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5 pages, 172 KiB

Open AccessEditorial

Special Issue on “Green Technologies for Production Processes”

by Wei Cai, Zhigang Jiang, Conghu Liu and Yan Wang

Processes 2021, 9(6), 1022; https://doi.org/10.3390/pr9061022 - 10 Jun 2021

Viewed by 1382

Abstract

Numerous pathways and narratives have been developed to shed light on how society could transform its production systems in line with the aspirational targets of the Paris Agreement and Sustainable Development Goals [...] Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

Research

Jump to: Editorial

16 pages, 1101 KiB

Open AccessArticle

Analysis the Drivers of Environmental Responsibility of Chinese Auto Manufacturing Industry Based on Triple Bottom Line

by Hua Zhang, Meihang Zhang, Wei Yan, Ying Liu, Zhigang Jiang and Shengqiang Li

Processes 2021, 9(5), 751; https://doi.org/10.3390/pr9050751 - 24 Apr 2021

Cited by 8 | Viewed by 2786

Abstract

The rapid increasing number of automobile products has brought great convenience to people’s living, but it has also caused serious environmental issues, waste of resources and energy shortage during its whole lifecycle. Corporate Environmental Responsibility (CER) refers to the company’s responsibility to avoid [...] Read more.

The rapid increasing number of automobile products has brought great convenience to people’s living, but it has also caused serious environmental issues, waste of resources and energy shortage during its whole lifecycle. Corporate Environmental Responsibility (CER) refers to the company’s responsibility to avoid damage to the natural environment derived from its corporate social responsibility (CSR), and it plays an important role in solving resource and environmental problems. However, due to various internal and external reasons, it is difficult for the automobile manufacturing industry to find the key drivers for the implementation of CER. This research proposes a model framework that uses the fuzzy decision-making test and evaluation laboratory (fuzzy DEMATEL) method to analyze the drivers of CER from the perspective of the triple bottom line (TBL) of economy, environment and society. Firstly, the common drivers of CER are collected using literature review and questionnaire survey methods. Secondly, the key drivers are analyzed by using the fuzzy DEMATEL. Finally, the proposed approach was verified through a case study. The research results show that some effective measures to implement CER can be provided for the government, the automobile manufacturing industry and the public to promote sustainable development of Chinese Auto Manufacturing Industry (CAMI). Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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21 pages, 1786 KiB

Open AccessArticle

On the Way to Integrate Increasing Shares of Variable Renewables in China: Activating Nearby Accommodation Potential under New Provincial Renewable Portfolio Standard

by Yinhe Bu and Xingping Zhang

Processes 2021, 9(2), 361; https://doi.org/10.3390/pr9020361 - 16 Feb 2021

Cited by 8 | Viewed by 1899

Abstract

More than 1.2 billion kW wind and solar power generation will be integrated in China by 2030. The new provincial renewable portfolio standard, officially implemented in 2020, establishes an efficient bridge between rapid capacity growth and limited accommodation capability. A data-driven prospect analysis [...] Read more.

More than 1.2 billion kW wind and solar power generation will be integrated in China by 2030. The new provincial renewable portfolio standard, officially implemented in 2020, establishes an efficient bridge between rapid capacity growth and limited accommodation capability. A data-driven prospect analysis framework was proposed to evaluate the activated potential under two kinds of nearby accommodation approaches and to explore the completion prospect of this new obligated quota from provincial levels. Empirical results illustrate diverse prospects across regions. Particularly, it is hard for two kinds of provinces to complete their obligated quotas merely via the single nearby accommodation approach: The first one is close to renewable energy resources but lacks flexible peak regulation capability in Northeast and Northwest China, and the other is close to the nationwide load center but lacks nearby integration from renewables in Southeast, North, and Middle China. Therefore, the pathway for the former is to activate more provincial accommodation potential either via releasing system flexibility or by substituting generation right, and the pathway for the latter is to introduce trans-regional or trans-provincial accommodation and import more renewable energy power. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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16 pages, 8408 KiB

Open AccessArticle

Rapid and Green Preparation of Multi-Branched Gold Nanoparticles Using Surfactant-Free, Combined Ultrasound-Assisted Method

by Phat Trong Huynh, Giang Dang Nguyen, Khanh Thi Le Tran, Thu Minh Ho, Vinh Quang Lam and Thanh Vo Ke Ngo

Processes 2021, 9(1), 112; https://doi.org/10.3390/pr9010112 - 07 Jan 2021

Cited by 7 | Viewed by 2379

Abstract

The conventional seed-mediated preparation of multi-branched gold nanoparticles uses either cetyltrimethylammonium bromide or sodium dodecyl sulfate. However, both surfactants are toxic to cells so they have to be removed before the multi-branched gold nanoparticles can be used in biomedical applications. This study describes [...] Read more.

