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The efficiency of the emission trading system (ETS) may help to control the total emission amount. The purpose of this paper is to investigate the generating cost issue in environmental/economic power dispatch, under the premise that the ETS has already been established.

The emission benefit and price level factors are introduced for transforming the bi‐objective optimization problem with the fuel cost and emission cost minimization into a single objective. In the developed mathematical model, both the total emission amount from all units and the permitted emission amount from each generating unit are taken into account. The successive linear programming method is employed to solve the optimization problem.

Simulation results of the IEEE 30‐bus test system show that a proper trading mechanism of emission permits is very important for generation companies to control the total emission amount and to reduce the overall generation cost.

Further research is needed to find out the impact on the generating cost caused by trading price fluctuation and the coping strategies.

The results can help to meet the requirements of current generating optimal dispatch.

A transmission tower usually experiences bolt loosening under long-term alternating cyclic load, which may lead to collapse of the tower in extreme operating conditions. The paper aims to propose a data-driven identification method for bolt looseness of complicated tower structures based on reduced-order models and numerical simulations to perceive and evaluate the health state of a tower in operation.

The equivalent stiffnesses of three types of bolt joints under various loosening scenarios are numerically determined by three-dimensional finite element (FE) simulations. The order of the FE model of a tower structure with bolt loosening is reduced by means of the component modal synthesis method, and the dynamic responses of the reducer-order model under calibration loads are simulated and used to create the dataset. An identification model for bolt looseness of the tower structure based on convolutional neural networks driven by the acceleration sensors is constructed.

An identification model for bolt looseness of the tower structure based on convolutional neural networks driven by the acceleration sensors is constructed and the applicability of the model is investigated. It is shown that the proposed method has a high identification accuracy and strong robustness to data noise and data missing. Meanwhile, the method is less dependent on the number and location of sensors and is easier to apply in real transmission lines.

This paper proposes a data-driven identification method for bolt looseness of a complicated tower structure based on reduced-order models and numerical simulations. Non-linear relationships between equivalent stiffness of bolted joints and bolt preload depicting looseness are obtained and reduced-order model of tower structure with bolt looseness is established. Finally, this paper investigates applicability of identification model for bolt looseness.

This paper aims to present a survey concerning the accuracy of thermoplastic polymeric parts fabricated by additive manufacturing (AM). Based on the scientific literature, the aim is to provide an updated map of trends and gaps in this relevant research field. Several technologies and investigation methods are examined, thus giving an overview and analysis of the growing body of research.

Permutations of keywords, which concern materials, technologies and the accuracy of thermoplastic polymeric parts fabricated by AM, are used for a systematic search in peer-review databases. The selected articles are screened and ranked to identify those that are more relevant. A bibliometric analysis is performed based on investigated materials and applied technologies of published papers. Finally, each paper is categorised and discussed by considering the implemented research methods.

The interest in the accuracy of additively manufactured thermoplastics is increasing. The principal sources of inaccuracies are those shrinkages occurring during part solidification. The analysis of the research methods shows a predominance of empirical approaches. Due to the experimental context, those achievements have consequently limited applicability. Analytical and numerical models, which generally require huge computational costs when applied to complex products, are also numerous and are investigated in detail. Several articles deal with artificial intelligence tools and are gaining more and more attention.

The cross-technology survey on the accuracy issue highlights the common critical aspects of thermoplastics transformed by AM. An updated map of the recent research literature is achieved. The analysis shows the advantages and limitations of different research methods in this field, providing an overview of research trends and gaps.