An Improved Simplex based Particle Swarm Optimization for Environmentally Constrained Economic Dispatch Problem in Thermal Power Plants

Chopra, Namarta; Brar, Yadwinder Singh; Dhillon, J.S.

doi:10.1007/978-981-15-4692-1_1

Cited by 3 publications

(2 citation statements)

References 22 publications

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“…Thus, it is not handled efficiently via local optimization techniques. Moving ahead, constrained OPF problems are solved using a simplex-based chaotic PSO (SCPSO) scheme for preventing PSO from early convergence (Chopra et al, 2021). The minimization of operational cost, enhancement of bus voltage profiles, and reduction of energy loss by focusing on the effects of the valve point load are the major objectives of the proposed scheme.…”

Section: Related Workmentioning

confidence: 99%

An effective solution to the optimal power flow problem using meta-heuristic algorithms

Aurangzeb,

Shafiq,

Alhussein

et al. 2023

Front. Energy Res.

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Financial loss in power systems is an emerging problem that needs to be resolved. To tackle the mentioned problem, energy generated from various generation sources in the power network needs proper scheduling. In order to determine the best settings for the control variables, this study formulates and solves an optimal power flow (OPF) problem. In the proposed work, the bird swarm algorithm (BSA), JAYA, and a hybrid of both algorithms, termed as HJBSA, are used for obtaining the settings of optimum variables. We perform simulations by considering the constraints of voltage stability and line capacity, and generated reactive and active power. In addition, the used algorithms solve the problem of OPF and minimize carbon emission generated from thermal systems, fuel cost, voltage deviations, and losses in generation of active power. The suggested approach is evaluated by putting it into use on two separate IEEE testing systems, one with 30 buses and the other with 57 buses. The simulation results show that for the 30-bus system, the minimization in cost by HJBSA, JAYA, and BSA is 860.54 $/h, 862.31, $/h and 900.01 $/h, respectively, while for the 57-bus system, it is 5506.9 $/h, 6237.4, $/h and 7245.6 $/h for HJBSA, JAYA, and BSA, respectively. Similarly, for the 30-bus system, the power loss by HJBSA, JAYA, and BSA is 9.542 MW, 10.102 MW, and 11.427 MW, respectively, while for the 57-bus system, the value of power loss is 13.473 MW, 20.552, MW and 18.638 MW for HJBSA, JAYA, and BSA, respectively. Moreover, HJBSA, JAYA, and BSA cause reduction in carbon emissions by 4.394 ton/h, 4.524, ton/h and 4.401 ton/h, respectively, with the 30-bus system. With the 57-bus system, HJBSA, JAYA, and BSA cause reduction in carbon emissions by 26.429 ton/h, 27.014, ton/h and 28.568 ton/h, respectively. The results show the outperformance of HJBSA.

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Section: Related Workmentioning

confidence: 99%

An effective solution to the optimal power flow problem using meta-heuristic algorithms

Aurangzeb,

Shafiq,

Alhussein

et al. 2023

Front. Energy Res.

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“…In [35], the authors have used Squirrel Search Algorithm to solve CEED for multi-area system. In [36], the authors have used an improved simplex based PSO for solving CEED. In [37], authors have modelled the ELD problem in presence of wind farms and flexible resources in a multi-objective framework and solved the problem by fuzzy logic.…”

Section: Introductionmentioning

confidence: 99%

Performance of Turbulent Flow of Water Optimization on Economic Load Dispatch Problem

et al. 2021

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The economic load dispatch (ELD) problems considering nonlinear characteristics where an optimal combination of power generating units is selected in order to minimize the total cost by economic allocation of power produced and the emission cost. As a consequence, optimal allocation is performed by considering both fuel cost and emission leading to Combined Economic and Emission Dispatch (CEED). This study presents a new Meta-heuristic algorithms (MHs) called the Turbulent Flow of Water Optimization (TFWO), which is based on the behaviour of whirlpools created in turbulent water flow, for solving different variants of ELD and CEED. To verify the robustness of the TFWO, various test network of CEED with effect of valve, and ELD with losses of transmission are incorporated. In comparison with seven well-known MHs such as Cuckoo Search Algorithm (CSA), Grey Wolf Algorithm (GW), Sine Cosine Algorithm (SCA), Earth Worm Optimization Algorithm (EWA), Tunicate Swarm Algorithm (TSA), Moth Search Algorithm (MSA) and Teaching Learning Based Optimization (TLBO), the TFWO provides the minimum fuel cost and significantly robust solutions of ELD problem over all tested networks. The results confirm the potential and effectiveness of the GWO to be a promising technique to solve various ELD problems.INDEX TERMS Turbulent Flow of Water Optimization (TFWO)); Economic Load Dispatch (ELD); Combined Economic and Emission Dispatch (CEED); Metaheuristic Optimization Algorithms.

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Dynamic environmental economic dispatch with an enhanced-accuracy probabilistic wind cost model

Rezaie¹,

Razmi

Safari³

et al. 2022

Electr Eng

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An Improved Simplex based Particle Swarm Optimization for Environmentally Constrained Economic Dispatch Problem in Thermal Power Plants

Cited by 3 publications

References 22 publications

An effective solution to the optimal power flow problem using meta-heuristic algorithms

An effective solution to the optimal power flow problem using meta-heuristic algorithms

Performance of Turbulent Flow of Water Optimization on Economic Load Dispatch Problem

Dynamic environmental economic dispatch with an enhanced-accuracy probabilistic wind cost model

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