Solar PV and battery energy storage (BES) costs for domestic consumers are constantly diminishing. On top of this, the end of the Feed-in-Tariff programme has significantly increased interest in combined PV + BES systems. In this paper, we explore the economics of domestic PV + BES systems, extending the current literature on the topic via the use of a large smart meter dataset and a demographic comparison. Predictably, time-varying tariffs and higher electricity prices generally strengthen the economic arguments for PV + BES systems, however our consumption data yields a wide range of Net Present Values for different consumers. In terms of demographics, we find that batteries are more favourable for more affluent households due to their larger consumption levels, though profitability becomes more uniform if the batteries are tailored to individual households. This is an important point for policy, since it indicates that if PV + BES systems become widely profitable this is unlikely to... [more]

This paper presents a comparative simulation study of the operation of various types of drivers dedicated for use in light-emitting diode (LED)-based light stripes. The study comprises an experimentally verified simulation in view of their influence on harmonic content generation and impact on electric energy quality. The simulation models were optimized in order to precisely reflect the currents and voltage waveforms recorded in the frame of laboratory measurements. The simulation parameters were adjusted in view of harmonic generation analysis and high-frequency (HF) transient presence resulting from circuit principles of operation. Two driver circuit types were analyzed in the framework of the study—a voltage stabilization circuit based on a Zener diode, and a current stabilization integrated circuit (IC) based on an AL8806 chip. The study results entail an analysis executed for light stripes comprising various numbers of LEDs connected to each driver and various numbers of each of... [more]

This paper presents a novel concept of the DC-AC system with the input voltage boost ability, seven-level output voltage modulation, and the input AC current reduction at the double frequency of the output voltage. The system integrates the NPC full-bridge inverter which is composed of four-level legs and an active input voltage balancer (AIVB). The DC-link is composed of three capacitors connected in a series. The source of the energy is connected directly to the middle capacitor while the upper and lower capacitors of the DC-link are charged by the AIVB. The operation of the AIVB leads to balancing of the DC-link voltage and a three-fold boosting of the input voltage. The AIVB utilizes a novel switched-capacitor (SC) topology and can be designed as a low-volume quasi-magneticless converter with a simple open-loop control. One of the proposed methods of the control of the AIVB allows for a double frequency reduction in the input current. The application of the AIVB allows for the use... [more]

A 1000 Nm3/h capacity pilot scale dual baghouse filter system was tested on flue gas and fly ash from a municipal solid waste incinerator, and the removal efficiency of dioxins, heavy metals and HCl was studied. Activated carbon was injected at the inlet of the first baghouse filter to remove the gas phase dioxins and heavy metals, and baking soda was injected at the inlet of the second baghouse filter to remove HCl. Concentrations of dioxins at the outlet of the first and second baghouse were 0.034 and 0.011 ng TEQ/Nm3, respectively, which were both far below the national emission standard. The particulate matter concentration was 0.85 mg/m3, and the heavy metals leaching concentration of the fly ash from the second baghouse filter was lower than the hazardous waste identification standard. HCl concentration was almost zero at the outlet of the second baghouse filter when the optimal equivalence ratio of baking soda to HCl was 1.6. In addition, the estimated fly ash yield was 2.35% of... [more]

The energy industry is employing new reliable and efficient renewable energy sources because of government and environment restrictions [...]

Considering the aero-hydro-mooring-control coupled performance of a floating Vertical Axis Wind Turbine (VAWT), the numerical model of the floating helical VAWT system is established, and the fully coupled simulation program of the floating helical VAWT is developed. The aerodynamic load of the wind turbine system is calculated using the unsteady BEM model, and the hydrodynamic load is calculated using the 3D potential theory. The floating foundation is considered as a rigid body, and the blades and tower are considered as flexible bodies. Based on the Kane method of a multi-body system, the dynamic responses of the VAWT could be solved in the time domain. A variable speed control model considering efficiency and load is established to match the rotating speed with the wind speed, and it could maintain the target output power under the influence of turbulent wind and large-scale movement of the floating foundation. The control strategy of limiting the target speed change rate and low-p... [more]

In this work, we present a three-stage multiobjective mixed-integer linear programming (MILP) for the optimal expansion planning and operation of isolated multienergy microgrids in remote areas. By selecting the optimal distributed generators (DGs) and energy storage systems (ESSs) mix selection, siting, sizing, and scheduling in the remote microgrid, the proposed model is targeted to minimize the annualized total cost of microgrids while enhancing the performance of the system, i.e., minimizing the voltage deviations and line power loss. To represent the electricity and heat flow between generation resources and various electrical, heating, and cooling loads in the isolated microgrid, linearized power flow, and heat flow constraints are employed in the proposed optimization model. The available capacity of DGs and ESSs are modeled as discrete constants instead of continuous variables for practical purpose. Numerical simulation results on a remote microgrid consisting of DGs, ESSs, and... [more]

