The increased integration of Electric Vehicles (EVs) into the distribution network can create severe issues—especially when demand response programs and time-varying electricity prices are applied, EVs tend to charge during the off-peak time to minimize the electricity cost. Hence, another peak demand might be created, and other solutions are required. Many researchers tried to solve the problem; however, limitations exist because of the decentralized topology of the network. The system operator is not allowed to control the end-users’ load due to security and privacy issues. To overcome this situation, we propose a novel data-energy management algorithm on the transformer’s level that controls the power demand profiles of the householders and exchange energy between them without violating their privacy and security. Our method is compared to an existing one in the literature based on a decentralized control strategy. Simulations show that our approach has reduced the electricity cost... [more]

Wind energy is one of the fastest growing renewable energy sources, and the most developed energy extraction device that harnesses this energy is the Horizontal Axis Wind Turbine (HAWT). Increasing the efficiency of HAWTs is one important topic in current research with multiple aspects to look at such as blade design and rotor array optimization. This study looked at the effect of wingtip devices, a split winglet, in particular, to reduce the drag induced by the wind vortices at the blade tip, hence increasing performance. Split winglet implementation was done using computational fluid dynamics (CFD) on the National Renewable Energy Lab (NREL) Phase VI sequence H. In total, there are four (4) blade configurations that are simulated, the base NREL Phase VI sequence H blade, an extended version of the previous blade to equalize length of the blades, the base blade with a winglet and the base blade with split winglet. Results at wind speeds of 7 m/s to 15 m/s show that adding a winglet in... [more]

Energy consumption is of great significance to the sustainable development of the economy. Due to the spatial heterogeneity of low-carbon growth in regional economies, the relationship between energy consumption and economic growth is complicated. However, a few researches have been published about spatial spillover effects and non-linearity of energy consumption and financial development on regional economic growth in China. Based on the panel data of 30 provinces in China from 2007 to 2017, this paper analyzes the spatial spillover effects and threshold effects of energy consumption and financial development on regional economic growth by using spatial and nonlinear econometric methods. The main conclusions are as follows. Spatial econometric methods show that financial development and energy consumption are two factors of production input to promote China’s economic growth. Meanwhile, energy consumption and financial development have spillover effects on regional economic growth. Ad... [more]

This work presents a validated workflow based on an algorithm developed in Grasshopper to parametrically control the building’s shape, by maximizing the solar irradiation incident on the building envelope and minimizing the embodied emissions. The algorithm is applied to a zero-emission building concept in Nordic and Mediterranean climate zones. The algorithm enables conducting both energy and environmental assessments through Ladybug tools. The emissions embodied in materials and the solar irradiation incident on the building envelope were estimated in the early design stage. A three-steps optimization process through evolutionary solvers, such as Galapagos (one-objective) and Octopus (multi-objective), has been conducted to shape the most environmentally responsive ZEB model in both climates. The results demonstrated the replicability of the algorithm to optimize the solar irradiation by producing an increment of solar incident irradiation equal to 35% in the Mediterranean area, and... [more]

The purpose of the work is a comparison of indirect carbon dioxide emissions between the different heat pump types that operate in Polish climate conditions. The analysis embraces air-to-water heat pump, ground-to-water heat pump, water-to-water heat pump and water-to-water heat pump with separating heat exchanger in the selected towns one in each climatic zone in the country. The study starts from determining seasonal coefficient of performance in each location using heating degree days to estimate seasonal heat demand. Seasonal coefficient of performance values enable an assessment which kind of heat pump meets the European Union requirements in every location. Eventually, indirect CO2 emissions that is caused by electrical energy production, are estimated for every heat pump in each location. Ground-to-water heat pump and water-to-water heat pump satisfy these requirements in each climatic zone in Poland. Air-to-water heat pump would be an energetic and ecological viable on a condit... [more]

The oxygen reduction reaction is an important reaction at the cathode in solid oxide fuel cells. Materials that exhibit high chemical and mechanical stability, high ionic and electronic conductivity, and are non-toxic are of great interest as cathodes for the reduction of oxygen. Here, we use density functional theory simulations to examine the efficacy of 12CaO·7Al2O3 and 12SrO·7Al2O3 electrides and their doped forms for the conversion of O2 gas to form O2− in their nanocages via encapsulation. Calculations show that encapsulation is exoergic in the un-doped electrides, and the formation of O2− is confirmed by the charge analysis. A stronger encapsulation is noted for C12A7 electride than the S12A7 electride. The C12A7 electride doped with B or Ga also exhibits exoergic encapsulation, but its encapsulation energy is slightly lower than that calculated for the un-doped C12A7 electride. There is an enhancement in the encapsulation for the S12A7 electride doped with B compared to its un-... [more]

