Ant Lion optimization algorithm for optimal sizing of renewable energy resources for loss reduction in distribution systems

Reddy, P. Dinakara Prasad; Reddy, Vijay; Manohar, T. Gowri

doi:10.1016/j.jesit.2017.06.001

Cited by 106 publications

(14 citation statements)

References 33 publications

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“…The solution of PFA is compared with various other methods as given in Table 4. It has been observed that the FPA is better than GOA-CSA [21], ALO [13], SFLA [10] and DA [16]. From the comparison, it can be said that the PFA is a keen competitor to various HSAs and fine tunes the decision variables towards global optima irrespective of size of search space.…”

Section: Scenario-1: Optimal Location and Sizing Of Pv Systemmentioning

confidence: 99%

“…The hybrid approach is used to find optimal rating and location of renewable DGs in IEEE 33-bus system for minimizing loss, operating cost, voltage deviation and inverse of voltage stability index. In [13], ant lion optimization (ALO) is proposed for optimal allocation of different kinds of single DG unit radial distribution system. The search space for WOA is reduced using index vector method (IVM).…”

Section: Introductionmentioning

confidence: 99%

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A new meta-heuristic pathfinder algorithm for solving optimal allocation of solar photovoltaic system in multi-lateral distribution system for improving resilience

Janamala

2021

SN Appl. Sci.

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A new meta-heuristic Pathfinder Algorithm (PFA) is adopted in this paper for optimal allocation and simultaneous integration of a solar photovoltaic system among multi-laterals, called interline-photovoltaic (I-PV) system. At first, the performance of PFA is evaluated by solving the optimal allocation of distribution generation problem in IEEE 33- and 69-bus systems for loss minimization. The obtained results show that the performance of proposed PFA is superior to PSO, TLBO, CSA, and GOA and other approaches cited in literature. The comparison of different performance measures of 50 independent trail runs predominantly shows the effectiveness of PFA and its efficiency for global optima. Subsequently, PFA is implemented for determining the optimal I-PV configuration considering the resilience without compromising the various operational and radiality constraints. Different case studies are simulated and the impact of the I-PV system is analyzed in terms of voltage profile and voltage stability. The proposed optimal I-PV configuration resulted in loss reduction of 77.87% and 98.33% in IEEE 33- and 69-bus systems, respectively. Further, the reduced average voltage deviation index and increased voltage stability index result in an improved voltage profile and enhanced voltage stability margin in radial distribution systems and its suitability for practical applications.

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Section: Scenario-1: Optimal Location and Sizing Of Pv Systemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

A new meta-heuristic pathfinder algorithm for solving optimal allocation of solar photovoltaic system in multi-lateral distribution system for improving resilience

Janamala

2021

SN Appl. Sci.

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“…The amount of power generation by a solar panel depends on different factors, which can be estimated by Equations ( 21) and (22). Above, η stands for efficiency, and T a denotes the ambient temperature.…”

Section: The Uncertainty Modeling For Pv Sourcesmentioning

confidence: 99%

“…The authors in [21] have investigated a multi-objective DG placement and sizing problem subject to reduce loss and to enhance the voltage profile using the shuffled frog leap algorithm. Optimal sizing of renewable energy resources with the goal of loss reduction in distribution grids using the ant lion optimization method is presented in [22]. A battery placement problem is also presented in [23], in which it is objected to reducing losses in a distribution grid with high penetration of solar sources.…”

Section: Introductionmentioning

confidence: 99%

Sizing and Sitting of DERs in Active Distribution Networks Incorporating Load Prevailing Uncertainties Using Probabilistic Approaches

et al. 2021

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In this study, a microgrid scheme encompassing photovoltaic panels, an energy storage system, and a diesel generator as a backup supply source is designed, and the optimal placement for installation is suggested. The main purpose of this microgrid is to meet the intrinsic demand without being supplied by the upstream network. Thus, the main objective in the design of the microgrid is to minimize the operational cost of microgrid’s sources subject to satisfy the loads by these sources. Therefore, the considered problem in this study is to determine the optimal size and placement for generation sources simultaneously for a microgrid with the objectives of minimization of cost of generation resources along with mitigation of power losses. In order to deal with uncertainties of PV generation and load forecasting, the lognormal distribution model and Gaussian process quantile regression (GPQR) approaches are employed. In order to solve the optimization problem, the lightning attachment procedure optimization (LAPO) and artificial bee colony (ABC) methods are employed, and the results are compared. The results imply the more effectiveness and priority of the LAPO approach in comparison with ABC in convergence speed and the accuracy of solution-finding.

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“…Whale Optimization Algorithm [89], motivated by the behaviors of Humpback whale, has been used to achieve the optimal size of distributed generators [90]. Ant Lion Optimization [91], which is designed based on the special hunting behavior of ant lions, has also been used to identify the optimum size of distributed generation [92] and find energy scheduling in microgrid [93]. Earliglow Algorithm, which takes advantage of both Jaya and strawberry algorithms, is applied in HEMS with significant achievements [94].…”

Section: Emerging and Hybrid Bio-inspired Approachesmentioning

confidence: 99%

Bio-Inspired Approaches for Smart Energy Management: State of the Art and Challenges

Nguyen

Jung

et al. 2020

Sustainability

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Sustainable energy development consists of design, planning, and control optimization problems that are typically complex and computationally challenging for traditional optimization approaches. However, with developments in artificial intelligence, bio-inspired algorithms mimicking the concepts of biological evolution in nature and collective behaviors in societies of agents have recently become popular and shown potential success for these issues. Therefore, we investigate the latest research on bio-inspired approaches for smart energy management systems in smart homes, smart buildings, and smart grids in this paper. In particular, we give an overview of the well-known and emerging bio-inspired algorithms, including evolutionary-based and swarm-based optimization methods. Then, state-of-the-art studies using bio-inspired techniques for smart energy management systems are presented. Lastly, open challenges and future directions are also addressed to improve research in this field.

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Ant Lion optimization algorithm for optimal sizing of renewable energy resources for loss reduction in distribution systems

Cited by 106 publications

References 33 publications

A new meta-heuristic pathfinder algorithm for solving optimal allocation of solar photovoltaic system in multi-lateral distribution system for improving resilience

A new meta-heuristic pathfinder algorithm for solving optimal allocation of solar photovoltaic system in multi-lateral distribution system for improving resilience

Sizing and Sitting of DERs in Active Distribution Networks Incorporating Load Prevailing Uncertainties Using Probabilistic Approaches

Bio-Inspired Approaches for Smart Energy Management: State of the Art and Challenges

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