scholarly journals Heat Exchanger Network Optimization Based on the Participatory Evolution Strategy for Streams

Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8392
Author(s):  
Jiaxing Chen ◽  
Guomin Cui ◽  
Mei Cao ◽  
Heri Kayange ◽  
Jian Li
Keyword(s):  
Heat Exchanger ◽  
Network Optimization ◽  
Heat Exchangers ◽  
Structural Model ◽  
Evolutionary Process ◽  
Optimal Solution ◽  
Evolutionary Strategy ◽  
Heat Exchanger Network ◽  
Global Optimal Solution ◽  
Global Optimal

The non-structural model of a heat exchanger network randomly selects a position of a node on hot and cold streams to generate a heat exchanger and an existing heat exchanger to participate in the evolution. Despite the model being more random and flexible, this selection method cannot easily find a good solution. In addition, the heat exchangers participating in the evolution might not be involved in all streams in each evolutionary process. A stream that does not participate in the evolution will have no significance to the current iteration. Therefore, many iterations are required to make each stream participate in the evolution, which limits the evolution efficiency of the optimization algorithm. In view of this shortcoming, this study proposes a participatory evolutionary strategy for streams based on hot streams. The proposed strategy reorders the existing heat exchangers on hot and cold streams and takes the corresponding measures to ensure that a heat exchanger is selected for each stream to participate in the evolution in every cycle. The proposed participatory evolutionary strategy for streams improves the global optimal solution for designs based on non-structural models. The effectiveness of the proposed strategy is demonstrated in two cases.

scholarly journals A Nodes-Based Non-Structural Model Considering a Series Structure for Heat Exchanger Network Synthesis

Processes ◽  
2020 ◽  
Vol 8 (6) ◽  
pp. 695
Author(s):  
Yue Xu ◽  
Heri Ambonisye Kayange ◽  
Guomin Cui
Keyword(s):  
Heat Exchanger ◽  
Heat Exchangers ◽  
Structural Model ◽  
Cost Effective ◽  
Maximum Energy ◽  
Network Synthesis ◽  
Heat Exchanger Network ◽  
Proposed Model ◽  
Effective Network ◽  
Heat Exchanger Network Synthesis

The aim of heat exchanger network synthesis is to design a cost-effective network configuration with the maximum energy recovery. Therefore, a nodes-based non-structural model considering a series structure (NNM) is proposed. The proposed model utilizes a simple principle based on setting the nodes on streams such that to achieve optimization of a heat exchanger network synthesis (HENS) problem. The proposed model uses several nodes to quantify the possible positions of heat exchangers so that the matching between hot and cold streams is random and free. Besides the stream splits, heat exchangers with series structures are introduced in the proposed model. The heuristic algorithm used to solve NNM model is a random walk algorithm with compulsive evolution. The proposed model is used to solve four scale cases of a HENS problem, the results show that the costs obtained by NNM model can be respectively lower 3226 $/a(Case 1), 11,056 $/a(Case 2), 2463 $/a(Case 3), 527 $/a(Case 4) than the best costs listed in literature.

Bee Immune Evolutionary Algorithm

2011 ◽  
Vol 268-270 ◽  
pp. 1184-1187 ◽  
Author(s):  
Zuo Yong Li ◽  
Chun Xue Yu ◽  
Lei Zang
Keyword(s):  
Genetic Algorithm ◽  
Local Search ◽  
Evolutionary Algorithm ◽  
Evolutionary Process ◽  
Optimal Solution ◽  
Global Optimal Solution ◽  
Second Best ◽  
Evolutionary Genetic ◽  
Global Optimal ◽  
Immune Evolutionary Algorithm

The bee immune evolutionary algorithm was proposed in order to improve effectively the optimal ability of bee evolutionary genetic algorithm. In the evolutionary process of bee, the algorithm made on immune evolutionary iteration calculation, generate next-generation population, in the proportions of fitness values for the best individual and second-best individuals in each generation. Because the algorithm takes in the neighborhood of space search as well out the neighborhood of space search for the some optimal individuals, meanwhile, with iterative numbers increase, capability of local search can be strengthened gradually; the bee immune evolutionary algorithm can approach the global optimal solution with higher accuracy. The calculated results for typical best functions show that the bee immune evolutionary algorithm has better optimal capability and stability.

