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Records with Subject: Process Monitoring
Showing records 17 to 41 of 316. [First] Page: 1 2 3 4 5 6 Last
Study on Radial Leakage Model and Law of Fractured Formation Drilling Fluid
Zelong Xie, Liang Zhu, Shubo Bi, Hui Ji, Tianyi Wang, Mengting Huang, Hao Zhang, Huimei Wu
June 7, 2023 (v1)
Keywords: cumulative leakage rate, drilling fluid leakage, fractured formation, herschel-bulkley flow pattern, leakage rate
Wellbore leakage mostly occurs in structurally developed fractured formations. Analyzing the real-time leakage rate during the drilling process plays an important role in identifying the leakage mechanism and its rules on-site. Based on the principles of fluid mechanics and using Herschel-Bulkley (H-B) drilling fluid, by reasonably simplifying the drilling fluid performance parameters, fracture roughness characteristic parameters, pressure difference between the wellbore and formation, and the radial extension length of drilling fluid, the radial leakage model is improved to improve the calculation accuracy. Using the Euler format in numerical analysis to solve the model and with the help of numerical analysis software, the radial leakage law of this flow pattern in the fractures is obtained. The results show that the deformation coefficient of the fracture index, fracture aperture, pressure difference, leakage rate, and cumulative leakage rate are positively correlated. The larger the... [more]
Design of a RGB-Arduino Device for Monitoring Copper Recovery from PCBs
Joan Morell, Antoni Escobet, Antonio David Dorado, Teresa Escobet
June 7, 2023 (v1)
Keywords: bioprocess optimization, chemical reactions, color sensing, copper recovery, mobile phone waste, non-invasive sensors, real-time monitoring system
The mobile phone industry, one of the fastest advancing sectors in production over the last few decades, has been associated with a high e-waste generation rate. Simultaneously, a high demand for the production of new electronic equipment has led to the scarcity of certain metals. In this context, many recent studies have focused on recovering certain metals from e-waste through the use of bioprocesses. Such recovery processes are based on the action of microorganisms that produce Fe(III) as an oxidant, in order to leach the copper contained in printed circuit boards. During the oxidation-reduction reaction between Fe(III) and metallic Cu, the color of the solution evolves from an initial reddish color, due to Fe(III), to a bluish-green color, due to the oxidized Cu. In this work, a hardware-software prototype is developed, through which the concentrations of the key analytes—Fe(III) and Cu(II)—can be determined in real time by monitoring the color of the solution. This is achieved thr... [more]
A CNN-Architecture-Based Photovoltaic Cell Fault Classification Method Using Thermographic Images
Chiwu Bu, Tao Liu, Tao Wang, Hai Zhang, Stefano Sfarra
May 23, 2023 (v1)
Keywords: automatic fault classification, CNN, deep learning, PV cell faults, thermography
Photovoltaic (PV) cells are a major part of solar power stations, and the inevitable faults of a cell affect its work efficiency and the safety of the power station. During manufacturing and service, it is necessary to carry out fault detection and classification. A convolutional-neural-network (CNN)-architecture-based PV cell fault classification method is proposed and trained on an infrared image data set. In order to overcome the problem of the original dataset’s scarcity, an offline data augmentation method is adopted to improve the generalization ability of the network. During the experiment, the effectiveness of the proposed model is evaluated by quantifying the obtained results with four deep learning models through evaluation indicators. The fault classification accuracy of the CNN model proposed here has been drawn by the experiment and reaches 97.42%, and it is superior to that of the models of AlexNet, VGG 16, ResNet 18 and existing models. In addition, the proposed model ha... [more]
Transformer Winding Fault Classification and Condition Assessment Based on Random Forest Using FRA
Mehran Tahir, Stefan Tenbohlen
May 23, 2023 (v1)
Keywords: condition assessment, decision tree (DT), frequency response analysis (FRA), Machine Learning, numerical indices, power transformer, random forest (RF)
At present, the condition assessment of transformer winding based on frequency response analysis (FRA) measurements demands skilled personnel. Despite many research efforts in the last decade, there is still no definitive methodology for the interpretation and condition assessment of transformer winding based on FRA results, and this is a major challenge for the industrial application of the FRA method. To overcome this challenge, this paper proposes a transformer condition assessment (TCA) algorithm, which is based on numerical indices, and a supervised machine learning technique to develop a method for the automatic interpretation of FRA results. For this purpose, random forest (RF) classifiers were developed for the first time to identify the condition of transformer winding and classify different faults in the transformer windings. Mainly, six common states of the transformer were classified in this research, i.e., healthy transformer, healthy transformer with saturated core, mecha... [more]
