Search results for: estimation of electricity

Authors: Amirhossein Mohajerzadeh, Abolghasem Mohajerzadeh

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In this paper, target parameter is estimated with desirable precision in hierarchical wireless sensor networks (WSN) while the proposed algorithm also tries to prolong network lifetime as much as possible, using efficient data collecting algorithm. Target parameter distribution function is considered unknown. Sensor nodes sense the environment and send the data to the base station called fusion center (FC) using hierarchical data collecting algorithm. FC builds underlying phenomena based on collected data. Considering the aggregation level, x, the goal is providing the essential infrastructure to find the best value for aggregation level in order to prolong network lifetime as much as possible, while desirable accuracy is guaranteed (required sample size is fully depended on desirable precision). First, the sample size calculation algorithm is discussed, second, the average queue length based on M/M[x]/1/K queue model is determined and it is used for energy consumption calculation. Nodes can decrease transmission cost by aggregating incoming data. Furthermore, the performance of the new algorithm is evaluated in terms of lifetime and estimation accuracy.

Keywords: aggregation, estimation, queuing, wireless sensor network

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Authors: Adenike Boyo Olasunkanmi Kesinro, Henry Boyo, Surukite Oluwole

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Utilizing solar energy in producing electricity can minimize environmental pollution generated by fossil fuel in producing electricity. Our research was base on the extraction of dye from Roystonea regia fruit by using methanol as solvent. The dye extracts were used as sensitizers in Dye-sensitized solar cell (DSSCs). Study was done on the electrical properties from the extracts of Roystonea regia fruit as Dye-sensitized solar cell (DSSCs). The absorptions of the extracts and extracts with dye were determined at different wavelengths (350-1000nm). Absorption peak was observed at 1.339 at wavelength 400nm. The obtained values for methanol extract Roystonea regia extract are, Imp = 0.015mA, Vmp = 12.0mV, fill factor = 0.763, Isc= 0.018 mA and Voc = 13.1 mV and efficiency of 0.32%. .The phytochemical screening was taken and it was observed that Roystonea regia extract contained less of anthocyanin compared to flavonoids. The nanostructured dye sensitized solar cell (DSSC) will provide economically credible alternative to present day silicon p–n junction photovoltaic.

Keywords: methanol, ethanol, titanium dioxide, roystonea regia fruit, dye-sensitized solar cell

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Authors: Joseph Levodo, Ndimbarafine Young Tobin, E. Messina, P. Edouma

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Energy efficiency can contribute significantly towards increasing clean energy access to modern energy services. Many developing countries have largely focused on expanding energy access by increasing supply. This is due to the fact the links between energy efficiency and clean energy access are often unnoticed. Energy efficiency measures offer the promise of reducing energy use and saving money on electricity bills, as well as reducing negative environmental externalities associated with the production of electricity. This paper seeks to address the economic and effectiveness of reducing energy consumption by integrating energy efficiency as a priority to meet energy access examines the barriers to energy efficient in sub-Saharan African countries. The findings from this study reveal that an appropriate policy can promote the development of more energy-efficient buildings, products and strengthen incentives for consumers, businesses, and industrial customers to pursue cost-effective energy-efficiency measures and to make investments that will provide future energy-efficiency improvements.

Keywords: barriers, Sub-Saharan Africa, cost effective, energy savings, clean energy

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Authors: Taiyo Matsumura, Kuninori Takahashi, Takashi Ono

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The purpose of this research is to improve the convenience of waiting for trains at level crossings and stations and to prevent accidents resulting from forcible entry into level crossings, by providing level crossing users and passengers with information that tells them when the next train will pass through or arrive. For this paper, we proposed methods for estimating operation by means of an average value method, variable response smoothing method, and exponential smoothing method, on the basis of open data, which has low accuracy, but for which performance schedules are distributed in real time. We then examined the accuracy of the estimations. The results showed that the application of an exponential smoothing method is valid.

Keywords: exponential smoothing method, open data, operation estimation, train schedule

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Authors: A. Moawad, K. C. Yao, A. Mansour, R. Gautier

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The detecting of an occupied frequency band is a major issue in cognitive radio systems. The detection process becomes difficult if the signal occupying the band of interest has faded amplitude due to multipath effects. These effects make it hard for an occupying user to be detected. This work mitigates the missed-detection problem in the context of cognitive radio in frequency-selective fading channel by proposing blind channel estimation method that is based on scattering transform. By initially applying conventional energy detection, the missed-detection probability is evaluated, and if it is greater than or equal to 50%, channel estimation is applied on the received signal followed by channel equalization to reduce the channel effects. In the proposed channel estimator, we modify the Morlet wavelet by using its first derivative for better frequency resolution. A mathematical description of the modified function and its frequency resolution is formulated in this work. The improved frequency resolution is required to follow the spectral variation of the channel. The channel estimation error is evaluated in the mean-square sense for different channel settings, and energy detection is applied to the equalized received signal. The simulation results show improvement in reducing the missed-detection probability as compared to the detection based on principal component analysis. This improvement is achieved at the expense of increased estimator complexity, which depends on the number of wavelet filters as related to the channel taps. Also, the detection performance shows an improvement in detection probability for low signal-to-noise scenarios over principal component analysis- based energy detection.

