ALBERT

Description: Horizontal wells can significantly improve the gas production and are expected to be an efficient exploitation method for the industrialization of natural gas hydrates (NGHs) in the future. However, the near-wellbore hydrate is highly prone to decomposition during the drilling process, owing to the disturbance aroused by the factors such as the drilling fluid temperature, pressure, and salinity. These issues can result in the engineering accidents such as bit sticking and wellbore instability, which are required for further investigations. This paper studies the characteristics of drilling fluid invasion into the marine NGH reservoir with varied drilling fluid parameters via numerical simulation. The effects of the drilling fluid parameters on the decomposition behavior of near-wellbore hydrates are presented. The simulating results show that the adjustments of drilling fluid density within the mud safety window have limited effects on the NGH decomposition, meanwhile the hydrates reservoir is most sensitive to the drilling fluid temperature variation. If the drilling fluid temperature grows considerably due to improper control, the range of the hydrates decomposition around the horizontal well tends to expand, which then aggravates wellbore instability. When the drilling fluid salinity varies in the range of 3.5–7.5%, the increase in the ion concentration speeds up the hydrate decomposition, which is adverse to maintaining wellbore stability.

Description: The electric power industry sector has become increasingly aware of how counterproductive voltage sag affects distribution network systems (DNS). The voltage sag backfires disastrously at the demand load side and affects equipment in DNS. To settle the voltage sag issue, this paper achieved its primary purpose to mitigate the voltage sag based on integrating a hydrogen fuel cell (HFC) with the DNS using a distribution static synchronous compensator (D-STATCOM) system. Besides, this paper discusses the challenges and opportunities of D-STATCOM in DNS. In this paper, using HFC is well-designed, modeled, and simulated to mitigate the voltage sag in DNS with a positive impact on the environment and an immediate response to the issue of the injection of voltage. Furthermore, this modeling and controller are particularly suitable in terms of cost-effectiveness as well as reliability based on the adaptive network fuzzy inference system (ANFIS), fuzzy logic system (FLC), and proportional–integral (P-I). The effectiveness of the MATLAB simulation is confirmed by implementing the system and carrying out a DNS connection, obtaining efficiencies over 94.5% at three-phase fault for values of injection voltage in HFC D-STATCOM using a P-I controller. Moreover, the HFC D-STATCOM using FLC proved capable of supporting the network by 97.00%. The HFC D-STATCOM based ANFIS proved capable of supporting the network by 98.00% in the DNS.

Description: Apart from numerous technical challenges, the transition towards a carbon-neutral energy supply is greatly hindered by limited economic feasibility of renewable energy sources. This results in their slow and bounded penetration in both commercial and residential sectors that are responsible for over 40% of final energy consumption. This paper aims to demonstrate that combined application of sophisticated planning methodologies at building-level and presents incentive mechanisms for renewables that can result in prosumers, featuring hybrid renewable energy systems (HRES), with economic performance comparable to that of conventional energy systems. The presented research enhances existing planning methodologies by integrating appliance-level demand side management into the decision process and investigates its effect on the planning problem. Moreover, the proposed methodology features an innovative and holistic approach that simultaneously assess electrical and thermal domain in both an isolated and grid-connected context. The analyzed hybrid system consists of solar photovoltaic, wind turbine and battery with thermal supply featuring solar thermal collector and a ground-source heat pump. Overall optimization problem is modeled as a mixed-integer linear program, while ranking of all feasible alternatives is made by the multicriteria decision-making algorithm against several technological, economic, and environmental criteria. A real-life scenario of energy system retrofit for a building in the United Kingdom was employed to demonstrate overall cost savings of 12% in the present market and regulation context.

Description: In the EU 28, the installed heating appliance stock is quite old, with an actual replacement rate of 4%. This is directly reflected in the average efficiency of the installed heating systems, where around 60% of the stock is rated with an energy class of C or D (the lowest classes of the energy label scale). The European project HARP aims at raising consumers’ awareness of the planned replacement of their old and inefficient heating appliances with more efficient and renewable solutions. In this direction, an energy labeling methodology for old appliances has been developed to rate the installed stock before the introduction of the EU energy label. The methodology has been developed for space heating appliances and water heaters, targeting two types of users: end consumers and professional users. The validation considered about 4600 space heating appliances and 800 water heaters built between 1972 and 2019. Three heating appliances and two water heaters were tested in the laboratory, confirming the reliability of the proposed methodology. The expected impact of defining an energy labeling methodology for installed heating appliances increases the current replacement rate of these appliances in the EU from 4% to 5%.

Description: This work presents a comprehensive theoretical analysis of current-mode power amplifiers as a function of input power for different biasing classes under the common simplifying assumption of constant transconductance and hard current cut-off/saturation. Typically, the theoretical analysis of power amplifier performance and behavior are carried out only at maximum output power. However, to achieve high data-rates, modern telecommunication systems adopt signals characterized by a very high peak-to-average power ratio, thus it is useful to analyze the power amplifier behavior as a function of power back-off. Moreover, in many cases, to enhance the efficiency and/or to apply harmonic shaping techniques, a clipped drain-source current, which approaches a square wave, is required. The classical analysis can be extended to low power levels only under the assumption of power-independent conduction angle, which is true only for class-A and class-B amplifiers, and does not take into account possible waveform clipping at maximum current. This work presents a complete theoretical Fourier analysis of FET-based power amplifiers as a function of quiescent drain-source current at any input power level and accounting for the clipped current case, up to the square-wave limit, reorganizing and completing the material that can be found in classical textbooks in the field.

