Reliability Improvement of Radial Distribution System by Optimal Placement and Sizing of Energy Storage System using TLBO

Lata, Preet; Vadhera, Shelly

doi:10.1016/j.est.2020.101492

Cited by 43 publications

(9 citation statements)

References 36 publications

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“…Note that BESS units' charging and discharging phases are identical to avoid the internal energy exchange between BESS units at each time interval. [65,66], E i max maximum capacity of the storage device that is set to 1.8 MWh. Equations ( 14) and ( 15) define the main substation's active and reactive power limits, identified as the reference bus in this analysis.…”

Section: ) Inequality Constraintsmentioning

confidence: 99%

Dynamic Multi-Objective Optimization of Grid-Connected Distributed Resources Along With Battery Energy Storage Management via Improved Bidirectional Coevolutionary Algorithm

Ali,

Liu,

Ali

et al. 2024

IEEE Access

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This paper explores the synergistic role of Distributed Resources (DR), including Distributed Generation (DG) and Battery Energy Storage Systems (BESS), in enhancing modern power systems' sustainability, reliability, and flexibility. It addresses the gap in concurrent distribution network reconfiguration and DR allocation, especially under the variability of renewable energy. The study aims to minimize energy costs, losses, and voltage deviations by integrating wind and solar PV-type DGs with BESS. A novel multi-objective function and an improved bi-directional coevolutionary (I-BiCo) Algorithm are employed to find the optimal RES and BESS placement and sizing, showing marked improvements over existing methods. Furthermore, statistical comparisons using hypervolume, objective function values (diversity), and near-global solutions (convergence) underscore the proposed algorithm's superiority over existing MOEAs. The final non-dominated solution, obtained through fuzzy set theory, highlights simulation results that minimize power loss, achieve substantial energy savings, and smooth demand, particularly with the integration of BESS devices. Moreover, optimal network reconfiguration (ONR) is a key strategy for balancing load demand. Simulation results affirm that minimizing bi-objective and tri-objective functions, coupled with optimal feeder reconfiguration, significantly reduces power loss and enhances voltage profiles, approaching unity across all buses. The proposed ONR formulation, in conjunction with DGs and BESS, maximizes the overall performance of power distribution networks. Furthermore, the paper addresses various time-dependent constraints of BESS, DG, and ONR, formulating and efficiently solving these constraints by integrating different constraint-handling techniques with the proposed multi-objective evolutionary algorithm. The study contributes to academic discourse and provides practical insights for designing more

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Section: ) Inequality Constraintsmentioning

confidence: 99%

Dynamic Multi-Objective Optimization of Grid-Connected Distributed Resources Along With Battery Energy Storage Management via Improved Bidirectional Coevolutionary Algorithm

Ali,

Liu,

Ali

et al. 2024

IEEE Access

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“…In [27], the author proposed the financial effect of automated sectionalizing switches in terms of cutting yearly financial losses associated with process trips and genetic algorithms is used in order to deal with the high number of substitutes to decrease the reliability indices. In order to increase the reliability of a radial distribution system, this researcher suggested an algorithm using the Teacher Learning based Optimization (TLBO) method for the ideal positioning and sizing of energy storage systems (ESSs) [28]. In order to coordinate manual and remote-controlled switching activities in a way that improves reliability, the author has suggested a combined switch mechanism technique.…”

Section: Associated Research Workmentioning

confidence: 99%

Economic Analysis of Isolator Placement in the Radial Network for Enhancement of Reliability Indicators

Madhav

Yadav

2023

Preprint

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This paper presents a novel technique to upgrade the distribution network reliability indices in the radial electrical distribution system. The genetic algorithm (GA) technique is used to determine the optimum position and number of isolators in the electrical distribution network. The problem formulation of this real problem is formulated with the product of unavailability and the total number of consumers affected under the constraints of the optimal number of switches. Among various reliability indices system average interruption duration index is selected to realize the problem. The technique is applied on 34 and 59 load point systems and the results show the acceptance of the suggested method in the paper. This algorithm is compared with particle swarm optimization on 22 and 34 bus system and found GA provide better result. It is also analyzed that the customer-oriented and energy-oriented indices upgraded sharply and consumers service indices are very good so that profit of the distribution company enhanced. All reliability indices improve after optimum switch placement in a radial distribution network. Diminution in Energy not served (ENS) shows that the last end of customers is satisfied with the performance of service provided in their area.

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“…Due to the stochastic nature of the power generated by renewable based DGs such as photovoltaic (PV) and wind turbines (WT), distribution companies need to deploy ESS to mitigate these uncertainties [4]. ESSs provide a shaved peak load profile [5,6] and maximize the intended benefits of DGs, such as reducing losses [7], improving power quality [8], and grid reliability [9].…”

Section: Literature Reviewmentioning

confidence: 99%

A multi-objective framework for distributed energy resources planning and storage management

et al. 2022

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Reliability Improvement of Radial Distribution System by Optimal Placement and Sizing of Energy Storage System using TLBO

Cited by 43 publications

References 36 publications

Dynamic Multi-Objective Optimization of Grid-Connected Distributed Resources Along With Battery Energy Storage Management via Improved Bidirectional Coevolutionary Algorithm

Dynamic Multi-Objective Optimization of Grid-Connected Distributed Resources Along With Battery Energy Storage Management via Improved Bidirectional Coevolutionary Algorithm

Economic Analysis of Isolator Placement in the Radial Network for Enhancement of Reliability Indicators

A multi-objective framework for distributed energy resources planning and storage management

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