Commercial buildings consume approximately 1.9 EJ of energy in the United States, 50% of which is for heating, cooling, and lighting applications. It is estimated that windows contribute up to 34% of the energy used for heating and cooling. However, window retrofits are not often undertaken to increase energy efficiency because of the high cost and disruptive nature of window installation. Highly efficient window technologies would also need shading devices for glare prevention and visual comfort. An automated window shading system with an appropriate control strategy is a technology that can reduce energy demand, maintain occupant comfort, and enhance the aesthetics and privacy of the built environment. However, the benefits of the automated shades currently used by the shading industry are not well studied. The topic merits an analysis that will help building owners, designers and engineers, and utilities make informed decisions using knowledge of the impact of this technology on ene... [more]

This article presents the application of data mining (DM) to long-term power quality (PQ) measurements. The Ward algorithm was selected as the cluster analysis (CA) technique to achieve an automatic division of the PQ measurement data. The measurements were conducted in an electrical power network (EPN) of the mining industry with distributed generation (DG). The obtained results indicate that the application of the Ward algorithm to PQ data assures the division with regards to the work of the distributed generation, and also to other important working conditions (e.g., reconfiguration or high harmonic pollution). The presented analysis is conducted for the area-related approach—all measurement point data are connected at an initial stage. The importance rate was proposed in order to indicate the parameters that have a high impact on the classification of the data. Another element of the article was the reduction of the size of the input database. The reduction of input data by 57% ass... [more]

This study investigates the production of biobased carbon materials from potato waste and its application in energy storage systems such as supercapacitors. Three different categories of carbons were produced: hydrochar (HC) from hydrothermal carbonization (HTC) at three different temperatures (200 °C, 220 °C, 240 °C) and two different duration times (two hours and five hours), pyrolyzed hydrochar (PHC) obtained via pyrolysis of the HTC chars at 600 °C and 900 °C for two hours and pyrochar from the pyrolysis of biomass at 600 °C and 900 °C for two hours. The carbon samples were analysed regarding their physico-chemical properties such as elemental composition, specific surface area, bulk density and surface functionalities as well as their electrochemical characteristics such as electric conductivity and specific capacity via cyclic voltammetry. N- and O-enriched carbon materials with promising specific surface areas of up to 330 m2 g−1 containing high shares of microporosity were prod... [more]

This paper proposes the concept “active energy agent (AEA)” to characterize the autonomous and interactive entities of power system. The future distribution network is a peer-to-peer (P2P) community based on numbers of AEAs. A two-stage “P2P Plus” mechanism is developed to address the electricity transaction within AEA community. In the first “P2P” stage, electricity is directly traded among AEAs via P2P price bidding. The model of P2P transaction is established, and the method of multi-dimensional willingness is adopted in price bidding. In the second “Plus” stage, the centralized coordination by distribution company (DisCo) is formulated as a constrained optimization problem, in which the objective is to maximize profit and the constraints are the basic rights of AEAs and line ratings of distribution network. A 30-bus test system including 29 AEAs and main grid is investigated. Numeric simulation results verify the effectiveness of the proposed models and methods regarding flow const... [more]

This work proposes a methodology to find performance and energy trade-offs for parallel applications running on Heterogeneous Multi-Processing systems with a single instruction-set architecture. These offer flexibility in the form of different core types and voltage and frequency pairings, defining a vast design space to explore. Therefore, for a given application, choosing a configuration that optimizes the performance and energy consumption is not straightforward. Our method proposes novel analytical models for performance and power consumption whose parameters can be fitted using only a few strategically sampled offline measurements. These models are then used to estimate an application’s performance and energy consumption for the whole configuration space. In turn, these offline predictions define the choice of estimated Pareto-optimal configurations of the model, which are used to inform the selection of the configuration that the application should be executed on. The methodology... [more]

This article presents the results of a study of energy and ecological indicators at different engine loads (BMEP) adjusting the Start of Injection (SOI) of a Compression Ignition Engine fuelled with blends of diesel (D), rapeseed methyl ester (RME)-based biodiesel and isopropanol (P). Fuel blends mixed at D50RME45P5, D50RME40P10 and D50RME30P20 proportions were used. Alcohol-based fuels, such as isopropanol, were chosen because they can be made from different biomass-based feedstocks and used as additives with diesel fuel in diesel engines. Diesel fuel and its blend with 10% alcohol have almost the same thermal efficiency (BTE). In further examination of energy and ecological indicators, combustion parameters were analysed at SOI 6 CAD BTDC using AVL BOOST software (BURN subprogram). Increasing alcohol content in fuel blends led to a reduced cetane number, which prolonged the ignition delay phase and intensified heat release in the premixed combustion phase. Higher combustion temperatu... [more]

In electricity markets, bilateral contracts (BC) are used to hedge against price volatility in the spot market. Pricing these contracts requires scheduling from either the buyer or the seller aiming to achieve the highest profit possible. Since this problem includes different players, a Generation Company (GC) and an Electricity Supplier Company (ESC) are considered. The approaches to solve this problem include the Nash Bargaining Solution (NBS) equilibrium and the Raiffa−Kalai−Smorodinsky (RKS) bargaining solution. The innovation of this work is the implementation of an algorithm based on the RKS equilibrium to find a compromise strategy when determining the concessions to be made by the parties. The results are promising and show that the RKS approach can obtain better results compared to the Nash equilibrium method applied to a case study.

