Dynamic economic dispatch using Lbest-PSO with dynamically varying sub-swarms

Chowdhury, Arkabandhu; Zafar, Hamim; Panigrahi, B. K.; Krishnanand, K. R.; Mohapatra, Ankita; Cui, Zhihua

doi:10.1007/s12293-013-0127-1

Cited by 14 publications

(5 citation statements)

References 30 publications

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“…The results produced by proposed algorithms on above considered different test systems of DED problem are compared with other state-of-the-art algorithms. These compared algorithms are listed as follows: EAPSO [59], MBF-SSO [60], DE [61], ABC [62], ICA [63], CMAES [64], Lbest-PSO [65], TVAC-IPSO [66], BBPSO [55], BBO [67], BSO [68], BLPSO [69], CSO [70], DE/BBO [71], LDISS [72], SOC [73], DE/eig [74], LWOA [75], SATLBO [76], SLPSO [77], LETLBO [78], MHEP-SQP [79], CDBCO [80], CSAPSO [81], ECE [82], MACO [83], CSADHS [84], IPSO [85], SALCSSA [86], HS [58], GHS [58], ODO-DE [87], ODO-PSO [87], BBO [88], ICPSO [89] and MTLA [90]. In order to check the efficiency of the proposed algorithms nPSO, nDE and ihPSODE, least values of population size (40), maximum number of iterations (500)/maximum number of function evaluations (5000) and independent runs (25) 9); for TSys-2 are reported in Table 10 (1,017,530.3328 $/day), Table 11 (1,016,756 $/day) and Table…”

Section: Resultsmentioning

confidence: 99%

Non-convex Dynamic Economic Dispatch Using an Innovative Hybrid Algorithm

Verma

Parouha

2021

J. Electr. Eng. Technol.

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An innovative hybrid algorithm (ihPSODE) is proposed in this paper to solve non-convex dynamic economic dispatch (DED) problem. It integrated with a novel particle swarm optimization (nPSO) and differential evolution (nDE). A new inertia weight, gradually varying acceleration coefficient and position update equation introduced in nPSO, to avoid stagnation. And in nDE a new mutation strategy and crossover rate are presented, to avoid premature convergence. Additionally, in ihPSODE after calculation identify best half member and discard rest of members from the population. In current population applied nPSO, to maintain exploration and exploitation. Then to enhance local search ability and improve convergence accuracy applied nDE. Hence, proposed ihPSODE has higher probability of avoiding local optima and it is likely to find global optima more quickly. Firstly, proposed ihPSODE as well as its anticipated integrating component nPSO and nDE are testified on IEEE CEC2006 constrained benchmark functions. Then performance of these proposed algorithms are evaluated with non-convex DED problem with valve-point effects using five different test systems (5-unit with losses, 10-unit without losses, 10-unit with losses, 15-unit with losses and 30-unit without losses). Several numerical and graphical experiments have been done to verify performances of proposed algorithms. Additionally, statistical and comparative analysis confirms superiority of proposed algorithms over many state-of-the-art algorithms.

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Section: Resultsmentioning

confidence: 99%

Non-convex Dynamic Economic Dispatch Using an Innovative Hybrid Algorithm

Verma

Parouha

2021

J. Electr. Eng. Technol.

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“…The dispatch period is one day which is divided into 24 intervals. Load demand and unit characteristics of the 10-unit are obtained from [36,37] and can be found in Tables 1 and 2 Table 2. Generator characteristics.…”

Section: Experiments Results and Discussionmentioning

confidence: 99%

Dynamic Power Dispatch Considering Electric Vehicles and Wind Power Using Decomposition Based Multi-Objective Evolutionary Algorithm

Qiao

Zhu

et al. 2017

Energies

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The intermittency of wind power and the large-scale integration of electric vehicles (EVs) bring new challenges to the reliability and economy of power system dispatching. In this paper, a novel multi-objective dynamic economic emission dispatch (DEED) model is proposed considering the EVs and uncertainties of wind power. The total fuel cost and pollutant emission are considered as the optimization objectives, and the vehicle to grid (V2G) power and the conventional generator output power are set as the decision variables. The stochastic wind power is derived by Weibull probability distribution function. Under the premise of meeting the system energy and user's travel demand, the charging and discharging behavior of the EVs are dynamically managed. Moreover, we propose a two-step dynamic constraint processing strategy for decision variables based on penalty function, and, on this basis, the Multi-Objective Evolutionary Algorithm Based on Decomposition (MOEA/D) algorithm is improved. The proposed model and approach are verified by the 10-generator system. The results demonstrate that the proposed DEED model and the improved MOEA/D algorithm are effective and reasonable.

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“…Díaz et al [16] proposed a novel method which could find the real modes of the rotor system through the coordinate transformation, which resulted in that the optimum extraction position of the balancing parameters can be determined. Besides, it has been demonstrated that the stability and efficiency of rotor system dynamic balancing could be improved through PSO algorithm [17][18][19].…”

Section: Introductionmentioning

confidence: 99%

Research on Dynamic Balance of Spindle Rotor System Based on Particle Swarm Optimization

Zhan

Wang

et al. 2021

Advances in Materials Science and Engineering

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The dynamic balance is a significant issue for the nonlinear dynamic characteristics of the spindle rotor system. However, there is a problem that the dynamic balance is lacking detailed study on optimization method. In the paper, a modal dynamic balance optimization model of spindle rotor system is proposed, which can intend to improve the accuracy of spindle rotor system modal dynamic balance. Because the multiorder unbalance components are the main spindle rotor system mode shapes, the particle swarm optimization (PSO) method is adopted. The sum of squares of residual vibration after balancing is taken as the optimization objective, and the correction is presented as the optimization variable in the optimization model. The optimal correction weight of every unbalance component is calculated through a modal matrix equation of PSO. The vibration amplitude that is greatly reduced after optimization balance is presented under different conditions. The balancing effect shows a better dynamic characteristic than that of traditional methods. And the fluctuation range of the axis track of the rotor system also shows reductive phenomenon. The proposed optimization spindle rotor system model is well verified through experiments. It can contribute a theoretical optimization foundation for available dynamic balance in spindle rotor system.

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Dynamic economic dispatch using Lbest-PSO with dynamically varying sub-swarms

Cited by 14 publications

References 30 publications

Non-convex Dynamic Economic Dispatch Using an Innovative Hybrid Algorithm

Non-convex Dynamic Economic Dispatch Using an Innovative Hybrid Algorithm

Dynamic Power Dispatch Considering Electric Vehicles and Wind Power Using Decomposition Based Multi-Objective Evolutionary Algorithm

Research on Dynamic Balance of Spindle Rotor System Based on Particle Swarm Optimization

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