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1
Laville, Bastien, Laure Blanc-Féraud, and Gilles Aubert. "Off-The-Grid Variational Sparse Spike Recovery: Methods and Algorithms." Journal of Imaging 7, no. 12 (December 6, 2021): 266. http://dx.doi.org/10.3390/jimaging7120266.
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Gridless sparse spike reconstruction is a rather new research field with significant results for the super-resolution problem, where we want to retrieve fine-scale details from a noisy and filtered acquisition. To tackle this problem, we are interested in optimisation under some prior, typically the sparsity i.e., the source is composed of spikes. Following the seminal work on the generalised LASSO for measures called the Beurling-Lasso (BLASSO), we will give a review on the chief theoretical and numerical breakthrough of the off-the-grid inverse problem, as we illustrate its usefulness to the super-resolution problem in Single Molecule Localisation Microscopy (SMLM) through new reconstruction metrics and tests on synthetic and real SMLM data we performed for this review.
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Ling, Yun, Huotao Gao, Guobao Ru, Haitao Chen, Boya Li, and Ting Cao. "Grid Reconfiguration Method for Off-Grid DOA Estimation." Electronics 8, no. 11 (October 23, 2019): 1209. http://dx.doi.org/10.3390/electronics8111209.
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Off-grid algorithms for direction of arrival (DOA) estimation have become attractive because of their advantages in resolution and efficiency over conventional ones. In this paper, we propose a grid reconfiguration direction of arrival (GRDOA) estimation method based on sparse Bayesian learning. Unlike other off-grid methods, the grid points of GRDOA are treated as dynamic parameters. The number and position of the grid points are varied iteratively via a root method and a fission process. Then, the grid gets reconfigured through some criteria. By iteratively updating the reconfigured grid, DOAs are estimated completely. Since GRDOA has fewer grid points, it has better computational efficiency than the previous methods. Moreover, GRDOA can achieve better resolution and relatively higher accuracy. Numerical simulation results validate the effectiveness of GRDOA.
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Sunday, Joshua, Chibuisi Chigozie, Ezekiel O. Omole, and John B. Gwong. "A Pair of Three-Step Hybrid Block Methods for the Solutions of Linear and Nonlinear First-Order Systems." European Journal of Mathematics and Statistics 3, no. 1 (January 24, 2022): 13–23. http://dx.doi.org/10.24018/ejmath.2022.3.1.86.
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In this research paper, a pair of three-step hybrid block methods is derived for the solutions of linear and nonlinear first-order systems. The derivation is carried out with the aid of collocation and interpolation technique and the adoption of power series as basis function. The first and second three-step hybrid block methods are derived by incorporating a single and double off-grid point(s) respectively within the three-step integration interval. The methods derived were then applied on some linear and nonlinear first-order systems to test their accuracy and efficiency. The results obtained show that the three-step hybrid block method with two off-grid points performed better than the three-step hybrid block method with one off-grid point. It was also clear from the results obtained that the two methods derived performed better than the existing methods with which we compared our results. We further analyzed the basic properties of the methods derived. These properties include zero-stability, consistence, convergence and region of absolute stability.
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Liu, Song, Lan Tang, Yechao Bai, and Xinggan Zhang. "A Sparse Bayesian Learning-Based DOA Estimation Method With the Kalman Filter in MIMO Radar." Electronics 9, no. 2 (February 18, 2020): 347. http://dx.doi.org/10.3390/electronics9020347.
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The direction of arrival (DOA) estimation problem as an essential problem in the radar system is important in radar applications. In this paper, considering a multiple-input and multiple-out (MIMO) radar system, the DOA estimation problem is investigated in the scenario with fast-moving targets. The system model is first formulated, and then by exploiting both the target sparsity in the spatial domain and the temporal correlation of the moving targets, a sparse Bayesian learning (SBL)-based DOA estimation method combined with the Kalman filter (KF) is proposed. Moreover, the performances of traditional sparse-based methods are limited by the off-grid issue, and Taylor-expansion off-grid methods also have high computational complexity and limited performance. The proposed method breaks through the off-grid limit by transforming the problem in the spatial domain to that in the time domain using the movement feature. Simulation results show that the proposed method outperforms the existing methods in the DOA estimation problem for the fast-moving targets.
