This paper explores current approaches and future directions for energy efficiency education and training in the tertiary sector. Energy efficiency is a significant element in many jobs across the economy, with potential for substantial growth. It crosses disciplinary boundaries, as the range of skills and knowledge required by practitioners is broad, reflecting the diversity and expanding range of work roles that require energy efficiency skills and knowledge. Limitations of education and training contribute to a situation where business and consumer decision-making often involves little or no consideration of energy, so outcomes are often sub-optimal. This increases costs, environmental and social impacts and undermines productivity improvement. As the significance of energy efficiency skills and knowledge in workplaces increases, more flexible and varied education and training models are needed to allow workers to upskill, gain new skills and integrate energy efficiency into busines... [more]

In this study, we propose a voltage estimation method for the radial distribution network with distributed generators (DGs) using high-precision measurements (HPMs). The proposed method uses the section loads center for voltage estimation because individual loads are not measured in the distribution system. The bus voltage was estimated through correction of the section load center by using an HPM at the end of the main feeder. The correction parameter of the section load center was calculated by comparing the initial voltage estimates and the measurements of the HPMs. After that, the voltage of the main feeder was re-estimated. Finally, the bus voltage in the lateral feeder was estimated based on the voltage estimates in the main feeder and the current measurements in the lateral feeder. The accuracy of the proposed algorithm was verified through case studies by using test systems implemented in MATLAB, Simulink, and Python environments. In order to verify the utilization of the propo... [more]

Under the new climate regime, renewable energy (RE) has received particular attention for mitigating the discharge of greenhouse gas. According to the third energy master plan in South Korea, by 2040, 30−35% of the energy demand must met with RE sources. To ensure relevant policy design to achieve this goal, it is crucial to analyze the public’s willingness to accept community-based RE projects. This study conducted a nationwide survey to understand the opinion of the public and also that of local inhabitants living near a RE project. A choice experiment was employed to measure public preferences toward RE projects. The analysis reveals that the type of energy source, distance to a residential area, and annual percentage incentives could affect acceptance levels. Additionally, investment levels were a factor in local inhabitants’ acceptance of energy-related projects. This study presents the relevant policy implications in accordance with the analysis results.

Penetration level of renewable energy (RE) in the utility grid is continuously increasing to minimize the environmental concerns, risk of energy security, and depletion of fossil fuels. The uncertain nature and availability of RE power for a short duration have created problems related to the protection, grid security, power reliability, and power quality. Further, integration of RE sources near the load centers has also pronounced the protection issues, such as false tripping, delayed tripping, etc. Hence, this paper introduces a hybrid grid protection scheme (HGPS) for the protection of the grid with RE integration. This combines the merits of the Stockwell Transform, Hilbert Transform, and Alienation Coefficient to improve performance of the protection scheme. The Stockwell Transform-based Median and Summation Index (SMSI) utilizing current signals, Hilbert Transform-based derivative index (HDI) utilizing voltage signals, and Alienation Coefficient index (ACI) utilizing voltage sign... [more]

Thermal interactions through longwave radiation exchange between buildings, especially in a dense urban environment, can strongly influence a building’s energy use and environmental impact. However, these interactions are either neglected or oversimplified in urban building energy modeling. We developed a new feature in EnergyPlus to explicitly consider this term in the surface heat balance calculations and developed an algorithm to batch calculating the surrounding surfaces’ view factors using a ray-tracing technique. We conducted a case study with a district in the Chicago downtown area to evaluate the longwave radiant heat exchange effects between urban buildings. Results show that the impact of the longwave radiant effects on annual energy use ranges from 0.1% to 3.3% increase for cooling and 0.3% to 3.6% decrease for heating, varying among individual buildings. At the district level, the total energy demand increases by 1.39% for cooling and decreases 0.45% for heating. We also ob... [more]

In this paper, the variations in hydropower generation are addressed considering the seasonality and ENSO (El Niño-Southern Oscillation) episodes. The dynamic hypothesis and the stock-flow structure of the Colombian electricity market were analyzed. Moreover, its dynamic behavior was analyzed by using Dynamic Systems tools aimed at providing deep insight into the system. The MATLAB/Simulink model was used to evaluate the Colombian electricity market. Since we combine System Dynamics and Dynamic Systems, this methodology provides a novel insight and a deeper analysis compared with System Dynamics models and can be easily implemented by policymakers to suggest improvements in regulation or market structures. We also provide a detailed description of the Colombian electricity market dynamics under a broad range of demand growth rate scenarios inspired by the bifurcation and control theory of Dynamic Systems.

