Multi-objective economic emission dispatch using interior search algorithm

Karthik, N.; Parvathy, A. K.; Rajagopalan, Arul

doi:10.1002/etep.2683

Cited by 44 publications

(20 citation statements)

References 58 publications

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“…The study conducted by Gandomi [29] proposed art-inspired optimization algorithm titled interior search algorithm (ISA) which had interior design and decoration as its base, and the algorithm is aimed at determining the global optimum solution. In [30], ISA was implemented to address the multi-objective economic emission dispatch problem. In case of conventional ISA, new variables were generated using rand functions which resulted in the local optima.…”

Section: Introductionmentioning

confidence: 99%

Levy Interior Search Algorithm-Based Multi-objective Optimal Reactive Power Dispatch for Voltage Stability Enhancement

Karthik

Parvathy

Arul

et al. 2020

Lecture Notes in Electrical Engineering

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Reactive power resource management is a crucial and vital step in order to have a safe and cost-effective power system option when it comes to voltage stability. The optimal reactive power dispatch (ORPD) has a key aim to find out the appropriate control variable values, for example, shunt VAR compensator settings, generator bus voltages, and tap settings of on-load tap change (OLTC) transformers. This objective is designed, by taking the constraints into account, and to ensure that the objective function is reduced. In the current research work, the researchers proposed a levy interior search algorithm (LISA) in order to elucidate multi-objective optimal reactive power dispatch challenges that mitigate the real power loss, and at the same time, it also saves the voltage quality. In this research article, the researchers considered real power loss and voltage stability index as objective functions. The paper has a primary objective, i.e., by taking large-scale power system into account, the researchers proposed a multi-objective interior search algorithm in order to get rid of multi-objective ORPD problem and to yield the best results from the secure and cost-effective operation of electric power systems. The researchers simulated the setup under IEEE 57-bus and large-scale IEEE 300-bus system to emphasize the efficacy of LISA. From the results, it can be confirmed that the proposed approach yielded much better results than the existing algorithms. KeywordsOptimal reactive power dispatch • Interior search algorithm (ISA) • Levy interior search algorithm (LISA) • Real power loss • Voltage stability index •

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Section: Introductionmentioning

confidence: 99%

Levy Interior Search Algorithm-Based Multi-objective Optimal Reactive Power Dispatch for Voltage Stability Enhancement

Karthik

Parvathy

Arul

et al. 2020

Lecture Notes in Electrical Engineering

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“…Recently, several researchers have paid attention to the economic emission dispatch (EED) dilemma (Abdelaziz et al , 2016; Damodaran and Sunil Kumar, 2018; ElDesouky, 2013; Hota et al , 2010; Karthik et al , 2019; Dhillon and Kothari, 2009). To build up an inclusive model of the DEED dilemma, the stochastic nature of WPGs and SPGs are also to be taken into consideration to lessen the over and under estimation of WPGs and SPGs output.…”

Section: Introductionmentioning

confidence: 99%

“…To build up an inclusive model of the DEED dilemma, the stochastic nature of WPGs and SPGs are also to be taken into consideration to lessen the over and under estimation of WPGs and SPGs output. Traditionally, the EED dilemma has been discussed in (Damodaran and Sunil Kumar, 2018; ElDesouky, 2013; Hota et al , 2010; Karthik et al , 2019) but the aforesaid matters have made the researchers to review a variety of aspects of the dilemma based on stochastic nature (Saravanan et al , 2017; Kalaiselvi et al , 2018).…”

Section: Introductionmentioning

confidence: 99%

Dynamic economic emission dispatch of thermal-wind-solar system with constriction factor-based particle swarm optimization algorithm

