Identification of Key Influencing Factors of Sustainable Development for Traditional Power Generation Groups in a Market by Applying an Extended MCDM Model

With the deepening reform of the power market, the external environment of China’s power industry is going through a huge change. China’s traditional power generation groups (TPGGs), with assets all over the country, are, due to a lack of market awareness about energy policies, facing serious challenges in developing competitive advantages, improving power transaction modes, optimizing profit models, and even realizing basic corporate strategies. In this study, we focus on identifying the key factors influencing sustainable development in an unprecedented market environment for TPGGs, so as to achieve overall sustainable development for the whole power generation sector in China. A hybrid framework based on Multiple-Criteria Decision-Making (MCDM) was proposed to recognize the key influencing factors under vague rule conditions. We developed a novel method combining three different MCDM methods with triangular fuzzy numbers (TFNs), fuzzy Delphi, fuzzy Decision-Making Trial and Evaluation Laboratory (DEMATEL), and Analytic Network Process (ANP), to cover uncertainty and make the problem-solving approach closer to the actual problem. A series of analyses indicate that the final 14 factors covering the five dimensions are considered to be important factors in the sustainable development of TPGGs. Based on the results, it can be said that “Gross energy margin„ and “Pricing bidding strategy„ dominate the impacts of TPGG’s sustainable development. Finally, we give some advice relating to practical measures to help TPGGs achieve sustainable development in the market-oriented industry environment

Tensile monotonic capacity of helical anchors in sand: interaction between helices

This note examines the interaction between the helices of a multi-helix anchor in terms of the mobilized drained capacity response in tension. Assessments are made on the basis of centrifuge tests in dense silica sand, supplemented with data from existing studies. The centrifuge tests were designed to isolate potential anchor installation effects from those due to the interactions between helices. The data show that additional helices will only contribute to anchor capacity if they are located outside the region of soil mobilized in the failure mechanism of the lower helices. In the dense sand considered in these centrifuge tests, this required helices to be separated by greater than nine diameters, and hence for the lowermost helix to be located at a depth greater than nine diameters. This separation distance is much higher than suggested in previous studies, which tended to attribute the low or nil contribution of additional helices to the soil disturbance generated during anchor installation.The accepted manuscript in pdf format is listed with the files at the bottom of this page. The presentation of the authors' names and (or) special characters in the title of the manuscript may differ slightly between what is listed on this page and what is listed in the pdf file of the accepted manuscript; that in the pdf file of the accepted manuscript is what was submitted by the author

Spatial Distribution, Contamination Assessment and Origin of Soil Heavy Metals in the Danjiangkou Reservoir, China

Soil heavy metal contamination is crucial due to menacing food safety and mortal health. At present, with the fast advancement of urbanization and industrialization, heavy metals are increasingly released into the soil by anthropogenic activities, and the soil ecosystem contamination around the Danjiangkou Reservoir is directly associated with water quality security of the reservoir. In this paper, using 639 soil samples from the Danjiangkou Reservoir, Henan Province, China, we studied a variety of space distribution characteristics of heavy metals in soil. Geographic information system analysis (GIS), geo-accumulation index (Igeo), contamination factor (CF), principal component analysis (PCA) model, and positive matrix factorization (PMF) model were used together to recognize and quantify the distribution, contamination, and origin of heavy metals. We uncovered an exceptional variety of heavy metal concentrations among the tested soils: the mean arsenic (As), cadmium (Cd), cobalt (Co), chromium (Cr), manganese (Mn), nickel (Ni), zinc (Zn), lead (Pb) and mercury (Hg) concentrations (14.54, 0.21, 18.69, 81.69, 898.42, 39.37, 79.50, 28.11, 0.04 mg/kg, respectively, in the topsoil (0–20 cm depth)), all exceed their background values. The mean Igeo value and CF values of these trace elements are both in descending order: Cd > Co > Mn > Ni > Pb > Zn > Cr > As > Hg. Cd was the highest contributor to the assessment of heavy metal pollution, with an average Igeo value over three, indicating that the study area is modestly contaminated by Cd. The PCA analysis and PMF model revealed three potential sources, including natural sources (PC1) for Cr, Co, Mn and Ni; agricultural sources (PC2) for Cd, Zn and Hg; and industrial emissions and transportation sources (PC3) for Pb. This study displays a map of heavy metal contamination in the eastern area topsoil of the Danjiangkou Reservoir, showing the most severe pollutant is Cd, which poses a threat to the water quality security of Danjiangkou Reservoir and provides a significant source identification for future contamination control

