A novel multi-objective self-adaptive modified<b>θ</b>-firefly algorithm for optimal operation management of stochastic DFR strategy

Kavousi‐Fard, Abdollah; Niknam, Taher; Baziar, Aliasghar

doi:10.1002/etep.1881

Cited by 9 publications

(12 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…To optimize the proposed objective function, firefly algorithm is used. This algorithm is inspired by blinking behavior of firefly for self‐protection or taking bait . In summary, it can be said that firefly d , which has more glitter, can absorb other c fireflies according to following Equation :

x_{d + 1} = x_{d} + β_{t} e^{- χ ρ_{dc}^{2}} ((),, x_{d} - x_{c}) + α_{t} ((),, rand - 0.5)

where α t is a random parameter, β t reflects the attractiveness of light source, ρ dc is the distance between 2 fireflies in situations x c and x d , and χ is determined according to the degree of the attractiveness and is very useful in convergence.…”

Section: Objective Function Optimizationmentioning

confidence: 99%

See 1 more Smart Citation

Predictive control strategy to improve stability of DFIG-based wind generation connected to a large-scale power system

Bagheri

Jalilvand

2016

Int. Trans. Electr. Energ. Syst.

View full text Add to dashboard Cite

Summary The present article aims to improve the small signal stability in a large‐scale network using model predictive control (MPC). The predictive strategy is based on the Laguerre function so as to reduce computational time in MPC and increase precise detection of control signals. This strategy is implemented in such a way to control the active and reactive power on rotor‐side converter (RSC) and increase RSC yield in the presence of uncertainties through application of appropriate switching to inverter. Therefore, static synchronous compensator is used in a way that the reactive power is compensated and by designing a damping controller the interarea oscillations will be reduced in New England large‐scale system. The simulation results were evaluated using MATLAB software in the field of time and frequency under different scenarios. Moreover, the proposed method was compared with conventional MPC and proportional‐integral controller while its superiority to stabilize and reduce the computational time is clearly shown.

show abstract

x_{d + 1} = x_{d} + β_{t} e^{- χ ρ_{dc}^{2}} ((),, x_{d} - x_{c}) + α_{t} ((),, rand - 0.5)

Section: Objective Function Optimizationmentioning

confidence: 99%

“…This algorithm is inspired by blinking behavior of firefly for self-protection or taking bait. 32 In summary, it can be said that firefly d, which has more glitter, can absorb other c fireflies according to following Equation 33:…”

Section: Firefly Algorithmmentioning

confidence: 99%

Predictive control strategy to improve stability of DFIG-based wind generation connected to a large-scale power system

Bagheri

Jalilvand

2016

Int. Trans. Electr. Energ. Syst.

View full text Add to dashboard Cite

show abstract

“…According to the literature, there are a number of approximate methods which can be useful for the uncertainty modeling in the power systems. Some of these methods are: Taylor series expansion method [3]; the common uncertain source approach [8,9]; the discretization technqiue [10]; the first-order second-moment method (FOSMM) [11,12], which is fundamentally a modification of the Taylor series expansion method; the cumulant method [12][13][14]; and the point estimate method [15][16][17][18][19][20]. The main idea behind these uncertainty modeling methods is to utilize approximate formulas for calculating the statistical moments of a random function which is somehow a function of random parameters.…”

Section: Introductionmentioning

confidence: 99%

Consideration effect of uncertainty in the reliability indices of power systems using a scenario-based approach

Abbasi

Solookinejad

Fard

et al. 2015

Journal of Intelligent &Amp; Fuzzy Systems

View full text Add to dashboard Cite

In power systems, reliability evaluations mainly depend on the precise forecasting of the reliability parameters of the internal components. Nonetheless, the procedure of calculating the reliability parameters such as failure rate and repair rate parameters is based on the failure statistics and measurements which can cause much inherent uncertainty and thus affecting the reliability indices of the system. Therefore, the main purpose of this work is to suggest a sufficient and easy-implemented approach based on scenario production to capture the uncertainty of the reliability parameters including the failure rate and repair rate variables. Here, the scenario generation process is constructed using the roulette wheel mechanism along with the probability density function of the random variables. Then, the proposed scenario based approach makes use of a scenario reduction mechanism to avoid high computational burden. This aspect of the proposed stochastic framework makes it useful for the optimization applications which require iterative analysis. In order to see the feasibility and satisfying performance of the proposed framework, an IEEE standard test system is used as the case study.

show abstract

“…Kavousi-Fard and Akbari-Zadeh used the shuffled frog leaping algorithm to reconfigure the network by considering three reliability indices and total system losses [14]. Kavousi-Fard et al used a firefly algorithm to investigate the multiobjective probabilistic distribution feeder reconfiguration problem considering reliability [15].…”

Section: Introductionmentioning

confidence: 99%

“…(1) renewable generation resources. Although they were not considered in conventional feeder reconfiguration problems [3][4][5][6][7][8][9][10][11][12][13][14][15], they should be considered in modern smart distribution systems;…”

Section: Introductionmentioning

confidence: 99%

Enhanced Particle Swarm Optimization-Based Feeder Reconfiguration Considering Uncertain Large Photovoltaic Powers and Demands

Hong

Lin²,

Hsu

2014

International Journal of Photoenergy

View full text Add to dashboard Cite

The Kyoto protocol recommended that industrialized countries limit their green gas emissions in 2012 to 5.2% below 1990 levels. Photovoltaic (PV) arrays provide clear and sustainable renewable energy to electric power systems. Solar PV arrays can be installed in distribution systems of rural and urban areas, as opposed to wind-turbine generators, which cause noise in surrounding environments. However, a large PV array (several MW) may incur several operation problems, for example, low power quality and reverse power. This work presents a novel method to reconfigure the distribution feeders in order to prevent the injection of reverse power into a substation connected to the transmission level. Moreover, a two-stage algorithm is developed, in which the uncertain bus loads and PV powers are clustered by fuzzy-c-means to gain representative scenarios; optimal reconfiguration is then achieved by a novel mean-variance-based particle swarm optimization. The system loss is minimized while the operational constraints, including reverse power and voltage variation, are satisfied due to the optimal feeder reconfiguration. Simulation results obtained from a 70-bus distribution system with 4 large PV arrays validate the proposed method.

show abstract

A novel multi-objective self-adaptive modifiedθ-firefly algorithm for optimal operation management of stochastic DFR strategy

Cited by 9 publications

References 36 publications

Predictive control strategy to improve stability of DFIG-based wind generation connected to a large-scale power system

Predictive control strategy to improve stability of DFIG-based wind generation connected to a large-scale power system

Consideration effect of uncertainty in the reliability indices of power systems using a scenario-based approach

Enhanced Particle Swarm Optimization-Based Feeder Reconfiguration Considering Uncertain Large Photovoltaic Powers and Demands

Contact Info

Product

Resources

About