The conventional seed-mediated preparation of multi-branched gold nanoparticles uses either cetyltrimethylammonium bromide or sodium dodecyl sulfate. However, both surfactants are toxic to cells so they have to be removed before the multi-branched gold nanoparticles can be used in biomedical applications. This study describes a green and facile method for the preparation of multi-branched gold nanoparticles using hydroquinone as a reducing agent and chitosan as a stabilizer, through ultrasound irradiation to improve the multi-branched shape and stability. The influence of pH, mass concentration of chitosan, hydroquinone concentration, as well as sonication conditions such as amplitude and time of US on the growth of multi-branched gold nanoparticles, were also investigated. The spectra showed a broad band from 500 to over 1100 nm, an indication of the effects of both aggregation and contribution of multi-branches to the surface plasmon resonance signal. Transmission electron microscopy measurements of GNS under optimum conditions showed an average core diameter of 64.85 ± 6.79 nm and 76.11 ± 14.23 nm of the branches of multi-branched particles. Fourier Transfer Infrared Spectroscopy was employed to characterize the interaction between colloidal gold nanoparticles and chitosan, and the results showed the presence of the latter on the surface of the GNS. The cytotoxicity of chitosan capped GNS was tested on normal rat fibroblast NIH/3T3 and normal human fibroblast BJ-5ta using MTT assay concentrations from 50–125 µg/mL, with no adverse effect on cell viability. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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20 pages, 3800 KiB

Open AccessArticle

Modified Multi-Crossover Operator NSGA-III for Solving Low Carbon Flexible Job Shop Scheduling Problem

by Xingping Sun, Ye Wang, Hongwei Kang, Yong Shen, Qingyi Chen and Da Wang

Processes 2021, 9(1), 62; https://doi.org/10.3390/pr9010062 - 29 Dec 2020

Cited by 25 | Viewed by 2827

Abstract

Low carbon manufacturing has received increasingly more attention in the context of global warming. The flexible job shop scheduling problem (FJSP) widely exists in various manufacturing processes. Researchers have always emphasized manufacturing efficiency and economic benefits while ignoring environmental impacts. In this paper, [...] Read more.

Low carbon manufacturing has received increasingly more attention in the context of global warming. The flexible job shop scheduling problem (FJSP) widely exists in various manufacturing processes. Researchers have always emphasized manufacturing efficiency and economic benefits while ignoring environmental impacts. In this paper, considering carbon emissions, a multi-objective flexible job shop scheduling problem (MO-FJSP) mathematical model with minimum completion time, carbon emission, and machine load is established. To solve this problem, we study six variants of the non-dominated sorting genetic algorithm-III (NSGA-III). We find that some variants have better search capability in the MO-FJSP decision space. When the solution set is close to the Pareto frontier, the development ability of the NSGA-III variant in the decision space shows a difference. According to the research, we combine Pareto dominance with indicator-based thought. By utilizing three existing crossover operators, a modified NSGA-III (co-evolutionary NSGA-III (NSGA-III-COE) incorporated with the multi-group co-evolution and the natural selection is proposed. By comparing with three NSGA-III variants and five multi-objective evolutionary algorithms (MOEAs) on 27 well-known FJSP benchmark instances, it is found that the NSGA-III-COE greatly improves the speed of convergence and the ability to jump out of local optimum while maintaining the diversity of the population. From the experimental results, it can be concluded that the NSGA-III-COE has significant advantages in solving the low carbon MO-FJSP. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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20 pages, 6312 KiB

Open AccessArticle

Flow and Diffusion Characteristics of Typical Halon Extinguishing Agent Substitute under Different Release Pressures

by Jiaming Jin, Renming Pan, Ruiyu Chen, Xiaokang Xu and Quanwei Li

Processes 2020, 8(12), 1684; https://doi.org/10.3390/pr8121684 - 21 Dec 2020

Cited by 4 | Viewed by 1983

Abstract

To provide guidance towards reducing the weight of the HFC-125 storage vessel by reducing the release pressure and to reveal the effects of release pressure on the extinguishing efficiency of HFC-125, we investigated the flow and diffusion characteristics of HFC-125 under six release [...] Read more.