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Atik, Md Atik-Uz-Zaman, and Abu Osman Al Mahbub. "Modeling Electricity Bill with the Reflection of CO2 Emissions and Methods of Implementing AMI for Smart Grid in Bangladesh." International Journal of Intelligent Systems and Applications 14, no. 5 (October 8, 2022): 14–21. http://dx.doi.org/10.5815/ijisa.2022.05.02.
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Taking into consideration the lack of circumstantial alertness, automated fault analysis and labor-saving switches, the present-day electrical power grid system has been deteriorating day by day. The backbone technology of this grid system is too ill-fitted to the on-going demand for electricity. Despite the fact that the government of Bangladesh has set a new target of reaching the total power generation to be 40,000 MW by 2030. Hence the infrastructure and corresponding technology of the electrical power sector are required to be modernized to cope with this gigantic target within a short time. Another challenging fact is that the rapid expansion of population and power-intensive industrialization trigger off the carbon emissions that lead to global climate change. Also, the constraints of electricity generation capacity, unidirectional way of communication, failure of power equipment and dropping off conventional sources of energy impose burden on the existing electric power grid. This paper articulates the needfulness of reflection on CO2 emissions or reduction in the electricity bill of the consumer in developing countries by employing a mathematical model and by proposing some fruitful methods to implement AMI for smart grid.
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Zhou, Xiaoli, Hongqiang Wang, Yongqiang Cheng, Yuliang Qin, and Haowen Chen. "Radar Coincidence Imaging for Off-Grid Target Using Frequency-Hopping Waveforms." International Journal of Antennas and Propagation 2016 (2016): 1–16. http://dx.doi.org/10.1155/2016/8523143.
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Radar coincidence imaging (RCI) is a high-resolution staring imaging technique without the limitation of the target relative motion. To achieve better imaging performance, sparse reconstruction is commonly used. While its performance is based on the assumption that the scatterers are located at the prediscretized grid-cell centers, otherwise, off-grid emerges and the performance of RCI degrades significantly. In this paper, RCI using frequency-hopping (FH) waveforms is considered. The off-grid effects are analyzed, and the corresponding constrained Cramér-Rao bound (CCRB) is derived based on the mean square error (MSE) of the “oracle” estimator. For off-grid RCI, the process is composed of two stages: grid matching and off-grid error (OGE) calibration, where two-dimension (2D) band-excluded locally optimized orthogonal matching pursuit (BLOOMP) and alternating iteration minimization (AIM) algorithms are proposed, respectively. Unlike traditional sparse recovery methods, BLOOMP realizes the recovery in the refinement grids by overwhelming the shortages of coherent dictionary and is robust to noise and OGE. AIM calibration algorithm adaptively adjusts the OGE and, meanwhile, seeks the optimal target reconstruction result.
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Audu, Haliru, Ahmed Adamu, and OlaJide Oladipo. "A mixed-methods study on the determinants of solar home systems utilization in rural, off-grid Nigeria." Journal of Global Economics and Business 4, no. 14 (June 30, 2023): 16–44. http://dx.doi.org/10.58934/jgeb.v4i14.171.
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This study employs a mixed-methods research approach to scrutinize the varied determinants influencing the willingness of off-grid rural households in Kwara State, Nigeria, to adopt Solar Home Systems (SHS). Integrating quantitative survey data from 400 households, qualitative findings derived from semi-structured interviews, and secondary data, the research provides a robust empirical framework. Through the application of Interval Regression and Tobit models, the analysis pinpoints income and education as key positive drivers towards SHS adoption, yet reveals a contrasting gender divide. Interestingly, a high level of satisfaction with the current energy provision emerges as a stumbling block to SHS acceptance. The research further identifies a distinct trend: households located further away from the grid exhibit a heightened propensity to pay for SHS, signifying a higher value attribution to SHS in these off-grid areas. The findings underscore the need for targeted interventions that encapsulate the diverse characteristics of households to ensure successful SHS promotion. The comprehensive insights garnered from this study offer indispensable guidance for policymakers and energy providers, bolstering strategic efforts to enhance SHS uptake and ultimately contributing to Nigeria's shift towards a more sustainable energy future.