From a practical point of view, a turbine load cycle (TLC) is defined as the time a turbine in a power plant remains in operation. TLC is used by many electric power plants as a stop indicator for turbine maintenance. In traditional operations, a maximum time for the operation of a turbine is usually estimated and, based on the TLC, the remaining operating time until the equipment is subjected to new maintenance is determined. Today, however, a better process is possible, as there are many turbines with sensors that carry out the telemetry of the operation, and machine learning (ML) models can use this data to support decision making, predicting the optimal time for equipment to stop, from the actual need for maintenance. This is predictive maintenance, and it is widely used in Industry 4.0 contexts. However, knowing which data must be collected by the sensors (the variables), and their impact on the training of an ML algorithm, is a challenge to be explored on a case-by-case basis. In... [more]

A large-scale two-dimensional computational fluid dynamics study is conducted in order to maximise the power output and smoothness of power delivery of a free-stream water wheel, a low-impact hydropower device. Based on models and methods developed in previous research, the study uses a genetic algorithm to optimise the geometry of a wheel with a given radius and depth, maximising two objective functions simultaneously. After convergence and suitable post-processing, a single optimal design is identified, featuring eight shortened blades that become fully immersed at the nadir point. The design results in a 71% reduction in blade material and a 113% increase in the work ratio while improving the hydraulic power by 8% compared to the previous best design. These characteristics are applied retroactively to a broad family of designs, resulting in significant improvements in performance. Analysis of the resulting designs indicates that when either the hydraulic power coefficient, rotor pow... [more]

In this work, an experimental study and kinetic characterization of the combustion process and a morphologic study of hydrogen/methane−air mixtures are presented. The experimental study was performed in an optical access cylindrical constant-volume combustion bomb. This bomb is equipped to register the instantaneous pressure during combustion and records the combustion images using the high-speed Schlieren optical technique. This provides straightforward information to compute the flame propagation speed and direct evidence of the apparition of cellularity on the flame front. Through the images of the combustion process, it is possible to conduct a morphological study of the process using a flame monitoring model. Simultaneously, by means of a two-zone thermodynamical model, with the temporal evolution of pressure as the main intake, significant parameters are determined during the combustion process of different fuels under premixed conditions: burning velocity, rate of combustion, bu... [more]

The use of sustainably sourced biomass is an important tool for mitigating the effects of climate change; but biomass is far from being a homogeneous resource. The aim of this study was to examine the decision-making process of industrial end-users considering biomass procurement. An online, two-part survey generated responses from 27 experienced professionals, representing a portfolio of facilities varying in size, technology, and biomass types, across Australia, Canada, Finland, and Sweden. A PAPRIKA conjoint analysis approach was used to analyze the data so that the attributes that influenced procurement decisions could be weighted and ranked. The results provided an insight into end-users’ views on factors including facility location, size, and biomass storage, handling, and procurement for different wood-based industrial services. The most important decision-making attribute appeared to be the type of biomass assortment, at individual, national, and aggregated levels. Of seven sub... [more]

In an attempt to solve the problem of the many parameters of the traditional active disturbance rejection controller (ADRC) and to accurately estimate the mover position and speed required by a permanent magnet synchronous linear motor (PMLSM) system, an improved ADRC and a novel nonsingular fast terminal sliding mode observer (NFTSMO) are proposed. Firstly, the traditional first-order ADRC is simplified, the tracking differentiator (TD) module is removed, and the direct error is used to replace the nonlinear function in the extended state observer (ESO) and nonlinear state error feedback (NLSEF) module. Based on the traditional NFTSMO, the smooth back electromotive force (EMF) is obtained by adding the TD to reduce the phase delay caused by the low-pass filter in the traditional sliding mode observer (SMO), and the actuator position and speed information are modulated from the observed back EMF based on the principle of a phase-locked loop (PLL). Simulation and experiments show that t... [more]

Synchronous reluctance (SynRel) machines are considered one of the promising and cost-effective solutions to many industrial and mobility applications. Nonetheless, achieving an optimal design is challenging due to the complex correlation between geometry and magnetic characteristics. In order to expand the limits formed by template-based geometries, this work approaches the problem by using topology optimization (TO) through the density method (DM). Optimization settings and their effects on results, both in terms of performance and computation time, are studied extensively by performing optimizations on the rotor of a benchmark SynRel machine. In addition, DM-based TO is applied to an existing rotor geometry to assess its use and performance as a design refinement tool. The findings are presented, highlighting several insights into how to apply TO to SynRel machine design and its limitations, boundaries for performance improvements and related computational cost.