Keywords: channel estimation, cognitive radio, scattering transform, spectrum sensing

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Authors: Sami Mestiri, Abdeljelil Farhat

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The aim of this current paper is to predict the credit risk of banks in Tunisia, over the period (2000-2005). For this purpose, two methods for the estimation of the logistic regression model with random effects: Penalized Quasi Likelihood (PQL) method and Gibbs Sampler algorithm are applied. By using the information on a sample of 528 Tunisian firms and 26 financial ratios, we show that Bayesian approach improves the quality of model predictions in terms of good classification as well as by the ROC curve result.

Keywords: forecasting, credit risk, Penalized Quasi Likelihood, Gibbs Sampler, logistic regression with random effects, curve ROC

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Authors: Hesheng Wang, Haoyu Wang, Chungang Zhuang

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Estimating the 6D pose of objects is a core step for robot bin-picking tasks. The problem is that various objects are usually randomly stacked with heavy occlusion in real applications. In this work, we propose a method to regress 6D poses by predicting three points for each object in the 3D point cloud through deep learning. To solve the ambiguity of symmetric pose, we propose a labeling method to help the network converge better. Based on the predicted pose, an iterative method is employed for pose optimization. In real-world experiments, our method outperforms the classical approach in both precision and recall.

Keywords: pose estimation, deep learning, point cloud, bin-picking, 3D computer vision

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Authors: Sofia Ahanj Sofia Ahanj, Mahsa Rahmani Mahsa Rahmani, Zahra Sadeghigol, Vida Nobakht Vida Nobakht

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Providing security in the electricity industry, as one of the vital infrastructures of the country, is one of the essential operations that must be taken in order to improve the security of the country. Resistant security strategies need to be regularly implemented as a dynamic process to improve security, and security evaluation is one of the most important steps in this process. Methodology in the field of evaluation in both technical and managerial dimensions is discussed in the laboratory. There are various standards in the field of general ICT technical-security evaluation. The most important are ISO / IEC 15408, ISO / IEC 27001 and NIST SP 800-53. In the present paper, these standards are first examined. Then, the standards and reports in the industrial field have been reviewed and compared, and finally, based on the results and special considerations of information and communication technology equipment in the electricity industry, the appropriate methodology has been presented.

Keywords: security standards, ISO/IEC 15408, ISA/IEC 62443 series, NIST SP 800-53, NISTIR 7628

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Authors: Muhammad Ghaffar Doggar, Farah

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The primary objective of this feasibility study is to conduct a techno-financial assessment for installation of biomass based power plant in Faisalabad division. The study involves identification of best site for power plant followed by an assessment of biomass resource potential in the area and propose power plant of suitable size. The study also entailed comprehensive supply chain analysis to determine biomass fuel pricing, transportation and storage. Further technical and financial analyses have been done for selection of appropriate technology for the power plant and its financial viability, respectively. The assessment of biomass resources and the subsequent technical analysis revealed that 20 MW biomass power plant could be implemented at one of the locations near Faisalabad city i.e. AARI Site, Near Chak Jhumra district Faisalabad, Punjab province. Three options for steam pressure; namely, 70 bar, 90 bar and 100 bar boilers have been considered. Using international experience and prices on power plant technology and local prices on locally available equipment, the study concludes biomass fuel price of around 50 US dollars (USD) per ton when delivered to power plant site. The electricity prices used for feasibility calculations were 0.13 USD per KWh for electricity from a locally financed project and 0.11 USD per KWh for internationally financed power plant. For local financing the most viable choice is the 70 bar solution and with international financing, the most feasible solution is using a 90 bar boiler. Between the two options, the internationally financed 90 bar boiler setup gives better financial results than the locally financed 70 bar boiler project. It has been concluded that 20 MW with 90 bar power plant and internationally financed would have an equity IRR of 23% and a payback period of 7 years. This will be a cheap option for installation of power plants.

Keywords: AARI, Ayub agriculture research institute, biomass - crops residue, KWh - electricity Units, MG - Muhammad Ghaffar

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Authors: Aries Nawel, Bentarzi Mohamed

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This paper deals with the study of some probabilistic and statistical properties of a Periodic Integer-Valued Moving Average Model (PINMA_{S}(q)). The closed forms of the mean, the second moment and the periodic autocovariance function are obtained. Furthermore, the time reversibility of the model is discussed in details. Moreover, the estimation of the underlying parameters are obtained by the Yule-Walker method, the Conditional Least Square method (CLS) and the Weighted Conditional Least Square method (WCLS). A simulation study is carried out to evaluate the performance of the estimation method. Moreover, an application on real data set is provided.

