Synergetic fusion of energy optimization and waste heat reutilization using nature-inspired algorithms: a case study of Kraft recovery process

Pati, Smitarani; Yadav, Drishti; Verma, Om Prakash

doi:10.1007/s00521-020-04828-4

Cited by 13 publications

(7 citation statements)

References 48 publications

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“…1, the energy balance and heat balance equations are depicted in this section. The energy balance and the heat balance equations are derived concerning the heat enthalpies and the latent heat of vaporization related to the temperatures and liquor concentrations of the respective stages of the evaporators (the correlation of the heat enthalpies and the latent heat of vaporization is stated in Appendix I of the Supporting Information) 18. In this work, the condensate output is considered, and the modified equations for each stage of the MSE are as follows:…”

Section: Model Development For An Ers‐incorporating Msementioning

confidence: 99%

“…Since the last eight decades, many research articles based on the steady-state energy modeling of MSE have been published [3,[6][7][8][9][10][11][12][13]. These articles represent a wide range of solution approaches for solving the set of nonlinear algebraic equations (SNLAE), such as different solvers (fsolver) [13], iterative methods (Gauss elimination, Gauss-Seidel, Newton-Raphson methods) [3], pinch analysis (composition and grand composition curve) [14,15], the interior-point method [16], genetic algorithms [17], differential evolution, particle swarm optimization [18], the water cycle algorithm [19], the artificial electric field algorithm [20,21], etc., in the MATLAB environment. The introduction of different new deterministic (nonlinear programming) and stochastic approaches (metaheuristic approaches) to find the optimal value makes it essential to check the best solution obtained in the minimum time period.…”

Section: Introductionmentioning

confidence: 99%

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Transient Modeling and Simulation of a Multiple‐Stage Evaporator in the Paper Industry

et al. 2022

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The present work investigates the energy performance analysis of a heptad‐based multiple‐stage evaporator (MSE) under steady and transient conditions, integrated with different energy reduction schemes (such as steam split, feed split, and feed preheater). The steady‐state analysis was performed to optimize the steam economy subjected to the developed steady‐state energy models as the equality constraints. The simulated optimization is a maximization problem and is solved by Interior‐Point Optimizer and Gray Wolf Optimizer on two different platforms, GAMS and MATLAB, respectively. Further, transient and stability analyses were performed by developing and representing the nonlinear dynamic energy models to the state‐space representation using linearization.

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Section: Model Development For An Ers‐incorporating Msementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Transient Modeling and Simulation of a Multiple‐Stage Evaporator in the Paper Industry

et al. 2022

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“…The present analysis considers a Heptad's effect-based MSE, which is operated at a paper mill in North Indian region at Saharanpur (U.P., India). 11 In the previous literature, it has been concluded that backward feed flow (BFF) configuration is most suitable (attributable to its comparatively high energy efficient performance) than the forward-and mixed-feed configurations. 9,10 With this fact in consideration, the present work exhaustively investigates the BFF configuration.…”

Section: System Descriptionmentioning

confidence: 99%

“…In the literature, various energy reduction schemes and configurations along with the nonlinear steady-state, dynamic modeling and simulation of MSE have been reported. [3][4][5][6][7][8][9] Classical numerical techniques (iterative methods), Interior-Point Methodology (I-PM, a dynamic programming approach 10 ), Genetic Algorithm (GA, a soft computing approach, [11][12][13] ) and Water Cycle Algorithm (WCA, a metaheuristic technique) 14 have been employed to solve the steadystate nonlinear models of MSE in search of the optimum steady-state unknown process parameters. 9 In addition, a number of metaheuristic approaches (such as Squirrel Search Algorithm, 15 Political optimizer, 16 and Water strider algorithm 17 ) have been proposed for solving realtime complex optimization tasks frequently encountered in engineering applications.…”

Section: Introductionmentioning

confidence: 99%

Water cycle algorithm tuned robust fractional‐order Proportional–Integral–Derivative controller for energy optimization and control of nonlinear Multiple Stage Evaporator: A case study of paper mill