Description: Contemporary agriculture has become very energy-intensive and mainly uses electricity, which is needed for technological processes on livestock farms. Livestock faeces are burdensome for the environment due to the release of methane into the atmosphere. This article presents the concept of a self-sufficient livestock farm as an off-grid energy circuit that is a part of the agricultural process. The key idea is to obtain an energy flow using the concept of a smart valve to achieve a self-sufficient energy process based on a biogas plant, renewable energy sources, and energy storage. During the production process, a livestock farm produces large amounts of waste in the form of grey and black manure. On the one hand, these products are highly harmful to the environment, but on the other, they are valuable input products for another process, i.e., methane production. The methane becomes the fuel for cogeneration generators that produce heat and electricity. Heat and electricity are partly returned to the main farming process and partly used by residents of the area. In this way, a livestock farm and the inhabitants of a village or town can become energy self-sufficient and independent of national grids. The idea described in this paper shows the process of energy production combining a biogas plant, renewable energy sources, and an energy storage unit that enable farmland to become fully self-sufficient through the energy flow between all constituents of the energy cycle being maintained by a smart valve.

Description: Due to the complex and variable conditions under which wind turbines operate, existing working condition classification methods are inadequate for condition assessment of the main transmission system. Because working conditions are too few after classification, it cannot effectively describe the complex and variable working conditions of wind turbine. This can lead to high false-alarm rates in the condition monitoring, which affect normal operations. This paper proposes a working condition classification method for the main transmission system of wind turbines based on supervisory control and data acquisition (SCADA) data. Firstly, correlation analysis of SCADA data acquired by wind farm is used to select the parameters relevant to the main transmission system. Secondly, according to the wind turbine control principle, the working conditions are initially divided into four phases: shutdown, start-up, maximum wind energy tracking, and constant speed. The k-means clustering algorithm is used to subdivide the maximum wind energy-tracking phase and constant speed phase, which account for a larger proportion of the working conditions, to achieve better classification. Finally, a case study is used to demonstrate the calculation of alarm thresholds and alarm rates for each working condition. The results are compared with the direct use of k-means clustering for working condition classification. It is concluded that the proposed method can significantly reduce the false-alarm rate of the vibration detection process.

Description: Building an effective Machine Learning (ML) model for a data set is a difficult task involving various steps. One of the most important steps is to compare a substantial amount of generated ML models to find the optimal one for deployment. It is challenging to compare such models with a dynamic number of features. Comparison is more than only finding differences of ML model performance, as users are also interested in the relations between features and model performance such as feature importance for ML explanations. This paper proposes RadialNet Chart, a novel visualisation approach, to compare ML models trained with a different number of features of a given data set while revealing implicit dependent relations. In RadialNet Chart, ML models and features are represented by lines and arcs, respectively. These lines are generated effectively using a recursive function. The dependence of ML models with a dynamic number of features is encoded into the structure of visualisation, where ML models and their dependent features are directly revealed from related line connections. ML model performance information is encoded with colour and line width in RadialNet Chart. Taken together with the structure of visualisation, feature importance can be directly discerned in RadialNet Chart for ML explanations. Compared with other commonly used visualisation approaches, RadialNet Chart can help to simplify the ML model comparison process with different benefits such as the following: more efficient in terms of helping users to focus their attention to find visual elements of interest and easier to compare ML performance to find optimal ML model and discern important features visually and directly instead of through complex algorithmic calculations for ML explanations.

Description: The radiation flux distributions produced by the concentrating solar systems used to produce thermal/electrical power are usually non-homogeneous. This results in non-uniform temperature distributions on the solar receivers, causing adverse effects on the system’s overall performance. An approach to better understand the problem is to study the surfaces around the focal zone where the radiation density is homogeneous (isosurfaces), generating them from experimental data. For this, it is necessary to superimpose built volumes of the different irradiance levels using parallel planes in different directions from the focal point of a concentrator. These volumes are known as effective volumes. This study presents the model used to generate effective volume produced by a point focus concentrator, comparing it with experimental results in a direction perpendicular to the focal axis. The effective volumes were developed considering a global optical error of the system of 2.8 mrad. The set of methods used to generate effective volumes has not been previously presented in the literature. The theoretical-experimental research consisted of the combination of the camera-target method and the simulations by the ray-tracing technique. The results showed effective volumes with the highest value of 10 MW/m2 and the lowest value of 4.5 MW/m2.

Description: The main purpose of this study is to identify the drivers of sustainable performance in firms that operate in the energy sector. Under the assumption of bidirectional impacts, we empirically tested the trade-offs between sustainable and financial performance, in light of neoclassical theory, the natural-resources-based view, and instrumental stakeholder theory. We hypothesize that, in the energy sector, sustainable performance is positively associated with firms’ financial performance and that sustainability reporting is an important driver of sustainable performance. We add primarily by considering the relevance of sustainability-policy-oriented factors and revising the role of sustainability reporting within. We provide empirical evidence based on a large panel of firm-year observations within the 2013–2020 time span, for firms that operate in the energy sector and are located in Europe. We have found strong support for the positive link between sustainable performance (proxied with ESG score) and returns, which conforms to the assumptions of the natural-resources-based view. However, we have also found some evidence that more sustainable firms face greater costs input, which is considered in neoclassical theory. We have also confirmed no relevance of the slack-resources-based view. Finally, we found sustainability reporting to be the most influential among the set of sustainability-policy-oriented factors. This evidence demonstrates that stakeholders’ pressure on firms’ transparency could be an important driver of sustainable performance in the energy sector.