• Energy Research
• other engineering and technologies close
• US close
• GB close
• IT close

A mathematical model of the LiAl/LiCl, KCl/FeS cell has been used to study the behavior of the system during relaxation and charging. The effects of state of charge, cell temperature, and current density are presented, and the influence of a period of relaxation on the subsequent charging operation is investigated. In addition, factors that can have a significant impact on the charging characteristics are identified.

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.

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.

UV/visible light is a promising radiation source for biomass pretreatment, but very little knowledge is available on the effect of UV on the thermal behavior of lignocellulose in comparison with more classical, physical pretreatment methods. In this paper, we investigate the effects of ball-milling and UV irradiation on two species of softwood and two species of hardwood, using X-ray diffractometry (XRD), evolved gas analysis-mass spectrometry (EGA-MS), and pyrolysis-gas chromatography coupled to mass spectrometry (Py-GC/MS). The XRD data showed that the crystalline fraction of cellulose was destroyed by milling, but not by irradiation. The EGA-MS data and isoconversional kinetic analysis showed that both milling and irradiation can reduce the thermal stability of wood up to a limit value. The Py-GC/MS data showed that irradiation caused the most significant changes in the pyrolytic behavior of the wood species, increasing the ratio of holocellulose to lignin pyrolysis products and the reactivity of cellulose toward the derivatizing agent. Softwoods were more affected by irradiation than hardwoods. This paper shows that UV irradiation can decrease the recalcitrance of biomass toward pyrolysis, but its efficiency is highly dependent on the type of lignocellulosic substrate.

The wind power forecasting error restricts the benefit of the wind farm in the electricity market. Considering the cooperation of wind power bidding and energy storage system (ESS) operation with uncertainty, this paper proposes a coordinated bidding/operation model for the wind farm to improve its benefits in the electricity market. The maximum entropy based deep reinforcement learning (RL) algorithm, Soft Actor-Critic (SAC) is used to construct the model. The maximum entropy framework enables the designed agent to explore various optimal possibilities, which means the learned coordinated bidding/operation strategy is more stable considering the forecasting error. Particularly, penalty terms are introduced into the benefit function to relax the constraints and improve the convergency. The case study illustrates that the learned policy can effectively improve the wind farm benefit while ensuring robustness.

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.