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Short-term generation scheduling is an important function in daily operational planning of power systems. It is defined as optimal scheduling of power generators over a scheduling period while respecting various generator constraints and system constraints. Objective of the problem includes costs associated with energy production, start-up cost and shut-down cost along with profits. The resulting problem is a large scale nonlinear mixed-integer optimization problem for which there is no exact solution technique available. The solution to the problem can be obtained only by complete enumeration, often at the cost of a prohibitively computation time requirement for realistic power systems. This paper presents a hybrid algorithm which combines Lagrangian Relaxation (LR) together with Evolutionary Algorithm (EA) to solve the problem in cooperative and competitive energy environments. Simulation studies were carried out on different systems containing various numbers of units. The outcomes from different algorithms are compared with that from the proposed hybrid algorithm and the advantages of the proposed algorithm are briefly discussed.

Inert gas is often used in the deoxygenation of microbial electrolysis cells (MECs) to maintain growth and viability of anaerobes. However, the effects of the gas atmosphere on hydrogen production and microbial community of MECs are often neglected. Here, the performances and biofilm microbiomes of MECs pre-sparged with different gases were compared. MECs pre-sparged with argon gas (Ar) yielded more hydrogen (3.73 ± 0.13 mol-H2/mol-acetate) and a higher hydrogen production rate (2.99 ± 0.17 L-H2/L-reactor-day) than MECs pre-sparged with N2 (3.41 ± 0.13 mol-H2/mol-acetate and 2.27 ± 0.28 L-H2/L-reactor-day, respectively). Microbiome analysis indicated that the relative abundance of Geobacter increased from 59.25% to 77.79% when the gas atmosphere in MECs shifted from N2 to Ar. Hydrogen production may have been catalyzed by nitrogenase from Geobacter and photosynthetic bacteria in MECs pre-sparged with Ar. These findings suggested that the gas atmosphere substantially influences the microbiome of anode biofilms and Ar sparging is most effective for enhancing hydrogen production in MECs.

Abstract In this study, we develop indices for the overall technical efficiency (OTE) and energy-saving target ratio (ESTR) using data envelopment analysis (DEA) to calculate the relative efficiency and energy-saving potential of 30 provinces in China from 1997 to 2014. The results are as follows: (1) the OTE of China is 79.187%, indicating that there is 20.813% potential for improvement. The OTE exhibits decreasing efficiency values from the coastal areas to the inland areas and has clear geographical relationships. The average values of OTE in the east, midland and west are 0.932, 0.694 and 0.703. Theoretically, the total energy savings of CE, HE, ME and BE are 11080.60PJ, 5124.71PJ, 4729.24PJ and 6797.39PJ. (2) Regarding CE, HE, ME and BE, the provinces with the highest comprehensive ranks are Henan, Shanxi, Shaanxi, and Gansu, which simultaneously have the greatest energy-saving potentials and energy-saving targets. (3) The HE has the largest average ESTR of 38.357% and the values for BE, CE, and ME are 25.759%, 23.874%, and 22.143%, respectively. The CE category is the greatest in total energy savings (40.171%), which is followed by BE (24.150%), HE (18.384%), and ME (17.293%).

Abstract Transportation de-carbonization is a complex problem involving the economy, population, technology and environment. Implementing the pathway simulation based on systematic methods will help to optimize the transportation sustainability plan. This study’s key motivation is that earlier research ignored the relationship between driving factors and the transmission process. To quantitatively identify the path and process of emission reduction, a hybrid system dynamics STIRPAT-SD model is proposed to explore the transportation optimization’s de-carbonization ability. This study fully considers the composition of elements and subsystems based on the STIRPAT theoretical model and visually shows the system’s feedback relationship. Transportation structural and technical optimization scenarios are set to identify the threshold reduction paths. It is found these optimization strategies have significant de-carbonization effects. And transportation structure policy has the highest de-carbonization efficiency, the emission intensity decreased by 9.1% under the TSS2 scenario (Transportation structure scenario). This study proposes a novelty model combining dynamic simulating processes with a significantly theoretical model to improve simulation and factor composition accuracy. And the joint scenario setting identifies the most effective de-carbonization pathway and clarifies the threshold of all possible pathways. Research findings can effectively track, test, predict the achievement of policy goals, and provide policy optimization references for the sustainable development related to the transportation system in practice.

