Study on supercritical CO2 coal-fired boiler based on improved genetic algorithm

Zhu, Meng; Zhou, Jiankang; Xiang, Jun; Xu, Jun; Li, Aishu; Chen, Lei; Wang, Lele; Hu, Song; Jiang, Long; Xiang, Jun

doi:10.1016/j.enconman.2020.113163

Cited by 22 publications

(6 citation statements)

References 43 publications

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“…Guo et al 25 evaluated the economic performance of 1000 MW SCPU concept units and found that the LCOE of the SCPU with intercooling was as low as 0.0397 USD kW −1 hour −1 . Zhu et al 32 carried out a detailed modeling analysis on the SCPU boiler side and then used the mass weighting method to estimate the cost of the SCPU boiler. Their results show that the cost of the SCPU boiler is higher than that of the conventional CPU, because the heating surface of tail flue increases, but the LCOE of the former is 9.26% pts lower than the latter.…”

Section: Introductionmentioning

confidence: 99%

Thermodynamic and economic comparison of supercritical carbon dioxide coal‐fired power system with different improvements

et al. 2021

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The supercritical carbon dioxide (SCO 2 ) Brayton cycle is expected to become the new generation of power cycle for coal-fired power units. Most previous studies on system and parameter optimizations of SCO 2 power systems aimed to improve thermal performance, and some of them also involved the economic performance evaluation of the configurations they proposed. However, the configurations included in previous economic analyses are limited, and the models used in different papers are different. Although many improved configurations of SCO 2 coal-fired power generation system have been proposed, currently, there is a lack of comparison under the unified thermal-economic evaluation standard. Thus, this study focuses on the economic optimization and comparison of the performances of different advanced configurations of SCO 2 coal-fired power systems under the unified standard. Thermodynamic and economic optimization models are developed, and various configurations are proposed, representing improvements from four aspects (mediumtemperature flue gas heat utilization, reheating, waste heat recovery, and main compressor intercooling) based on a recompression system. The system parameters are also economically optimized with the genetic algorithm. Results show that integrating the SCO 2 benchmark cycle, medium temperature economizer, single-reheat, flue bypass, low temperature economizer and main compressor intercooling into the coal-fired power unit yields excellent thermo-economic performance. This configuration has the highest power generation efficiency of 47.93% and the lowest levelized cost of electricity of 0.0540 USD kW −1 hour −1 compared to others. Furthermore, the influences of specific parameters on power generation cost are analyzed.

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Section: Introductionmentioning

confidence: 99%

Thermodynamic and economic comparison of supercritical carbon dioxide coal‐fired power system with different improvements

et al. 2021

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“…Genetic algorithms (GAs) [23] are a subset of evolutionary algorithms [24], that have emerged as flexible and efficient metaheuristic methods for solving optimization problems and achieving a high level of problem-solving efficacy in most research domains, e.g., aircraft design [25], battery systems [26], resource allocation [27], job-shop scheduling [28], virtual machine placement [29], cloud task scheduling [30], quadratic assignment [31], and vehicle…”

Section: Genetic Algorithmsmentioning

confidence: 99%

A Novel Many-Objective Recommendation Algorithm for Multistakeholders

Wang

Chen

2020

IEEE Access

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Most traditional recommender systems focus specifically on increasing consumer satisfaction by providing a list of relevant content to consumers. However, the perspectives of other multisided marketplace stakeholders are also equally important, i.e., the exposure for suppliers or providers and profit for the platform. The suppliers want their products to be presented to users, and the objective of the platform is to maximize their profit. Nevertheless, because consumers' preferences and the objectives of providers as well as the platform may conflict with each other, it degrades the utility of the recommendation methods by only considering users' views. Therefore, in this work, we use a many-objective optimization method to maintain a tradeoff among five objectives for three stakeholders and obtain multiple Pareto front solutions in a single run. We first combine customer lifetime value and user purchase preference to create a new similarity model (Sim_RFMP) to increase the recommendation accuracy of the recommendation list. Furthermore, we propose a many-objective model (NBHXMAOEA) for multistakeholder recommendation. In NBHXMAOEA, we present a novel N-block heuristic crossover operator (NBHX) that recombines blocks of chromosomes based on heuristics. Through extensive experiments, the results demonstrate that our proposed NBHXMAOEA achieves superior performance in terms of average accuracy, diversity, novelty, provider coverage, and platform profit to its competing methods. INDEX TERMS Many-objective, recommender systems, similarity model, stakeholders.

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“…The economic analysis of the SCPG system was performed in Refs. [ 22 , 23 ], where it was shown that it had a lower levelized cost of electricity ( LCOE ) than a traditional steam-based system. Xu et al [ 24 ] adopted a more accurate economic model, indicating that the LCOE of the SCPG system was 1.32% lower than that of the traditional steam-based system and that the recuperator was the crucial component affecting the system costs.…”

Section: Introductionmentioning

confidence: 99%

Layout Comparison and Parameter Optimization of Supercritical Carbon Dioxide Coal-Fired Power Generation Systems under Environmental and Economic Objectives

Chen

Han

Bai

et al. 2022

Entropy

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In the current studies, the supercritical carbon dioxide coal-fired power generation systems show efficiency and cost advantages over the traditional steam-based power systems. However, few studies have considered simultaneously environmental and economic objectives in the multi-objective analysis process. This study conducts a layout comparison and parameter optimization of the systems under the above two objectives. Initially, the thermodynamic, environmental, and economic models of the systems are established. Subsequently, the optimal layout is determined by the two-stage layout comparison. Further, multi-objective optimization is performed for the selected layout, and the optimal design parameters are determined by the decision process. Finally, the sensitivities of three selected parameters to the optimization results are analyzed. The results show that the basic layout coupled with overlap and intercooling schemes is optimal. Its ultimate environmental impact (UEI) and levelized cost of electricity (LCOE) are 219.8 kp-eq and 56.9 USD/MWh, respectively. The two objectives UEI and LCOE are conflicting. Based on a trade-off between them, the maximum temperature/pressure of the system is determined to be 635.3 °C/30.1 MPa. The coal price per unit of heat shows the highest sensitivity, and the pinch temperature difference of the recuperator shows opposite sensitivities at the UEI below 218 kp-eq and above 223 kp-eq.

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Study on supercritical CO2 coal-fired boiler based on improved genetic algorithm

Cited by 22 publications

References 43 publications

Thermodynamic and economic comparison of supercritical carbon dioxide coal‐fired power system with different improvements

Thermodynamic and economic comparison of supercritical carbon dioxide coal‐fired power system with different improvements

A Novel Many-Objective Recommendation Algorithm for Multistakeholders

Layout Comparison and Parameter Optimization of Supercritical Carbon Dioxide Coal-Fired Power Generation Systems under Environmental and Economic Objectives

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