Bonobo Optimizer

Consumer-Driven Demand-Side Management Using K-Mean Clustering and Integer Programming in Standalone Renewable Grid

Amulti‐objectiveapproach for the optimal design of a standalone hybrid renewable energy system

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