AO-BBO: A Novel Optimization Algorithm and Its Application in Plant Drug Extraction

2019 ◽  
Vol 19 (2) ◽  
pp. 139-145 ◽  
Author(s):  
Bote Lv ◽  
Juan Chen ◽  
Boyan Liu ◽  
Cuiying Dong
Keyword(s):  
Optimization Algorithm ◽  
Learning Strategy ◽  
Optimal Solution ◽  
Population Diversity ◽  
Global Optimal Solution ◽  
Plant Medicine ◽  
Suitability Index ◽  
Sensing Model ◽  
Local Optimal Solution ◽  
Global Optimal

<P>Introduction: It is well-known that the biogeography-based optimization (BBO) algorithm lacks searching power in some circumstances. </P><P> Material & Methods: In order to address this issue, an adaptive opposition-based biogeography-based optimization algorithm (AO-BBO) is proposed. Based on the BBO algorithm and opposite learning strategy, this algorithm chooses different opposite learning probabilities for each individual according to the habitat suitability index (HSI), so as to avoid elite individuals from returning to local optimal solution. Meanwhile, the proposed method is tested in 9 benchmark functions respectively. </P><P> Result: The results show that the improved AO-BBO algorithm can improve the population diversity better and enhance the search ability of the global optimal solution. The global exploration capability, convergence rate and convergence accuracy have been significantly improved. Eventually, the algorithm is applied to the parameter optimization of soft-sensing model in plant medicine extraction rate. Conclusion: The simulation results show that the model obtained by this method has higher prediction accuracy and generalization ability.</P>

scholarly journals Best Proximity Point Results in Complex Valued Metric Spaces

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Binayak S. Choudhury ◽  
Nikhilesh Metiya ◽  
Pranati Maity
Keyword(s):  
Minimum Distance ◽  
Metric Spaces ◽  
Optimal Solution ◽  
Global Optimal Solution ◽  
Complex Valued Metric Space ◽  
Fixed Point Equation ◽  
Point Equation ◽  
Global Optimal ◽  
Metric Function ◽  
Complex Valued

We introduce the concept of proximity points for nonself-mappings between two subsets of a complex valued metric space which is a recently introduced extension of metric spaces obtained by allowing the metric function to assume values from the field of complex numbers. We apply this concept to obtain the minimum distance between two subsets of the complex valued metric spaces. We treat the problem as that of finding the global optimal solution of a fixed point equation although the exact solution does not in general exist. We also define and use the concept of P-property in such spaces. Our results are illustrated with examples.

A Practical Approach to Energy Optimization Using Pinch Analysis: A Case Study of an Oil Refinery

2021 ◽  
Author(s):  
Paschal Uzoma Ndunagu ◽  
Emeka Emmanuel Alaike ◽  
Theophile Megueptchie
Keyword(s):  
Heat Exchanger ◽  
Heat Exchangers ◽  
Energy Savings ◽  
Operating Cost ◽  
Energy Optimization ◽  
Distillation Unit ◽  
Pinch Analysis ◽  
Cost Index ◽  
Heat Exchanger Network ◽  
Total Cost

Abstract The objective of this paper is to perform an energy optimization study using pinch analysis on the Heat Exchanger Network (HEN) of a Crude Distillation Unit to maximum heat recovery, minimize energy consumption and increase refining margin. The heat exchanger network (HEN) considered comprises exchangers from the pre-heat section of the atmospheric distillation unit, which recovers heat from the product streams to incrementally heat the crude oil feed stream before entering the furnace. This paper illustrates how to perform a detailed HEN retrofitting study using an established design method known as Pinch Analysis to reduce the operating cost by increasing energy savings of the HEN of an existing complex refinery of moderate capacity. Analysis and optimization were carried out on the HEN of the CDU consist a total of 19 heat exchangers which include: process to process (P2P) heat exchangers, heaters and coolers. In the analysis, different feasible retrofit scenarios were generated using the pinch analysis approach. The retrofit designs included the addition of new heat exchangers, rearrangement of heat exchanger (re-sequencing) and re-piping of existing exchangers. Aspen Hysys V9 was used to simulate the CDU and Aspen Energy Analyser was used to perform pinch analysis on the HEN of the pre-heat train. Several retrofit scenarios were generated, the optimum retrofit solution was a trade-off between the capital cost of increasing heat exchanger surface area, payback time, energy / operating cost savings of hot and cold utilities. Results indicated that by rearrangement (Re-sequencing), the pre-heat train can reduce hot (fired heat) and cold (air and cooling water) utilities consumption to improve energy savings by 8% which includes savings on fired heat of about 4.6 MW for a payback period of 2 years on capital investment. The results generated were based on a ΔTmin of 10°C and pinch temperature of 46.3°C. Initial sensitivity analysis on the ΔTmin indicated that variation of total cost index is quite sensitive and increases with increase in ΔTmin at the temperature range of 14.5-30°C, however total cost index remains constant and minimal at a temperature range between 10°C-14.5°C for the CDU preheat train under study. In addition, the implementation of the optimum retrofit result is straightforward and feasible with minimum changes to the existing base case/design.

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