The shift towards renewable energy and decreasing battery prices have led to numerous installations of PV and battery systems in industrial and public buildings. Furthermore, the fluctuation of energy costs is increasing since energy sources based on solar and wind power depend on the weather situation. In order to reduce energy costs, it is necessary to plan energy-hungry activities while taking into account private PV production, battery capacity, and energy market prices. This problem was posed in the 2021 “IEEE-CIS Technical Challenge on Predict + Optimize for Renewable Energy Scheduling”. The target was to solve the two subtasks of forecasting the base load and of computing an optimal schedule of a list of energy intensive activities with inter-dependencies. We describe our approach to this challenge, which resulted in the third place of the leaderboard. For the prediction of the base load, we use a combination of a statistical and a machine learning approach. For the optimization... [more]

This paper proposes a state-of-charge estimation technique to meet highly dynamic power requirements in electric vehicles. When the power going in/out the battery is highly dynamic, the statistics of the measurement noise are expected to deviate and maybe change over time from the expected laboratory specified values. Therefore, we propose to integrate adaptive noise identification with the dual-Kalman filter to obtain a robust and computationally-efficient estimation. The proposed technique is verified at the pack and cell levels using a 3.6 V lithium-ion battery cell and a 12.8 V lithium-ion battery pack. Standardized electric vehicle tests are conducted and used to validate the proposed technique, such as dynamic stress test, urban dynamometer driving schedule, and constant-current discharge tests at different temperatures. Results demonstrate a sustained improvement in the estimation accuracy and a high robustness due to immunity to changes in the statistics of the process and meas... [more]

This paper proposes a new strategy for modeling predictability uncertainty in a stochastic context for decision making within a Virtual Power Plant (VPP). Modeling variable renewable energy generation is an essential step for effective VPP planning and operation. However, it is also a challenging task due to the uncertain nature of its sources. Therefore, developing tools to effectively predict these uncertainties is essential for the optimal participation of VPPs in the electricity market. The purpose of this paper is to present a novel method to model the uncertainties associated with energy dispatching in a VPP using the Unscented Transform (UT) method. The proposed algorithm minimizes the risks associated with the VPP operation in a computationally efficient and simple manner, and can be used in real-time on a power system. The proposed framework was evaluated based on an Electric Power System (EPS) model with historical data. Case studies have been performed to demonstrate the eff... [more]

In the oil shale in situ conversion project, it is urgent to solve the problem that the reaction degree of organic matter cannot be determined. The yield and composition of organic products in each stage of the oil shale pyrolysis reaction change regularly, so it is very important to master the process of the pyrolysis reaction and reservoir change for oil shale in situ conversion project. In the in situ conversion project, it is difficult to directly obtain cores through drilling for kerogen maturity testing, and the research on judging the reaction process of subsurface pyrolysis based on the maturity of oil products has not been carried out in-depth. The simulation experiments and geochemical analysis carried out in this study are based on the oil shale of the Nenjiang Formation in the Songliao Basin and the pyrolysis oil samples produced by the in situ conversion project. Additionally, this study aims to clarify the evolution characteristics of maturity parameters such as effective... [more]

Advances in communication technologies and protocols among vehicles, charging stations, and controllers have enabled the application of scheduling techniques to prioritize EV fleet charging. From the perspective of users, residential EV charging must particularly address cost-effective solutions to use energy more efficiently and preserve the lifetime of the battery—the most expensive element of an EV. Considering this matter, this research addresses a residential EV charging scheduling model including battery degradation aspects when discharging. Due to the non-linear characteristics of charging and battery degradation, we consider a mixed integer non-linearly constrained formulation with the aim of scheduling the charging and discharging of EVs to satisfy the following goals: prioritizing charging, reducing charging costs and battery degradation, and limiting the power demand requested to the distribution transformer. The results shows that, when EVs are discharged before charging up... [more]

The development of high-performance CO2 capture and separation adsorbents is critical to alleviate the deteriorating environmental issues. Herein, N atom-doped layered graphene (N-MGN) was introduced to form triazine and pyridine as potential CO2 capture and separation adsorbents via regulation of interlayer spacings. Structural analyses showed that accessible surface area of the N-MGN is 2521.72 m2 g−1, the porosity increased from 9.43% to 84.86%. At ultra-low pressure, N-MGN_6.8 have exhibited a high CO2 adsorption capacity of 10.59 mmol/g at 298 K and 0.4 bar. At high pressure, the absolute adsorption capacities of CO2 in N-MGN_17.0 (40.16 mmol g−1) at 7.0 MPa and 298 K are much larger than that of N-doping slit pore. At 298 K and 1.0 bar, the highest selectivity of CO2 over N2 reached up to ~133 in N-MGN_6.8. The research shows that N doping can effectively improve the adsorption and separation capacity of CO2 and N2 in layered graphene, and the interlayer spacing has an important... [more]

