Optimal power flow solution of power system incorporating stochastic wind power using Gbest guided artificial bee colony algorithm

Roy, Ranjit; Jadhav, H. T.

doi:10.1016/j.ijepes.2014.07.010

Cited by 151 publications

(125 citation statements)

References 56 publications

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“…The best solutions of other optimization methods previously mentioned are compared with the FCGCS approach and Table 6 presents the statistical results. It can be seen that the optimal result of FCGCS is better than those in [11,21,26]. However, the best solutions as given in [10,12] are better than our proposed FCGCS method, which are indeed infeasible solutions.…”

Section: Case 14 Voltage Stability Indexmentioning

confidence: 79%

“…compared with Case 1.1. Furthermore, the comparison of system voltage profiles between Case 1.1 and Case 1.3 is presented in Figure 5, which [3] 0.093269 0.093952 0.094171 LTLBO [24] 0.0974 0.0983 0.1006 DE-PS [25] 0.0978 0.0997 0.1022 GABC [26] 0.1007 0.1052 0.1097 BBO [12] 0.1020 0.1105 0.1207 clearly shows the improvement of bus voltage profile. The simulation results of FCGCS and other methods summarized in Table 5 indicate the FCGCS method has powerful searching ability.…”

Section: Case 12 Active Power Lossesmentioning

confidence: 99%

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Optimal Power Flow Using Gbest‐Guided Cuckoo Search Algorithm with Feedback Control Strategy and Constraint Domination Rule

Chen

Qiu

Zhang

et al. 2017

Mathematical Problems in Engineering

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The optimal power flow (OPF) is well-known as a significant optimization tool for the security and economic operation of power system, and OPF problem is a complex nonlinear, nondifferentiable programming problem. Thus this paper proposes a Gbestguided cuckoo search algorithm with the feedback control strategy and constraint domination rule which is named as FCGCS algorithm for solving OPF problem and getting optimal solution. This FCGCS algorithm is guided by the global best solution for strengthening exploitation ability. Feedback control strategy is devised to dynamically regulate the control parameters according to actual and specific feedback value in the simulation process. And the constraint domination rule can efficiently handle inequality constraints on state variables, which is superior to traditional penalty function method. The performance of FCGCS algorithm is tested and validated on the IEEE 30-bus and IEEE 57-bus example systems, and simulation results are compared with different methods obtained from other literatures recently. The comparison results indicate that FCGCS algorithm can provide high-quality feasible solutions for different OPF problems.

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Section: Case 14 Voltage Stability Indexmentioning

confidence: 79%

Section: Case 12 Active Power Lossesmentioning

confidence: 99%

Optimal Power Flow Using Gbest‐Guided Cuckoo Search Algorithm with Feedback Control Strategy and Constraint Domination Rule

Chen

Qiu

Zhang

et al. 2017

Mathematical Problems in Engineering

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“…In 2014, Panda and Tripathy [104] presented an OPF solution for modified power system in which three conventional generators are replaced by wind-energy conversion systems (WECS). To justify the limitation of reactive power generation capability of WECS, genetic algorithm (GA) and a modified bacteria [92][93][94][95][96][97][98][99][100][101][102][103][104][105][106] foraging algorithm are employed independently, for determining the optimal schedule. In 2015, Panda and Tripathy [105] presented a modified bacteria foraging algorithm, which is capable of handling multiobjective optimization problems.…”

Section: 4mentioning

confidence: 99%

“…The resulting risk measure formulates risk-based constraints for the postcontingency line flows. In 2015, Roy and Jadhav [106] presented an OPF study in view of probabilistic nature of wind power. The wind power intermittency is modelled by the parameters of Weibull probability function.…”

Section: 4mentioning

confidence: 99%

Optimal Power Flow Techniques under Characterization of Conventional and Renewable Energy Sources: A Comprehensive Analysis

Khan

Singh

2017

Journal of Engineering

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The exhaustive knowledge of optimal power flow (OPF) methods is critical for proper system operation and planning, since OPF methods are utilized for finding the optimal state of any system under system constraint conditions, such as loss minimization, reactive power limits, thermal limits of transmission lines, and reactive power optimization. Incorporating renewable energy sources optimized the power flow of system under different constraints. This work presents a comprehensive study of optimal power flows methods with conventional and renewable energy constraints. Additionally, this work presents a progress of optimal power flow solution from its beginning to its present form. Authors classify the optimal power flow methods under different constraints condition of conventional and renewable energy sources. The current and future applications of optimal power flow programs in smart system planning, operations, sensitivity calculation, and control are presented. This study will help the engineers and researchers to optimize power flow with conventional and renewable energy sources.

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“…Furthermore, the improvement of parameters is also considered in the proposed method. As to the problem of constraints, in many literatures, evolutionary algorithms choose the penalty function method to handle the inequality constraints of dependent variables [12,[22][23][24]. However, the method requires many penalty factors, and the setting and adjustment of these parameters may increase the complexity of the algorithm.…”

Section: Introductionmentioning

confidence: 99%

Improved Krill Herd Algorithm with Novel Constraint Handling Method for Solving Optimal Power Flow Problems

Chen

Zhang

2018

Energies

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Abstract:As one of the most important tools used in operation and planning of power systems, the optimal power flow (OPF) problem considering the economy and security is large-scale, complex and hard to solve. In this paper, an improved krill herd algorithm (IKHA) has been proposed. In IKHA, the onlooker search mechanism is introduced to reduce the probability of falling into local optimum; and the parameter values of the proposed algorithm including inertia weight and step-length scale factor are varied according to the iteration of evolutionary process, which improves the exploration and exploitation capabilities. Moreover, a novel constraint handling method is proposed to guide the individual to the feasible space and ensure that the optimal solution satisfies the security constraints. Then, IKHA is combined with the novel constraint handling method to solve the multi-constrained OPF problem, and its performance is tested on the IEEE 30 bus, IEEE 57 bus and IEEE 118 bus systems for 10 different simulation cases containing linear and non-linear objective functions. The simulation results demonstrate that the proposed method can solve the OPF problem successfully and obtain better solutions compared with other methods reported in the recent literatures, which prove the feasibility and effectiveness of the improvements in this work.

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Optimal power flow solution of power system incorporating stochastic wind power using Gbest guided artificial bee colony algorithm

Cited by 151 publications

References 56 publications

Optimal Power Flow Using Gbest‐Guided Cuckoo Search Algorithm with Feedback Control Strategy and Constraint Domination Rule

Optimal Power Flow Using Gbest‐Guided Cuckoo Search Algorithm with Feedback Control Strategy and Constraint Domination Rule

Optimal Power Flow Techniques under Characterization of Conventional and Renewable Energy Sources: A Comprehensive Analysis

Improved Krill Herd Algorithm with Novel Constraint Handling Method for Solving Optimal Power Flow Problems

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