Reserve constrained multi-area economic dispatch employing differential evolution with time-varying mutation

Sharma, Manisha; Pandit, Manjaree; Srivastava, Laxmi

doi:10.1016/j.ijepes.2010.12.033

Cited by 89 publications

(68 citation statements)

References 36 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The updated position in Step 4 may have violated from inequality constraints in (8) and (9) due to the over or under velocity. If the updated position of ith particle in dth dimension (or generator) is larger/lower than the effective maximum/minimum, the updated position is set to the effective maximum/minimum.…”

Section: Procedures Of Mpso-tvac Algorithm For Eld Problemmentioning

confidence: 99%

“…Recently, modern heuristic methods such as genetic algorithm [5,6], evolutionary programming [7], differential evolution [8], ant colony optimization [9], tabu search [10], simulated annealing [11], neural network [12], and particle swarm optimization (PSO) [13][14][15][16][17][18] have been successfully applied to nonconvex ELD problems. However, these approaches are not always promising a global optimum solution and sometimes are trapped at local point.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients for Economic Load Dispatch with Generator Constraints

Abdullah

Bakar

Rahim

et al. 2014

Journal of Electrical Engineering and Technology

View full text Add to dashboard Cite

-This paper proposes a Modified Particle Swarm Optimization with Time VaryingAcceleration Coefficients (MPSO-TVAC) for solving economic load dispatch (ELD) problem. Due to prohibited operating zones (POZ) and ramp rate limits of the practical generators, the ELD problems become nonlinear and nonconvex optimization problem. Furthermore, the ELD problem may be more complicated if transmission losses are considered. Particle swarm optimization (PSO) is one of the famous heuristic methods for solving nonconvex problems. However, this method may suffer to trap at local minima especially for multimodal problem. To improve the solution quality and robustness of PSO algorithm, a new best neighbour particle called 'rbest' is proposed. The rbest provides extra information for each particle that is randomly selected from other best particles in order to diversify the movement of particle and avoid premature convergence. The effectiveness of MPSO-TVAC algorithm is tested on different power systems with POZ, ramp-rate limits and transmission loss constraints. To validate the performances of the proposed algorithm, comparative studies have been carried out in terms of convergence characteristic, solution quality, computation time and robustness. Simulation results found that the proposed MPSO-TVAC algorithm has good solution quality and more robust than other methods reported in previous work.

show abstract

Section: Procedures Of Mpso-tvac Algorithm For Eld Problemmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients for Economic Load Dispatch with Generator Constraints

Abdullah

Bakar

Rahim

et al. 2014

Journal of Electrical Engineering and Technology

View full text Add to dashboard Cite

show abstract

“…V is the wind speed (m/sec), which varies randomly with time however the data collected from field have shown that V approximately follows [9] (v≥0) (10) Where c and k are referred to as the scale factor and shape factor, respectively. Correspondingly, the probability density function of V is: (11) The relation between the input wind power and the output electric power depends on many factors, like the efficiencies of generator, wind rotor, gearbox, and inverter, depending on what kind of turbine is being employed. The generic relation between wind power and wind speed can be given as [9]:…”

Section: The Weibull Probability Distribution Of Wind Powermentioning

confidence: 99%

Optimal Operation of Wind-thermal generation using differential evolution

Chaudhary¹

2013

IOSR-JEEE

View full text Add to dashboard Cite

“…Heuristic based methods [5]- [7], and generalized Benders decomposition [8] have been proposed to deal with multi-area unit commitment problem. MA-DEDs usually include constraints like power balance in each area, tie-lines capacity constraints, tie-lines security [9] and reserve constraints [6].…”

Section: Introductionmentioning

confidence: 99%

Optimal multi‐area generation schedule considering renewable resources mix: a real‐time approach

Soroudi

Rabiee²

2013

IET Generation, Transmission & Distribution

View full text Add to dashboard Cite

This paper proposes a new model for multi-area dynamic economic dispatch (MA-DED) problem, taking into account hydro-thermal generating units, wind power generation and power pool market, for supplying the overall demand of the system for a given horizon. The uncertainties in wind power generations, energy prices and demand of the system are also modeled to make the proposed approach more practical in case of real-time operation of practical power systems. Scenario based approach is adopted for uncertainty modeling. In order to make the proposed MA-DED applicable in real-time operation of power systems, optimality condition decomposition technique is employed along with parallel computation ability. The proposed approach is examined on a three-area interconnected power network, to demonstrate its applicability for real-time scheduling of joint thermal and undispatchable renewable energy resources.

show abstract

Reserve constrained multi-area economic dispatch employing differential evolution with time-varying mutation

Cited by 89 publications

References 36 publications

Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients for Economic Load Dispatch with Generator Constraints

Modified Particle Swarm Optimization with Time Varying Acceleration Coefficients for Economic Load Dispatch with Generator Constraints

Optimal Operation of Wind-thermal generation using differential evolution

Optimal multi‐area generation schedule considering renewable resources mix: a real‐time approach

Contact Info

Product

Resources

About