Light-emitting diode (LED) digital twins enable the implementation of fast digital design flows for LED-based products as the lighting industry moves towards Industry 4.0. The LED digital twin developed in the European project Delphi4LED mimics the thermal-electrical-optical behavior of a physical LED. It consists of two parts: a package-level LED compact thermal model (CTM), coupled to a chip-level multi-domain model. In this paper, the accuracy and computation time reductions achieved by using LED CTMs, compared to LED detailed thermal models, in 3D system-level models with a large number of LEDs are investigated. This is done up to luminaire-level, where all heat transfer mechanisms are accounted for, and up to 60 LEDs. First, we characterize a physical phosphor-converted white high-power LED and apply LED-level modelling to produce an LED detailed model and an LED CTM following the Delphi4LED methodology. It is shown that the steady-state junction temperature errors of the LED CTM,... [more]

The main objective of the paper is to determine the impact of the COVID-19 pandemic on the level of energy poverty in Poland. In order to achieve such a goal, the first part of the article presents the definition of energy poverty and the nature of its measures, as well as the determinants and policies of the state addressing the issue of energy poverty mitigation. In the second part of the paper, the results of research into the level of energy poverty are analyzed and the variables affecting energy poverty in Poland during the pandemic are determined. It was established on the basis of these results that the present pandemic contributed to the aggravation of financial difficulties in Polish households with regard to financing expenditure on energy carriers. It was found that COVID-19 had a negative impact on the average disposable income of Polish households, which, with the increase in prices and expenditure on energy carriers, led to an increase in the proportion of disposable inco... [more]

In this paper a novel fault detection, isolation, and identification (FDI&E) scheme using a coupling diagnosis method with the integration of the model-based method and unsupervised learning algorithm is proposed and developed for monitoring gas turbine sensor faults, which represents an integration of Square Root Cubature Kalman Filters (SRCKF) and an improved Density-Based Spatial Clustering of Application with Noise (DBSCAN) algorithm. A detection indicator produced by SRCKF with a specific hypothesis is used for extracting sensor fault features against process and measurement noise, as well as operating conditions. Then, an improved DBSCAN is implemented based on a voting scheme to detect and isolate the faulty sensors. Finally, a residual-based fault estimation scheme is proposed to track sensor fault evolution and help to judge the types of faults. Moreover, the observability of the model involved is analyzed to verify the stable operation of the FDI&E scheme. Various experiments... [more]

Motor-driven equipment (ME) is one of the key components in an air-conditioning system, which contributes to the vast majority of the total energy consumption by air-conditioning systems. Distinguishing variable- and constant-speed equipment is important since the energy simulation models of the two types differ. Traditionally, types of ME are known in advance, and energy consumption data are consequently analyzed. However, in the application scenarios of energy consumption data mining, precedent information on the ME type could be missing. Thus, this study applies this process in reverse, providing new insight into energy consumption data of ME to recognize variable-speed ME in an air-conditioning system. The energy consumption data of ME in an air-conditioning system implemented in a commercial building were collected and numerically analyzed. A proposed simple parameter, coefficient of the median, and several numerical parameters were calculated and used to distinguish variable- fro... [more]

The Air-conditioning System (ACS), used in office buildings in the hot summer and cold winter zone of China, are always operate intermittently. The dynamic thermal behaviors of building walls with real climate conditions may be different from those with only the representative day’s climate conditions, due to the time varying nature of the climate, which will lead to the variation of the ACS loads. A numerical calculation was performed to analyze the effects of insulation form on heat behavior of external walls and ACS loads. The results indicate that cooling transmission load with inside insulation reaches its maximum value when the solar-air temperature in daytime is the highest, while that with outside insulation occurs at the time when the air temperature at night is the highest during summer. Heating transmission load for the wall with external and internal insulation both peaks in the day with lowest mean outdoor temperature during the last non-working period. Inside insulation c... [more]

Power-to-methane technology (P2M) deployment at wastewater treatment plants (WWTPs) for seasonal energy storage might land on the agenda of decision-makers across EU countries, since large WWTPs produce a notable volume of biogas that could be injected into the natural gas grid with remarkable storage capacities. Because of the recent rapid increase of local photovoltaics (PV), it is essential to explore the role of WWTPs in energy storage and the conditions under which this potential can be realized. This study integrates a techno-economic assessment of P2M technology with commercial/investment attractiveness of seasonal energy storage at large WWTPs. Findings show that a standardized 1 MWel P2M technology would fit with most potential sites. This is in line with the current technology readiness level of P2M, but increasing electricity prices and limited financial resources of WWTPs would decrease the commercial attractiveness of P2M technology deployment. Based on a Hungarian case st... [more]

Three-level neutral-point clamped cascaded converters (3LNPC-CC) are widely used in high power nigh-voltage applications. This paper mainly discusses the open-circuit fault in DC-side of the 3LNPC-CC. Optimized by the sequence pulse modulation, a sequence smooth modulation (SSM) is proposed to keep the DC-side voltage balance while the 3LNPC-CC suffers open-circuit fault from DC-side. The SSM found efficient switch-state path through a 3-D cube model and simplified the path from thousands of switch state. The SSM avoids the complex calculation in the voltage-balancing modulation, while the dynamic character of it was less influenced. At the same time, the modulation changes the voltage level smoothly and balances the fault DC-side voltage effectively. The characters of the proposed modulation are verified by the simulation and the experiment.

