Strategic distribution network planning with smart grid technologies

This paper presents a multiyear distribution network planning optimization model for managing the operation and capacity of distribution systems with significant penetration of distributed generation (DG). The model considers investment in both traditional network and smart grid technologies, including dynamic line rating, quadrature-booster, and active network management, while optimizing the settings of network control devices and, if necessary, the curtailment of DG output taking into account its network access arrangement (firm or non-firm). A set of studies on a 33 kV real distribution network in the U.K. has been carried out to test the model. The main objective of the studies is to evaluate and compare the performance of different investment approaches, i.e., incremental and strategic investment. The studies also demonstrate the ability of the model to determine the optimal DG connection points to reduce the overall system cost. The results of the studies are discussed in this paper

GIS-based decision support systems to minimise soil impacts in logging operations

Mechanised logging operations can leave negative impacts, like ruts, on forest soils. To avoid this, forestry planners and machine operators need decision support systems that can estimate soil trafficability and help to minimise soil impacts. The main objective of this thesis was to evaluate whether or how different data, stored in a geographic information system (GIS), can contribute to improved estimation of soil trafficability. Requirements for implementation of soil trafficability maps in forestry GIS applications were also described. A soil trafficability map, based on several GIS data using multi-criteria decision analysis (MCDA), was proposed in Paper I. Availability and implementation of soil trafficability maps, mainly depth-to-water (DTW) maps, in some European countries, was reviewed in Paper II. Effect of DTW map resolutions to predict soil moisture was evaluated in Paper IV, and the study showed that a spatial resolution of 1–2 m was sufficient. Risk for rutting was analysed in relation to field-measured and GIS data in Papers III, V and VI. GIS data included digital elevation models, DTW maps, hydrological data, soil type, and clay content maps. The results showed that planning forwarder trails and evaluating different alternatives can be improved by using a soil trafficability map. GIS data of high quality is required to achieve acceptable results. Easy or free access to soil trafficability maps facilitate their application in forestry operations. DTW maps, together with other data, can be used to estimate risk for rutting. Clay content maps and hydrological data, at current resolution, need further development but showed potential to predict risk for rutting. More studies are required to estimate temporal and spatial variability of soil trafficability maps. In conclusion, GIS-based decision support systems should be used for planning of logging operations to minimise risk for rutting

Electroflotation for Treatment of Paint Wastewater: Experiments, Kinetics and Hydrodynamics

Electroflotation (EF) is a process used to remove suspended particles from water using the gas bubbles generated from the water electrolysis. This dissertation focuses on the fundamental principles and applications of EF in the treatment of industrial wastewaters, and in particular, treatment of automotive paint wastewater. In the first part, an extensive review of applications of electroflotation in the treatment of different categories of industrial wastewaters, including the fundamentals of the process, electrode materials, design aspects and process variables, is conducted. The second part is focusing on the kinetic study, statistical analysis and empirical modeling of available experimental data from batch tests of electroflotation treatment of auto paint wastewater. The kinetics of the TSS (Total Suspended Solids) removal was best described with the second-order rate constants. It was confirmed, statistically, that the initial TSS concentration and Current Density were the most significant process variables. Further, empirical equations of the treatment efficiency were produced. In the third part, an experimental program was carried out in a pilot-scale continuous-flow electroflotation reactor on electroflotation treatment of paint wastewater. The total suspended solids removal was investigated as functions of operational parameters, including the hydraulic retention time (HRT), current density and influent total solids (TS) concentration. The maximum TSS removal rate achieved in the experiments was 95%. It was found that the TSS and turbidity removal rates decrease with the increase of influent TS concentration and are directly related to the applied current density and HRT. The electroflotation system showed to be energy-efficient compared to the commercial systems. In the fourth part of this study, by performing the tracer tests, the hydrodynamics and flow characteristics of the electroflotation reactor were investigated. The experiments were conducted at the various HRTs and under the electric current ON/OFF modes. Because of the presence of stagnant regions in the reactor, the calculated residence times were lower than the theoretical HRTs. It was recommended that by selecting a shorter HRT, better flow characteristics can be achieved. Also, the EF gas bubbles, hydrodynamically, showed to improve the treatment efficiency of the EF reactor

Landmark Attention: Random-Access Infinite Context Length for Transformers

While Transformers have shown remarkable success in natural language processing, their attention mechanism's large memory requirements have limited their ability to handle longer contexts. Prior approaches, such as recurrent memory or retrieval-based augmentation, have either compromised the random-access flexibility of attention (i.e., the capability to select any token in the entire context) or relied on separate mechanisms for relevant context retrieval, which may not be compatible with the model's attention. In this paper, we present a novel approach that allows access to the complete context while retaining random-access flexibility, closely resembling running attention on the entire context. Our method uses a landmark token to represent each block of the input and trains the attention to use it for selecting relevant blocks, enabling retrieval of blocks directly through the attention mechanism instead of by relying on a separate mechanism. Our approach seamlessly integrates with specialized data structures and the system's memory hierarchy, enabling processing of arbitrarily long context lengths. We demonstrate that our method can obtain comparable performance with Transformer-XL while significantly reducing the number of retrieved tokens in each step. Finally, we show that fine-tuning LLaMA 7B with our method successfully extends its context length capacity to over 32k tokens, allowing for inference at the context lengths of GPT-4. We release the implementation of landmark attention and the code to reproduce our experiments at https://github.com/epfml/landmark-attention/.Comment: Published as a conference paper at NeurIPS 2023 - 37th Conference on Neural Information Processing System

Comparative Overview on LCA Software Programs for Application in the Façade Design Process

Façades impact the environmental performance of a building by their passive contribution to operational energy demand and by embodied energy and emissions during each life cycle phase. LCA is a method widely used to quantify the environmental contribution. The use of LCA software programs in façade planning can guide design decisions and contribute to environmental optimisation. A large amount of LCA software programs have been developed so far, all of which differ in their focus and requirements. This paper aims to address these differences and investigate the capability and suitability of these programs for façade design. It is structured in four sections. The first part introduces LCA in the building and façade design context. The second part introduces categories to understand the different capabilities of LCA software products. Hereafter, eleven products are evaluated based on these categories. The fourth part focuses on the suitability of software products for simple or complex façades. The study concludes that there are different software choices available for almost every level of user knowledge. While Gabi, Simapro, and Umberto require users to work to a high level of proficiency, software programs like eLCA, CAALA, and 360 Optimi do not require much user knowledge over LCA, but provide a range of other opportunities