Firefly algorithm based energy loss minimization approach for optimal sizing &amp;amp; placement of distributed generation

Nadhir, Ketfi; Djabali, Chabane; Bouktir, T.

doi:10.1109/icmsao.2013.6552580

Cited by 17 publications

(12 citation statements)

References 10 publications

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“…The integration of the solar PV in the system has reduced the active power loss by 83.6% for DoC feeder. The voltage profile of weak bus has increased by 0.0724p.u.The proposed method for determining the hosting capacity of Solar PV into the grid is tested into IEEE33-bus standard system [9] and is compared with existing methods where the proposed method is found satisfactory to others.…”

Section: Resultsmentioning

confidence: 99%

Determining the Hosting Capacity of Solar Photovoltaic in a Radial Distribution Network Using an Analytical Approach

Dahal¹,

Jha²,

Bhattarai³

et al. 2019

J. Adv. Coll. Engin. Mgt.

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Integrating high photovoltaic (PV) on distribution grid system has a positive impact by significantly reducing the losses and improving the voltage profile at the same time reducing the pollution of the environment However, integrating high proportions of PV in the distribution grid can bring the grid to its operational limits and result in power quality issues. The maximum PV capacity that can be integrated without incurring any grid impacts is referred to as the PV hosting capacity of the grid. This paper intends to evaluate the hosting capacity of solar PV in Dodhara-Chandani (DoC) distribution feeder as one of the feeder of Integrated Nepal Power System (INPS), considering grid parameters and operating condition in Nepal. Three main criteria were investigated for determining the hosting capacity of PV; reverse power flow, maximum voltage deviation of feeder and current carrying limit of conductor. The analysis has been performed by means of static load-flow simulation in Electrical Transient & Analysis Program (ETAP) and coding in MATLAB R2017a. The study shows that PV of rated capacity 687kWp can be installed at a point of interconnection (POI) whereas an optimal placement of solar PV is found to be at 18th node (in between starting and end of the feeder) considering minimum system losses. The minimum voltage profile at end of the feeder has improved by 8 % while the active power loss reduction of network has reduced by 83.6 % after the integration of solar PV. The results indicate voltage at different buses and the ampacity of most of the conductors have been improved after the integration of PV system into DoC feeder.

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Section: Resultsmentioning

confidence: 99%

Determining the Hosting Capacity of Solar Photovoltaic in a Radial Distribution Network Using an Analytical Approach

Dahal¹,

Jha²,

Bhattarai³

et al. 2019

J. Adv. Coll. Engin. Mgt.

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“…The application of evolutionary algorith ms like Part icle Swarm Optimization, Genetic Algorith m, Tabu search, Artificial Neural Net works and Ant Colony Optimization to determine the shortest path with co mputationally less effort have been reported in the literature [15], [21]- [23]. Firefly Algorith m, a new meta-heuristic finds application in various optimization problems such as makespan minimizat ion in permutation flow shop scheduling [24], scheduling jobs on computational grids [25], optimal supplier select ion [26] and optimal p lacement and sizing of distributed generation in radial d istribution system [27]. Firefly algorith m has been applied for network optimization problems like queuing [28], travelling salesman problem [29], clustering and network partitioning [30].…”

Section: Related Workmentioning

confidence: 99%

Reliable Mobile Ad-Hoc Network Routing Using Firefly Algorithm

Persis¹,

Robert²

2016

IJISA

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Routing in Mobile Ad-hoc NETwork (MANET) is a contemporary graph problem that is solved using various shortest path search techniques. The routing algorith ms employed in modern routers use deterministic algorith ms that extract an exact nondominated set of solutions from the search space. The search efficiency of these algorithms is found to have an exponential time co mp lexity in the worst case. Moreover this problem is a mult i-objective optimization problem in nature for MA NET and it is required to consider changing topology layout. This study attempts to employ a formulat ion incorporating objectives viz., delay, hopdistance, load, cost and reliability that has significant impact on network performance. Simu lation with different random topologies has been carried out to illustrate the imp lementation of an exhaustive search algorith m and it is observed that the algorithm could handle small-scale networks limited to 15 nodes. A random search meta-heuristic that adopts the nature of firefly swarm has been proposed for larger networks to yield an appro ximated non-dominated path set. Firefly Algorith m is found to perform better than the exact algorithm in terms of scalability and computational time.

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“…Setting up of renewable energy resources in power system arrangement can gives the better impacts like voltage profile improvement and reduction in losses [1].Renewable energy sources usage is increasing day by day fastly, due to its number of benefits like small size, few environmental causes, less cost [2].These non-conventional energy resources like wind, hydro, biomass, solar, ocean and geothermal energy are naturally spread in all over the world [3].Reducing the power system loss, minimizing the variation in voltage and infraction the limits of power flow are the main objectives of the optimal sizing and placement of renewable energy sources [4]. Also, these sources are intermittent in nature i.e there is variability present in some of the sources [5].…”

Section: Introductionmentioning

confidence: 99%

PSO Algorithm based Loss Minimization Approach for Optimal Placement and Sizing of Renewable Energy Source

Kaur¹

2017

IJRASET

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In this research paper, PSO is joint with Newton Raphson method of power flow to optimize optimal location along with size of renewable energy source. A NR method is used to measure the losses and find the voltage at each bus. The PSO is used to locate the best location as well as sizing of renewable energy source. The main aim is to reduce the losses and keep the voltage profile acceptable. IEEE 30 bus standard system is used for the observations. There is the comparison of results of system without renewable energy source and with renewable energy source by some methods of optimization. Wind farm is considered as the renewable energy source.

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Firefly algorithm based energy loss minimization approach for optimal sizing & placement of distributed generation

Cited by 17 publications

References 10 publications

Determining the Hosting Capacity of Solar Photovoltaic in a Radial Distribution Network Using an Analytical Approach

Determining the Hosting Capacity of Solar Photovoltaic in a Radial Distribution Network Using an Analytical Approach

Reliable Mobile Ad-Hoc Network Routing Using Firefly Algorithm

PSO Algorithm based Loss Minimization Approach for Optimal Placement and Sizing of Renewable Energy Source

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