A Novel Workflow for Early Time Transient Pressure Data Interpretation in Tight Oil Reservoirs with Physical Constraints
Tongjing Liu, Liwu Jiang, Jinju Liu, Juan Ni, Xinju Liu, Pengxiang Diwu
May 2, 2023 (v1)
Keywords: early time transient data, new type curves, physical constraints, pseudo threshold pressure gradient (TPG), skin factor, tight oil reservoirs
In this work, a novel workflow has been proposed, validated and applied to interpret the early time transient pressure data in tight oil reservoirs with physical constraints. More specifically, the theoretical model was developed to obtain the transient pressure response for a vertical well in tight oil reservoirs with consideration of pseudo threshold pressure gradient (TPG). Then, a physical constraint between the skin factor and formation permeability has been proposed based on the physical meaning of percolation theory. This physical constraint can be applied to determine the lower limit of the skin factor which can reduce the uncertainty during the interpretation process. It is found that the influence range of the skin factor and permeability may partially overlap during the interpretation process without consideration of physical constraints. Additionally, it is found that the equivalent wellbore radius is more reasonable by considering the skin factor constraints. Furthermore,... [more]
Early Warning of High-Voltage Reactor Defects Based on Acoustic−Electric Correlation
Shuguo Gao, Chao Xing, Zhigang Zhang, Chenmeng Xiang, Haoyu Liu, Hongliang Liu, Rongbin Shi, Sihan Wang, Guoming Ma
May 2, 2023 (v1)
Keywords: adaptive noise reduction, joint diagnosis, k-nearest neighbors, reactor defect, relevance significance
Traditional high-voltage reactor monitoring and diagnosis research has problems such as high sampling demand, difficulty in noise reduction on site, many false alarms, and lack of on-site data. In order to solve the above problems, this paper proposes an acoustic−electric fusion high-voltage reactor acquisition system and defect diagnosis method based on reactor pulse current and ultrasonic detection signal. Using the envelope peak signal as the basic detection data, the sampling requirement of the system is reduced. To fill the missing data with partial discharge (PD) information, a method based on k-nearest neighbor (KNN) is proposed. An adaptive noise reduction method is carried out, and a noise threshold calculation method is given for the field sensors. A joint analysis method of acoustic and electrical signals based on correlation significance is established to determine whether a discharge event has occurred based on correlation significance. Finally, the method is applied to a... [more]
Integration of Thermal and RGB Data Obtained by Means of a Drone for Interdisciplinary Inventory
Joanna Paziewska, Antoni Rzonca
April 28, 2023 (v1)
Keywords: data integration, dense matching, thermal imagery, UAV
Thermal infrared imagery is very much gaining in importance in the diagnosis of energy losses in cultural heritage through non-destructive measurement methods. Hence, owing to the fact that it is a very innovative and, above all, safe solution, it is possible to determine the condition of the building, locate places exposed to thermal escape, and plan actions to improve the condition of the facility. The presented work is devoted to the technology of creating a dense point cloud and a 3D model, based on data obtained from UAV. It has been shown that it is possible to build a 3D point model based on thermograms with the specified accuracy by using thermal measurement marks and the dense matching method. The results achieved in this way were compared and, as the result of this work, the model obtained from color photos was integrated with the point cloud created on the basis of the thermal images. The discussed approach exploits measurement data obtained with three independent devices (t... [more]
Research on Calculation Method for Discharge Capacity of Draining Well in Tailing Ponds Based on “Simplification-Fitting” Method
Sha Wang, Guodong Mei, Lijie Guo, Xuyang Xie, Krzysztof Skrzypkowski
April 28, 2023 (v1)
Keywords: discharge capacity, draining well, empirical formula, simplification fitting, window type
The existing empirical formulas concerning draining systems are complex in their expression: there are difficulties in locating the intersection point among different flow patterns and parameters vary depending on the water level, resulting in a large amount of data to be processed and low calculation efficiency. To solve these problems, a “simplification-fitting” method was proposed herein to calculate the discharge capacity of a window-type draining well, and optimal and reasonable locations were selected as discrete points of water level to deduce the increasing progressive relationship of free flow discharge capacity among discrete points according to the window size and longitudinal layout of window-type draining wells. Additionally, the algorithm simplified the discharge formulas of half-pressure flow and pressure flow and defined the convergence criteria for water level-discharge capacity to further simplify the expression of pressure flow. The comparison and contrast between th... [more]
