Accurate and comprehensive methods for the assessment of radiated electromagnetic emissions in modern electric transportation systems are a necessity. The characteristics and susceptibility of modern victim signaling and communication radio services, operating within and outside the right-of-way, require an update of the measurement methods integrating or replacing the swept frequency technique with time domain approaches. Applicable standards are the EN 50121 (equivalent to the IEC 62236) and Urban Mass Transport Association (UMTA) with additional specifications from project contracts. This work discusses the standardized methods and settings, and the representative operating conditions, highlighting areas where improvements are possible and opportune (statistical characterization of measurement results, identification and distinction of emissions and line resonances, and narrowband and broadband phenomena). In particular for the Electromagnetic Compatibility (EMC) assessment with new... [more]

The State of Charge (SOC) estimation is a significant issue for safe performance and the lifespan of Lithium-ion (Li-ion) batteries. In this paper, a Robust Adaptive Online Long Short-Term Memory (RoLSTM) method is proposed to extract SOC estimation for Li-ion Batteries in Electric Vehicles (EVs). This real-time, as its name suggests, method is based on a Recurrent Neural Network (RNN) containing Long Short-Term Memory (LSTM) units and using the Robust and Adaptive online gradient learning method (RoAdam) for optimization. In the proposed architecture, one sequential model is defined for each of the three inputs: voltage, current, and temperature of the battery. Therefore, the three networks work in parallel. With this approach, the number of LSTM units are reduced. Using this suggested method, one is not dependent on precise battery models and can avoid complicated mathematical methods. In addition, unlike the traditional recursive neural network where content is re-written at any tim... [more]

This paper proposes a Electro-Magnetic Transient (EMT) model of a 2 GW offshore network with the parallel operation of two Modular Multi-level Converter (MMC)—High Voltage Direct Current (HVDC) transmission links connecting four Offshore Wind Farms (OWFs) to two onshore systems, which represent a large scale power system. Additionally, to mitigate the challenges corresponding to voltage and frequency stability issues in large scale offshore networks, a Direct Voltage Control (DVC) strategy is implemented for the Type-4 Wind Generators (WGs), which represent the OWFs in this work. The electrical power system is developed in the power system simulation software RSCADTM, that is suitable for performing EMT based simulations. The EMT model of 2 GW offshore network with DVC in Type-4 WGs is successfully designed and it is well-coordinated between the control structures in MMCs and WGs.

In Korea apartment buildings, most energy is consumed as heating energy. In order to reduce heating energy in apartment buildings, it is required to reduce the amount of energy used in heating systems. Energy saving in heating systems can be achieved through operation and control based on efficient operation plans. The efficient operation plan of the heating system should be based on the predicted heating load. Thus, various methods have been developed for predicting heating loads. Recently, artificial intelligence techniques (e.g., ANN: artificial neural network) have been used to predict heating loads. The process for determination of input data variables is necessary to obtain the accuracy of predicted results using an ANN model. However, there is a lack of studies to evaluate the accuracy level of the predicted results caused by the selection and combination of input variables. There is a need to evaluate the performance of an ANN model for prediction of residential heating loads.... [more]

A novel high-resolution method for forecasting cloud motion from all-sky images using deep learning is presented. A convolutional neural network (CNN) was created and trained with more than two years of all-sky images, recorded by a hemispheric sky imager (HSI) at the Institute of Meteorology and Climatology (IMUK) of the Leibniz Universität Hannover, Hannover, Germany. Using the haze indexpostprocessing algorithm, cloud characteristics were found, and the deformation vector of each cloud was performed and used as ground truth. The CNN training process was built to predict cloud motion up to 10 min ahead, in a sequence of HSI images, tracking clouds frame by frame. The first two simulated minutes show a strong similarity between simulated and measured cloud motion, which allows photovoltaic (PV) companies to make accurate horizon time predictions and better marketing decisions for primary and secondary control reserves. This cloud motion algorithm principally targets global irradiance... [more]

This paper presents analysis and study of the single-phase transverse-flux machine. The finite element method results of the machine are compared with the laboratory measurements to confirm the accuracy of the computer model. This computer model is then used to investigate the effect of the machine’s geometry on its output characteristics. Parametric analysis of the machine is carried out to find the optimal air-gap diameter at which the cogging torque of the machine is minimal. In addition, the influence of the coil cross-section on the torque and output power characteristics of the machine is investigated and discussed.

