Optimal Placement and Sizing of Wind Turbine Generators and Superconducting Magnetic Energy Storages in a Distribution System

Hashem, Mohamed; Abdel‐Salam, M.; El-Mohandes, Mohamed Th.; Nayel, Mohamed; Ebeed, Mohamed

doi:10.1016/j.est.2021.102497

Cited by 43 publications

(18 citation statements)

References 44 publications

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“…A comparison is made with the recent literature that focused on similar problems and is presented in Table 4. In Reference 37, optimal sizing of the HRES is achieved in the city of Visakhapatnam using mutation‐based QPSO by considering life cycle emissions along with LPSP and LCoE. However, the ramping rate limitations of the thermal power plants and battery degradation are not focused.…”

Section: Simulation Results and Analysismentioning

confidence: 99%

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A hybrid multiobjective optimization technique for optimal sizing of BESS‐WtE supported multi‐MW HRES to overcome ramp rate limitations on thermal stations

Nuvvula

Elangovan

Kishore³

2021

Int Trans Electr Energ Syst

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In India, favorable renewable energy policies have resulted in a higher proportion of renewable energy in the system. However, this led to the lower capacity utilization factor of thermal power stations. Any additional burden on thermal stations by enforcing higher ramp rates during peak hours would seriously affect technically as well as economically. In this regard, further renewable additions must be supported by energy storage systems to meet the ramping requirements. Wasteto-energy (WtE) plants play a crucial role in improving grid resilience in a highrenewable energy scenario to support expensive battery energy storage systems.In this article, the potential of WtE is assessed for a smart city in India, selected based on the possible urban and industrial growth, along with three other renewable energy technologies such as floating solar, bifacial rooftops solar, and wind energy conversion systems. The selected location has a total renewable energy potential of 439 MW. To achieve the municipality's techno-economic objectives, a multiobjective-enabled adaptive local attractor-based quantum-behaved particle swarm optimization (ALA-mQPSO) is proposed with mutation. With the proposed ALA-mQPSO, Pareto optimal sets of the hybrid renewable energy sources aided by the combination of battery energy storage system and WtE plant is achieved. The Pareto fronts are then compared with the benchmark techniques

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Section: Simulation Results and Analysismentioning

confidence: 99%

“…36 A suggested multiobjective-function-based optimization technique backed by superconducting magnetic energy storages and optimal positioning and sizing of WTGs and SMESs in a distribution system is used to address problems related with the penetration of intermittent wind-turbine power. 37…”

Section: Current Electric Energy Scenario In Indiamentioning

confidence: 99%

A hybrid multiobjective optimization technique for optimal sizing of BESS‐WtE supported multi‐MW HRES to overcome ramp rate limitations on thermal stations

Nuvvula

Elangovan

Kishore³

2021

Int Trans Electr Energ Syst

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“…The EM issue was handled by equilibrium optimizer (EO) for the multiple objective function that involves cost lessening, voltage profile, voltage stability enhancement. Hashem et al 36 have explained determining the optimum location and sizing of WTGs and SMESs in distribution scheme with the help of presented model depending on multi‐objective‐function. The presented method based upon EO together with loss sensitivity factor.…”

Section: Recent Research Work: a Brief Reviewmentioning

confidence: 99%

Artificial cell swarm optimization and vapor liquid equilibrium for energy management system in smart grid

Ganesan¹,

Xavier²

2022

Int J Numerical Modelling

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This article proposes a hybrid approach for energy management system in smart grid. The smart grid system contains photovoltaic, wind turbine, micro turbine, battery. The proposed hybrid approach is the combination of artificial cell swarm optimization (ACSO) and vapor liquid equilibrium (VLE); therefore, it is termed as ACSO‐VLE. The aim of the proposed approach is minimization of fuel cost, operation and maintenance cost, hourly power variation in the grid connected micro grid system. The necessary load demand of grid connected micro grid system is continually monitored by ACSO. The VLE is enhanced the perfect consolidation of micro grid with respect to predicted load demand. During the micro grid operation, the first approach is focused the scheduling of various renewable energy sources to lessen the cost of electricity. The aim of the second method is to balance the power flow and diminish the impacts of predicting errors depending on rule summarized from the scheduled power reference. The proposed model is carried out in MATLAB; its efficiency is examined to with and without grid of micro grid system. The effectiveness of ACSO‐VLE technique is analyzed through the comparison analysis using the existing techniques. The proficiency is analyzed utilizing cost analysis including power generation of photovoltaic, micro and wind turbine, battery. The Root mean square error (RMSE), MAPE and Mean bias error (MBE) under 50 counts of trails of the proposed technique are 9.3, 4.2 and 2.7, l. Likewise, the RMSE, MAPE and MBE under 100 counts of trails are 13.5, 3.9 and 5.7. The mean, median, standard deviation attains 0.9681, 0.9062, and 0.1099.

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“…New ones include the Monarch Butterfly Optimization (MBO) [ 28 ], Slime Mould Algorithm (SMA) [ 29 ], Moth Search Algorithm (MSA) [ 30 ], hunger games search (HGS) [ 31 ], RUNge Kutta method (RUN) [ 32 ], colony predation algorithm (CPA) [ 33 ], Weighted mean of vectors (INFO) [ 34 ] and Harris Hawks Optimization (HHO) [ 20 ]. They are widely used in engineering to optimize traditional complex engineering problems such as distribution system [ 35 ], power flow [ 36 ], and power grid [ 37 ]. It is also often applied to solve optimization problems in the biological field [ 38 , 39 ].…”

Section: Introductionmentioning

confidence: 99%

Levy Equilibrium Optimizer algorithm for the DNA storage code set

Zhang

2022

PLoS ONE

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The generation of massive data puts forward higher requirements for storage technology. DNA storage is a new storage technology which uses biological macromolecule DNA as information carrier. Compared with traditional silicon-based storage, DNA storage has the advantages of large capacity, high density, low energy consumption and high durability. DNA coding is to store data information with as few base sequences as possible without errors. Coding is a key technology in DNA storage, and its results directly affect the performance of storage and the integrity of data reading and writing. In this paper, a Levy Equilibrium Optimizer (LEO) algorithm is proposed to construct a DNA storage code set that satisfies combinatorial constraints. The performance of the proposed algorithm is tested on 13 benchmark functions, and 4 new global optima are obtained. Under the same constraints, the DNA storage code set is constructed. Compared with previous work, the lower bound of DNA storage code set is improved by 4–13%.

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Optimal Placement and Sizing of Wind Turbine Generators and Superconducting Magnetic Energy Storages in a Distribution System

Cited by 43 publications

References 44 publications

A hybrid multiobjective optimization technique for optimal sizing of BESS‐WtE supported multi‐MW HRES to overcome ramp rate limitations on thermal stations

A hybrid multiobjective optimization technique for optimal sizing of BESS‐WtE supported multi‐MW HRES to overcome ramp rate limitations on thermal stations

Artificial cell swarm optimization and vapor liquid equilibrium for energy management system in smart grid

Levy Equilibrium Optimizer algorithm for the DNA storage code set

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