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Ma, Jitong, Jiacheng Zhang, Zhengyan Yang, and Tianshuang Qiu. "Off-Grid DOA Estimation Using Sparse Bayesian Learning for MIMO Radar under Impulsive Noise." Sensors 22, no. 16 (August 20, 2022): 6268. http://dx.doi.org/10.3390/s22166268.
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Direction of arrival (DOA) estimation is an essential and fundamental part of array signal processing, which has been widely used in radio monitoring, autonomous driving of vehicles, intelligent navigation, etc. However, it remains a challenge to accurately estimate DOA for multiple-input multiple-output (MIMO) radar in impulsive noise environments. To address this problem, an off-grid DOA estimation method for monostatic MIMO radar is proposed to deal with non-circular signals under impulsive noise. In the proposed method, firstly, based on the property of non-circular signal and array structure, a virtual array output was built and a real-valued sparse representation for the signal model was constructed. Then, an off-grid sparse Bayesian learning (SBL) framework is proposed and further applied to the virtual array to construct novel off-grid sparse model. Finally, off-grid DOA estimation was realized through the solution of the sparse reconstruction with high accuracy even in impulsive noise. Numerous simulations were performed to compare the algorithm with existing methods. Simulation results verify that the proposed off-grid DOA method enables evident performance improvement in terms of accuracy and robustness compared with other works on impulsive noise.
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Guo, Jia, Zhi Gang Li, Ya Ping Cheng, and Chun Yan Cui. "The Research of Two Staged Non-Isolated Photovoltaic Grid Connected Inverter Control Method." Advanced Materials Research 773 (September 2013): 139–42. http://dx.doi.org/10.4028/www.scientific.net/amr.773.139.
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Grid-connected inverter topologies and control methods are analyzed and compared on the basis of two non-isolated PV grid-connected inverter circuit topology as 3kVA grid connected PV systems. In this paper, the current control method, the DC bus voltage outer grid current inner loop of the dual closed-loop PI control method. Sampled signal through the system circuit for processing, resulting in a SPWM drive signal to control the conduction of the power devices off the grid current control.
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Chibuisi, C., B. O. Osu, S. O. Edeki, G. O. Akinlabi, C. Olunkwa, and O. P. Ogundile. "Implementation of Two-step Hybrid Block Adams Moulton Solution Methods for First Order Delay Differential Equations." Journal of Physics: Conference Series 2199, no. 1 (February 1, 2022): 012017. http://dx.doi.org/10.1088/1742-6596/2199/1/012017.
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Abstract In this paper, Hybrid Block Adams Moulton Methods for step number k = 2 merged with two and three off-grid points were obtained and implemented in solving first order delay differential equations without the use of interpolation condition in evaluating the delay expression. The discrete schemes of these off-grid hybrid block methods were assessed through the continuous development of the linear multistep collocation method using a matrix conversion formula. The results obtained after the implementation of the proposed method in for numerical experiment of some first-order DDEs, the BHAMM2 schemes performed better and faster in satisfying the axioms for convergence and region of absolute stability than the BHAMM3 schemes at fixed step size z when examined with other existing methods.
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BENTON, J. R., S. S. IYENGAR, W. DENG, N. BRENER, and V. S. SUBRAHMANIAN. "TACTICAL ROUTE PLANNING: NEW ALGORITHMS FOR DECOMPOSING THE MAP." International Journal on Artificial Intelligence Tools 05, no. 01n02 (June 1996): 199–218. http://dx.doi.org/10.1142/s0218213096000146.