To provide guidance towards reducing the weight of the HFC-125 storage vessel by reducing the release pressure and to reveal the effects of release pressure on the extinguishing efficiency of HFC-125, we investigated the flow and diffusion characteristics of HFC-125 under six release pressures in the present study. The influence of release pressure on the degree of superheat, injection duration, pressure loss, jet angle, and concentration distribution were analyzed. Results show that the degree of superheat and the injection duration both decreased with the release pressure. The bubble expansion in the HFC-125 could slow down the pressure decrease in the storage vessel. The flow process in the pipeline can be divided into three phases: pipeline filling, stable flow, and mixed gases release. Both of the maximum and mean values of the pipeline pressure loss increased with the release pressure. The maximum concentration value decreased with the increase of the distance from the nozzle. The maximum concentration value in the near field from the nozzle increased with the release pressure. The concentration and holding time (duration above 17.6% volume concentration) of HFC-125 in the near field from the nozzle met the requirements of minimum performance standards (MPS) for HFC-125. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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18 pages, 2139 KiB

Open AccessArticle

Study on the Sustainability Evaluation Method of Logistics Parks Based on Emergy

by Cui Wang, Hongjun Liu, Li’e Yu and Hongyan Wang

Processes 2020, 8(10), 1247; https://doi.org/10.3390/pr8101247 - 02 Oct 2020

Cited by 8 | Viewed by 2347

Abstract

To improve the sustainable development ability of logistics parks, this study constructs a sustainability evaluation method of logistics parks based on emergy; analyzes the input (energy, land, investment, equipment, information technology, and human resources) and output (income and waste) of logistics parks from [...] Read more.

To improve the sustainable development ability of logistics parks, this study constructs a sustainability evaluation method of logistics parks based on emergy; analyzes the input (energy, land, investment, equipment, information technology, and human resources) and output (income and waste) of logistics parks from the perspective of emergy; studies the characteristics of the emergy flow of logistics parks; and constructs the function, structure, ecological efficiency, and sustainable development indexes of logistics parks. The basic situation, resource efficiency, and environmental friendliness of the logistics parks are comprehensively evaluated from the emergy point of view. On this basis, targeted decision suggestions are provided for the sustainable development of logistics parks. Finally, the feasibility and effectiveness of the method are verified by an example. This study reveals the internal relationship among economic, environmental, and social benefits of logistics parks through emergy and provides theoretical and methodological support for the sustainable development of logistics parks. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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12 pages, 3794 KiB

Open AccessArticle

Multi-Objective Optimization of Workshop Scheduling with Multiprocess Route Considering Logistics Intensity

by Yu Sun, Qingshan Gong, Mingmao Hu and Ning Yang

Processes 2020, 8(7), 838; https://doi.org/10.3390/pr8070838 - 15 Jul 2020

Cited by 5 | Viewed by 2541

Abstract

In order to solve the problems of flexible process route and workshop scheduling scheme changes frequently in the multi-variety small batch production mode, a multiprocess route scheduling optimization model with carbon emissions and cost as the multi-objective was established. At the same time, [...] Read more.

In order to solve the problems of flexible process route and workshop scheduling scheme changes frequently in the multi-variety small batch production mode, a multiprocess route scheduling optimization model with carbon emissions and cost as the multi-objective was established. At the same time, it is considered to optimize under the existing machine tool conditions in the workshop, then the theory of logistics intensity between equipment is introduced into the model. By designing efficient constraints to ensure reasonable processing logic, and then applying multilayer coding genetic algorithm to solve the case. The optimization results under single-target and multi-target conditions are contrasted and analyzed, so as to guide enterprises to choose a reasonable scheduling plan, improve the carbon efficiency of the production line, and save costs. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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20 pages, 1500 KiB

Open AccessArticle

Measuring the Implications of Sustainable Manufacturing in the Context of Industry 4.0

by Larisa Ivascu

Processes 2020, 8(5), 585; https://doi.org/10.3390/pr8050585 - 14 May 2020

Cited by 39 | Viewed by 4397

Abstract

Sustainability is increasingly being addressed globally. The manufacturing industry faces various constraints and opportunities related to sustainable development. Currently, there are few methodological frameworks for evaluating sustainable organizational development. Assessing and improving organizational capacity is important for producers and researchers in the field [...] Read more.