To address inaccurate prediction in remaining useful life (RUL) in current Lithium-ion batteries, this paper develops a Long Short-Term Memory Network, Sliding Time Window (LSTM-STW) and Gaussian or Sine function, Levenberg-Marquardt algorithm (GS-LM) fusion batteries RUL prediction method based on ensemble empirical mode decomposition (EEMD). Firstly, EEMD is used to decompose the original data into high-frequency and low-frequency components. Secondly, LSTM-STW and GS-LM are used to predict the high-frequency and low-frequency components, respectively. Finally, the LSTM-STW and GS-LM prediction results are effectively integrated in order to obtain the final prediction of the lithium-ion battery RUL results. This article takes the lithium-ion battery data published by NASA as input. The experimental results show that the method has higher accuracy, including the phenomenon of sudden capacity increase, and is less affected by the prediction starting point. The performance of the propos... [more]

This paper presents an analysis related to thermal simulation of the test structure dedicated to heat-diffusion investigation at the nanoscale. The test structure consists of thin platinum resistors mounted on wafer made of silicon dioxide. A bottom part of the structure contains the silicon layer. Simulations were carried out based on the thermal simulator prepared by the authors. Simulation results were compared with real measurement outputs yielded for the mentioned test structure. The authors also propose the Grünwald−Letnikov fractional space-derivative Dual-Phase-Lag heat transfer model as a more accurate model than the classical Fourier−Kirchhoff (F−K) heat transfer model. The approximation schema of proposed model is also proposed. The accuracy and computational properties of both numerical algorithms are presented in detail.

The rapidly increasing penetration of wind power into sending-side systems makes the wind power curtailment problem more severe. Enhancing the total transfer capability (TTC) of the transmission channel allows more wind power to be delivered to the load center; therefore, the curtailed wind power can be reduced. In this paper, a new method is proposed to enhance TTC, which works by optimizing the day-ahead thermal generation schedules. First, the impact of thermal generation plant/unit commitment on TTC is analyzed. Based on this, the day-ahead thermal generation scheduling rules to enhance TTC are proposed herein, and the corresponding optimization models are established and solved. Then, the optimal day-ahead thermal generation scheduling method to enhance TTC is formed. The proposed method was validated on the large-scale wind power base sending-side system in Gansu Province in China; the results indicate that the proposed method can significantly enhance TTC, and therefore, reduce... [more]

This study forecasts electricity demand in a smart grid environment. We present a prediction method that uses a combination of forecasting values based on time-series clustering. The clustering of normalized periodogram-based distances and autocorrelation-based distances are proposed as the time-series clustering methods. Trigonometrical transformation, Box−Cox transformation, autoregressive moving average (ARMA) errors, trend and seasonal components (TBATS), double seasonal Holt−Winters (DSHW), fractional autoregressive integrated moving average (FARIMA), ARIMA with regression (Reg-ARIMA), and neural network nonlinear autoregressive (NN-AR) are used for demand forecasting based on clustering. The results show that the time-series clustering method performs better than the method using the total amount of electricity demand in terms of the mean absolute percentage error (MAPE).

The present paper is a review on efficiency issues related to three important sectors of the transportation systems: railways, electrical vehicles, and marine. For the three sectors, the authors, in reference of their knowledge and research area, show the results of a wide literature analysis, in order to highlight which are the measures, in terms of technological solutions and management techniques, which are recently investigated and implemented, for improving the three transportation systems, from the point of view of efficiency. In particular, for the railway transportation sector, a wide analysis is presented, detecting which are the main measures adopted for improving the efficiency, related to the power systems for supplying trains and to the train traffic control, with a focus on the storage system integration. For electric road vehicles the analysis is focused on the plug-in electrical vehicles and on the infrastructure for their recharge, with an emphasis on how these vehicle... [more]

Glazing is considered as a preferred solution for the buildability, aesthetic, and comfort of commercial buildings since glass cover can protect occupants from external environmental conditions, ensure the light transmission, and provide view and ventilation. At the same time, in the context of climate change and global warming, the use of renewable solar energy, such as solar and wind power, are encouraged to be utilized. Specifically, solar energy has become a renewable energy source that is clean and endless, at reasonable cost, to contribute to energy security as well as ensure sustainable development. Therefore, the study proposes a method for supporting the decision making in installing solar panels on vertical glazing façades of the building in the worst case that the remaining radiant energy from the sun was only transferred to the inside of the building. The Life Cycle Assessment and the Life Cycle Costing methodologies are applied to consider both environmental and economic a... [more]

This study analyzed the cost performance of electricity efficiency programs implemented by 116 investor-owned utilities between 2009 and 2015 in 41 states, representing about three-quarters of the total spending on U.S. efficiency programs. We applied our typology to characterize efficiency programs along several dimensions (market sector, technology, delivery approach, and intervention strategy) and report the costs incurred by utilities and other program administrators to achieve electricity savings as a result of the programs. Such cost performance data can be used to compare relative costs of different types of efficiency programs, evaluate efficiency options alongside other electricity resources, benchmark local efficiency programs against regional and national cost estimates, and assess the costs of meeting state efficiency policies. The savings-weighted average cost of saved electricity for the period was $0.025/kilowatt-hour (kWh). The cost of saved electricity for programs tha... [more]