A Framework for Multivariate Statistical Quality Monitoring of Additive Manufacturing: Fused Filament Fabrication Process
Moath Alatefi, Abdulrahman M. Al-Ahmari, Abdullah Yahia AlFaify, Mustafa Saleh
April 28, 2023 (v1)
Keywords: additive manufacturing, control chart, fused deposition modeling process, fused filament fabrication, heuristic optimization, multivariate quality characteristics, process monitoring, transformation methods
Advances in additive manufacturing (AM) processes have increased the number of relevant applications in various industries. To keep up with this development, the process stability of AM processes should be monitored, which is conducted through the assessment of the outputs or product characteristics. However, the use of univariate control charts to monitor an AM process might lead to misleading results, as most additively manufactured products have more than one correlated quality characteristic (QC). This paper proposes a framework for monitoring the multivariate quality characteristics of AM processes, and the proposed framework was applied to monitor a fused filament fabrication (FFF) process. In particular, specimens were designed and produced using the FFF process, and their QCs were identified. Then, critical quality characteristic data were collected using a precise measurement system. Furthermore, we propose a transformation algorithm to ensure the normality of the collected da... [more]
Flow-Induced Vibration of a Reversed U-Shaped Jumper Conveying Oil-Gas Two-Phase Flow
Hongjun Zhu, Tang Tang, Quanhua Li
April 28, 2023 (v1)
Keywords: flow pattern evolution, flow-induced vibration, fluid–structure interaction, gas–liquid two-phase flow, reversed U-shaped jumper
Subsea jumpers connecting the underwater wellhead and nearby manifold commonly undergo flow-induced vibration (FIV) due to the spatially frequent alteration in the flow direction, velocity, pressure and phase volume fraction of the oil−gas two-phase flow, potentially leading to fatigue damage. This paper reports the numerical results of the FIV of a reversed U-shaped jumper excited by gas−liquid two-phase flow, which evolves from the initial slug flow with a fixed gas−liquid ratio of 1:2 when transporting through the jumper. The FIV response and flow pattern evolution are examined with a gas flow rate of Qg = 4−12 kg/s and a liquid flow rate of QL = 96−288 kg/s. When the gas−liquid flow passes through the jumper, the flow regime subsequently presents the slug flow, bubble flow, churn flow and imperfect annular flow. The out-of-plane response frequency coincides with the pressure fluctuation frequency for the four connecting bends, suggesting the fluid−structure interaction (FSI). Never... [more]
Fuzzy Algorithms for Diagnosis of Furnace Transformer Insulation Condition
Alexander S. Karandaev, Igor M. Yachikov, Andrey A. Radionov, Ivan V. Liubimov, Nikolay N. Druzhinin, Ekaterina A. Khramshina
April 27, 2023 (v1)
Keywords: diagnostic criteria, diagnostic sensitivity, furnace transformer, fuzzy logic, monitoring, technical condition
Implementation of the smart transformer concept is critical for the deployment of IIoT-based smart grids. Top manufacturers of power electrics develop and adopt online monitoring systems. Such systems become part of high-voltage grid and unit transformers. However, furnace transformers are a broad category that this change does not affect yet. At the same time, adoption of diagnostic systems for furnace transformers is relevant because they are a heavy-duty application with no redundancy. Creating any such system requires a well-founded mathematical analysis of the facility’s condition, carefully selected diagnostic parameters, and setpoints thereof, which serve as the condition categories. The goal hereof was to create an expert system to detect insulation breach and its expansion as well as to evaluate the risk it poses to the system; the core mechanism is mathematical processing of trends in partial discharge (PD). We ran tests on a 26-MVA transformer installed on a ladle furnace at... [more]
Localization of Disconnection Faults in PV Installations Using the Multiple Frequencies Injection Method
Jae-Sub Ko, Dae-Kyong Kim
April 27, 2023 (v1)
Keywords: disconnection failure, failure detecting, multiple frequency injection, PV system
This paper proposes a method to detect disconnection faults and their exact location in PV systems. The proposed method injects multiple frequencies into a PV system with a transmitter and detects the injected signal using a receiver. The signal detected by the receiver exhibits different frequency characteristics on a disconnection failure. Based on this characteristic, a disconnection failure can be detected. In addition, by detecting the frequency radiated through the disconnection point, the exact disconnection point can be detected.