Keywords: periodic integer-valued moving average, periodically correlated process, time reversibility, count data

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Authors: Myisha Ahmad, G. M. Jahid Hasan

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Electricity is the pinnacle of human civilization. At present, the growing concerns over significant climate change have intensified the importance of the use of renewable energy technologies for electricity generation. The interest is primarily due to better energy security, smaller environmental impact and providing a sustainable alternative compared to the conventional energy sources. Solar power, wind, biomass, tidal power, and wave power are some of the most reliable sources of renewable energy. Ocean approximately holds 2×10³ TW of energy and has the largest renewable energy resource on the planet. Ocean energy has many forms namely, encompassing tides, ocean circulation, surface waves, salinity and thermal gradients. Ocean tide in particular, associates both potential and kinetic energy. The study is focused on the latter concept that deals with tidal current energy conversion technologies. Tidal streams or marine currents generate kinetic energy that can be extracted by marine current energy devices and converted into transmittable energy form. The principle of technology development is very comparable to that of wind turbines. Conversion of marine tidal resources into substantial electrical power offers immense opportunities to countries endowed with such resources and this work is aimed at addressing such prospects of Bangladesh. The study analyzed the extracted current velocities from numerical model works at several locations in the Bay of Bengal. Based on current magnitudes, directions and available technologies the most fitted locations were adopted and possible annual generation capacity was estimated. The paper also examines the future prospects of tidal current energy along the Bay of Bengal and establishes a constructive approach that could be adopted in future project developments.

Keywords: bay of Bengal, energy potential, renewable energy, tidal current

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Authors: Junkyeong Kim, Jooyoung Park, Aoqi Zhang, Seunghee Park

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The tensile force of Pre-Stressed Concrete (PSC) girder is the most important factor for evaluating the performance of PSC girder bridges. To measure the tensile force of PSC girder, several NDT methods were studied. However, conventional NDT method cannot be applied to the real-size PSC girder because the PS tendons could not be approached. To measure the tensile force of real-size PSC girder, this study proposed embedded EM sensor based tensile force estimation method. The embedded EM sensor could be installed inside of PSC girder as a sheath joint before the concrete casting. After curing process, the PS tendons were installed, and the tensile force was induced step by step using hydraulic jacking machine. The B-H loop was measured using embedded EM sensor at each tensile force steps and to compare with actual tensile force, the load cell was installed at each end of girder. The magnetization energy loss, that is the closed area of B-H loop, was decreased according to the increase of tensile force with regular pattern. Thus, the tensile force could be estimated by the tracking the change of magnetization energy loss of PS tendons. Through the experimental result, the proposed method can be used to estimate the tensile force of the in-situ real-size PSC girder bridge.

Keywords: tensile force estimation, embedded EM sensor, magnetization energy loss, PSC girder

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Authors: O. T. Oluriz, O. D. Akinyemi, J. A.Olowofela, O. A. Idowu, S. A. Ganiyu

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This study was carried out using aeromagnetic data which record variation in the magnitude of the earth magnetic field in order to detect local changes in the properties of the underlying geology. The aeromagnetic data (Sheet No. 261) was acquired from the archives of Nigeria Geological Survey Agency of Nigeria, obtained in 2009. The study present estimation of source parameters within an area of about 3,025 square kilometers on geographic latitude to and longitude to within Ibadan and it’s environs in Oyo State, southwestern Nigeria. The area under study belongs to part of basement complex in southwestern Nigeria. Estimation of source parameters of aeromagnetic data was achieve through the application of source imaging parameters (SPI) techniques that provide delineation, depth, dip contact, susceptibility contrast and mineral potentials of magnetic signatures within the region. The depth to the magnetic sources in the area ranges from 0.675 km to 4.48 km. The estimated depth limit to shallow sources is 0.695 km and depth to deep sources is 4.48 km. The apparent susceptibility values of the entire study area obtained ranges from 0.01 to 0.005 [SI]. This study has shown that the magnetic susceptibility within study area is controlled mainly by super paramagnetic minerals.

Keywords: aeromagnetic, basement complex, meta-sediment, precambrian

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Authors: Angelica Gonzalez O, Leonardo Rivera Cadavid, Diego Fernando Manotas

