The development and utilization of wave energy is inseparable from the wave energy converter, and its stability is an important condition for operation. Heave is the biggest factor affecting the stable power generation of wave energy converters. The key method to solve this problem is to install a suitable heave plate. Therefore, the design of the heave plate is particularly important. Based on a new type of horizontal rotor wave energy converter, this paper proposes three different shapes of heave plate design schemes and completes the calculation and modeling of the engineering prototype. First, the three types of heave plate devices were numerically simulated using hydrodynamic calculation software to compare their stable performances and verify the feasibility of the scheme. Subsequently, an experimental model was made according to the parameters of the engineering prototype, and a tank experiment was carried out under the same working conditions to further study the influence of t... [more]

In recent years, the penetration of photovoltaic (PV) power generation in Taiwan has increased significantly. However, most photovoltaic facilities, especially for small-scale sites, do not include relevant monitoring and real-time measurement devices. The invisible power generation from these PV sites would cause a huge challenge on power system scheduling. Therefore, appropriate methods to estimate invisible PV power generation are needed. The main purpose of this paper is to propose an improved fuzzy model for estimating the PV power generation, which includes the clustering processing for PV sites, selection of representative PV sites, and the improvement of the conventional fuzzy model. First, this research uses the K-nearest neighbor (KNN) algorithm to fill in some of the missing data; then, two clustering algorithms are applied to cluster all the photovoltaic sites. Next, the relationship between the power generation of a single PV site and the total generation of all sites at t... [more]

Cittaslow is a network of small cities which have adopted the assumptions of the “slow city” model and strive towards the improvement of the quality of life for their residents. This is a network of cities which put pro-social and pro-environmental measures in the first place, while ensuring that the unique character of every city is preserved. A city which wishes to join the Cittaslow network must go through the so-called certification process and satisfy a number of criteria classified in seven macro-areas, including the “energy and environmental policy” area. Significantly, after becoming a member of the network, the city is obligated to carry out activities that will enable it to meet the membership criteria to a higher degree, and in particular to satisfy the criteria it has previously failed to meet. Considering the above, the aim of this study has been to evaluate the activities initiated and implemented by the member cities of the Polish Cittaslow network in the sphere of the “... [more]

Hydrothermal liquefaction (HTL) uses heat and pressure to liquefy the organic matter in biomass/waste feedstocks to produce biocrude. When hydrotreated the biocrude is converted into transportation fuels including sustainable aviation fuel (SAF). Further, by liquifying the organic matter in wet wastes such as sewage sludge, manure, and food waste, HTL can prevent landfilling or other disposal methods such as anerobic digestion, or incineration. A significant roadblock to the development of a new route for SAF is the strict approval process, and the large volumes required (>400 L) for testing. Tier α and β testing can predict some of the properties required for ASTM testing with <400 mL samples. The current study is the first to investigate the potential for utilizing wet-waste HTL biocrude (WWHTLB) as an SAF feedstock. Herein, several WWHTLB samples were produced from food waste, sewage sludge, and fats, oils, and grease, and subsequently hydrotreated and distilled to produce SAF sa... [more]

Freezing construction in saline stratum under the action of groundwater is typical. To study the coupling effect of the groundwater velocity and salinity on the freezing in saline stratum, the freezing temperature of saline sand with different salinities was obtained through experiments. A controllable velocity double-pipe freezing physical model test system for saline sand was established. The temperature distribution in saturated saline sand under different salinities and velocities were studied. The test results showed that the temporal and spatial evolutions of the temperature field were affected by the velocity and salinity. Under the same boundary temperature, the higher the salinity, the lower the temperature at the measuring point on the main surface and interface. The overlapping time varies significantly. The analysis results showed that the larger velocity and the higher the salinity, the longer the overlapping time. The velocity and salinity inhibited the development of the... [more]

The energy transition has shown that fossil generation can be complemented with renewable energy and other resources capable of providing flexibility to the energy system’s operation, in compliance with the wholesale electricity market’s rules. This paper proposes a market-based methodology for introducing flexible demand in the energy dispatch, optimizing the scheduling of electricity system operation in the short-term, and considers the challenge of implementing an incentive scheme for participants in demand-response programs. The scheme includes the criteria of the elasticity of substitution and a renewable energy quota. This methodology is focused on a strategic demand shift to minimize the cost of supply; increase the dispatch of renewable energy; control CO2 emissions; and satisfy the generation, demand, and transmission operating constraints. These conditions encourage the development of a simulation tool that allows a sensitivity analysis to aid decision-making by operators and... [more]