Energy Monitoring in the Wild: Platform Development and Lessons Learned from a Real-World Demonstrator
Filipe Quintal, Daniel Garigali, Dino Vasconcelos, Jonathan Cavaleiro, Wilson Santos, Lucas Pereira
April 27, 2023 (v1)
Keywords: case study, electricity monitoring, long-term, platform, prototyping, retrofitting
This paper presents the development and evaluation of EnnerSpectrum, a platform for electricity monitoring. The development was motivated by a gap between academic, fully custom-made monitoring solutions and commercial proprietary monitoring approaches. EnnerSpectrum is composed of two main entities, the back end, and the Gateway. The back end is a server comprised of flexible entities that can be configured to different monitoring scenarios. The Gateway interacts with equipment at a site that cannot interact directly with the back end. The paper presents the architecture and configuration of EnnerSpectrum for a long-term case study with 13 prosumers of electricity for approximately 36 months. During this period, the proposed system was able to adapt to several building and monitoring conditions while acquiring 95% of all the available consumption data. To finalize, the paper presents a set of lessons learned from running such a long-term study in the real world.
Flow Pattern and Resistance Characteristics of Gas−Liquid Two-Phase Flow with Foam under Low Gas−Liquid Flow Rate
Bin Wang, Jianguo Hu, Weixiong Chen, Zhongzhao Cheng, Fei Gao
April 27, 2023 (v1)
Keywords: flow pattern, gas–liquid flow rate, resistance
To reduce the cost of arranging air foam flooding equipment at each wellhead, a method of establishing centralized air foam flooding injection stations is proposed. The flow pattern and resistance characteristics of air foam flooding mixtures in different initial conditions are studied. Experimental results indicate that the probability density function of stratified flow is obtained by comparing stainless steel and transparent pipes. If the gas−liquid ratio is kept constant, then the shape of the probability density function remains unchanged in both stainless steel and transparent tubes. Meanwhile, the flow pattern under the gas−liquid ratio is determined by comparing the image recognition results with the probability density function, and a formula for calculating the resistance and pressure drop of the gas and liquid two-phase flow in the horizontal and upward pipes is established. Compared with the experiments, the error results of the calculation are small. Thus, the proposed equ... [more]
A Dynamic Multi-Cell FCL to Improve the Fault Ride through Capability of DFIG-Based Wind Farms
M. R. Shafiee, H. Shahbabaei Kartijkolaie, M. Firouzi, S. Mobayen, A. Fekih
April 26, 2023 (v1)
Keywords: fault-ride through (FRT), multi-cell fault current limiter (MCFCL), wind farms (WFs)
Endowing wind farms (WFs) with fault ride through (FRT) capability is crucial to their continuous availability under various operating conditions. This paper proposes a dynamic adaptive multi-cell fault current limiter (MCFCL) topology to enhance the FRT capability of grid connected WFs. The proposed MCFCL consists of one transient cell (TC) and multi resistive cells (RCs) directly connected to the grid’s high voltage without using any series injection transformers nor any series connection of semiconductor switches. The transient cell of the MCFCL includes two transient limiting reactors (TLRs) to mitigate the transient fault current and limit the rate of change of the currents of the semiconductor switches during fault occurrence. The number of RCs in the MCFCL is determined based on voltage sag level. These latter are inserted in the fault path to provide an adaptive voltage sag compensation mechanism according to the voltage sag level. Assessment of the MCFCL under various sag cond... [more]
The Influence of an Additional Sensor on the Microprocessor Temperature
Gilbert De Mey, Andrzej Kos
April 26, 2023 (v1)
Keywords: microprocessor, temperature sensors, throughput improvement
This paper deals with the problem of inserting a temperature sensor in the neighbourhood of a chip to monitor the junction temperature. If the sensor is not in the middle of the heat source, the recorded temperature can be quite different from the chip temperature we are mainly interested in. For the steady state temperature, it is rather easy to introduce a correction factor. For the transient behaviour of the temperature, there is a tremendous difference between the chip and the sensor temperature, which cannot be neglected if the temperature is used as a parameter to change, for example, the clock frequency in order to improve the throughput.