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Energy poverty considers a population that does not have access to modern energy service. In particular, an area of a country that is not connected to the national electricity grid is known as a Non-Interconnected Zone (NIZ). Access to electricity has a significant impact on the welfare and development opportunities of the population. Different studies have shown that most health problems have an empirical cause and effect relationship with multidimensional energy poverty. Likewise, research has been carried out to review the consequences of not having access to electricity, and its results have concluded a statistically significant relationship between energy poverty and sources of drinking water, access to clean water, risks of mosquito bites, obesity, sterilization, marital status, occupation, and residence. Therefore, extensive research has been conducted in the construction of an energy poverty measure based on an index. Some of these studies introduce a Multidimensional Energy Poverty Index (MEPI), Compose Energy Poverty Index (CEPI), Low Income High Costs indicator (LIHC), among others. For this purpose, this study analyzes the energy poverty index using a multicriteria analysis determining the set of feasible alternatives - for which Colombia's ZNI will be used as a case study - to be considered in the problem and the set of relevant criteria in the characterization of the ZNI, from which the prioritization is obtained to determine the level of adjustment of each alternative with respect to the performance in each criterion. Additionally, this study considers the installation of Micro-Grids (MG). This is considered a straightforward solution to this problem because an MG is a local electrical grid, able to operate in grid-connected and island mode. Drawing on those insights, this study compares an energy poverty index considering an MG installation and calculates the impacts of different criterias in an energy poverty index in NIZ.

Keywords: multicirteria, energy poverty, rural, microgrids, non-interconnect zones

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Authors: N. Haj Salem, M. Belhadj, S. Ben Jomâa, R. Dhouieb, S. Saadi, M. A. Mesrati, A. Chadly

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Introduction: The hyoid bone is considered as one of many bones used to identify a missed person. There is a specificity of each population group in human identifications. Objective: To analyze the relationship between age, sex and metric parameters of hyoid bone in Tunisian population sample, using CT-scan. Materials and Methods: A prospective study was conducted in the Department of Forensic Medicine of FattoumaBourguiba Hospital of Monastir-Tunisia during 4 years. A total of 240 samples of hyoid bone were studied. The age of cases ranged from 18 days to 81 years. The specimens were collected only from the deceased of known age. Once dried, each hyoid bone was scanned using CT scan. For each specimen, 10 measurements were taken using a computer program. The measurements consisted of 6 lengths and 4 widths. A regression analysis was used to estimate the relationship between age, sex, and different measurements. For age estimation, a multiple logistic regression was carried out for samples ≤ 35 years. For sex determination, ROC curve was performed. Discriminant value finally retained was based on the best specificity with the best sensitivity. Results: The correlation between real age and estimated age was good (r²=0.72) for samples aged 35 years or less. The unstandardised canonical function equation was estimated using three variables: maximum length of the right greater cornua, length from the middle of the left joint space to the middle of the right joint space and perpendicular length from the centre point of a line between the distal ends of the right and left greater cornua to the centre point of the anterior view of the body of the hyoid bone. For sex determination, the ROC curve analysis reveals that the area under curve was at 81.8%. Discriminant value was 0.451 with a specificity of 73% and sensibility of 79%. The equation function was estimated based on two variables: maximum length of the greater cornua and maximum length of the hyoid bone. Conclusion: The findings of the current study suggest that metric analysis of the hyoid bone may predict the age ≤ 35 years. Sex estimation seems to be more reliable. Further studies dealing with the fusion of the hyoid bone and the current study could help to achieve more accurate age estimation rates.

Keywords: anthropology, age estimation, CT scan, sex determination, Tunisia

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Authors: Ana Clara Santos, Maria Manuela Portela, Bettina Schaefli

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This work assesses the performance of an analytical model framework to generate daily flow duration curves, FDCs, based on climatic characteristics of the catchments and on their streamflow recession coefficients. According to the analytical model framework, precipitation is considered to be a stochastic process, modeled as a marked Poisson process, and recession is considered to be deterministic, with parameters that can be computed based on different models. The analytical model framework was tested for three case studies with different hydrological regimes located in Switzerland: pluvial, snow-dominated and glacier. For that purpose, five time intervals were analyzed (the four meteorological seasons and the civil year) and two developments of the model were tested: one considering a linear recession model and the other adopting a nonlinear recession model. Those developments were combined with recession coefficients obtained from two different approaches: forward and inverse estimation. The performance of the analytical framework when considering forward parameter estimation is poor in comparison with the inverse estimation for both, linear and nonlinear models. For the pluvial catchment, the inverse estimation shows exceptional good results, especially for the nonlinear model, clearing suggesting that the model has the ability to describe FDCs. For the snow-dominated and glacier catchments the seasonal results are better than the annual ones suggesting that the model can describe streamflows in those conditions and that future efforts should focus on improving and combining seasonal curves instead of considering single annual ones.