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This paper defines a new approach and investigates a fundamental problem in route planners. This capability is important for robotic vehicles(Martian Rovers, etc.) and for planning off-road military maneuvers. The emphasis throughout this paper will be on the design and analysis and hieiaichical implementation of our route planner. This work was motivated by anticipation of the need to search a grid of a trillion points for optimum routes. This cannot be done simply by scaling upward from the algorithms used to search a grid of 10,000 points. Algorithms sufficient for the small grid are totally inadequate for the large grid. Soon, the challenge will be to compute off-road routes more than 100 km long and with a one or two-meter grid. Previous efforts are reviewed and the data structures, decomposition methods and search algorithms are analyzed and limitations are discussed. A detailed discussion of a hieraichical implementation is provided and the experimental results are analyzed.
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Si, Weijian, Fuhong Zeng, Changbo Hou, and Zhanli Peng. "A Sparse-Based Off-Grid DOA Estimation Method for Coprime Arrays." Sensors 18, no. 9 (September 10, 2018): 3025. http://dx.doi.org/10.3390/s18093025.
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Recently, many sparse-based direction-of-arrival (DOA) estimation methods for coprime arrays have become popular for their excellent detection performance. However, these methods often suffer from grid mismatch problem due to the discretization of the potential angle space, which will cause DOA estimation performance degradation when the target is off-grid. To this end, we proposed a sparse-based off-grid DOA estimation method for coprime arrays in this paper, which includes two parts: coarse estimation process and fine estimation process. In the coarse estimation process, the grid points closest to the true DOAs, named coarse DOAs, are derived by solving an optimization problem, which is constructed according to the statistical property of the vectorized covariance matrix estimation error. Meanwhile, we eliminate the unknown noise variance effectively through a linear transformation. Due to finite snapshots effect, some undesirable correlation terms between signal and noise vectors exist in the sample covariance matrix. In the fine estimation process, we therefore remove the undesirable correlation terms from the sample covariance matrix first, and then utilize a two-step iterative method to update the grid biases. Combining the coarse DOAs with the grid biases, the final DOAs can be obtained. In the end, simulation results verify the effectiveness of the proposed method.
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Li, Jianfeng, Xiong Xu, Ping Li, and Qiting Zhang. "Partial Dictionary Based Off-Grid DOA Estimation Using Combined Coprime and Nested Array." Wireless Communications and Mobile Computing 2021 (May 27, 2021): 1–8. http://dx.doi.org/10.1155/2021/9939651.
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A partial dictionary based direction of arrival (DOA) estimation method which addresses the off-grid problem and exploits combined coprime and nested array (CCNA) is proposed. Compared to general coprime array, CCNA yields two sparse coprime subarrays in the coarray domain by adding a third subarray in the physical-array domain. To ensure the DOA estimation performance, the subarray with larger aperture is chosen, and the cyclic phase ambiguity caused by the sparse subarray allows partial dictionary covering arbitrary cycle to represent the whole atoms, and then, the off-grid sparse reconstruction method is developed to amend the grid mismatch. After the sparse recovery and off-grid compensation, ambiguous DOA estimations can be eliminated by substituting the estimations into the whole virtual array. Multiple simulations verify that the proposed algorithm outperforms the other state-of-the-art methods in terms of DOA estimation accuracy and angular resolution.
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Gong, Zhenghui, Xiaolong Su, Panhe Hu, Shuowei Liu, and Zhen Liu. "Deep Unfolding Sparse Bayesian Learning Network for Off-Grid DOA Estimation with Nested Array." Remote Sensing 15, no. 22 (November 10, 2023): 5320. http://dx.doi.org/10.3390/rs15225320.
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Recently, deep unfolding networks have been widely used in direction of arrival (DOA) estimation because of their improved estimation accuracy and reduced computational cost. However, few have considered the existence of a nested array (NA) with off-grid DOA estimation. In this study, we present a deep sparse Bayesian learning (DSBL) network to solve this problem. We first establish the signal model for off-grid DOA with NA. Then, we transform the array output into a real domain for neural networks. Finally, we construct and train the DSBL network to determine the on-grid spatial spectrum and off-grid value, where the loss function is calculated using reconstruction error and the sparsity of network output, and the layers correspond to the steps of the sparse Bayesian learning algorithm. We demonstrate that the DSBL network can achieve better generalization ability without training labels and large-scale training data. The simulation results validate the effectiveness of the DSBL network when compared with those of existing methods.