Composite Terminal Guidance Law for Supercavitating Torpedoes with Impact Angle Constraints

A novel composite terminal guidance law with impact angle constraints is proposed for supercavitating torpedoes to intercept maneuvering warships. Based on an adaptive super-twisting algorithm and nonsingular terminal sliding mode (NTSM), the proposed guidance law can guarantee the finite-time convergence of line-of-sight (LOS) angle error and the LOS angular rate error. The new guidance law is a combination of finite-time stability theory, sliding mode control (SMC), tracking differentiator (TD), disturbance observer (DO), and dynamic surface control. A high-order sliding mode TD is used for denoising, tracking, and differentiating the measured target heading angle. A novel DO, with its finite-time stability proved, is designed to estimate the target lateral acceleration for feedforward compensation to attenuate chattering in control input. In the case of a first-order-lag autopilot, a new kind of tracking differentiator is adopted to compute the first-order time derivative of the virtual control command, which can improve the accuracy of dynamic surface control and avoid the “explosion of items” problem encountered with the backstepping control. Finally, numerical simulation results are presented to validate the effectiveness and superiority of the proposed TD, DO, and the composite guidance law

Enhancement of aromatics production from catalytic co-pyrolysis of walnut shell and LDPE via a two-step approach

A two-step catalytic co-pyrolysis (TSCCP) of walnut shell (WNS) and low-density polyethylene (LDPE) was innovatively studied at a lab-scale fixed-bed reactor using HZSM-5 as a catalyst. Various characterization techniques such as FTIR, Raman spectroscopy, SEM, thermal gravimetric analysis (TGA) and Van Krevelen diagram were applied to explore structure evolutions of the derived chars aiming at revealing the step-wise copyrolysis mechanisms. In comparison with conventional one-step catalytic co-pyrolysis (OSCCP), the TSCCP has much higher oil production, and less gas and solid yields. The yield of aromatics increased by 34.2 %. Oxygenated compounds in oil were dramatically reduced. As a result, more water was generated. These experimental results have demonstrated that the two-step approach can significantly enhance the synergy of WNS with LDPE. Characterizations revealed that the TSCCP stages the interactions of cellulose, hemicellulose and lignin with LDPE. The interaction of lignin with LDPE was thoroughly examined. Possible mechanisms were put forward to explain the synergistic effects of WNS with LDPE enhanced by the two-step approach

Energy Trading Strategy of Distributed Energy Resources Aggregator in Day-Ahead Market Considering Risk Preference Behaviors

Distributed energy resources aggregators (DERAs) are permitted to participate in regional wholesale markets in many counties. At present, new market players such as aggregators participate in China’s power market transactions. However, studies related to market trading strategy have mostly focused on centralized wind power and PV generation units. Few studies have been conducted on the decision-making strategies for DERAs in China’s power market. This paper proposes an auxiliary decision-making model for distributed energy systems to participate in the day-ahead market with more reasonable trading strategies. Firstly, the Gaussian mixture model (GMM) is used to deal with the uncertainties of wind power and photovoltaic (PV) output in the distributed energy system. Secondly, the information gap decision theory (IGDT) is used to deal with the uncertainty of price fluctuations in the spot electricity market. Thirdly, according to the different risk preferences of the DERAs facing market price fluctuation, the robust decision model and opportunity decision-making model in the day-ahead market are constructed, respectively. Finally, to deal with the irrational behavior of the DERAs’ perception of “gain” and “loss” with market risks in China’s two-tier market environment, the prospect theory and the marine predator’s algorithm (MPA) are employed to obtain a day-ahead trading decision scheme for DERA. The analyses show that RDES with robust preference can withstand greater price volatility in the day-ahead market; they will reduce the bidding expectations and increase the system operating cost to improve the achievability of the expected revenue. However, DERAs under the opportunity strategy is more inclined to sell electricity to the market and offset system operating costs with revenue. The proposed model can provide strategic reference for DERAs with different risk preferences to bid in day-ahead market and can improve the level of aggregators’ participation in electricity trading