China is the largest fruit producer and consumer market in the world. Understanding the growing conditions responses to climate change is the key to predict future site suitability of main cultivation areas for certain deciduous fruit trees. In this study, we used dynamic and growing degree day models driven by downscaled daily temperatures from 22 global climate models to project the effects of climate change on growing conditions for deciduous fruit trees under two representative concentration pathway (RCP) 4.5 and RCP8.5 scenarios over 2 future time periods (represented by central years 2050s and 2085s) in northern China. The results showed a general increase of available winter chill for all sites under RCP4.5 scenario, and the most dramatic increase in chill accumulation could reach up to 36.8% in northeast regions for RCP8.5. However, the forecasted chill will decrease by 6.4% in southeast stations under RCP8.5 by 2085s. Additionally, the increase rate of growing season heat showed spatially consistency, and the most pronounced increase was found in the RCP8.5 by 2085s. For the southwest station, median heat accumulation increased by 20.8% in the 2050s and 37.1% in the 2085s under RCP8.5. Similar increasing range could be found in the northeast station; the median growing season heat increased by 19.8% and 38.8% in the 2050s and 2085s under RCP8.5, respectively. Moreover, the date of last spring frost was expected to advance and the frequency of frost occurrences was projected to decline in the study area compared to the past. Overall, the present study improves understanding regarding site-specific characteristics of climatic suitability for deciduous fruit tree cultivation in main producing regions of northern China. The results could provide growers and decision-makers with theoretical evidence to take adaptive measure to ensure fruit production in future.

Purpose This study aims to consider environmental sustainability, a global challenge under the preview of sustainable development goals, highlighting the significance of knowledge economy in attaining sustainable aggregate demand behavior globally. For this purpose, 155 countries that have data available from 1995 to 2021 were selected. The purpose of selecting these countries is to test the global responsibility of the knowledge economy to attain environmental sustainability. Design/methodology/approach Results are estimated with the help of panel quantile regression. The empirical existence of aggregate demand-based environmental Kuznets curve (EKC) was tested using non-linear tests. Moreover, principal component analysis has been incorporated to construct the knowledge economy index. Findings U-shaped aggregate demand-based EKC at global level is validated. However, environmental deterioration increases with an additional escalation after US$497.945m in aggregate demand. As a determinant, the knowledge economy is reducing CO2 emissions. The knowledge economy has played a significant role in global responsibility, shifting the EKC downward and extending the CO2 reduction phase for every selected country. Further, urbanization, energy intensity, financial development and trade openness significantly deteriorate the environmental quality. Originality/value This study contains the empirical existence of aggregate demand-based EKC. The role of the knowledge economy is examined through an index which is calculated by using four pillars of the knowledge economy (technology, innovations, education and institutions). This study is based on a combined panel of all the countries for which the data was available.

The division of return stroke current among the arresters and groundings of two unenergized test distribution lines, one horizontally configured and the other vertically configured, was studied at the International Center for Lightning Research and Testing in Florida. The division of return stroke currents for the vertically configured line was initially similar to the division on the horizontally configured line: at the time the return stroke current reached peak value (after one microsecond, or so) the two closest arresters/grounds on both lines passed about 90% of the total current. However, the time during which the return stroke current flowed primarily through the closest arresters to the neutral conductor was significantly shorter on the vertically configured line. On that line, the arrester current was about equally divided among all four arresters after several tens of microseconds. The arrester current division as a function of time measured on the vertical line was successfully modeled using the published VI-characteristic, while the division on the horizontal line after some tens of microseconds was only successfully modeled if the residual voltage of the two arresters closest to the current injection point was reduced by 20%. Based on the triggered lightning current division observed on our line, the minimum energy absorbed in each of the two arresters closest to the strike point during a typical natural first stroke is estimated to be 40 kJ.

AbstractIf the energy‐density of prey bodies is not uniform, predators usually should maximize their rate of energy intake while foraging by selectively consuming energy‐rich regions of their prey and discarding other parts. In this study, the hypothesis of selective body‐part consumption was tested using two species of dasyurid marsupials, Sminthopsis youngsoni and Ningaui ridei, and their invertebrate prey in arid central Australia. Energy‐densities were similar for several divergent types of prey, including whole insects, centipedes, and spiders (20.2 ± 2.19 (sd) J/mg ash‐free dry mass), but there were marked differences in energy‐density among orders of insects and also between different body regions of invertebrates. In captivity, the two dasyurid species consumed different body regions of prey in the same way. For beetles and cockroaches, the rank order for selection of body parts was abdomen, thorax, head, then legs; for centipedes it was body, then head + legs; and for spiders it was opisthosoma, prosoma and then legs. Selection of prey body regions by the marsupials correlated closely with the energy‐densities of these regions, and also with the rates of energy intake that they yielded. In the field, selection of body parts of arthropod prey by dasyurids probably occurs primarily when prey is abundant. This selection should allow maximization of rates of energy intake in favourable periods and should, in turn, allow dasyurid predators to effectively exploit pulses of prey resources in the temporally variable desert environment.

An energy-saving ethanol fermentation technology was developed using uncooked fresh sweet potato as raw material. A mutant strain of Aspergillus niger isolated from mildewed sweet potato was used to produce abundant raw starch saccharification enzymes for treating uncooked sweet potato storage roots. The viscosity of the fermentation paste of uncooked sweet potato roots was lower than that of the cooked roots. The ethanol fermentation was carried out by Zymomonas mobilis, and 14.4 g of ethanol (87.2% of the theoretical yield) was produced from 100g of fresh sweet potato storage roots. Based on this method, an energy-saving, high efficient and environment-friendly technology can be developed for large-scale production of fuel ethanol from sweet potato roots.