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Gambino, Valeria, Riccardo Del Citto, Paolo Cherubini, Carlo Tacconelli, Andrea Micangeli, and Romano Giglioli. "Methodology for the Energy Need Assessment to Effectively Design and Deploy Mini-Grids for Rural Electrification." Energies 12, no. 3 (February 12, 2019): 574. http://dx.doi.org/10.3390/en12030574.
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In order to successfully deploy a large number of decentralized energy systems in developing countries, it is necessary to standardize effective methodologies and procedures to develop off-grid/mini-grid systems. Considering that the energy need assessment provides inputs and assumptions used in business modelling and mini-grid design, the accuracy of its results directly affects the technical and financial feasibility studies. Thus, the approach for applying a proven methodology for the energy need assessment of rural communities is aimed at obtaining reliable input data for the mini-grid development. This helps in reducing both the financial challenges by mitigating the uncertainties in electricity demand and the technical challenges by contributing to adequately size off-grid power generation systems, with a view to boost toward a common overall objective of mini-grid’s optimization methods and tools. Hence, taking into consideration that target communities differ in terms of needs and context conditions, the proposed paper describes an inclusive methodology that can be adapted case-by-case. It provides an effective applied solution the lack of proven guidelines from project developers or literature, giving priority to data collection methods able to achieve a large sample representative of the market, with high accuracy in estimating the energy consumptions from electricity substitutes.
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Chen , Peng, Zhimin Chen, Xuan Zhang, and Linxi Liu. "SBL-Based Direction Finding Method with Imperfect Array." Electronics 7, no. 12 (December 11, 2018): 426. http://dx.doi.org/10.3390/electronics7120426.
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The imperfect array degrades the direction finding performance. In this paper, we investigate the direction finding problem in uniform linear array (ULA) system with unknown mutual coupling effect between antennas. By exploiting the target sparsity in the spatial domain, the sparse Bayesian learning (SBL)-based model is proposed and converts the direction finding problem into a sparse reconstruction problem. In the sparse-based model, the off-grid errors are introduced by discretizing the direction area into grids. Therefore, an off-grid SBL model with mutual coupling vector is proposed to overcome both the mutual coupling and the off-grid effect. With the distribution assumptions of unknown parameters including the noise variance, the off-grid vector, the received signals and the mutual coupling vector, a novel direction finding method based on SBL with unknown mutual coupling effect named DFSMC is proposed, where an expectation-maximum (EM)-based step is adopted by deriving the estimation expressions for all the unknown parameters theoretically. Simulation results show that the proposed DFSMC method can outperform state-of-the-art direction finding methods significantly in the array system with unknown mutual coupling effect.
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Yakubu, Dauda Gulibur, Ali Shokri, Geoffrey Micah Kumleng, and Daniela Marian. "Second Derivative Block Hybrid Methods for the Numerical Integration of Differential Systems." Fractal and Fractional 6, no. 7 (July 10, 2022): 386. http://dx.doi.org/10.3390/fractalfract6070386.
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The second derivative block hybrid method for the continuous integration of differential systems within the interval of integration was derived. The second derivative block hybrid method maintained the stability properties of the Runge–Kutta methods suitable for solving stiff differential systems. The lack of such stability properties makes the continuous solution not reliable, especially in solving large stiff differential systems. We derive these methods by using one intermediate off-grid point in between the familiar grid points for continuous solution within the interval of integration. The new family had a high accuracy, non-overlapping piecewise continuous solution with very low error constants and converged under the suitable conditions of stability and consistency. The results of computational experiments are presented to demonstrate the efficiency and usefulness of the methods, which also indicate that the block hybrid methods are competitive with some strong stability stiff integrators.
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Zhou, Xiaoli, Hongqiang Wang, Yongqiang Cheng, and Yuliang Qin. "Off-Grid Radar Coincidence Imaging Based on Variational Sparse Bayesian Learning." Mathematical Problems in Engineering 2016 (2016): 1–12. http://dx.doi.org/10.1155/2016/1782178.