Modern energy automation solutions and demand response applications rely on load profiles to monitor and manage electricity consumption effectively. The introduction of smart control systems capable of handling additional fuzzy parameters, such as weather data, through machine learning methods, offers valuable insights in an attempt to adjust consumer behavior optimally. Following recent advances in the field of fuzzy control, this study presents the design and implementation of a fuzzy control system that processes environmental data in order to recommend minimum energy consumption values for a residential building. This system follows the forward chaining Mamdani approach and uses decision tree linearization for rule generation. Additionally, a hybrid feature selector is implemented based on XGBoost and decision tree metrics for feature importance. The proposed structure discovers and generates a small set of fuzzy rules that highlights the energy consumption behavior of the building... [more]

This paper, for the first time, investigates the possibility of exploiting a nonlinear bistable snap-through buckling structure employing piezoelectric transducers, to implement an autonomous sensor of mechanical vibrations, with an embedded energy harvesting functionality. The device is operated in the presence of noisy vibrations superimposed on a subthreshold deterministic (sinusoidal) input signal. While the capability of the device to harvest a significant amount of energy has been demonstrated in previous works, here, we focus on the signal processing methodology aimed to extract from the sensor output the information about the noise level (in terms of the standard deviation) and the root mean square amplitude of the deterministic component. The developed methodology, supported by experimental evidence, removes the contribution to the overall piezoelectric output voltage ascribable to the deterministic component using a thresholding and windowing algorithm. The contribution to th... [more]

During the day, photovoltaic (PV) systems are exposed to different sunlight conditions in addition to partial shading (PS). Accordingly, maximum power point tracking (MPPT) techniques have become essential for PV systems to secure harvesting the maximum possible power from the PV modules. In this paper, optimized control is performed through the application of relatively newly developed optimization algorithms to PV systems under Partial Shading (PS) conditions. The initial value of the duty cycle of the boost converter is optimized for maximizing the amount of power extracted from the PV arrays. The emperor penguin optimizer (EPO) is proposed not only to optimize the initial setting of duty cycle but to tune the gains of controllers used for the boost converter and the grid-connected inverter of the PV system. In addition, the performance of the proposed system based on the EPO algorithm is compared with another newly developed optimization technique based on the cuttlefish algorithm... [more]

Accurate and real-time acquisition of vehicle state parameters is key to improving the performance of vehicle control systems. To improve the accuracy of state parameter estimation for distributed drive electric vehicles, an unscented Kalman filter (UKF) algorithm combined with the Huber method is proposed. In this paper, we introduce the nonlinear modified Dugoff tire model, build a nonlinear three-degrees-of-freedom time-varying parametric vehicle dynamics model, and extend the vehicle mass, the height of the center of gravity, and the yaw moment of inertia, which are significantly influenced by the driving state, into the vehicle state vector. The vehicle state parameter observer was designed using an unscented Kalman filter framework. The Huber cost function was introduced to correct the measured noise and state covariance in real-time to improve the robustness of the observer. The simulation verification of a double-lane change and straight-line driving conditions at constant spee... [more]

In this work, we present results from the largest study of measured, whole-building energy performance for commercial LEED-certified buildings, using 2016 energy use data that were obtained for 4417 commercial office buildings (114 million m2) from municipal energy benchmarking disclosures for 10 major U.S. cities. The properties included 551 buildings (31 million m2) that we identified as LEED-certified. Annual energy use and greenhouse gas (GHG) emission were compared between LEED and non-LEED offices on a city-by-city basis and in aggregate. In aggregate, LEED offices demonstrated 11% site energy savings but only 7% savings in source energy and GHG emission. LEED offices saved 26% in non-electric energy but demonstrated no significant savings in electric energy. LEED savings in GHG and source energy increased to 10% when compared with newer, non-LEED offices. We also compared the measured energy savings for individual buildings with their projected savings, as determined by LEED poi... [more]

Building Integrated Photovoltaic (BIPV) modules are a new type of photovoltaic (PV) modules that are widely used in distributed PV stations on the roof of buildings for power generation. Due to the high installation location, BIPV modules suffer from lightning hazard greatly. In order to evaluate the risk of lightning stroke and consequent damage to BIPV modules, the studies on the lightning attachment characteristics and the lightning energy withstand capability are conducted, respectively, based on numerical and experimental methods in this paper. In the study of lightning attachment characteristics, the numerical simulation results show that it is easier for the charges to concentrate on the upper edge of the BIPV metal frame. Therefore, the electric field strength at the upper edge is enhanced to emit upward leaders and attract the lightning downward leaders. The conclusion is verified through the long-gap discharge experiment in a high voltage lab. From the experimental study of m... [more]

The oil injection method was studied to maximize the cooling performance of an electric vehicle motor with a hairpin winding. The cooling performance of the motor using the oil cooling method is proportional to the contact area of the oil and the coil. A numerical analysis was conducted to examine the effect of the spray nozzle type on the oil flow. The dripping nozzle forms the thickest oil film on the coil, making it the most effective for cooling of hairpin-type motors. Subsequently, an experimental study was conducted to optimize the nozzle diameter and number of nozzles. When the inlet diameter and number was 6.35 mm and 6, the oil film formation rate was 53%, yielding the most uniform oil film. Next, an experiment was performed to investigate the effects of the oil temperature and flow rate on the oil flow. The oil film formation rate was the highest (83%) when the oil temperature was 40 °C and the flow rate was 6 LPM.