Nowadays, the high share of electricity production from renewables drives coal-fired power plants to adopt a more flexible operation scheme and, at the same time, maintain flue gas emissions within respective standards. A 500 kWth pulverized coal furnace was used to study pre-dried lignite combustion or co-combustion as an available option for these plants. Bituminous coal from Czech Republic and pre-dried lignite from Greece were blended for the experiments. Particle emissions measurements with a heated Electrical Low Pressure Impactor (ELPI+) and Scanning Electron Microscopy with Energy Dispersive Spectroscopy (SEM/EDS) analyses were performed. The effect of the pre-dried lignite proportions in the fuel feed and the combustion conditions regarding the combustion air staging were the two parameters selected for this study. Skeletal density values were measured from the cyclone prior to the impactor. Results are depicted with respect to the aerodynamic and Stokes diameter for impactor... [more]

Battery-less sensors need a fast and stable wireless charging mechanism to ensure that they are being correctly activated and properly working. The major drawback of state-of-the-art wireless power transfer solutions stands in the maximum Equivalent Isotropic Radiated Power (EIRP) established from local regulations, even using directional antennas. Indeed, the maximum transferred power to the load is limited, making the charging process slow. To overcome such limitation, a novel method for implementing an effective wireless charging system is described. The proposed solution is designed to guarantee many independent charging contributions, i.e., multiple tones are used to distribute power along transmitted carriers. The proposed rectenna system is composed by a set of narrow-band rectifiers resonating at specific target frequencies, while combining at DC. Such orthogonal frequency schema, providing independent charging contributions, is not affected by the phase shift of incident signa... [more]

This paper presents an alternative approach to the flow control of an oxidizer in a proton exchange membrane (PEM) fuel cell system in which pure oxygen is the gas supplied to the cathode channel of the stack. The proposed oxygen flow control is implemented based on information about the current drawn from the fuel cell stack and the voltage variation in the stack. This information and a fuzzy-logic-based control algorithm are used to increase oxygen utilization in a PEM fuel cell system without a recirculation system in relation to the control, in which the oxygen flow rate is determined only in proportion to the current drawn from the stack. To verify the validity of the adopted assumptions, simulation tests of the proposed fuzzy control algorithm were conducted, for which parameters were adopted arbitrarily and determined with help of genetic algorithms. For simulation research, the proposed empirical mathematical model was used, which describes the mathematical relationship between... [more]

Our study combines machine learning techniques and dynamic moving window and expanding window methods to predict crises in the US natural gas market. Specifically, as machine learning models, we employ extreme gradient boosting (XGboost), support vector machines (SVMs), a logistic regression (LogR), random forests (RFs), and neural networks (NNs). The data set used to develop the model covers the period 1994 to 2019 and contains 121 explanatory variables, including those related to crude oil, stock markets, US bond and gold futures, the CBOE Volatility Index (VIX) index, and agriculture futures. To the best of our knowledge, this study is the first to combine machine learning techniques with dynamic approaches to predict US natural gas crises. To improve the model’s prediction accuracy, we applied a suite of parameter-tuning methods (e.g., grid-search) to select the best-performing hyperparameters for each model. Our empirical results demonstrated very good prediction accuracy for US n... [more]

This paper presents a novel deep learning architecture for short-term load forecasting of building energy loads. The architecture is based on a simple base learner and multiple boosting systems that are modelled as a single deep neural network. The architecture transforms the original multivariate time series into multiple cascading univariate time series. Together with sparse interactions, parameter sharing and equivariant representations, this approach makes it possible to combat against overfitting while still achieving good presentation power with a deep network architecture. The architecture is evaluated in several short-term load forecasting tasks with energy data from an office building in Finland. The proposed architecture outperforms state-of-the-art load forecasting model in all the tasks.