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Radar coincidence imaging (RCI) is a high-resolution staring imaging technique motivated by classical optical coincidence imaging. In RCI, sparse reconstruction methods are commonly used to achieve better imaging result, while the performance guarantee is based on the general assumption that the scatterers are located at the prediscretized grid-cell centers. However, the widely existing off-grid problem degrades the RCI performance considerably. In this paper, an algorithm based on variational sparse Bayesian learning (VSBL) is developed to solve the off-grid RCI. Applying Taylor expansion, the unknown true dictionary is approximated accurately to a linear model. Then target reconstruction is reformulated as a joint sparse recovery problem that recovers three groups of sparse coefficients over three known dictionaries with the constraint of the common support shared by the groups. VSBL is then applied to solve the problem by assigning appropriate priors to the three groups of coefficients. Results of numerical experiments demonstrate that the algorithm can achieve outstanding reconstruction performance and yield superior performance both in suppressing noise and in adapting to off-grid error.
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Jahan, Ibrahim Salem, Vojtech Blazek, Stanislav Misak, Vaclav Snasel, and Lukas Prokop. "Forecasting of Power Quality Parameters Based on Meteorological Data in Small-Scale Household Off-Grid Systems." Energies 15, no. 14 (July 20, 2022): 5251. http://dx.doi.org/10.3390/en15145251.
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Off-grid power systems are often used to supply electricity to remote households, cottages, or small industries, comprising small renewable energy systems, typically a photovoltaic plant whose energy supply is stochastic in nature, without electricity distributions. This approach is economically viable and conforms to the requirements of the European Green Deal and the Fit for 55 package. Furthermore, these systems are associated with a lower short circuit power as compared with distribution grid traditional power plants. The power quality parameters (PQPs) of such small-scale off-grid systems are largely determined by the inverter’s ability to handle the impact of a device; however, this makes it difficult to accurately forecast the PQPs. To address this issue, this work compared prediction models for the PQPs as a function of the meteorological conditions regarding the off-grid systems for small-scale households in Central Europe. To this end, seven models—the artificial neural network (ANN), linear regression (LR), interaction linear regression (ILR), quadratic linear regression (QLR), pure quadratic linear regression (PQLR), the bagging decision tree (DT), and the boosting DT—were considered for forecasting four PQPs: frequency, the amplitude of the voltage, total harmonic distortion of the voltage (THDu), and current (THDi). The computation times of these forecasting models and their accuracies were also compared. Each forecasting model was used to forecast the PQPs for three sunny days in August. As a result of the study, the most accurate methods for forecasting are DTs. The ANN requires the longest computational time, and conversely, the LR takes the shortest computational time. Notably, this work aimed to predict poor PQPs that could cause all the equipment in off-grid systems to respond in advance to disturbances. This study is expected to be beneficial for the off-grid systems of small households and the substations included in existing smart grids.
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Liu, Qi-yong, Qun Zhang, Fu-fei Gu, Yi-chang Chen, Le Kang, and Xiao-yu Qu. "Downward-Looking Linear Array 3D SAR Imaging Based on Multiple Measurement Vectors Model and Continuous Compressive Sensing." Journal of Sensors 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/6207828.
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This paper concerns the problems of huge data and off-grid effect of cross-track direction in downward-looking linear array (DLLA) 3D SAR imaging. Since the 3D imaging needs a great deal of memory space, we consider the methods of downsampling to reduce the data quantity. In the azimuth direction, we proposed a method based on the multiple measurement vectors (MMV) model, which can enhance computational efficiency and elevate the performance of antinoise, to recover the signal. Further, in cross-track direction, since the resolution is restricted by the length of array, as well as platform size, the influence of off-grid effect is more serious than azimuth direction. Continuous compressive sensing (CCS), which can solve the off-grid effect of the classical compressive sensing (CS), is presented to obtain the precise imaging result under the noise scenarios. Finally, we validate our method by extension numerical experiments.