Behera

Barisal³

et al. 2020

WJE

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Purpose Dynamic economic and emission dispatch (DEED) aims to optimally set the active power generation with constraints in a power system, which should target minimum operation cost and at the same time minimize the pollution in terms of emission when the load dynamically changes hour to hour. The purpose of this study is to achieve optimal economic and emission dispatch of an electrical system with a renewable generation mix, consisting of 3-unit thermal, 2-unit wind and 2-unit solar generators for dynamic load variation in a day. An improved version of a simple, easy to understand and popular optimization algorithm particle swarm optimization (PSO) referred to as a constriction factor-based particle swarm optimization (CFBPSO) algorithm is deployed to get optimal solution as compared to PSO, modified PSO and red deer algorithm (RDA). Design/methodology/approach Different model with and without wind and solar power generating systems; with valve point effect is analyzed. The thermal generating system (TGs) are the major green house gaseous emission producers on earth. To take up this ecological issue in addition to economic operation cost, the wind and solar energy sources are integrated with the thermal system in a phased manner for electrical power generation and optimized for dynamic load variation. This DEED being a multi-objective optimization (MO) has contradictory objectives of fuel cost and emission. To get the finest combination of the two objectives and to get a non-dominated solution the fuzzy decision-making (FDM) method is used herein, the MO problem is solved by a single objective function, including min-max price penalty factor on emission in the total cost to treat as cost. Further, the weight factor accumulation (WFA) technique normalizes the pair of objectives into a single objective by giving each objective a weightage. The weightage is decided by the FDM approach in a systematic manner from a set of non-dominated solutions. Here, the CFBPSO algorithm is applied to lessen the total generation cost and emission of the thermal power meeting the load dynamically. Findings The efficacy of the contribution of stochastic wind and solar power generation with the TGs in the dropping of net fuel cost and emission in a day for dynamic load vis-à-vis the case with TGs is established. Research limitations/implications Cost and emission are conflicting objectives and can be handled carefully by weight factors and penalty factors to find out the best solution. Practical implications The proposed methodology and its strategy are very useful for thermal power plants incorporating diverse sources of generations. As the execution time is very less, practical implementation can be possible. Social implications As the cheaper generation schedule is obtained with respect to time, cost and emission are minimized, a huge revenue can be saved over the passage of time, and therefore it has a societal impact. Originality/value In this work, the WFA with the FDM method is used to facilitate CFBPSO to decipher this DEED multi-objective problem. The results reveal the competence of the projected proposal to satisfy the dynamic load demand and to diminish the combined cost in contrast to the PSO algorithm, modified PSO algorithm and a newly developed meta-heuristic algorithm RDA in a similar system.

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“…This method had Gaussian function-based niche search method in order to improve the Pareto-optimal front solutions' distribution and accuracy. 37 Generally, there is no satisfactory performance registered from meta-heuristic algorithm in the multimodel fitness landscapes. Real-coded chemical reaction (RCCRO) algorithm was proposed in the study 12 in which the algorithm mimics the molecular interaction as in the chemical reaction so as to achieve the low energy (global) state.…”

Section: Introductionmentioning

confidence: 99%

“…Mine blast algorithm (MBA) was discussed in Ali and Elazim 20 to solve MoPs, and other recent search techniques that were proposed to solve ELD, ED, and MoPs are floating search space, 21 enhanced moth-flame optimizer, 22 immune algorithm, 23 multiobjective biogeography-based optimization, 24 artificial bee colony algorithm, 25 ant colony optimization, 26 Franklin and Coulomb law-based algorithm, 27 population variant differential evolution, 28 stochastic fractal search algorithm, 29 quantum-inspired particle swarm optimization (QPSO), 30 quadratic approximation-based hybrid artificial cooperative search algorithm, 31 opposition-based harmony search algorithm (OHS), 32 spiral optimization algorithm, 33 chaotic firefly algorithm, 34 mixed integer optimization problem, 35 stochastic weight trade-off chaotic Non-dominated Sorting Particle Swarm Optimization (NSPSO), 36 and interior search algorithm (ISA). 37 Generally, there is no satisfactory performance registered from meta-heuristic algorithm in the multimodel fitness landscapes. This might be due to the reason that it gets confined to the local optima.…”

Section: Introductionmentioning

confidence: 99%

Chaotic self‐adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints

Rajagopalan

Kasinathan²,

Karthik

et al. 2019

Int Trans Electr Energ Syst

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Summary The main goal behind the combined economic emission dispatch (CEED) is to reduce the costs incurred upon fuel and emission for the generating units available without any intention to violate the generator and security constraints. Hence, the CEED must be handled after considering two challenging goals such as the costs involved with emission and fuel. In this paper, chaotic self‐adaptive interior search algorithm (CSAISA) was proposed to solve the CEED problems, considering the nonlinear behavior of generators in terms of valve point effects, prohibited operating zones, and security constraints. The proposed algorithm was tested for its effectiveness using 11‐generating units (without security), IEEE‐30 bus system, and IEEE‐118 bus system with security constraints. The results of the proposed CSAISA were compared with interior search algorithm (ISA), harmony search algorithm (HSA), differential evolution (DE), particle swarm optimization (PSO), and genetic algorithm (GA). To conclude, the proposed CSAISA outperformed all other algorithms in terms of convergence speed, implementation time, and solution quality, which was tested using performance metrics.

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Multi-objective economic emission dispatch using interior search algorithm

Cited by 44 publications

References 58 publications

Levy Interior Search Algorithm-Based Multi-objective Optimal Reactive Power Dispatch for Voltage Stability Enhancement

Levy Interior Search Algorithm-Based Multi-objective Optimal Reactive Power Dispatch for Voltage Stability Enhancement

Dynamic economic emission dispatch of thermal-wind-solar system with constriction factor-based particle swarm optimization algorithm

Chaotic self‐adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints

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