Optimal Active–Reactive Power Dispatch Considering Stochastic Behavior of Wind, Solar and Small-Hydro Generation

Sarda, Jigar; Pandya, Kartik S.

doi:10.1007/978-981-13-1819-1_25

Cited by 7 publications

(3 citation statements)

References 10 publications

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“…6 Finally, the behavior of the river flow for small hydro generator can be modeled by the distribution of Gumbel. 12,13 In References 14-16, some classical methods like quadratic and non-linear programming are being used to solve OPF. These methods are depending on assumptions that may cause wrong results.…”

Section: Literature Reviewmentioning

confidence: 99%

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Hybrid cross entropy—cuckoo search algorithm for solving optimal power flow with renewable generators and controllable loads

Sarda

Pandya

Lee

2021

Optim Control Appl Methods

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The demand of energy is increasing due to the growing population of the world and improvements of technology. One of the best significant solution techniques to fulfill this energy demand is utilization of renewable energy sources (RESs). Modern power systems, which integrate RESs, such as wind, small hydro or solar energy sources need to carry out the uncertainty by the accessibility of demanded or injected power. Therefore, it is necessary to consider uncertainty costs in optimal power flow (OPF) problems. This paper proposed a novel hybrid meta‐heuristic algorithm entitled cross entropy—cuckoo search algorithm (CE‐CSA). The application of levy flights in the cuckoo search algorithm (CSA) improves the local exploitation capability while the CE method is used in the initial stage for global exploration due to its fast convergence. The effectiveness of the proposed hybrid algorithm has been demonstrated in solving the OPF problem, considering RESs and controllable loads for different stochastic scenarios in a benchmark system to minimize the total operation cost. To verify its effectiveness, its performance is compared with the most advanced and recently proposed hybrid meta‐heuristic techniques. Simulation results show that the proposed algorithm can solve the OPF problems with RESs and controllable loads efficiently and can give better solutions compared to different techniques. The conventional statistical method called analysis of variance (ANOVA) test, Tukey honestly significant difference test, and Wilcoxon sign rank test are performed for comparative analysis of different techniques. The results of this test show the validation of CE‐CSA compared to different optimization techniques.

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Section: Literature Reviewmentioning

confidence: 99%

“…Similarly, solar irradiance can be modeled by the Lognormal or Beta PDF 6 . Finally, the behavior of the river flow for small hydro generator can be modeled by the distribution of Gumbel 12,13 . In References 14–16, some classical methods like quadratic and non‐linear programming are being used to solve OPF.…”

Section: Introductionmentioning

confidence: 99%

Hybrid cross entropy—cuckoo search algorithm for solving optimal power flow with renewable generators and controllable loads

Sarda

Pandya

Lee

2021

Optim Control Appl Methods

Self Cite

View full text Add to dashboard Cite

show abstract

“…The integration of RESs in the distribution system affects operating conditions and the characteristics of the distributed generation. One of the most common problems that must be dealt with when using renewable energy is the uncertainty effect, because the power produced from RESs depends on weather conditions [1,2]. RES is a type of distributed generation (DG).…”

Section: Introductionmentioning

confidence: 99%

A MODA and MODE Comparison for Optimal Allocation of Distributed Generations with Different Load Levels

et al. 2019

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In this paper, the performance of different optimization techniques namely, multi-objective dragonfly algorithm (MODA) and multi-objective differential evolution (MODE) are presented and compared. The uncertainty effect of a wind turbine (WT) on the performance of the distribution system is taken into account. The point estimate method (PEM) is used to model the uncertainty in wind power. Optimization methods are applied to determine the multi-objective optimal allocation of distributed generation (DG) in radial distribution systems at a different load level (light, normal, heavy load level). The multi-objective function is expressed to minimize the total power loss, total operating cost, and improve the voltage stability index of the radial distribution system (RDS). Multi-objective proposed algorithms are used to generate the Pareto optimal solutions; and a fuzzy decision-making function is used to produce a hybrid function for obtaining the best compromise solution. The proposed algorithms are carried out on 33-bus and IEEE-69-bus power systems. The simulation results show the effectiveness of installing the proper size of DG at the suitable location based on different techniques.

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Dynamic optimal power flow with cross entropy covariance matrix adaption evolutionary strategy for systems with electric vehicles and renewable generators

2021

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Summary Modern power systems which integrate renewable energy sources (RESs), such as wind or solar energy sources and plug‐in electric vehicles (PEVs), need to carry out the uncertainty due to the access of demanded or injected power. Therefore, it is necessary to consider uncertainty costs in optimal power flow problems. To develop the uncertainty cost functions, log‐normal probability distribution function (PDF) for solar irradiance, normal PDF for unloading and loading behavior of PEVs, and Rayleigh PDF for wind speed are considered. In this work, a dynamic optimal power flow (DOPF) model is formulated by considering the uncertainties of RESs and PEVs. A newly hybrid metaheuristic algorithm named cross entropy (CE) covariance matrix adaption evolutionary strategy (CMAES) is proposed to evaluate the DOPF problem in a modified IEEE 118‐bus system. The application of adaptive step length in the CMAES method improves the local exploitation capability, while the CE method is used in the initial stage for global exploration due to its fast convergence. Simulation results indicate that the proposed technique can solve the DOPF problems with RESs and PEVs effectively and can provide high‐quality solutions compared to different techniques. The conventional statistical method called ANOVA test is performed for comparative analysis of different techniques. The results of this test show the validation of CE‐CMAES compared to different optimization techniques. Therefore, the proposed method could be easily and efficiently applied by power system operators in real‐time optimal power flow operations.

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Optimal Active–Reactive Power Dispatch Considering Stochastic Behavior of Wind, Solar and Small-Hydro Generation

Cited by 7 publications

References 10 publications

Hybrid cross entropy—cuckoo search algorithm for solving optimal power flow with renewable generators and controllable loads

Hybrid cross entropy—cuckoo search algorithm for solving optimal power flow with renewable generators and controllable loads

A MODA and MODE Comparison for Optimal Allocation of Distributed Generations with Different Load Levels

Dynamic optimal power flow with cross entropy covariance matrix adaption evolutionary strategy for systems with electric vehicles and renewable generators

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