Unless humanity achieves United Nations Sustainable Development Goals (SDGs) by 2030 and restores the relatively stable climate of pre-industrial CO2 levels (as early as 2140), species extinctions, starvation, drought/floods, and violence will exacerbate mass migrations. This paper presents conceptual designs and techno-economic analyses to calculate sustainable limits for growing high-protein seafood and macroalgae-for-biofuel. We review the availability of wet solid waste and outline the mass balance of carbon and plant nutrients passing through a hydrothermal liquefaction process. The paper reviews the availability of dry solid waste and dry biomass for bioenergy with CO2 capture and storage (BECCS) while generating Allam Cycle electricity. Sufficient wet-waste biomass supports quickly building hydrothermal liquefaction facilities. Macroalgae-for-biofuel technology can be developed and straightforwardly implemented on SDG-achieving high protein seafood infrastructure. The analyses i... [more]

A significant growth in PV (photovoltaic) system installations have been observed during the last decade. The PV array has a nonlinear output characteristic because of weather intermittency. Partial shading is an environmental phenomenon that causes multiple peaks in the power curve and has a negative effect on the efficiency of the conventional maximum power point tracking (MPPT) methods. This tends to have a substantial effect on the overall performance of the PV system. Therefore, to enhance the performance of the PV system under shading conditions, the global MPPT technique is mandatory to force the PV system to operate close to the global maximum. In this paper, for the first time, a stochastic fractal search (SFS) optimization algorithm is applied to solve the dilemma of tracking the global power of PV system based triple-junction solar cells under shading conditions. SFS has been nominated because it can converge to the best solution at a fast rate. Moreover, balance between exp... [more]

The paper deals with the impact of the technological break duration during the cold storage cycle on the energy demand of the cold store for vegetables and fruit and the temperature distribution in the ground under the cold store. The studied facility was a two-chamber vegetable cold store located in southern Poland used to store carrots (Daucus carota) for nine months a year. The experiments were conducted for 12 months (01.05.2017−30.04.2018). The technological break during this period lasted three months (from 1 July 2018 to 30 September 2018). Continuous measurements (with 1-h frequency) were made in order to determine the boundary conditions for numerical analysis. The measured parameters included indoor air temperature, outdoor air temperature, ground temperature under the building and in its vicinity. There were 22 measuring points andPT100 sensors were used. The numerical analysis was based on the elementary balances method. WUFIplus® software was used as a calculation supporti... [more]

The state-of-charge (SOC) is a fundamental indicator representing the remaining capacity of lithium-ion batteries, which plays an important role in the battery’s optimized operation. In this paper, the model-based SOC estimation strategy is studied for batteries. However, the battery’s model parameters need to be extracted through cumbersome prior experiments. To remedy such deficiency, a recursive least squares (RLS) algorithm is utilized for model parameter online identification, and an adaptive square-root unscented Kalman filter (SRUKF) is designed to estimate the battery’s SOC. As demonstrated in extensive experimental results, the designed adaptive SRUKF combined with RLS-based model identification is a promising SOC estimation approach. Compared with other commonly used Kalman filter-based methods, the proposed algorithm has higher precision in the SOC estimation.

Uncertainty of greenhouse gas (GHG) emissions was analyzed using the parametric Monte Carlo simulation (MCS) method and the non-parametric bootstrap method. There was a certain number of observations required of a dataset before GHG emissions reached an asymptotic value. Treating a coefficient (i.e., GHG emission factor) as a random variable did not alter the mean; however, it yielded higher uncertainty of GHG emissions compared to the case when treating a coefficient constant. The non-parametric bootstrap method reduces the variance of GHG. A mathematical model for estimating GHG emissions should treat the GHG emission factor as a random variable. When the estimated probability density function (PDF) of the original dataset is incorrect, the nonparametric bootstrap method, not the parametric MCS method, should be the method of choice for the uncertainty analysis of GHG emissions.