Sampling Rate Impact on Electrical Power Measurements Based on Conservative Power Theory
Larissa R. Souza, Ruben B. Godoy, Matheus A. de Souza, Luigi G. Junior, Moacyr A. G. de Brito
April 25, 2023 (v1)
Keywords: accurate measurements, Conservative Power Theory, sampling rate
This article presents a study of the sampling rate effect on electrical power measurements whose definitions are based on the Conservative Power Theory (CPT). The definitions of active power and reactive power of the CPT were applied in the MATLAB® software by varying the sampling rate and using a digital power meter as a reference. The measurements were performed in scenarios with linear and non-linear loads. Due to the usage of an integral in the CPT calculus, an error was verified associated with the reactive power being inversely proportional to the sampling rate. From the present study, it is possible to conclude that depending on the sample rate, the errors associated with the reactive power measurements are unacceptable and make the CPT implementation unfeasible. The results also presented effective information about the minimal sampling rate needed to make these errors neglected and to assist in choosing suitable microprocessors for the digital implementation of the CPT. It is... [more]
Implementation of Non-Destructive Electrical Condition Monitoring Techniques on Low-Voltage Nuclear Cables: I. Irradiation Aging of EPR/CSPE Cables
Ehtasham Mustafa, Ramy S. A. Afia, Oumaima Nouini, Zoltán Ádám Tamus
April 24, 2023 (v1)
Keywords: dielectric spectroscopy, elongation at break, extended voltage response, low-voltage cables, nuclear power plant, radiation aging
In a nuclear power plant environment, low-voltage cables experience different stresses during their service life which challenge their integrity. A non-destructive and reliable condition monitoring technique is desired to determine the state of these low-voltage cables during service and for the life extension of nuclear power plants. Hence, in this research work, an EPR/CSPE-based low-voltage cable was exposed to γ-rays for five different absorbed doses. The overall behavior of the cable under stress was characterized by frequency and time domain electrical measurements (capacitance, tan δ, and Extended Voltage Response) and a mechanical measurement (elongation at break). Significant variations in the electrical parameters were observed, as was a decline in the elongation at break values. A strong correlation between the measurement methods was observed, showing the ability of the electrical methods to be adopted as a non-destructive condition monitoring technique.
Cost Benefit of Implementing Advanced Monitoring and Predictive Maintenance Strategies for Offshore Wind Farms
Alan Turnbull, James Carroll
April 24, 2023 (v1)
Keywords: asset management, condition monitoring, economics, offshore wind energy, predictive maintenance
Advancements in wind turbine condition monitoring systems over the last decade have made it possible to optimise operational performance and reduce costs associated with component failure and other unplanned maintenance activities. While much research focuses on providing more automated and accurate fault diagnostics and prognostics in relation to predictive maintenance, efforts to quantify the impact of such strategies have to date been comparatively limited. Through time-based simulation of wind farm operation, this paper quantifies the cost benefits associated with predictive and condition-based maintenance strategies, taking into consideration both direct O&M costs and lost production. Predictive and condition-based strategies have been modelled by adjusting known component failure and repair rates associated with a more reactive approach to maintenance. Results indicate that up to 8% of direct O&M costs can be saved through early intervention along with up to 11% reduction in lost... [more]
A Practical Load Disaggregation Approach for Monitoring Industrial Users Demand with Limited Data Availability
Sara Tavakoli, Kaveh Khalilpour
April 24, 2023 (v1)
Keywords: demand-side management (DSM), industrial load, load disaggregation, nonintrusive load monitoring
The emergence of smart sensors has had a significant impact on the utility industry. In particular, it has made the planning and implementation of demand-side management (DSM) programmes easier. Nevertheless, for various reasons, some users may not implement smart meters for load monitoring. This paper addresses such cases, particularly large-scale industrial users, which, despite heavy electrical loads coming from many different processes, implement only simple energy measuring equipment for billing purposes. This necessitates the utilisation of novel methodologies for load disaggregation, often referred to as nonintrusive load monitoring (NILM). The availability of such tools can create multifold benefits for industrial park management, utility service providers, regulators, and policymakers. Here, we introduce an optimisation algorithm for nonintrusive load disaggregation that is low-cost, speedy, and acceptably accurate. As a case study, we used real network data of three industria... [more]
Application of Dynamic Fault Tree Analysis to Prioritize Electric Power Systems in Nuclear Power Plants
Sejin Baek, Gyunyoung Heo
April 21, 2023 (v1)
Keywords: Alternate AC Diesel Generator, dynamic fault tree, multi-unit, station blackout
Because the scope of risk assessments at nuclear power plants (NPPs) is being extended both spatially and temporally, conventional, or static fault trees might not be able to express failure mechanisms, or they could be unnecessarily conservative in their expression. Therefore, realistic assessment techniques are needed to adequately capture accident scenarios. In multi-unit probabilistic safety assessment (PSA), fault trees naturally become more complex as the number of units increases. In particular, when considering a shared facility between units of the electric power system (EPS), static fault trees (SFTs) that prioritize a specific unit are limited in implementing interactions between units. However, dynamic fault trees (DFTs) can be available without this limitation by using dynamic gates. Therefore, this study implements SFTs and DFTs for an EPS of two virtual NPPs and compares their results. In addition, to demonstrate the dynamic characteristics of the shared facilities, a st... [more]
Comprehensive Review of Short-Term Voltage Stability Evaluation Methods in Modern Power Systems
Aleksandar Boričić, José L. Rueda Torres, Marjan Popov
April 21, 2023 (v1)
Keywords: real-time monitoring, short-term voltage stability, stability evaluation, state of the art
The possibility to monitor and evaluate power system stability in real-time is in growing demand. Whilst most stability-related studies focus on long-term voltage stability and frequency stability, very little attention is given to the issue of short-term (voltage) instability. In this paper, the most common evaluation methods present in the literature are summarized, with a focus on their applicability to modern power systems with a large amount of renewable energy integration. The paper presents a first-of-a-kind structured review of this topic. We find that all existing methods have noteworthy limitations that necessitate further improvements. Additionally, the need of having an inclusive short-term instability prediction method is demonstrated, due to strong interactions between various short-term instability mechanisms. These findings provide a good foundation for further research and advancement in the field of real-time stability monitoring.