Sustainability is increasingly being addressed globally. The manufacturing industry faces various constraints and opportunities related to sustainable development. Currently, there are few methodological frameworks for evaluating sustainable organizational development. Assessing and improving organizational capacity is important for producers and researchers in the field and local, national, and international authorities. This research proposes a hierarchical framework for sustainability assessment of manufacturing industry in Romania. The proposed framework integrates performance elements and measures to improve all the processes and activities from the triple perspective of sustainability. Sustainability assessment captures the entire supply chain of the organization, including stakeholder interests and end-of-life directions for products. To establish the elements to be integrated in the development of the proposed framework, market research (online questionnaire-for the characterization of Industry 4.0) and the Delphi method were used to identify the categories of performance indicators that must be measured to identify organizational capacity for sustainable development. The framework was tested by an automotive manufacturing organization. A number of improvements have been identified that relate to Industry 4.0 facilities and the application of the facilities related to recovering the value of the product at the end of its life cycle. This hierarchical framework can be customized in detail for the specific of each organization and can be adapted in other industries, including banking, retail, and other services. It can be observed that waste management and the interests of the stakeholders are major implications that must be measured and properly motivated. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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22 pages, 1932 KiB

Open AccessArticle

Implementation Criteria for Intelligent Systems in Motor Production Line Process Management

by Yao-Chin Lin, Ching-Chuan Yeh, Wei-Hung Chen and Kai-Yen Hsu

Processes 2020, 8(5), 537; https://doi.org/10.3390/pr8050537 - 03 May 2020

Cited by 7 | Viewed by 4311

Abstract

In this study, the factors that affect the implementation of intelligent systems in motor production lines are analyzed. A motor production line located in Vietnam is used as the research object. The research methods include secondary data collection, field study, and interviews. This [...] Read more.

In this study, the factors that affect the implementation of intelligent systems in motor production lines are analyzed. A motor production line located in Vietnam is used as the research object. The research methods include secondary data collection, field study, and interviews. This study demonstrates the following: firstly, the implementation of intelligent systems in motor production lines is heading toward Industry 4.0. Secondly, it is proposed that three functional systems—robot arm, image recognition, and big data analysis—can be introduced in the motor production line. This study analyzes the process involved in coil and motor production lines and attempts to combine intelligent system functions. It is expected that in the future, manpower will be reduced, production line productivity will increase, and intelligent production lines will be proposed. The factors that affect the introduction of intelligent systems in motor production lines are improved, and the importance of intelligent systems, which has been rarely considered in previous studies, is highlighted. In the implementation criteria of the intelligent system in the process management of the motor production line, this study provides some suggestions (to coil and motor assembly line) for the production process management. These suggestions can be provided as a reference for production lines that acquaint with intelligent systems. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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19 pages, 3643 KiB

Open AccessArticle

Fluid–Solid Coupling Model and Simulation of Gas-Bearing Coal for Energy Security and Sustainability

by Shixiong Hu, Xiao Liu and Xianzhong Li

Processes 2020, 8(2), 254; https://doi.org/10.3390/pr8020254 - 24 Feb 2020

Cited by 12 | Viewed by 2583

Abstract

The optimum design of gas drainage boreholes is crucial for energy security and sustainability in coal mining. Therefore, the construction of fluid–solid coupling models and numerical simulation analyses are key problems for gas drainage boreholes. This work is based on the basic theory [...] Read more.