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Xu, S., B. Wang, and J. Liu. "On the use of Schwarz–Christoffel conformal mappings to the grid generation for global ocean models." Geoscientific Model Development 8, no. 10 (October 29, 2015): 3471–85. http://dx.doi.org/10.5194/gmd-8-3471-2015.
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Abstract. In this article we propose two grid generation methods for global ocean general circulation models. Contrary to conventional dipolar or tripolar grids, the proposed methods are based on Schwarz–Christoffel conformal mappings that map areas with user-prescribed, irregular boundaries to those with regular boundaries (i.e., disks, slits, etc.). The first method aims at improving existing dipolar grids. Compared with existing grids, the sample grid achieves a better trade-off between the enlargement of the latitudinal–longitudinal portion and the overall smooth grid cell size transition. The second method addresses more modern and advanced grid design requirements arising from high-resolution and multi-scale ocean modeling. The generated grids could potentially achieve the alignment of grid lines to the large-scale coastlines, enhanced spatial resolution in coastal regions, and easier computational load balance. Since the grids are orthogonal curvilinear, they can be easily utilized by the majority of ocean general circulation models that are based on finite difference and require grid orthogonality. The proposed grid generation algorithms can also be applied to the grid generation for regional ocean modeling where complex land–sea distribution is present.
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Tunlasakun, Khanchai. "DSP - Based Islanding Protection for Photovoltaic Grid Connected Inverter." Applied Mechanics and Materials 291-294 (February 2013): 2007–10. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.2007.
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This research presents the DSP - based islanding protection for photovoltaic grid connected inverter with under / over frequency and under / over voltage islanding protection methods. The design is based on the TMS320VC33PGE digital signal processor on the NI SPEEDY 33 board from National Instrument Inc. The prototype is monitor the grid frequency and grid voltage at the point of common coupling (PCC) between the photovoltaic grid connected inverter, the local load and the distribution. The results of study, the prototype can turn off relay between photovoltaic grid connected inverter and utility grid when the frequency is change under 48Hz or over 52Hz and the voltage is change under 200V or over 240V.
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Hou, Yunfei, Yingnan Zhang, Wenzhu Gui, Di Wang, and Wei Dong. "Meshless Search SR-STAP for Airborne Radar Based on Meta-Heuristic Algorithms." Sensors 23, no. 23 (November 27, 2023): 9444. http://dx.doi.org/10.3390/s23239444.
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The sparse recovery (SR) space-time adaptive processing (STAP) method has excellent clutter suppression performance under the condition of limited observation samples. However, when the cluttering is nonlinear in a spatial-Doppler profile, it will cause an off-grid effect and reduce the sparse recovery performance. A meshless search using a meta-heuristic algorithm (MH) can completely eliminate the off-grid effect in theory. Therefore, genetic algorithm (GA), differential evolution (DE), particle swarm optimization (PSO), and grey wolf optimization (GWO) methods are applied to SR-STAP for selecting exact clutter atoms in this paper. The simulation results show that MH-STAP can estimate the clutter subspace more accurately than the traditional algorithm; PSO-STAP and GWO-STAP showed better clutter suppression performance in four MH-STAP methods. To search for more accurate clutter atoms, PSO and GWO are combined to improve the method’s capacity for global optimization. Meanwhile, the fitness function is improved by using prior knowledge of the clutter distribution. The simulation results show that the improved PSO-GWO-STAP algorithm provides excellent clutter suppression performance, which solves the off-grid problem better than does single MH-STAP.
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Tafula, José Eduardo, Constantino Dário Justo, Pedro Moura, Jérôme Mendes, and Ana Soares. "Multicriteria Decision-Making Approach for Optimum Site Selection for Off-Grid Solar Photovoltaic Microgrids in Mozambique." Energies 16, no. 6 (March 21, 2023): 2894. http://dx.doi.org/10.3390/en16062894.