The charging loads of electric vehicles (EVs) at residential premises are controlled through a tariff system based on fixed timing. The conventional tariff system presents the herding issue, such as with many connected EVs, all of them are directed to charge during the same off-peak period, which results in overloading the power grid and high charging costs. Besides, the random nature of EV users restricts them from following fixed charging times. Consequently, the real-time pricing scenarios are natural and can support optimizing the charging load and cost for EV users. This paper aims to develop charging cost optimization algorithm (CCOA) for residential charging of EVs. The proposed CCOA coordinates the charging of EVs by heuristically learning the real-time price pattern and the EV’s information, such as the battery size, current state-of-charge, and arrival & departure times. In contrast to the holistic price, the CCOA determines a threshold price value for each arrival and depart... [more]

South Korea is surrounded by the sea on three sides. The characteristics of offshore wind resources vary from region to region due to the influence of the distribution of the coastline and differences in roughness length and atmospheric stability between the coast and the sea. In particular, turbulent gusts and low-level wind shear occurring near the hub height of the wind turbine within the atmospheric boundary layer have a significant effect on the load of wind turbines. These severe weather phenomena are closely related to atmospheric stability. Therefore, the objective of this study is to determine differences in wind resource characteristics in the South Korean offshore and coast in relation to variations in atmospheric stability using observation data from the HeMOSU-1 meteorological tower in the West Sea and the Boseong meteorological observation tower on the southern coast. On the southern coast, changes in sea and land breezes are observed throughout diurnal and nocturnal peri... [more]

The objective of this paper is to propose the real-time implementation of a fault-tolerant strategy based on fuzzy logic controller (FLC) for a Six-Phase Axial Flux Permanent Magnet Synchronous Machine (6P-AFPMSM) for electrical energy production. This type of machine, suitable for high-power applications, is highly affected by the harmonics of the inductances and the electromotive force (emf) compared to the classical three-phase radial flux machine, which will influence the controller parameters of the machine. The proposed control strategy based on FLC is independent of the system model and guarantees the robustness of the process against disturbances and parameter variations of the model. An experimental comparison between FLC and a classical PI controller confirms the efficiency and the robustness of the proposed controller in healthy and faulty conditions with one open phase.

Commercial virtual power plants (CVPP) connect the form of renewable energy resource portfolio to the power market and reduce the risk of the unstable operation of a single renewable energy. Combining different kinds of large-scale renewable energy in CVPP to provide capacity services like base load, peak shaving, and valley-filling, etc., for the system loads is an urgent problem to be solved. Therefore, it is valuable to analyze the capacity allocation ratio of the CVPP to maximize the utilization of all kinds of energy, especially for the large-scale multi-energy base. This paper proposed a multi-energy coordinated operation framework by considering various load demands, including base load and peak shaving for the capacity allocation of CVPP based on the world’s largest renewable energy resource base on the upstream area of the Yellow River. The main procedures of this framework are as follows: (1) A paratactic model satisfying base load and peak shaving is proposed to determine th... [more]

Renewable distributed generators (RDGs) are widely embedded in electrical distribution networks due to their economic, technological, and environmental benefits. However, the main problem with RDGs, photovoltaic generators, and wind turbines, in particular, is that their output powers are constantly changing due to variations in sun irradiation and wind speed, leading to power system uncertainty. Such uncertainties should be taken into account when selecting the optimal allocation of RDGs. The main innovation of this paper is a proposed efficient metaheuristic optimization technique for the sizing and placement of RDGs in radial distribution systems considering the uncertainties of the loading and RDG output power. A Monte Carlo simulation method, along with the backward reduction algorithm, is utilized to create a set of scenarios to model these uncertainties. To find the positions and ratings of the RDGs, the artificial gorilla troops optimizer (GTO), a new efficient strategy that mi... [more]

This article presents the results of the development of a hybrid research platform for fundamental and empirical modeling and analysis of energy management of shared electric vehicles. The article describes the hybrid model and its specific features in detail. Within the model architecture, a part of the fundamental model, empirical model and data collection tools were interconnected. The uniqueness lies in the models of electric cars created for a specific vehicle using cost-optimal parameterizations, as well as the implementation of a cloud solution, which is based on custom data communication, custom data logger and cost-optimized parameterization of machine learning algorithms. Experimental verification was performed on a real electric car in public traffic. The car is part of casharing platform.

This study aims to examine the energy-use inefficiency in Central Asian (CA) countries by using the analytical framework of the energy-environmental Kuznets curve (EEKC). This study’s contribution to the literature, in the first place, is to explicitly target the CA countries in the EEKC analysis. The empirical analyses identified the energy-use inefficiency of Turkmenistan, Uzbekistan, and Kazakhstan, and could demonstrate the contributions of weak policy governance and their natural resource abundance. This analytical result could also be endorsed by the Uzbekistan case. Thus, the policy implication is that there would be much room for these countries to improve their energy-use efficiency by enhancing their performance of energy policies.