The optimum design of gas drainage boreholes is crucial for energy security and sustainability in coal mining. Therefore, the construction of fluid–solid coupling models and numerical simulation analyses are key problems for gas drainage boreholes. This work is based on the basic theory of fluid–solid coupling, the correlation definition between coal porosity and permeability, and previous studies on the influence of adsorption expansion, change in pore free gas pressure, and the Klinkenberg effect on gas flow in coal. A mathematical model of the dynamic evolution of coal permeability and porosity is derived. A fluid–solid coupling model of gas-bearing coal and the related partial differential equation for gas migration in coal are established. Combined with an example of the measurement of the drilling radius of the bedding layer in a coal mine, a coupled numerical solution under negative pressure extraction conditions is derived by using COMSOL Multiphysics simulation software. Numerical simulation results show that the solution can effectively guide gas extraction and discharge during mining. This study provides theoretical and methodological guidance for energy security and coal mining sustainability. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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17 pages, 5097 KiB

Open AccessArticle

Energy-Economizing Optimization of Magnesium Alloy Hot Stamping Process

by Mengdi Gao, Qingyang Wang, Lei Li and Zhilin Ma

Processes 2020, 8(2), 186; https://doi.org/10.3390/pr8020186 - 05 Feb 2020

Cited by 11 | Viewed by 3613

Abstract

Reducing the mass of vehicles is an effective way to improve energy efficiency and mileage. Therefore, hot stamping is developed to manufacture lightweight materials used for vehicle production, such as magnesium and aluminum alloys. However, in comparison with traditional cold stamping, hot stamping [...] Read more.

Reducing the mass of vehicles is an effective way to improve energy efficiency and mileage. Therefore, hot stamping is developed to manufacture lightweight materials used for vehicle production, such as magnesium and aluminum alloys. However, in comparison with traditional cold stamping, hot stamping is a high-energy-consumption process, because it requires heating sheet materials to a certain temperature before forming. Moreover, the process parameters of hot stamping considerably influence the product forming quality and energy consumption. In this work, the energy-economizing indices of hot stamping are established with multiobjective consideration of energy consumption and product forming quality to find a pathway by which to obtain optimal hot stamping process parameters. An energy consumption index is quantified by the developed models, and forming quality indices are calculated using a finite element model. Response surface models between the process parameters and energy-economizing indices are established by combining the Latin hypercube design and response surface methodology. The multiobjective problem is solved using a multiobjective genetic algorithm (NSGA-II) to obtain the Pareto frontier. ZK60 magnesium alloy hot stamping is applied as a case study to obtain an optimal combination of parameters, and compromise solutions are compared through stamping trials and numerical simulations. The obtained results may be used for guiding process optimization regarding energy saving and the method of manufacturing parameters selection. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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19 pages, 3710 KiB

Open AccessArticle

An Optimization Approach Considering User Utility for the PV-Storage Charging Station Planning Process

by Yingxin Liu, Houqi Dong, Shengyan Wang, Mengxin Lan, Ming Zeng, Shuo Zhang, Meng Yang and Shuo Yin

Processes 2020, 8(1), 83; https://doi.org/10.3390/pr8010083 - 08 Jan 2020

Cited by 16 | Viewed by 2744

Abstract

Based on the comprehensive utilization of energy storage, photovoltaic power generation, and intelligent charging piles, photovoltaic (PV)-storage charging stations can provide green energy for electric vehicles (EVs), which can significantly improve the green level of the transportation industry. However, there are many challenges [...] Read more.

Based on the comprehensive utilization of energy storage, photovoltaic power generation, and intelligent charging piles, photovoltaic (PV)-storage charging stations can provide green energy for electric vehicles (EVs), which can significantly improve the green level of the transportation industry. However, there are many challenges in the PV-storage charging station planning process, making it theoretically and practically significant to study approaches to planning. This paper promotes a bi-level optimization planning approach for PV-storage charging stations. First, taking PV-storage charging stations and EV users as the upper- and lower-level problems, respectively, during the planning process, a bi-level optimization model for PV-storage charging stations considering user utility is established for capacity allocation and user behavior-based electricity pricing. Second, the model is converted into a single-level mixed-integer linear programming model using the piecewise linear utility function, Karush–Kuhn–Tucker (KKT) conditions, and linearization methods. Finally, to verify the validity of the proposed model and the solution algorithm, a commercial solver is used to solve the optimization model and obtain the planning scheme. The results show that the proposed bi-level optimization model can provide a more economical and reasonable planning scheme than the single-level model, and can reduce the investment cost by 8.84%, operation and maintenance cost by 13.23%, and increase net revenue by 5.11%. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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15 pages, 2298 KiB

Open AccessArticle

Multi-Objective Parameter Optimization Dynamic Model of Grinding Processes for Promoting Low-Carbon and Low-Cost Production

by Mingmao Hu, Yu Sun, Qingshan Gong, Shengyang Tian and Yuemin Wu

Processes 2020, 8(1), 3; https://doi.org/10.3390/pr8010003 - 18 Dec 2019

Cited by 6 | Viewed by 2299

Abstract

Grinding is widely used in mechanical manufacturing to obtain both precision and part requirements. In order to achieve carbon efficiency improvement and save costs, carbon emission and processing cost models of the grinding process are established in this study. In the modeling process, [...] Read more.