Verma

Yadav

Pati

et al. 2021

Asia-Pacific J Chem Eng

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In paper industries, Multiple Stage Evaporator (MSE) is used to concentrate black liquor. Due to the energy intensive nature of MSE, the global energy scenario stresses on optimizing its energy efficiency. Moreover, the necessity of a tight control of product quality demands superior understanding of system dynamics for controller design. This paper presents a robust fractional‐order Proportional–Integral–Derivative (FOPID) controller for concentration control of black liquor in Heptad's effect MSE. First, the steady‐state unknown process parameters are estimated by solving the nonlinear steady‐state model. Thereafter, these optimal process parameters are utilized to simulate the nonlinear dynamic model to obtain the transfer functions. By using these transfer functions, the FOPID controller is designed whose parameters are tuned via Water Cycle Algorithm (WCA). The competence of WCA toward controller tuning is validated by comparing with other optimization techniques (Genetic Algorithm [GA], Simulated Annealing [SA], Particle Swarm Optimization [PSO], and Krill Herd [KH]). Moreover, the performance of the proposed FOPID controller in concentration control, set‐point tracking, and noise suppression is validated by comparing with conventional PID, two‐degree of freedom‐PID (2‐DOF‐PID), and Internal Model Control (IMC) controllers. The results demonstrate that FOPID controller reduces the Integral Square Error (ISE) by 91.05%, 89.81%, and 78.84%, respectively, with respect to PID, 2‐DOF‐PID, and IMC. Also, the proposed FOPID controller improves the system transience with high robustness.

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“…Furthermore, the exhaustive computation of Jacobian Matrix and the dependency on the initial guess turn out to be drawbacks of the NR Method (Verma et al, 2017b). Besides, various approaches have been proposed to solve these issues of optimization of SE and SC including the Interior-Point Method (I-PM), a dynamic programming approach, GA, a nature-inspired approach (Verma et al, 2019;Verma et al, 2018dVerma et al, , 2017bVerma et al, , 2017c and other nature-inspired algorithms (Pati et al, 2020).…”

Section: Introductionmentioning

confidence: 99%

Energy optimization of Multiple Stage Evaporator system using Water Cycle Algorithm

Yadav

Verma

2020

Heliyon

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Black liquor, a residual stream from the Kraft recovery process of paper mills is an incipient biomass energy resource which finds prospective biofuel-based industrial applications to ensure process self-sufficiency and sustainability. Black liquor is concentrated using Multiple Stage Evaporator, the utmost energy intensive unit, before using it as biofuel. Pertaining to the contemporary global energy scenario, improvement in energy efficiency of Multiple Stage Evaporator becomes indispensable. The present work investigates the non-linear modeling and simulation-based optimization of Heptads' stage based Multiple Stage Evaporator in backward feed flow configuration integrated with various energy saving strategies. A novel metaheuristic approach, Water Cycle Algorithm has been employed to search the optimum estimates of unknown process variables and therefore, the optimum energy efficiency parameters. The optimization results demonstrate the efficiency of Water Cycle Algorithm in screening the most appropriate operating strategy, i.e. , hybrid model of all energy saving strategies (steam-split, feed-split and feed-preheating) with optimum energy efficiency i.e. Steam Economy of 7.092 and Steam Consumption of 1.919 kg/s. Moreover, a comparative analysis of the results with previous literature and real-time plant estimates reveal that the hybrid model offers improvement of 52.84% in Steam Economy and reduction in Steam Consumption by 28.13% when compared to the real plant data.

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Synergetic fusion of energy optimization and waste heat reutilization using nature-inspired algorithms: a case study of Kraft recovery process

Cited by 13 publications

References 48 publications

Transient Modeling and Simulation of a Multiple‐Stage Evaporator in the Paper Industry

Transient Modeling and Simulation of a Multiple‐Stage Evaporator in the Paper Industry

Water cycle algorithm tuned robust fractional‐order Proportional–Integral–Derivative controller for energy optimization and control of nonlinear Multiple Stage Evaporator: A case study of paper mill

Energy optimization of Multiple Stage Evaporator system using Water Cycle Algorithm

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