Crude oil and natural gas are crucial to the Russian economy. Therefore, this study examined the interconnections between crude oil price, natural gas price, and Russian economic policy uncertainty (EPU) over the period 1994−2019 using multivariate DCC-MGARCH models. The findings show that there are strong interconnections (co-movement) between the energy prices and EPU in Russia, and that it might be misleading to assume independence or neutrality between the variables. Although Russia is also a crucial player in both the natural gas and the crude oil markets, this study reveals that there is a stronger co-movement of the EPU with gas price than with the oil price. Russia is the largest exporter of natural gas and the second-largest producer; it is plausible that the natural gas price correlates with EPU more than the crude oil price. Further, the correlation between gas price and EPU and the correlation between crude oil price and EPU have similar patterns. Each declines almost in th... [more]

Gentry biomass, as a residue from the mezcal production process, may be an interesting bioenergy alternative; however, its high ash content limits its application. In this study, pellets were generated with agave fiber mixed with Pinus species sawdust in the following six proportions (%): 100−0 (control), 80−20, 60−40, 40−60, 20−80 and 0−100 (control). The physical, chemical and energetic properties of the pellets were evaluated according to the UNE-EN ISO 17225-6, UNE EN ISO 17827-2, UNE-EN ISO 17828, UNE-EN ISO 18122, UNE-EN ISO 18123, UNE-EN ISO 18125, and UNE-EN ISO 18134-1 standards. The results showed significant statistical differences (p < 0.05) among the treatments tested. The percentage of volatile material and fixed carbon ranged from 86.53 to 89.96% and 4.17 to 8.16%, respectively; the ash content ranged from 0.27 to 10.06%, and the calorific value ranged from 17.33 to 18.03 MJ/kg. Bulk density ranged from 725.76 to 737.37 kg/m3 and the impact-strength index was in the r... [more]

Aiming at the poor precision problem in phase difference measurements with unknown frequencies in engineering practice, a new phase difference measurement method is proposed for Coriolis mass flowmeter based on correlation theories. Firstly, the signal frequency was estimated by using an adaptive notch filter, which was applied to filter the waves and determined the integer period of the sampling signals, and the non-integer period sampling signals needed to be extended. Then, the Hilbert transformation was conducted relative to the extended signals, and the correlation functions of these extended signals with the transformed signals can be computed. Finally, the formula of phase difference can be obtained by utilizing the sinusoidal function. Compared to traditional methods, such as the correlation method, the Hilbert transformation method, and sliding Goertzel algorithm, the proposed method is suitable for both integer period and non-integer period sampling signals, and its accuracy,... [more]

Costs of cooling installations cause them to be very rarely used in residential buildings in countries located in heating-dominated climates, like Poland. Hence, there arises the need to assess indoor thermal comfort during summer and to indicate ways to reduce possible overheating. This paper presents an attempt to use the thermal network model of the building zone of EN ISO 13790 to assess indoor operative temperature during four warm months from June to September. The model of the naturally ventilated single-family residential building located in central Poland was used. Performed calculations for the base case resulted in 38 and 63 days within the comfort zone at 80% acceptance level in a total of 122 days in the analyzed period for EN 15251 and ASHRAE standards, respectively. Use of external shading on windows and the roof with lower solar absorptance resulted in 46 and 70 days with acceptable conditions, respectively. Further application of night ventilation resulted in the 38 an... [more]

This study addresses the output impedance model of the LCL-type grid-connected converter considering the dead-time effects and the digital control delay. The model shows that the digital control delay will affect the accuracy of the output impedance of the grid-connected converter, and the dead-time effects are only equivalent to superimposing a disturbance voltage on the original output impedance model. The derived output impedance model is verified by comparing it with the switching model in the PSIM simulation environment. The harmonic interaction between converter cluster and utility grid is modeled and analyzed based on the output impedance model. A combined harmonic suppression strategy is incorporated into every converter control scheme to suppress the harmonic interaction. Simulation results are presented to demonstrate the correctness of harmonic interaction analysis and the effectiveness of the proposed suppression strategy.

Production from the North Sea reservoirs often results in a pressure decrease below the bubble point. The gas is liberated from oil, in the form of bubbles or as a continuous flowing phase. In such cases, the two phases, gas and oil, flow in the reservoir simultaneously, and the flow is governed by the values of relative permeabilities. Traditional core flooding in low permeability rocks is challenging, therefore we use a novel experimental approach to determine the oil relative permeabilities below the critical gas saturation. A mathematical model has been created to reconstruct both the gas and the oil relative permeabilities for the whole saturation range. Laboratory observations have shown that in low-permeable rocks the relative permeabilities may strongly decrease, even when the amount of the liberated gas is small. The goal of this work is to verify, on a specific example, whether the designed model for the relative permeabilities may explain the observed production behavior for... [more]