Grinding is widely used in mechanical manufacturing to obtain both precision and part requirements. In order to achieve carbon efficiency improvement and save costs, carbon emission and processing cost models of the grinding process are established in this study. In the modeling process, a speed-change-based adjustment function was introduced to dynamically derive the change of the target model. The carbon emission model was derived from the grinding force using regression. Considering the constraints of machine tool equipment performance and processing quality requirements, the grinding wheel’s linear velocity, cutting feed rate, and the rotation speed of the workpiece were selected as the optimization variables, and the improved NSGA-II algorithm was applied to solve the optimization model. Finally, fuzzy matter element analysis was used to evaluate the most optimal processing plan. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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24 pages, 4368 KiB

Open AccessArticle

A Risk Aversion Dispatching Optimal Model for a Micro Energy Grid Integrating Intermittent Renewable Energy and Considering Carbon Emissions and Demand Response

by Xiaoxu Fu, Wei Fan, Hongyu Lin, Nan Li, Peng Li, Liwei Ju and Feng’ao Zhou

Processes 2019, 7(12), 916; https://doi.org/10.3390/pr7120916 - 03 Dec 2019

Cited by 3 | Viewed by 1947

Abstract

This paper focuses on an optimal schedule for a micro energy grid considering the maximum total carbon emission allowance (MTEA). Firstly, the paper builds an energy devices operation model and demand response (DR) model. Secondly, to maximize the economical operation revenue, the basic [...] Read more.

This paper focuses on an optimal schedule for a micro energy grid considering the maximum total carbon emission allowance (MTEA). Firstly, the paper builds an energy devices operation model and demand response (DR) model. Secondly, to maximize the economical operation revenue, the basic scheduling model for the micro energy grid is constructed. Thirdly, the conditional value at risk method and robust stochastic theory are introduced to describe the uncertainty of wind power, photovoltaic power, and load, and a risk aversion model is proposed. Finally, this paper selects the Xinxiang active distribution network demonstration project in Jining, China as an example. The results show that: (1) a micro energy grid can make the most use of the complementary characters of different energy sources to meet different energy demands for electricity, heat, cold, and gas; (2) the risk aversion scheduling model can represent the influence of uncertainty variables in objective functions and constraints, and provide a basis for decision makers who have different attitudes; and (3) DR can smooth the energy load curves. MTEA can enhance the competitiveness of the clean energy market, thus promoting the grid-connected generation of clean energy. Therefore, the risk aversion model can maximize the economic benefits and provide a basis for decision makers while rationally controlling risks. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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17 pages, 509 KiB

Open AccessArticle

Evaluating Production Process Efficiency of Provincial Greenhouse Vegetables in China Using Data Envelopment Analysis: A Green and Sustainable Perspective

by Yuhu Liang, Xu Jing, Yanan Wang, Yan Shi and Junhu Ruan

Processes 2019, 7(11), 780; https://doi.org/10.3390/pr7110780 - 01 Nov 2019

Cited by 11 | Viewed by 2983

Abstract

The evaluation of vegetable production process efficiency is of great significance for energy saving and waste reduction in production processes. However, few studies have considered the effect of greenhouse vegetable production process efficiency on energy saving and waste reduction. In this paper, data [...] Read more.

