A new efficient BBO based method for simultaneous placement of inverter-based DG units and capacitors considering harmonic limits

Ghaffarzadeh, Navid; Sadeghi, H.

doi:10.1016/j.ijepes.2016.01.030

Cited by 65 publications

(40 citation statements)

References 26 publications

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“…Besides, the mutation operator helps to increase the diversity of solutions. Because the BBO algorithm does not depend on a particular problem, it is widely used in various fields, such as pathology test [14,15], distributed generation [16], intelligent identification [17][18][19] and other fields recently. While BBO algorithm also has some disadvantages, including easy to fall into the local optimization, poor exploration ability, strong randomness and lacking theoretical basis.…”

Section: Introductionmentioning

confidence: 99%

“…[pModify , pMutate] ← updateProbability() 16: end while Algorithm 2 the main algorithm of sortPopulation (Population P).…”

mentioning

confidence: 99%

“…Generation max ) cp 5: for i = 1 to NP do 6: for j = 1 to NP-1 do 7: if (Pun j , Pun j+1 ≤ ε) or (Pun j = Pun j+1 ) and ( f j+1 < f j ) then 8: swap (P j , P j+1 ) 9: else if (Pun j > Pun j+1 ) then 10: swap (P j , P j+1 ) 11: end if 12: end for 13: if no swap then 14: break 15: end if 16: end for…”

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confidence: 99%

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Biogeography-Based Optimization of the Portfolio Optimization Problem with Second Order Stochastic Dominance Constraints

2017

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Abstract:The portfolio optimization problem is the central problem of modern economics and decision theory; there is the Mean-Variance Model and Stochastic Dominance Model for solving this problem. In this paper, based on the second order stochastic dominance constraints, we propose the improved biogeography-based optimization algorithm to optimize the portfolio, which we called εBBO. In order to test the computing power of εBBO, we carry out two numerical experiments in several kinds of constraints. In experiment 1, comparing the Stochastic Approximation (SA) method with the Level Function (LF) algorithm and Genetic Algorithm (GA), we get a similar optimal solution by εBBO in [0, 0.6] and [0, 1] constraints with the return of 1.174% and 1.178%. In [−1, 2] constraint, we get the optimal return of 1.3043% by εBBO, while the return of SA and LF is 1.23% and 1.26%. In experiment 2, we get the optimal return of 0.1325% and 0.3197% by εBBO in [0, 0.1] and [−0.05, 0.15] constraints. As a comparison, the return of FTSE100 Index portfolio is 0.0937%. The results prove that εBBO algorithm has great potential in the field of financial decision-making, it also shows that εBBO algorithm has a better performance in optimization problem.

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Section: Introductionmentioning

confidence: 99%

“…[pModify , pMutate] ← updateProbability() 16: end while Algorithm 2 the main algorithm of sortPopulation (Population P).…”

mentioning

confidence: 99%

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Biogeography-Based Optimization of the Portfolio Optimization Problem with Second Order Stochastic Dominance Constraints

2017

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“…Research from [14] presents a new hybrid method based on biogeography-based optimization (BBO) to solve harmonic estimation problems in cases of time varying power signals in presence of different noises. BBO is used for other applications to optimize allocation of DGs and capacitors considering harmonic pollution [15].…”

Section: Introductionmentioning

confidence: 99%

Optimal Allocation of Active Power Filter On real distribution network for improvement of power quality by use of BBO: A case study

Samadaei

Khosravi

Sheikholeslami

2017

IIUMEJ

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ABSTRACT:Â According to development of power electronics device, harmonic distortion spread on the network. Thus harmonic is a threat for instrument, network, decreasing of line capacity and etc. Active power ï¬lter (APF) can be employed for harmonic compensation in power systems. In this paper a distorted distribution feeder is considered and analyzed from power quality viewpoint using power analyzer device and simulated in MATLAB-Mfile. Then the size and place of active power filters are determined by use of Biogeography Based Optimization (BBO). The goal of this optimization is minimizing of losses and total harmonic distortion (THD) in feeder by considering economical cost.Â The performance of the approaches are assessed and appreciated by a case study on the Ghaemshahr-Iran Distribution network. Measurement is done on the city network by power analyzer CA8310. All data was collected on Computer. Then researcher algorithm BBO, it is selected the best place and size for Active power filter. The results show a good performance.

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“…To avoid these problems, the international standards such as IEEE Standard 519 imposes limits for individual and total harmonic distortion of PCC voltages and currents [11]. Accordingly, some recent studies investigated the impact of the harmonic limitations, given in the standards such as IEEE Standard 519 on the hosting capacity of the distribution systems for the DG units with inverter interfaces generating harmonic distortion [12]- [19]. In general, these studies concluded that the maximum allowable harmonic distortion levels stated in the standards considerably limit the hosting capacity of the systems for the DG units with inverter interfaces.…”

Section: Introductionmentioning

confidence: 99%

Hosting capacity assessment and improvement for photovoltaic-based distributed generation in distorted distribution networks

Sakar

Balcı

Aleem

et al. 2016

2016 IEEE 16th International Conference on Environment and Electrical Engineering (EEEIC)

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Abstract-In this paper, the hosting (or maximum allowable) capacity of a photovoltaic (PV)-based distributed generation (DG) unit for a typical two bus distorted distribution system, is analyzed. The harmonic constraints, total and individual harmonic distortion limits stated in IEEE Standard 519, and the conventional hosting capacity constraints, bus rms voltage limit and the current carrying capability limit of the supply cables are taken into account. In the analysis, various simulations are carried out to show the effect of the nonlinearity degrees of the loads on the system's hosting capacity. It is clearly seen from the analysis results that the harmonic distortion limits significantly constrain the PV-based DG unit hosting capacity for the higher nonlinearity levels of the consumer. Accordingly, a C-type filter is designed to maximize the hosting capability of the studied system while providing desired power factor and satisfying the harmonic and conventional hosting capacity constraints. Besides, the numerical results are given to point out that a higher allowable hosting capacity is obtained with the proposed filter design approach compared to two traditional filter design approaches, which aims to attain minimization of voltage total harmonic distortion and minimization of current total demand distortion by considering the same constraints of the proposed approach.

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A new efficient BBO based method for simultaneous placement of inverter-based DG units and capacitors considering harmonic limits

Cited by 65 publications

References 26 publications

Biogeography-Based Optimization of the Portfolio Optimization Problem with Second Order Stochastic Dominance Constraints

Biogeography-Based Optimization of the Portfolio Optimization Problem with Second Order Stochastic Dominance Constraints

Optimal Allocation of Active Power Filter On real distribution network for improvement of power quality by use of BBO: A case study

Hosting capacity assessment and improvement for photovoltaic-based distributed generation in distorted distribution networks

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