Anaerobic digestion (AD) has undergone many developments since its first appearance. Despite that, there are still some environmental and economical obstacles that are limiting its sustainability. On the other hand, different types of starch have proven their effectiveness in some different applications. Food processing industries are considered one of the largest generators of waste in the environment. With an aid of the response surface methodology (RSM), the proposed study aimed to find an optimised way to overcome the obstacles by studying the impacts of the starch isolated from the potato peels on the biogas produced from the AD of potato peels before and after starch separation. The study found that potato peels represented approximately 12.5% of the potato total weight. The starch has only a slight influence on the quantity of the biogas produced and much lower influences on its quality. This finding suggests further investigation is required on the production of starch bio-base... [more]

This study focuses on the determination of optimum layout configurations for a linear array of identical mutually interacting truncated cylinders. Optimum configurations correspond to those that maximize either the total heave exciting force acting on all cylinders of the array or the heave exciting force applied on pairs of cylinders within the array. For achieving this goal, we developed and applied an efficient optimization numerical process (ONP), where a robust hydrodynamic numerical model, capable of solving the diffraction problem of the examined multi-body arrangement in the frequency domain, was appropriately coupled with a genetic algorithm solver in an integrated computational environment. Initially, the efficiency of the ONP is demonstrated by comparing results with those of other investigations that resulted from the deployment of classical optimization methods. Then, ONP is applied for a linear array of nine cylinders for determining the optimum layout configurations unde... [more]

The aim of this study is to comprehensively evaluate the energy consumption in the automotive industry, clarifying the effect of its productive processes. For this propose, the material flow of the vehicles has been elaborated, from mining to vehicle assembly. Initially, processes where each type of material was used, and the relationship between them, were clarified. Subsequently, material flow was elaborated, while considering materials input in each process. Consequently, the consumption of energy resources (i.e., oil, natural gas, coal, and electricity) was calculated. Open data were utilized, and the effects on the Japanese vehicle market were analyzed as a case study. Our results indicate that the energy that is required for vehicle production is 41.8 MJ/kg per vehicle, where mining and material production processes represent 68% of the total consumption. Moreover, 5.23 kg of raw materials and energy resources are required to produce 1 kg of vehicle. Finally, this study proposed... [more]

This paper examines the dynamic relationship between crude oil prices and the U.S. exchange rate within the structural break detection context. Based on monthly data from January 1996 to April 2019, this paper identifies structural breaks in movements of oil price and examines the dynamic relationship between crude oil prices and the U.S. exchange rate movement by introducing the economic policy uncertainty and using the TVP-VAR (Time-Varying Parameter-Vector Auto Regression ) model. Empirical results indicate that shocks to crude oil prices have immediate and short-term impacts on movements in the exchange rate which are emphasized during the confidence intervals of structural breaks. Oil price shocks and economic policy uncertainty are interrelated and influence movements in the U.S. exchange rate. Since the U.S. dollar is the main currency of the international oil market and the U.S. has become a major exporter of crude oil, the transmission of price shocks to the U.S. exchange rate... [more]

This paper presents a review of isolated matrix inverters. The study contributes to creating a point of reference for a comprehensive classification of existing solutions. Over 30 topologies were reviewed, and the main advantages and disadvantages discussed. Applications of isolated matrix inverters are summarized in a tabular form to demonstrate their flexibility for different power and voltage levels achieved due to the presence of a transformer. These inverters have been proposed for the uninterruptible power supplies, high and low-voltage/power photovoltaic systems, low-power fuel cell, different low- and high-voltage battery and/or electric vehicle chargers, audio amplifiers. The fully controlled switches on both terminals of these converters typically can provide the bidirectional power transfer capability, which is also addressed for most of the topologies, but requires some modification in their modulation strategy. Average efficiency of today’s isolated matrix inverters is com... [more]

This paper presents an intelligent system for the detection of non-technical losses of electrical energy associated with the fraudulent behaviors of system users. This proposal has three stages: a non-supervised clustering of consumption profiles based on a hybrid algorithm between self-organizing maps (SOM) and genetic algorithms (GA). A second stage for demand forecasting is based on ARIMA (autoregressive integrated moving average) models corrected intelligently through neural networks (ANN). The final stage is a classifier based on random forests for fraudulent user detection. The proposed intelligent approach was trained and tested with real data from the Colombian Caribbean region, where the utility reports energy losses of around 18% of the total energy purchased by the company during the five last years. The results show an average overall performance of 82.9% in the detection process of fraudulent users, significantly increasing the effectiveness compared to the approaches (68%... [more]