Keywords: analytical streamflow distribution, stochastic process, linear and non-linear recession, hydrological modelling, daily discharges

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Authors: Navid Mohammadzadeh, Huy Truong-Ba, Michael Cholette

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The solar tower (ST) plant is a promising technology to exploit large-scale solar irradiation. With thermal energy storage, ST plant has the potential to shift generation to high electricity price periods. However, the size of storage limits the dispatchability of the plant, particularly when it should compete with uncertainty in forecasts of solar irradiation and electricity prices. The purpose of this study is to explore the size of storage when Rolling Horizon Control (RHC) is employed for dispatch scheduling. To this end, RHC is benchmarked against perfect knowledge (PK) forecast and two day-ahead dispatching policies. With optimisation of dispatch planning using PK policy, the optimal achievable profit for a specific size of the storage is determined. A sensitivity analysis using Monte-Carlo simulation is conducted, and the size of storage for RHC and day-ahead policies is determined with the objective of reaching the profit obtained from the PK policy. A case study is conducted for a hypothetical ST plant with thermal storage located in South Australia and intends to dispatch under two market scenarios: 1) fixed price and 2) wholesale spot price. The impact of each individual source of uncertainty on storage size is examined for January and August. The exploration of results shows that dispatching with RH controller reaches optimal achievable profit with ~15% smaller storage compared to that in day-ahead policies. The results of this study may be applied to the CSP plant design procedure.

Keywords: solar tower plant, spot market, thermal storage system, optimized dispatch planning, sensitivity analysis, Monte Carlo simulation

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Authors: Cheng Zeng, George Michailidis, Hitoshi Iyatomi, Leo L. Duan

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The conditional density characterizes the distribution of a response variable y given other predictor x and plays a key role in many statistical tasks, including classification and outlier detection. Although there has been abundant work on the problem of Conditional Density Estimation (CDE) for a low-dimensional response in the presence of a high-dimensional predictor, little work has been done for a high-dimensional response such as images. The promising performance of normalizing flow (NF) neural networks in unconditional density estimation acts as a motivating starting point. In this work, the authors extend NF neural networks when external x is present. Specifically, they use the NF to parameterize a one-to-one transform between a high-dimensional y and a latent z that comprises two components [zₚ, zₙ]. The zₚ component is a low-dimensional subvector obtained from the posterior distribution of an elementary predictive model for x, such as logistic/linear regression. The zₙ component is a high-dimensional independent Gaussian vector, which explains the variations in y not or less related to x. Unlike existing CDE methods, the proposed approach coined Augmented Posterior CDE (AP-CDE) only requires a simple modification of the common normalizing flow framework while significantly improving the interpretation of the latent component since zₚ represents a supervised dimension reduction. In image analytics applications, AP-CDE shows good separation of 𝑥-related variations due to factors such as lighting condition and subject id from the other random variations. Further, the experiments show that an unconditional NF neural network based on an unsupervised model of z, such as a Gaussian mixture, fails to generate interpretable results.

Keywords: conditional density estimation, image generation, normalizing flow, supervised dimension reduction

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Authors: Mahdiyeh Zafaranchi, Ethan S. Cantor, William T. Riddell, Jess W. Everett

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The New Jersey Department of Military and Veteran’s Affairs (NJ DMAVA) operates over 50 facilities throughout the state of New Jersey, U.S. NJDMAVA is under a mandate to move toward decarbonization, which will eventually include eliminating the use of natural gas and other fossil fuels for heating. At the same time, the organization requires increased resiliency regarding electric grid disruption. These competing goals necessitate adopting the use of on-site renewables such as photovoltaic and geothermal power, as well as implementing power control strategies through microgrids. Planning for these changes requires a detailed understanding of current and future electricity use on yearly, monthly, and shorter time scales, as well as a breakdown of consumption by heating, ventilation, and air conditioning (HVAC) equipment. This paper discusses case studies of two buildings that were simulated using the QUick Energy Simulation Tool (eQUEST). Both buildings use electricity from the grid and photovoltaics. One building also uses natural gas. While electricity use data are available in hourly intervals and natural gas data are available in monthly intervals, the simulations were developed using monthly and yearly totals. This approach was chosen to reflect the information available for most NJ DMAVA facilities. Once completed, simulation results are compared to metrics recommended by several organizations to validate energy use simulations. In addition to yearly and monthly totals, the simulated peak demands are compared to actual monthly peak demand values. The simulations resulted in monthly peak demand values that were within 30% of the measured values. These benchmarks will help to assess future energy planning efforts for NJ DMAVA.

Keywords: building energy modeling, eQUEST, peak demand, smart meters

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Authors: Bonginkosi A. Thango, Jacobus A. Jordaan, Agha F. Nnachi

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In this day and age, there is a proliferate concern from all governments across the globe to barricade the environment from greenhouse gases, which absorb infrared radiation. As a result, solar photovoltaic (PV) electricity has been an expeditiously growing renewable energy source and will eventually undertake a prominent role in the global energy generation. The selection and purchasing of energy-efficient transformers that meet the operational requirements of the solar photovoltaic energy generation plants then become a part of the Independent Power Producers (IPP’s) investment plan of action. Taking these into account, this paper proposes a procedure that put into effect the intricate financial analysis necessitated to precisely evaluate the transformer service lifetime no-load and load loss factors. This procedure correctly set forth the transformer service lifetime loss factors as a result of a solar PV plant’s sporadic generation profile and related levelized costs of electricity into the computation of the transformer’s total ownership cost. The results are then critically compared with the conventional transformer total ownership cost unaccompanied by the emission costs, and demonstrate the significance of the sporadic energy generation nature of the solar PV plant on the total ownership cost. The findings indicate that the latter play a crucial role for developers and Independent Power Producers (IPP’s) in making the purchase decision during a tender bid where competing offers from different transformer manufactures are evaluated. Additionally, the susceptibility analysis of different factors engrossed in the transformer service lifetime cost is carried out; factors including the levelized cost of electricity, solar PV plant’s generation modes, and the loading profile are examined.