Efficient and Robust Image Communication Techniques for 5G Applications in Smart Cities
Lavish Kansal, Gurjot Singh Gaba, Naveen Chilamkurti, Byung-Gyu Kim
April 21, 2023 (v1)
Keywords: BER, DCT, FFT, MRC, OFDM, PSNR
A wide range of multimedia applications must be supported by the modern fifth generation (5G) wireless communication systems for realizing the diverse applications in smart cities. The diverse applications such as real-time monitoring of roads, smart homes, smart industries, etc., for a sustainable smart city emphasizes a robust and efficient image transmission. In this paper, the influence of maximal ratio combining (MRC) on the reception of images with different orthogonal frequency division multiplexing (OFDM) versions is studied. The different OFDM versions considered here are the fast Fourier transform (FFT) based OFDM and discrete cosine transform (DCT) based OFDM. A comparison between diverse modulation levels for the images transmitted through different OFDM methodologies, along with variation in a number of receiving antennas for MRC, is proposed for additive white gaussian noise (AWGN) and Rayleigh fading channels. The diverse modulation levels used are binary phase shift key... [more]
A More Efficient Technique to Power Home Monitoring Systems Using Controlled Battery Charging
Joaquim Amândio Azevedo, Filipe Edgar Santos
April 21, 2023 (v1)
Keywords: energy harvesting, energy monitoring, power supply, wireless sensor networks, ZigBee
Home energy monitoring has recently become a very important issue and a means to reduce energy consumption in the residential sector. Sensors and control systems are deployed at various locations in a house and an intelligent system is used to efficiently manage the consumed energy. Low power communication systems are used to provide low power consumption from a smart meter. Several of these systems are battery operated. Other systems use AC/DC adapters to supply power to sensors and communication systems. However, even using low-power technology, such as ZigBee, the power consumption of a router can be high because it must always be powered on. In this work, to evaluate power consumption, a system for monitoring energy usage and indoor air quality was developed. A technique is proposed to efficiently supply power to the components of the system. All sensor nodes are battery operated, and relays are used to control the battery charging process. In addition, an energy harvesting system... [more]
Neighborhood Energy Modeling and Monitoring: A Case Study
Francesco Causone, Rossano Scoccia, Martina Pelle, Paola Colombo, Mario Motta, Sibilla Ferroni
April 20, 2023 (v1)
Keywords: building energy modeling, energy monitoring, neighborhood
Cities and nations worldwide are pledging to energy and carbon neutral objectives that imply a huge contribution from buildings. High-performance targets, either zero energy or zero carbon, are typically difficult to be reached by single buildings, but groups of properly-managed buildings might reach these ambitious goals. For this purpose we need tools and experiences to model, monitor, manage and optimize buildings and their neighborhood-level systems. The paper describes the activities pursued for the deployment of an advanced energy management system for a multi-carrier energy grid of an existing neighborhood in the area of Milan. The activities included: (i) development of a detailed monitoring plan, (ii) deployment of the monitoring plan, (iii) development of a virtual model of the neighborhood and simulation of the energy performance. Comparisons against early-stage energy monitoring data proved promising and the generation system showed high efficiency (EER equal to 5.84), to b... [more]
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