The effect of different supports such as silica (SBA-15), activated carbon (AC), and mesoporous alumina (Al2O3) on catalytic activities of hydrotreating nickel molybdenum (NiMo) catalysts was demonstrated for upgrading vacuum residue. Nitrogen adsorption-desorption analysis showed that SBA-15 and the AC-supported NiMo catalyst possessed a very high surface area compared to the alumina-supported catalyst. However, NiMo/Al2O3 catalyst possesses a higher pore diameter and pore volume with an appropriate surface area. X-ray diffraction (XRD) analysis showed that active metals were dispersed in the catalytic supports. Transmission electron microscopy (TEM) analysis revealed the presence of type II active MoS2 sites in the NiMo/Al2O3 catalyst, which showed weak metal-support interactions having a high intrinsic activity. Catalyst activities such as hydrodesulfurization (HDS), hydrodemetallization (HDM) and asphaltene conversion (HDAs), and hydrocracking conversions of a vacuum residue were e... [more]

As the core equipment of a traction power supply system, the traction transformer is very important to ensure the safe and reliable operation of the system. At present, the three-ratio method is mainly used to distinguish transformer faults, whereas such a method has some defects, such as insufficient coding and over-general fault classification. At the same time, on-site maintenance personnel make an empirical judgment based on various test data, which is subjective and uncertain to a certain extent. For cases with multiple abnormal data and relatively complex conditions, on-site personnel often need to discuss and even dismantle the transformer to identify the fault, which is time-consuming and costly. In order to improve the effect of fault diagnosis for traction transformer, this paper uses Bayesian network to correlate the cause and effect of various tests and faults. By combining the results of field tests, the fault is diagnosed by the causal probability of the Bayesian network,... [more]

Wind power generation is one of the renewable energy generation methods which maintains good momentum of development at present. However, its extremely intense intermittences and uncertainties bring great challenges to wind power integration and the stable operation of wind power grids. To achieve accurate prediction of wind power generation in China, a hybrid prediction model based on the combination of Wavelet Decomposition (WD) and Long Short-Term Memory neural network (LSTM) is constructed. Firstly, the nonstationary time series is decomposed into multidimensional components by WD, which can effectively reduce the volatility of the original time series and make them more stable and predictable. Then, the components of the original time series after WD are used as input variables of LSTM to predict the national wind power generation. Forty points were used, 80% as training samples and 20% as testing samples. The experimental results show that the MAPE of WD-LSTM is 5.831, performing... [more]

In this paper, a peer-to-peer (P2P) renewable energy trading mechanism for microgrids when energy suppliers are equipped with storage devices is studied. A dynamic energy storage management strategy based on the local trading price is proposed and each supplier decides the amount of energy to be sold and stored in real time. An iterative auction algorithm is presented to obtain the market equilibrium and optimal energy allocation schedule. The economic analysis of introducing energy storage devices in this trading market is further studied. Numerical examples of two 7 × 24-h energy trading scenarios with 20 consumers and 20 solar energy producers are used to illustrate the feasibility of this proposed trading mechanism, with sensitivity analysis of different parameters on social welfare. A comparison of the hourly optimal local trading price of these two markets is demonstrated to explain the dynamic process. It is found that in those days with high solar radiation, compared with the m... [more]

Water vapor sorption in salt hydrates is a promising method to realize seasonal solar heat storage. Several of these materials have already shown promising performance for this application. However, a significant bottle neck for applications is the low thermal conductivity. In this study, several fabrication methods of the fixation of salts and their hydrates on metals to overcome the problem are presented. The products are analyzed concerning the hydration states, the corrosion behavior, the chemical compatibility, and the mechanical stability.

This article presents a field test of how deep renovation affects indoor climate quality. The studied apartment building was built in 1968 and is located in Finland, within the Nordic climate zone. The deep renovation included façade repair with extra insulation, new windows with trickle vents, new balcony glass and doors, and the installation of an exhaust air heat pump into the existing mechanical exhaust air ventilation. The indoor climate conditions and building envelope tightness were measured before and after the renovation. As a result of these energy renovation measures, the building envelope tightness improved by nearly 40% and the uncontrolled supply of air (draughts) decreased by approximately 24%. The overall energy consumption of the building decreased by 45%. Above all, the long testing period gives credibility to the study. The field test brought up the challenge of supplying an adequate amount of fresh air. This article highlights the fact that windows are part of a mec... [more]

Energy transitions around the world will change the spatial fingerprint of the electricity sector, but there is a lack of studies on citizen preferences for siting the future mix of electricity technologies. Using the case of Switzerland in 2035, we present a serious board game to form and elicit citizen preferences for spatial siting of a full mix of electricity technologies and we test this game with 44 participants in the city of Zurich. The game proves to help elicit valid preferences of the participants and lead to measurable learning effects about this complex, multi-dimensional topic. The results show that these 44 participants prefer a diverse mix of renewable technologies for Switzerland in 2035. In terms of siting, these participants consistently choose the efficiency strategy, where new plants are concentrated in the areas where they produce most electricity at least cost, in contrast to the strategy of regional equity, where all Swiss regions would equally build new generat... [more]