Recent major advancements in drone charging station design are related to the differences in coil design between the material (copper or aluminum) and inner thickness (diameter design) to address power transfer optimization and increased efficiency. The designs are normally challenged with reduced weight on the drone’s side, which can lead to reduced payload or misalignment position issues between receiver and transmitter, limiting the performance of wireless charging. In this work, the coil combination was tested in vertical alignment from 2 cm to 50 cm, and in lateral misalignment positions that were stretched across 2, 5, 8, 10, and 15 cm ranges. Simulated and experimental results demonstrated improved transfer distances when the drone battery load was 100 Ω. With the proposed design, the vertical transfer power that was achieved was 21.12 W, 0.460 A, with 81.5% transfer efficiency, while the maximum lateral misalignment air gap that was achieved was 2 cm with 19.22 W and 74.15% eff... [more]

The flashover performance of contaminated insulators highly depends on the type of pollutant and its present concentration. In this paper, important agricultural salts (NaCl, K2SO4, NaHCO3, CaSO4, KHCO3, MgSO4, NH4), 2Fe(SO4)2, and 6H2O (ferrous ammonium sulphate, dust, and urea) at different concentrations, and biological contaminants, such as algae and fungi, were taken as pollutants, and the AC flashover behavior of a porcelain-cap-and-pin-type insulator polluted with these two different pollutants was investigated. The experiment was carried out by a semi-natural method, wherein the insulator was first polluted artificially; thereafter, natural fog was applied to measure the wet flashover voltage. Test results indicated that the flashover voltages were affected by both soluble salts and non-soluble components deposited on the insulator surface. In the case of the thickly contaminated layers, non-soluble deposits greatly reduced the flashover voltage. Moreover, by using regression a... [more]

Optimizing the schedule of thermal generators is probably the most important task when the operation of power systems is managed. This issue is known as the unit commitment problem in operational research. It has been profoundly studied in the literature, where several techniques have been proposed to address a computationally tractable solution. In turn, the ongoing changes of paradigms in energy markets focus the attention on the unit commitment problem as a powerful tool to handle new trends, such as the high renewable energy sources penetration or widespread use of non-conventional energy-storage technologies. A review on the unit commitment problem is propo- sed in this paper. The easy understanding of the diverse techniques applied in the literature for new researchers is the main goal of this state-of-art as well as identifying the research gaps that could be susceptible to further developments. Moreover, an overview of the evolution of the Mixed Integer Linear Programming formu... [more]

The stable and efficient operation of power systems requires them to be optimized, which, given the growing availability of load data, relies on load forecasting methods. Fast and highly accurate Short-Term Load Forecasting (STLF) is critical for the daily operation of power plants, and state-of-the-art approaches for it involve hybrid models that deploy regressive deep learning algorithms, such as neural networks, in conjunction with clustering techniques for the pre-processing of load data before they are fed to the neural network. This paper develops and evaluates four robust STLF models based on Multi-Layer Perceptrons (MLPs) coupled with the K-Means and Fuzzy C-Means clustering algorithms. The first set of two models cluster the data before feeding it to the MLPs, and are directly comparable to similar existing approaches, yielding, however, better forecasting accuracy. They also serve as a common reference point for the evaluation of the second set of two models, which further en... [more]

In domestic induction heating applications, cookware can be considered an equivalent load in a series resistor−inductor−capacitor resonant converter. Therefore, the electrical parameters of an equivalent circuit change according to the cookware material, size and the cookware position on the heating coil. This study proposes an online estimation method for detecting the cookware status, determining the material and estimating the equivalent heating resistance of cookware on an induction heating cooker (IHC) for power control. The proposed method could turn off the circuit in abnormal situations such as low equivalent heating coverage rate or non-ferromagnetic cookware and adjust the power in normal situations. In the method, a half-bridge series resonant converter (HBSRC) generates two test patterns with three resonant voltage pulses to detect cookware every 10 ms, only the current feedback information is needed to avoid the calculation loads and times necessary for complex signal oper... [more]

The climate policy of the EU enforced substantial changes for producers and suppliers of energy. New assets and providers of capital are needed to fulfill the policy requirements. To provide comparability and facilitate an investment process, EU law requires companies to prepare annual financial statements according to International Financial Reporting Standards. One of these accounting standards—IFRS 16 Leases—specifies how to recognize, measure, present and disclose leases. It came into force in 2019 and implemented a single lessee accounting model, contrary to a dual accounting approach for lease accounting. The latter approach enabled companies to keep leased tangible assets and respective liabilities off-balance sheet. By using a sample of companies from the energy industry (oil, gas, energy and mining sectors) that are listed on the Warsaw Stock Exchange, we examine, measure, and analyze the impact of IFRS 16 Leases implementation on the value of assets, liabilities and leverage... [more]