Energy Trading Strategy of Distributed Energy Resources Aggregator in Day-Ahead Market Considering Risk Preference Behaviors

Distributed energy resources aggregators (DERAs) are permitted to participate in regional wholesale markets in many counties. At present, new market players such as aggregators participate in China’s power market transactions. However, studies related to market trading strategy have mostly focused on centralized wind power and PV generation units. Few studies have been conducted on the decision-making strategies for DERAs in China’s power market. This paper proposes an auxiliary decision-making model for distributed energy systems to participate in the day-ahead market with more reasonable trading strategies. Firstly, the Gaussian mixture model (GMM) is used to deal with the uncertainties of wind power and photovoltaic (PV) output in the distributed energy system. Secondly, the information gap decision theory (IGDT) is used to deal with the uncertainty of price fluctuations in the spot electricity market. Thirdly, according to the different risk preferences of the DERAs facing market price fluctuation, the robust decision model and opportunity decision-making model in the day-ahead market are constructed, respectively. Finally, to deal with the irrational behavior of the DERAs’ perception of “gain” and “loss” with market risks in China’s two-tier market environment, the prospect theory and the marine predator’s algorithm (MPA) are employed to obtain a day-ahead trading decision scheme for DERA. The analyses show that RDES with robust preference can withstand greater price volatility in the day-ahead market; they will reduce the bidding expectations and increase the system operating cost to improve the achievability of the expected revenue. However, DERAs under the opportunity strategy is more inclined to sell electricity to the market and offset system operating costs with revenue. The proposed model can provide strategic reference for DERAs with different risk preferences to bid in day-ahead market and can improve the level of aggregators’ participation in electricity trading

Cloning of Cold-Adapted Dextranase and Preparation of High Degree Polymerization Isomaltooligosaccharide

Intestinal diseases are mainly caused by a decrease in the relative abundance of probiotics and an increase in the number of pathogenic bacteria due to dysbiosis of the intestinal flora. High degree polymerization isomaltooligosaccharide (IMO) can promote probiotic metabolism and proliferation. In this study, the dextranase (PsDex1711) gene of marine bacterial Pseudarthrobacter sp. RN22 was cloned and expressed in Escherichia coli BL21 (DE3). The optimal pH and temperature of the dextranase were 6.0 and 30 °C, respectively, showing the highest stability at 20 °C. The dextran T70 could be hydrolyzed to produce IMO3, IMO4, IMO5, and IMO6 with a high degree of polymerization. The hydrolysate of 1 mg/mL could significantly promote the growth of Lactobacillus and Bifidobacterium after 12 h culture and the formation of biofilms by 58.2%. The hydrolysates could promote the proliferation of probiotics. Furthermore, the IC50 of scavenging rate of DPPH, hydroxyl radical, and superoxide anion was less than 20 mg/mL. This study provides a crucial theoretical basis for the application of dextranase such as pharmaceutical and food industries

Cloning of Cold-Adapted Dextranase and Preparation of High Degree Polymerization Isomaltooligosaccharide

Intestinal diseases are mainly caused by a decrease in the relative abundance of probiotics and an increase in the number of pathogenic bacteria due to dysbiosis of the intestinal flora. High degree polymerization isomaltooligosaccharide (IMO) can promote probiotic metabolism and proliferation. In this study, the dextranase (PsDex1711) gene of marine bacterial Pseudarthrobacter sp. RN22 was cloned and expressed in Escherichia coli BL21 (DE3). The optimal pH and temperature of the dextranase were 6.0 and 30 °C, respectively, showing the highest stability at 20 °C. The dextran T70 could be hydrolyzed to produce IMO3, IMO4, IMO5, and IMO6 with a high degree of polymerization. The hydrolysate of 1 mg/mL could significantly promote the growth of Lactobacillus and Bifidobacterium after 12 h culture and the formation of biofilms by 58.2%. The hydrolysates could promote the proliferation of probiotics. Furthermore, the IC50 of scavenging rate of DPPH, hydroxyl radical, and superoxide anion was less than 20 mg/mL. This study provides a crucial theoretical basis for the application of dextranase such as pharmaceutical and food industries