Keywords: solar photovoltaic plant, transformer, total ownership cost, loss factors

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Authors: Meiling Yang, Shuguo Xie, Yilong Zhu

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Nowadays, due to diverse electric products and complex electromagnetic environment, the localization and troubleshooting of the electromagnetic radiation source is urgent and necessary especially on the condition of far field. However, based on the existing DOA positioning method, the system or devices are complex, bulky and expensive. To address this issue, this paper proposes a single antenna radiation source localization method. A single antenna moves to form a virtual antenna array combined with DOA and MUSIC algorithm to position accurately, meanwhile reducing the cost and simplify the equipment. As shown in the results of simulations and experiments, the virtual antenna array DOA estimation modeling is correct and its positioning is credible.

Keywords: virtual antenna array, DOA, localization, far field

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Authors: Ahmed Aisa, Tariq Iqbal

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This letter talks about the ready-to-use design of a solar water heating system because, in Canada, the average consumption of hot water per person is approximately 50 to 75 L per day and the average Canadian household uses 225 L. Therefore, this paper will demonstrate the method of designing a solar water heating system with thermal storage. It highlights the renewable hybrid power system, allowing you to obtain a reliable, independent system with the optimization of the ingredient size and at an improved capital cost. The system can provide hot water for a big building. The main power for the system comes from solar panels. Solar Advisory Model (SAM) and HOMER are used. HOMER and SAM are design models that calculate the consumption of hot water and cost for a house. Some results, obtained through simulation, were for monthly energy production, annual energy production, after tax cash flow, the lifetime of the system and monthly energy usage represented by three types of energy. These are system energy, electricity load electricity and net metering credit.

Keywords: water heating, thermal storage, capital cost solar, consumption

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Authors: M. Kislu Noman, Syed Mohammed Shamsul Islam, Shahriar Hassan, Raihana Pervin

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With the increasing rate of wireless devices and high bandwidth operations, wireless networking and communications are becoming over crowded. To cope with such crowdy and messy situation, massive MIMO is designed to work with hundreds of low costs serving antennas at a time as well as improve the spectral efficiency at the same time. TDD has been used for gaining beamforming which is a major part of massive MIMO, to gain its best improvement to transmit and receive pilot sequences. All the benefits are only possible if the channel state information or channel estimation is gained properly. The common methods to estimate channel matrix used so far is LS, MMSE and a linear version of MMSE also proposed in many research works. We have optimized these methods using genetic algorithm to minimize the mean squared error and finding the best channel matrix from existing algorithms with less computational complexity. Our simulation result has shown that the use of GA worked beautifully on existing algorithms in a Rayleigh slow fading channel and existence of Additive White Gaussian Noise. We found that the GA optimized LS is better than existing algorithms as GA provides optimal result in some few iterations in terms of MSE with respect to SNR and computational complexity.

Keywords: channel estimation, LMMSE, LS, MIMO, MMSE

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Authors: S. Suman, G. N. Singh

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The present manuscript addresses the estimation procedure of population parameter using Poisson probability distribution when characteristic under study possesses a rare sensitive attribute. The generalized form of unrelated randomized response model is suggested in order to acquire the truthful responses from respondents. The resultant estimators have been proposed for two situations when the information on an unrelated rare non-sensitive characteristic is known as well as unknown. The properties of the proposed estimators are derived, and the measure of confidentiality of respondent is also suggested for respondents. Empirical studies are carried out in the support of discussed theory.

Keywords: Poisson distribution, randomized response model, rare sensitive attribute, non-sensitive attribute

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Authors: Saurabh Chanana, Monika Arora

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Demand response is getting increased attention these days due to the increase in electricity demand and introduction of renewable resources in the existing power grid. Traditionally demand response programs involve large industrial consumers but with technological advancement, demand response is being implemented for small residential and commercial consumers also. In this paper, demand response program aims to reduce the peak demand as well as overall energy consumption of the residential customers. Air conditioners are the major reason of peak load in residential sector in summer, so a dynamic model of air conditioning load with thermostat action has been considered for applying demand response programs. A programmable communicating thermostat (PCT) is a device that uses real time pricing (RTP) signals to control the thermostat setting. A new model incorporating PCT in air conditioning load has been proposed in this paper. Results show that introduction of PCT in air conditioner is useful in reducing the electricity payments of customers as well as reducing the peak demand.