Every sector of the global economy is faced with environmental problems and their resulting consequences to their day-to-day operations. Due to the rising threat of global climate change, the green banking (GB) concept has been given significant attention in recent green finance literature. Therefore, the main purpose of this study was to identify the impact of GB practices on banks’ environmental performance and sources of green financing of private commercial banks (PCBs) in Bangladesh. Using a survey method, the primary data were obtained from a cross-sectional sample of 322 banking employees of PCBs in Bangladesh. In order to identify the key relationships existing between the study variables, structural equation modelling (SEM) approach was employed. The empirical findings indicated that banks’ employees, daily-operations, and policy-related GB practices have significant positive effects on green financing, contrary to banks’ customer-related GB practice, which was not statistical... [more]

Given the availability of a wide range of properties not possessed by individual materials, nanocomposites based on conducting polymers and inorganic materials have attracted much deserved attention. However, there has been little attempt to optimize the synthesis and thermal properties of polyaniline−clay nanocomposites. In this study, the synthesis and thermal properties of polyaniline (PANi) and polyaniline−clay nanocomposites (PACN) were performed by systematically varying the feed composition. Both PANi and polyaniline−montmorillonite (MMT) nanocomposites were prepared by using ammonium persulfate (APS) as the oxidant. The chemical structure of the nanocomposites was studied by Fourier transform infrared spectroscopy (FTIR). FTIR spectra confirmed the presence of clay in the nanocomposites and the existence of mainly the emiraldine form of PANi. Thermal analysis was performed by using thermogravimetric analysis (TGA) and differential scanning calorimetry (DSC). The morphology and... [more]

This article summarises the experimental testing campaign performed at the Joint Research Centre (JRC) on the demonstrator battery electric vehicle (BEV) of the European Union Horizon 2020 research project QUIET. The project, launched in October 2017, aimed at developing an improved and energy-efficient electric vehicle with increased driving range under real-world driving conditions, focusing on three areas: improved energy management, lightweight materials with enhanced thermal insulation properties, and improved safety and comfort. A heating, venting, and air conditioning (HVAC) system based on the refrigerant R290 (propane), a phase change material (PCM) thermal storage system, infrared heating panels in the near field of the passengers, lightweight materials for seat internal structures, and composite vehicle doors with a novel atomically precise manufacturing (APM) aluminium foam are all the breakthrough technologies installed on the QUIET demonstrator vehicle. All these innovati... [more]

The growing integration of intermittent renewable energy sources (RESs) and the increasing trend of shutting down fossil-fuel-based power plants has brought about the need for additional flexibility in energy systems. This flexibility can be provided in various forms, including controllable generation and consumption, storage, conversions, and exchanges with interconnected systems. In this context, an increasing focus is placed on the development of smart energy systems (SESs) that combine different types of distributed energy resources (DERs), information and communication technologies (ICTs), demand side management (DSM), and energy conversion technologies. The utilization of SESs can lead to multiple benefits for the stakeholders involved; therefore, the assessment of their performance is a primary concern. Due to their multidisciplinary nature, there are no known or universally accepted standards for assessing the performance of SESs. Previous efforts only define key performance in... [more]

This paper suggests a novel way to manufacture power-efficient building-integrated photovoltaic (BIPV) modules that are aesthetically acceptable for use in zero-energy buildings (ZEBs). An optical pattern is formed using additive manufacturing (AM) to maximize the number of sunrays that reach the solar cells and to hide cells beneath the pattern. The optical pattern was optimized by simulation, then selected PV modules were fabricated to ensure that they met the optimal optical pattern conditions. Increase in pattern angle and lens space yielded increase in the output power of the PV module, but reduced the aesthetic functionality. This color BIPV technology is expected to help expand the BIPV market and reduce carbon for “net zero” objectives.

This paper proposes a fault diagnosis method for ship electrical power systems on the basis of an improved convolutional neural network (CNN) to support normal ship operation. First, according to the mathematical model of the ship electrical power system, the simulation model of the ship electrical power system is built using the MATLAB/Simulink simulation software platform in order to understand the normal working state and fault state of the generator and load in the power system. Then, the model is simulated to generate the fault response curve, and the picture dataset of the network model is obtained. Second, a CNN fault diagnosis model is designed using TensorFlow, an open-source tool for deep learning. Finally, network model training is performed, and the optimal diagnosis results of the ship electrical power system are obtained to realize structural parameter optimization and diagnosis. The diagnosis results show that the established simulation model and improved CNN can provide... [more]