The evaluation of vegetable production process efficiency is of great significance for energy saving and waste reduction in production processes. However, few studies have considered the effect of greenhouse vegetable production process efficiency on energy saving and waste reduction. In this paper, data envelopment analysis (DEA) is used to analyze the production process efficiency and the effective use of input elements of greenhouse vegetables at the provincial level in China. The results reveal that many chemical fertilizers, farmyard manure, and pesticides in China are inefficient. On the other hand, the pure technical efficiency of greenhouse tomatoes and cucumbers is low in most areas of China. Meanwhile, the scale efficiency of greenhouse eggplants and greenhouse peppers is low in most areas of China. In order to save energy and develop green sustainable agriculture, we put forward some suggestions to improve the production efficiency of greenhouse vegetables in different provinces. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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12 pages, 223 KiB

Open AccessArticle

The Impact of Authorized Remanufacturing on Sustainable Remanufacturing

by Xiqiang Xia and Cuixia Zhang

Processes 2019, 7(10), 663; https://doi.org/10.3390/pr7100663 - 27 Sep 2019

Cited by 18 | Viewed by 2212

Abstract

Remanufacturing could effectively solve resource shortage and environment crisis and achieve sustainable development of the economy. The original equipment manufacturer (OEM) could not only focus on its core business (i.e., producing new products), but also get profit from remanufacturing through the intellectual property [...] Read more.

Remanufacturing could effectively solve resource shortage and environment crisis and achieve sustainable development of the economy. The original equipment manufacturer (OEM) could not only focus on its core business (i.e., producing new products), but also get profit from remanufacturing through the intellectual property rights. Based on the authorized remanufacturing, the game model between a manufacturer and a remanufacturer was constructed. Based on the game model, the impact of authorized remanufacturing on sustainable remanufacturing is analysed, and the coordination mechanism between manufacturer and remanufacturer is given. The main results are as follows: the OEM could increase its profit and change its unfavourable market competition status by authorizing remanufacturing; a franchise contract could make the sustainability supply chain optimized; when the ratio of the environment effect is greater than a certain threshold, centralized decision-making could not only increase the supply chain revenue, but also reduce the impact on the environment. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

15 pages, 5590 KiB

Open AccessArticle

Experimental and Numerical Simulation Study on Co-Incineration of Solid and Liquid Wastes for Green Production of Pesticides

by Bin Zhang, Jinjie He, Chengming Hu and Wei Chen

Processes 2019, 7(10), 649; https://doi.org/10.3390/pr7100649 - 23 Sep 2019

Cited by 11 | Viewed by 2682

Abstract

A large amount of solid and liquid waste is produced in pesticide production. It is necessary to adopt appropriate disposal processes to reduce pollutant emissions. A co-incineration scheme for mixing multi-component wastes in a rotary kiln was proposed for waste disposal from pesticide [...] Read more.

A large amount of solid and liquid waste is produced in pesticide production. It is necessary to adopt appropriate disposal processes to reduce pollutant emissions. A co-incineration scheme for mixing multi-component wastes in a rotary kiln was proposed for waste disposal from pesticide production. According to the daily output of solid and liquid wastes, the proportion of mixing was determined. An experiment of the co-incineration of solid and liquid wastes was established. Experimental results showed that the mixed waste could be completely disposed at 850 °C, and the residence time in the kiln exceeded 1 h. A model method for mixture and diesel oil-assisted combustion was proposed. Numerical simulation was performed to predict the granular motion and reveal the combustion interactions of the co-incineration of mixed wastes in the rotary kiln. Simulation results reproduced movements, such as rolling and cascading, and obtained the optimum rotational speed and diesel oil flow for the rotary kiln incineration operation. The simulation showed that the temperature in the kiln was maintained at 850 °C, and the mass fraction of CO and O₂ at the outlet reached the standard for the complete combustion of the waste. Finally, the rotary kiln incineration and flue gas treatment processes were successfully applied in engineering for green production of pesticides. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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14 pages, 1641 KiB

Open AccessArticle

The Biomass Potential and GHG (Greenhouse Gas) Emissions Mitigation of Straw-Based Biomass Power Plant: A Case Study in Anhui Province, China

by Hui Li, Xue Min, Mingwei Dai and Xinju Dong

Processes 2019, 7(9), 608; https://doi.org/10.3390/pr7090608 - 09 Sep 2019

Cited by 8 | Viewed by 3788

Abstract

Anhui Province (AHP), a typical agriculture-based province in China, has a significant amount of biomass resources for the development of biomass power plants. By the end of 2016, 23 straw based biomass power plants were established in AHP, aggregating to 6560 MW capacity, [...] Read more.