Keywords: demand response, home energy management, programmable communicating thermostat, thermostatically controlled appliances

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Authors: Hussain Ali Bekhet, Endang Jati Mat Sahid

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For the past few decades, the Malaysian economy has expanded at an impressive pace, whilst, the Malaysian population has registered a relatively high growth rate. These factors had driven the growth of final energy demand. The ballooning energy demand coupled with the country’s limited indigenous energy resources have resulted in an increased of the country’s net import. Therefore, acknowledging the precarious position of the country’s energy self-sufficiency, this study has identified three main concerns regarding energy security, namely; over-dependence on fossil fuel, increasing energy import dependency, and increasing energy consumption per capita. This paper discusses the recent energy demand and supply trends, highlights the policies that are affecting energy security in Malaysia and suggests strategic options towards achieving energy security. The paper suggested that diversifying energy sources, reducing carbon content of energy, efficient utilization of energy and facilitating low-carbon industries could further enhance the effectiveness of the measures as the introduction of policies and initiatives will be more holistic.

Keywords: electricity, energy policy, energy security, Malaysia

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Authors: Ariadne Katsouras, Andrea Chareunsy

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The number of large hydroelectric dams in the world has increased from almost 6,000 in the 1950s to over 45,000 in 2000. Dams are often built to increase the economic development of a country. This can occur in several ways. Large dams take many years to build so the construction process employs many people for a long time and that increased production and income can flow on into other sectors of the economy. Additionally, the provision of electricity can help raise people’s living standards and if the electricity is sold to another country then the money can be used to provide other public goods for the residents of the country that own the dam. Dams are also built to control flooding and provide irrigation water. Most dams are of these types. This paper will give an overview of the environmental and economic theories of the impact of dams in different regions of the world. There is a difference in the degree of environmental and economic impacts due to the varying climates and varying social and political factors of the regions. Production of greenhouse gases from the dam’s reservoir, for instance, tends to be higher in tropical areas as opposed to Nordic environments. However, there are also common impacts due to construction of the dam itself, such as, flooding of land for the creation of the reservoir and displacement of local populations. Economically, the local population tends to benefit least from the construction of the dam. Additionally, if a foreign company owns the dam or the government subsidises the cost of electricity to businesses, then the funds from electricity production do not benefit the residents of the country the dam is built in. So, in the end, the dams can benefit a country economically, but the varying factors related to its construction and how these are dealt with, determine the level of benefit, if any, of the dam. Some of the theories or practices used to evaluate the potential value of a dam include cost-benefit analysis, environmental impacts assessments and regressions. Systems analysis is also a useful method. While these theories have value, there are also possible shortcomings. Cost-benefit analysis converts all the costs and benefits to dollar values, which can be problematic. Environmental impact assessments, likewise, can be incomplete, especially if the assessment does not include feedback effects, that is, they only consider the initial impact. Finally, regression analysis is dependent on the available data and again would not necessarily include feedbacks. Systems analysis is a method that can allow more complex modelling of the environment and the economic system. It would allow a clearer picture to emerge of the impacts and can include a long time frame.

Keywords: comparison, economics, environment, hydroelectric dams

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Authors: Huinan Zhang, Wenjie Jiang

Abstract:

Accurate estimation of tropical cyclone intensity is of great importance for disaster prevention and mitigation. Existing techniques are largely based on satellite imagery data, and research and utilization of the inner thermal core structure characteristics of tropical cyclones still pose challenges. This paper presents a two-stage tropical cyclone intensity estimation network based on the fusion of coarse and fine-grained features from microwave brightness temperature data. The data used in this network are obtained from the thermal core structure of tropical cyclones through the Advanced Technology Microwave Sounder (ATMS) inversion. Firstly, the thermal core information in the pressure direction is comprehensively expressed through the maximal intensity projection (MIP) method, constructing coarse-grained thermal core images that represent the tropical cyclone. These images provide a coarse-grained feature range wind speed estimation result in the first stage. Then, based on this result, fine-grained features are extracted by combining thermal core information from multiple view profiles with a distributed network and fused with coarse-grained features from the first stage to obtain the final two-stage network wind speed estimation. Furthermore, to better capture the long-tail distribution characteristics of tropical cyclones, focal loss is used in the coarse-grained loss function of the first stage, and ordinal regression loss is adopted in the second stage to replace traditional single-value regression. The selection of tropical cyclones spans from 2012 to 2021, distributed in the North Atlantic (NA) regions. The training set includes 2012 to 2017, the validation set includes 2018 to 2019, and the test set includes 2020 to 2021. Based on the Saffir-Simpson Hurricane Wind Scale (SSHS), this paper categorizes tropical cyclone levels into three major categories: pre-hurricane, minor hurricane, and major hurricane, with a classification accuracy rate of 86.18% and an intensity estimation error of 4.01m/s for NA based on this accuracy. The results indicate that thermal core data can effectively represent the level and intensity of tropical cyclones, warranting further exploration of tropical cyclone attributes under this data.