Molten chloride salt is recognized as a promising heat transfer and storage medium in concentrating solar power in recent years, but there is a serious lack for thermal property data of molten chloride salts. In this work, local structures and thermal properties for molten chloride salt—including NaCl, MgCl2, and ZnCl2—were precisely simulated by Born−Mayer−Huggins (BMH) potential in a rigid ion model (RIM) and a polarizable ion model (PIM). Compared with experimental data, distances between cations, densities, and heat capacities of molten chloride slats calculated from PIM agree remarkably better than those from RIM. The polarization effect brings an extra contribution to screen large repulsive Coulombic interaction of cation−cation, and then it makes shorter distance between cations, larger density and lower heat capacity. For NaCl, MgCl2, and ZnCl2, PIM simulation deviations of distances between cations are respectively 3.8%, 3.7%, and 0.3%. The deviations of density and heat capac... [more]

Energy obtained from renewable sources is an important element of the sustainable development strategy of the European Union and its member states. The aim of this research is, therefore, to assess the potential and use of renewable energy sources and their effectiveness from the regional perspective in Poland. The research covered the years 2012 and 2018. The diversification of production and potential of renewable energy sources was defined on the basis of biogas and biomass. Calculations made using the data envelopment analysis (DEA) method showed that, in 2012, only three voivodeships achieved the highest efficiency in terms of the use of biogas and biomass resources; in 2018, this number increased to four. Comparing the effective units in 2012 and 2018, it can be seen that their efficiency frontier moved upwards by 56% in terms of biogas and 21% in terms of to biomass. Despite a large relative increase in the production of heat from biogas by 99% compared to the production of heat... [more]

The aerodynamics of a rotor with pitch imbalance has been investigated experimentally and numerically in the present work. The comparison of mean velocity and turbulence intensity in the balanced and unbalanced cases indicated that a pitch imbalance modifies both the mean velocity and the turbulent activity; the latter is weakly increased by the imbalance. Spectral analysis indicated that the dynamics of the wake is also affected by the pitch imbalance since the tip vortices loose strength and disorganise more quickly than in the balanced case. The pitch imbalance has, however, a detrimental effect on the power coefficient and it affects the thrust coefficient as well. Only the blade affected by the imbalance shows significant modifications of the applied load, while the other blades operate with the same loading conditions.

Green hydrogen for mobility represents an alternative to conventional fuel to decarbonize the transportation sector. Nevertheless, the thermodynamic properties make the transport and the storage of this energy carrier at standard conditions inefficient. Therefore, this study deploys a georeferenced optimal transport infrastructure for four base case scenarios in France and Germany that differs by production distribution based on wind power potential and demand capacities for the mobility sector at different penetration shares for 2030 and 2050. The restrained transport network to the road infrastructure allows focusing on the optimum combination of trucks operating at different states of aggregations and storage technologies and its impact on the annual cost and hydrogen flow using linear programming. Furthermore, four other scenarios with production cost investigate the impact of upstream supply chain cost, and eight scenarios with daily transport and storage optimization analyse the... [more]

Wireless inductive-coupled power transfer is a very appealing technique for the battery recharge of autonomous devices like surveillance drones. The charger design mainly focuses on lightness and fast-charging to improve the drone mission times and reduce the no-flight gaps. The charger secondary circuit mounted on the drone generally consists of a full-bridge rectifier and a second-order filter. The filter cut-off frequency is usually chosen to make the rectifier output voltage constant and so that the battery is charged with continuous quantities. Previous works showed that an increase in power transfer is achieved, if compared to the traditional case, when the second-order filter resonant frequency is close to the double of the wireless charger excitation and the filter works in resonance. This work demonstrates that the condition of resonance is necessary but not sufficient to achieve the power increment. The bridge rectifier diodes must work in discontinuous-mode to improve the po... [more]

The transition of the energy system in Poland has a long time horizon and demands a substantial investment effort supported by proper economic evaluation. It requires a precise Social Discount Rate (SDR) estimation as discounting makes the present value of long-term effects extremely sensitive to the discount rate level. However, Polish policymakers have little information on SDR: the predominant practice applies a priori fixed 5% discount rate, while studies devoted only to Poland are quite rare. To eliminate this research gap, our paper aims at estimating SDR for Poland, applicable in energy transition policies. We derive SDR for three datasets varying in length, twofold: using market rates via Consumption Rate of Interest (CRI) and Social Opportunity Cost (SOC) of capital, and prescriptive Ramsey and Gollier approaches based on Social Welfare Function (SWF). The results indicate that the rates based on CRI and SOC deviate substantially with changing data timeframes and market condit... [more]