The aim of this study was the performance evaluation of anaerobic digestion of dairy wastewater in a multi-section horizontal flow reactor (HFAR) equipped with microwave and ultrasonic generators to stimulate biochemical processes. The effects of increasing organic loading rate (OLR) ranging from 1.0 g chemical oxygen demand (COD)/L·d to 4.0 g COD/L·d on treatment performance, biogas production, and percentage of methane yield were determined. The highest organic compounds removals (about 85% as COD and total organic carbon—TOC) were obtained at OLR of 1.0−2.0 g COD/L·d. The highest biogas yield of 0.33 ± 0.03 L/g COD removed and methane content in biogas of 68.1 ± 5.8% were recorded at OLR of 1.0 g COD/L·d, while at OLR of 2.0 g COD/L·d it was 0.31 ± 0.02 L/COD removed and 66.3 ± 5.7%, respectively. Increasing of the OLR led to a reduction in biogas productivity as well as a decrease in methane content in biogas. The best technological effects were recorded in series with an operating... [more]

This work presents a thermoeconomic comparison between two different solar energy technologies, namely the evacuated flat-plate solar collectors and the photovoltaic panels, integrated as auxiliary systems into two renewable polygeneration plants. Both plants produce electricity, heat and cool, and are based on a 6 kWe organic Rankine cycle (ORC), a 17-kW single-stage H2O/LiBr absorption chiller, a geothermal well at 96 °C, a 200 kWt biomass auxiliary heater, a 45.55 kWh lithium-ion battery and a 25 m2 solar field. In both configurations, electric and thermal storage systems are included to mitigate the fluctuations due to the variability of solar radiation. ORC is mainly supplied by the thermal energy produced by the geothermal well. Additional heat is also provided by solar thermal collectors and by a biomass boiler. In an alternative layout, solar thermal collectors are replaced by photovoltaic panels, producing additional electricity with respect to the one produced by the ORC. To... [more]

Load forecasting impacts directly financial returns and information in electrical systems planning. A promising approach to load forecasting is the Echo State Network (ESN), a recurrent neural network for the processing of temporal dependencies. The low computational cost and powerful performance of ESN make it widely used in a range of applications including forecasting tasks and nonlinear modeling. This paper presents a Bayesian optimization algorithm (BOA) of ESN hyperparameters in load forecasting with its main contributions including helping the selection of optimization algorithms for tuning ESN to solve real-world forecasting problems, as well as the evaluation of the performance of Bayesian optimization with different acquisition function settings. For this purpose, the ESN hyperparameters were set as variables to be optimized. Then, the adopted BOA employs a probabilist model using Gaussian process to find the best set of ESN hyperparameters using three different options of ac... [more]

Optimal fast charging is an important factor in battery management systems (BMS). Traditional charging strategies for lithium-ion batteries, such as the constant current−constant voltage (CC−CV) pattern, do not take capacity aging mechanisms into account, which are not only disadvantageous in the life-time usage of the batteries, but also unsafe. In this paper, we employ the dynamic optimization (DP) method to achieve the optimal charging current curve for a lithium-ion battery by introducing limits on the intercalation-induced stresses and the solid−liquid interface film growth based on an electrochemical−thermal model. Furthermore, the backstepping technique is utilized to control the temperature to avoid overheating. This paper concentrates on solving the issue of minimizing charging time in a given target State of Charge (SoC), while limiting the capacity loss caused by intercalation-induced stresses and film formation. The results indicate that the proposed optimal charging method... [more]

Field-Programmable Gate Array (FPGA) provides the possibility to design new “electromagnetic compatibility (EMC) friendly” control techniques for power electronic converters. Such control techniques use pseudo-random modulators (RanM) to control the converter switches. However, some issues connected with the FPGA-based design of RanM, such as matching the range of fixed-point numbers, might be challenging. The modern programming tools, such as LabVIEW, may facilitate the design process, but there are still fixed-point operations and limitations in arithmetic operations. This paper presents the design insights on the FPGA-based EMC friendly control system for DC/DC converter. Probability density functions (PDF) are used to analyse and improve pseudo-random algorithms. The theoretical algorithms, hardware details and experimental results are presented and discussed in terms of conducted electromagnetic interference emission.

This paper presents a three-dimensional modeling approach to simulate the thermal performance of a Li-ion battery module for a new urban car. A single-battery cell and a 52.3 Ah Li-ion battery module were considered, and a Newman, Tiedemann, Gu, and Kim (NTGK) model was adopted for the electrochemical modeling based on input parameters from the discharge experiment. A thermal−electrochemical coupled method was established to provide insight into the temperature variations over time under various discharge conditions. The distribution temperature of a single-battery cell was predicted accurately. Additionally, in a 5C discharge condition without a cooling system, the temperature of the battery module reached 114 °C, and the temperature difference increased to 25 °C under a 5C discharging condition. This condition led to the activation of thermal runaway and the possibility of an explosion. However, the application of a reasonable fan circulation and position reduced the maximum temperat... [more]

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.