Recently we demonstrated the simultaneous detection of the chemiluminescence of the radicals OH* (310 nm) and CH* (430 nm), as well as the thermal radiation of soot in laminar and turbulent methane/air diffusion flames. As expected, a strong spatial and temporal coupling of OH* and CH* in laminar and moderate turbulent flames was observed. Taking advantage of this coupling, multispecies tomography enables us to quantify the reconstruction quality completely independent of any phantom studies by simply utilizing the reconstructed distribution of both species. This is especially important in turbulent flames, where it is difficult to separate measurement noise from turbulent fluctuations. It is shown that reconstruction methods based on Tikhonov regularization should be preferred over the widely used algebraic reconstruction technique (ART) and multiplicative algebraic reconstruction techniques (MART), especially for high-speed imaging or generally in the limit of low signal-to-noise rat... [more]

Kites can be used to harvest wind energy at higher altitudes while using only a fraction of the material required for conventional wind turbines. In this work, we present the kite system of Kyushu University and demonstrate how experimental data can be used to train machine learning regression models. The system is designed for 7 kW traction power and comprises an inflatable wing with suspended kite control unit that is either tethered to a fixed ground anchor or to a towing vehicle to produce a controlled relative flow environment. A measurement unit was attached to the kite for data acquisition. To predict the generated tether force, we collected input−output samples from a set of well-designed experimental runs to act as our labeled training data in a supervised machine learning setting. We then identified a set of key input parameters which were found to be consistent with our sensitivity analysis using Pearson input−output correlation metrics. Finally, we designed and tested the a... [more]

This paper is intended to perform a comparative and qualitative review among eight tools to measure energy sustainability. Therefore, it was necessary to create a theoretical and conceptual framework based on four criterias of selection and six categories of comparison. In this work, the conceptual bases that supported the research and the methodology created to carry out the comparative review will be presented. This analysis was based on the intrinsic concepts of energy sustainability of each of the reviewed tools with a critical qualitative analysis. Some conclusions shown through the conceptual framework developed that it was possible to apply an innovative methodology to qualitatively compare different tools to measure sustainability. The importance of this reflects the difficulty of conceptualizing the subjectivity of sustainable development, as shown throughout the paper, where it is often not possible to obtain a measurable result since the measured phenomenon is too complex to... [more]

The growing number of renewable energy plants connected to the power system through static converters have been pushing the development of new strategies to ensure transient stability of these systems. The virtual synchronous generator (VSG) emerged as a way to contribute to the system stabilization by emulating the behavior of traditional synchronous machines in the power converters operation. This paper proposes a modification in the VSG implementation to improve its contribution to the power system transient stability. The proposal is based on the virtualization of the resistive superconducting fault current limiters’ (SFCL) behavior through an adaptive control that performs the VSG armature resistance change in short-circuit situations. A theoretical analysis of the problem is done based on the equal-area criterion, simulation results are obtained using PSCAD, and experimental results are obtained in a Hardware-In-the-Loop (HIL) test bench to corroborate the proposal. Results show... [more]

This paper introduces a new point-absorber wave energy converter (WEC) with a moonpool buoy—the moonpool platform wave energy converter (MPWEC). The MPWEC structure includes a cylinder buoy and a moonpool buoy and a Power Take-off (PTO) system, where the relative movement between the cylindrical buoy and the moonpool buoy is exploited by the PTO system to generate energy. A 1:10 scale model was physically tested to validate the numerical model and further prove the feasibility of the proposed system. The motion responses of and the power absorbed by the MPWEC studied in the wave tank experiments were also numerically analyzed, with a potential approach in the frequency domain, and a computational fluid dynamics (CFD) code in the time domain. The good agreement between the experimental and the numerical results showed that the present numerical model is accurate enough, and therefore considering only the heave degree of freedom is acceptable to estimate the motion responses and power ab... [more]

To optimize the thermal design of AlGaN-GaN high-electron-mobility transistors (HEMTs), which incorporate high power densities, an accurate prediction of the underlying thermal transport mechanisms is crucial. Here, a HEMT-structure (Al0.17Ga0.83N, GaN, Al0.32Ga0.68N and AlN on a Si substrate) was investigated using a time-domain thermoreflectance (TDTR) setup. The different scattering contributions were investigated in the framework of phonon transport models (Callaway, Holland and Born-von-Karman). The thermal conductivities of all layers were found to decrease with a temperature between 300 K and 773 K, due to Umklapp scattering. The measurement showed that the AlN and GaN thermal conductivities were a magnitude higher than the thermal conductivity of Al0.32Ga0.68N and Al0.17Ga0.83N due to defect scattering. The layer thicknesses of the HEMT structure are in the length scale of the phonon mean free path, causing a reduction of their intrinsic thermal conductivity. The size-effect of... [more]

The current paper investigates two particular features of a novel rotary split engine. This internal combustion engine incorporates a number of positive advantages in comparison to conventional reciprocating piston engines. As a split engine, it is characterized by a significant difference between the expansion and compression ratios, the former being higher. The processes are decoupled and take place simultaneously, in different chambers and on the different sides of the rotating pistons. Initially, a brief description of the engine’s structure and operating principle is provided. Next, the configuration of the compression chamber and the sealing system are examined. The numerical study is conducted using CFD simulation models, with the relevant assumptions and boundary conditions. Two parameters of the compression chamber were studied, the intake port design (initial and optimized) and the sealing system size (short and long). The best option was found to be the combination of the op... [more]