Along with the increasing share of non-synchronous power sources, the inertia of power systems is being reduced, which can give rise to frequency containment problems should an outage of a generator or a power infeed happen. Low system inertia is eventually unavoidable, thus power system operators need to be prepared for this condition. This paper addresses the problem of low inertia in the power system from two different perspectives. At a system level, it proposes an operation planning methodology, which utilises a combination of power flow and dynamic simulation for calculation of existing inertia and, if need be, synthetic inertia (SI) to fulfil the security criterion of adequate rate of change of frequency (RoCoF). On a device level, it introduces a new concept for active power controller, which can be applied virtually to any power source with sufficient response time to create synthetic inertia. The methodology is demonstrated for a 24 h planning period, for which it proves to b... [more]

The use of air source heat pump systems for space heating and cooling is a convenient retrofitting strategy for reducing building energy costs. This can be combined with the rooftop installation of photovoltaic panels, which can cover, to a significant degree—or even significantly exceed the building’s electricity needs, moving towards the zero energy building concept. Alternatively, increased capacity for rooftop photovoltaic (PV) installation may support the ongoing process of transforming the Greek power system away from the reliance on fossil fuels to potentially become one of the leaders of the energy transition in Europe by 2030. Standard building energy simulation tools allow good assessment of the Heating, Ventilation and Air Conditioning (HVAC) and PV systems’ interactions in transient operation. Further, their use enables the rational sizing and selection of the type of panels type for the rooftop PV installation to maximize the return on investment. The annual performance of... [more]

The paper presents a new concept of determining the resultant position of a UAV (Unmanned Aerial Vehicle) based on individual SBAS (Satellite-Based Augmentation System) determinations from all available EGNOS (European Geostationary Navigation Overlay Service) satellites for the SPP (Single Point Positioning) code method. To achieve this, the authors propose a weighted mean model to integrate EGNOS data. The weighted model was based on the inverse of the square of the mean position error along the component axes of the BLh ellipsoidal frame. The calculations included navigation data from the EGNOS S123, S126, S136 satellites. In turn, the resultant UAV position model was determined using the Scilab v.6.0.0 software. Based on the proposed computational strategy, the mean values of the UAV BLh coordinates’ standard deviation were better than 0.2 m (e.g., 0.0000018° = 0.01″ in angular measurement). Additionally, the numerical solution used made it possible to increase the UAV’s position a... [more]

Despite large amounts of available roof space, long pay-back periods for investments in photovoltaic (PV) power plants often hinder PV installations in industrial parks. Photovoltaic citizen participation initiatives (PV-CPI) are an alternative way of financing PV power plants that add non-financial benefits to these investments. This paper analyzed the feasibility of the installation of PV power plants focused on high rates of self-consumption financed by citizen participation initiatives on the roofs of five companies located in the Austrian Ennshafen industrial business park based on the net present value and the discounted pay-back period and compared it to a standard financing scheme, assuming a predetermined interest rate for participants as well as economies of scale with respect to the specific installation costs due to a joint purchase of the PV power plants. To calculate the feasibility, site-specific data and literature input have been used. The results show that despite an... [more]

The high share of electric vehicles (EVs) in the transportation sector is one of the main pillars of sustainable development. Availability of a suitable charging infrastructure and an affordable electricity cost for battery charging are the main factors affecting the increased adoption of EVs. The installation location of fixed charging stations (FCSs) may not be completely compatible with the changing pattern of EV accumulation. Besides, their power withdrawal location in the network is fixed, and also, the time of receiving the power follows the EVs’ charging demand. The EV charging demand pattern conflicts with the network peak period and causes several technical challenges besides high electricity prices for charging. A mobile battery energy storage (MBES) equipped with charging piles can constitute a mobile charging station (MCS). The MCS has the potential to target the challenges mentioned above through a spatio-temporal transfer in the required energy for EV charging. Accordingl... [more]

Thin-film organic solar cell (OSC) performances have been investigated in detail by improved analytical computation in this work. The generation of excitons inside OSC has been estimated by using the optical transfer matrix method (OTMM) to include the optical phenomena of the incident light. The dissociation of these excitons into free charge carriers has been investigated to find the most appropriate one. OSC performances have been evaluated by an improved analytical solution of electrical transport equations including (i) exciton generation obtained from OTMM, (ii) dissociation probability incorporating Gaussian distribution to account for the natural fact of the difference in photon-energy producing excitons, (iii) recombination of charge carriers, all together. OSC properties such as JSC, VOC, FF, PCE, Pmax, absorbance, and quantum efficiency have been investigated with the variation of different parameters; this might be useful to improve OSC. Again, the presented detailed deriva... [more]