Keywords: Artificial intelligence, deep learning, data mining, remote sensing

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Authors: Muhammad Shoaib, Hassan M. Al-Swaidan

Abstract:

Air pollution has been a major challenge for the scientists today, due to the release of toxic emissions from various industries like power plants, desalination plants, industrial processes and transportation vehicles. Harmful emissions into the air represent an environmental pressure that reflects negatively on human health and productivity, thus leading to a real loss in the national economy. Variety of air pollutants in the form of carbon oxides, hydrocarbons, nitrogen oxides, sulfur oxides, suspended particulate material etc. are present in air due to the combustion of different types of fuels like crude oil, diesel oil and natural gas. Among various pollutants, NOx and SOx emissions are considered as highly toxic due to its carcinogenicity and its relation with various health disorders. In Kingdom of Saudi Arabia electricity is generated by burning of crude, diesel or natural gas in the turbines of electricity stations. Out of these three, crude oil is used extensively for electricity generation. Due to the burning of the crude oil there are heavy contents of gaseous pollutants like sulfur dioxides (SOx) and nitrogen oxides (NOx), gases which are ultimately discharged in to the environment and is a serious environmental threat. The breakthrough point in case of lab studies using 1 gm of sliced activated carbon adsorbant comes after 20 and 30 minutes for NOx and SOx, respectively, whereas in case of PP8 plant breakthrough point comes in seconds. The saturation point in case of lab studies comes after 100 and 120 minutes and for actual PP8 plant it comes after 60 and 90 minutes for NOx and SOx adsorption, respectively. Surface characterization of NOx and SOx adsorption on SAC confirms the presence of peaks in the FT-IR spectrum. CHNS study verifies that the SAC is suitable for NOx and SOx along with some other C and H containing compounds coming out from stack emission stream from the turbines of a power plant.

Keywords: activated carbon, flue gases, NOx and SOx adsorption, physical activation, power plants

Procedia PDF Downloads 347

Authors: Bastien Sanglard, Lou Magnat, Ligia Barna, Julian Carrey, Sébastien Lachaize

Abstract:

Cooking is a primary need for humans, several techniques being used around the globe based on different sources of energy: electricity, solid fuel (wood, coal...), fuel or liquefied petroleum gas. However, all of them leads to direct or indirect greenhouse gas emissions and sometimes health damage in household. Therefore, the solar concentrated power represent a great option to lower the damages because of a cleaner using phase. Nevertheless, the construction phase of the solar cooker still requires primary energy and materials, which leads to environmental impacts. The aims of this work is to analyse the ecological impacts of a commercialaluminium parabola and to compare it with other means of cooking, taking the boiling of 2 litres of water three times a day during 40 years as the functional unit. Life cycle assessment was performed using the software Umberto and the EcoInvent database. Calculations were realized over more than 13 criteria using two methods: the international panel on climate change method and the ReCiPe method. For the reflector itself, different aluminium provenances were compared, as well as the use of recycled aluminium. For the structure, aluminium was compared to iron (primary and recycled) and wood. Results show that climate impacts of the studied parabola was 0.0353 kgCO2eq/kWh when built with Chinese aluminium and can be reduced by 4 using aluminium from Canada. Assessment also showed that using 32% of recycled aluminium would reduce the impact by 1.33 and 1.43 compared to the use of primary Canadian aluminium and primary Chinese aluminium, respectively. The exclusive use of recycled aluminium lower the impact by 17. Besides, the use of iron (recycled or primary) or wood for the structure supporting the reflector significantly lowers the impact. The impact categories of the ReCiPe method show that the parabola made from Chinese aluminium has the heaviest impact - except for metal resource depletion - compared to aluminium from Canada, recycled aluminium or iron. Impact of solar cooking was then compared to gas stove and induction. The gas stove model was a cast iron tripod that supports the cooking pot, and the induction plate was as well a single spot plate. Results show the parabolic solar cooker has the lowest ecological impact over the 13 criteria of the ReCiPe method and over the global warming potential compared to the two other technologies. The climate impact of gas cooking is 0.628kgCO2/kWh when used with natural gas and 0.723 kgCO2/kWh when used with a bottle of gas. In each case, the main part of emissions came from gas burning. Induction cooking has a global warming potential of 0.12 kgCO2eq/kWh with the electricity mix of France, 96.3% of the impact being due to electricity production. Therefore, the electricity mix is a key factor for this impact: for instance, with the electricity mix of Germany and Poland, impacts are 0.81kgCO2eq/kWh and 1.39 kgCO2eq/kWh, respectively. Therefore, the parabolic solar cooker has a real ecological advantages compared to both gas stove and induction plate.

Keywords: life cycle assessement, solar concentration, cooking, sustainability

Procedia PDF Downloads 184