Anhui Province (AHP), a typical agriculture-based province in China, has a significant amount of biomass resources for the development of biomass power plants. By the end of 2016, 23 straw based biomass power plants were established in AHP, aggregating to 6560 MW capacity, which is now ranked second in China. This paper presents the current development status and GHG (Greenhouse Gas) mitigation effect of the straw based biomass power plants in Anhui Province. Total biomass production in 2016 was calculated as 41.84 million tons. Although there is huge biomass potential in AHP, the distribution is heterogeneous with a gradually decreasing trend from north to south. Furthermore, the installed capacity of power generation is also unmatched with the biomass resources. Based on a calculation made in 2016, approximately 3.44 million tons of CO₂-eq were mitigated from the biomass power plants in AHP. The large-scale development of biomass power plants remains a challenge for the future, especially in areas of AHP with a low biomass density. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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15 pages, 2753 KiB

Open AccessArticle

An All-Factors Analysis Approach on Energy Consumption for the Blast Furnace Iron Making Process in Iron and Steel industry

by Biao Lu, Suojin Wang, Kai Tang and Demin Chen

Processes 2019, 7(9), 607; https://doi.org/10.3390/pr7090607 - 08 Sep 2019

Cited by 5 | Viewed by 3558

Abstract

The blast furnace iron making process (BFIMP) is the key of the integrated steel enterprise for energy saving due to its largest energy consumption proportion. In this paper, an all-factors analysis approach on energy consumption was proposed in BFIMP. Firstly, the BFIMP composition [...] Read more.

The blast furnace iron making process (BFIMP) is the key of the integrated steel enterprise for energy saving due to its largest energy consumption proportion. In this paper, an all-factors analysis approach on energy consumption was proposed in BFIMP. Firstly, the BFIMP composition and production data should be collected. Secondly, the material flows and energy flows analysis models could be established based on material balance and the thermal equilibrium. Then, the all influence factors (mainly including material flows, energy flows and operation parameters) on energy consumption were obtained. Thirdly, the main influence factors, which influenced the coke ratio (CR) and the pulverized coal injection ratio (PCIR), were obtained by using the partial correlation analysis (PCA) method, because CR and PCIR were the key energy consumption performance in BFIMP. Furthermore, anall-factors analysis result could be achieved by a multivariate linear model (MLR), which was established through these main influence factors. The case study showed that the PCIR was the most effective parameter on CR; when it was increased by 1% (0.84 kg/t), the CR would reduce by 0.507 kg/t. Therefore, the increase in PCIR consumption is the key measure to realize energy saving for BFIMP. The results showed that the improvement of some material flows, energy flows and operation parameters could increase the amount of PCIR, such as sinter size, ore grade, sinter grade, M10, blast volume, blast temperature and especially for sinter alkalinity. Moreover, theall-factors analysis approach on energy consumption can widely be used in various BFIMPs, too. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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21 pages, 1261 KiB

Open AccessArticle

Multiple Scenarios Forecast of Electric Power Substitution Potential in China: From Perspective of Green and Sustainable Development

by Jing Wu, Zhongfu Tan, Gejirifu De, Lei Pu, Keke Wang, Qingkun Tan and Liwei Ju

Processes 2019, 7(9), 584; https://doi.org/10.3390/pr7090584 - 02 Sep 2019

Cited by 12 | Viewed by 2330

Abstract

To achieve sustainable social development, the Chinese government conducts electric power substitution strategy as a green move. Traditional fuels such as coal and oil could be replaced by electric power to achieve fundamental transformation of energy consumption structure. In order to forecast and [...] Read more.

To achieve sustainable social development, the Chinese government conducts electric power substitution strategy as a green move. Traditional fuels such as coal and oil could be replaced by electric power to achieve fundamental transformation of energy consumption structure. In order to forecast and analyze the developing potential of electric power substitution, a forecasting model based on a correlation test, the cuckoo search optimization (CSO) algorithm and extreme learning machine (ELM) method is constructed. Besides, China’s present situation of electric power substitution is analyzed as well and important influencing factors are selected and transmitted to the CSO-ELM model to carry out the fitting analysis. The results showed that the CSO-ELM model has great forecasting accuracy. Finally, combining with the cost, policy supports, subsidy mechanism and China’s power consumption data in the past 21 years, four forecasting scenarios are designed and the forecasting results of 2019–2030 are calculated, respectively. Results under multiple scenarios may give suggestions for future sustainable development. Full article

(This article belongs to the Special Issue Green Technologies for Production Processes)

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