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Given the constraints associated with grid expansion costs, limited access to reliable electricity, and priorities in addressing the climate agenda and Sustainable Development Goals in low-income countries, microgrids and off-grid solar projects represent a viable solution for rural electrification. This type of solution has the advantage of being less expensive than conventional technologies, is rapidly scalable, affordable, environmentally sustainable, and can play a critical role in empowering rural communities. In this context, this study proposed a spatial framework for off-grid solar energy planning based on a Geographical Information System and Boolean logic, Fuzzy logic, and Analytic Hierarchy Process Multicriteria Decision-Making methods. The results of the applied methodology show that the selection of optimal locations for off-grid solar photovoltaic microgrid projects in Mozambique is significantly influenced by the following order of criteria: climatology, orography, technical and location, social, and institutional criteria. Geographically, about 49% or 344,664.36 km2 of the total study area is initially suitable for an off-grid solar photovoltaic microgrid project; 4% is low suitable, 14% is moderately suitable, 18% is suitable, and 13% is highly suitable. However, 51% of the ranked areas fall into the not feasible and restricted areas, mainly in conservation areas, protected areas, and areas at high risk of flooding and cyclones, covering a total of 387,005.5 km2 within the study area. In general, the approach helps to reduce uncertainty and increase flexibility to identify appropriate sites and strengthen indicators of sustainable development impacts of decentralized rural electrification.
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Dash, Santanu Kumar, Suprava Chakraborty, and Devaraj Elangovan. "A Brief Review of Hydrogen Production Methods and Their Challenges." Energies 16, no. 3 (January 20, 2023): 1141. http://dx.doi.org/10.3390/en16031141.
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Hydrogen is emerging as a new energy vector outside of its traditional role and gaining more recognition internationally as a viable fuel route. This review paper offers a crisp analysis of the most recent developments in hydrogen production techniques using conventional and renewable energy sources, in addition to key challenges in the production of Hydrogen. Among the most potential renewable energy sources for hydrogen production are solar and wind. The production of H2 from renewable sources derived from agricultural or other waste streams increases the flexibility and improves the economics of distributed and semi-centralized reforming with little or no net greenhouse gas emissions. Water electrolysis equipment driven by off-grid solar or wind energy can also be employed in remote areas that are away from the grid. Each H2 manufacturing technique has technological challenges. These challenges include feedstock type, conversion efficiency, and the need for the safe integration of H2 production systems with H2 purification and storage technologies.
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Mirza, Hamid Ali, Laeeq Aslam, Muhammad Asif Zahoor Raja, Naveed Ishtiaq Chaudhary, Ijaz Mansoor Qureshi, and Aqdas Naveed Malik. "A New Computing Paradigm for Off-Grid Direction of Arrival Estimation Using Compressive Sensing." Wireless Communications and Mobile Computing 2020 (August 25, 2020): 1–9. http://dx.doi.org/10.1155/2020/9280198.
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In this paper, a method for solving grid mismatch or off-grid target is presented for direction of arrival (DOA) estimation problem using compressive sensing (CS) technique. Location of the sources are at few angles as compare to the entire angle domain, i.e., spatially sparse sources, and their location can be estimated using CS methods with ability of achieving super resolution and estimation with a smaller number of samples. Due to grid mismatch in CS techniques, the source energy is distributed among the adjacent grids. Therefore, a fitness function is introduced which is based on the difference of the source energy among the adjacent grids. This function provides the best discretization value for the grid through iterative grid refinement. The effectiveness of the proposed scheme is verified through extensive simulations for different number of sources.
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Wang, Xi, Qinyi Chen, and Jingyi Wang. "Fuzzy rough set based sustainable methods for energy efficient smart city development." Journal of Intelligent & Fuzzy Systems 40, no. 4 (April 12, 2021): 8173–83. http://dx.doi.org/10.3233/jifs-189640.
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The lightening system inside the residential or commercial building consumes the highest electrical power. For an energy efficient smart city development, some sustainable and low power consumption methods need to be explored. In this direction, we proposed solar energy based auto-intelligent LED light controlling system that uses wireless sensor network (WSN) with computation and control model for LED on/off and dimming of LED lights inside the building area. The WSN is employed with some sensor devices that sense and gather ambient context information which is transmitted to computation model. LEDs get power supply from photovoltaic solar panel systems that have inbuilt battery banks. Fuzzy rough set is a simplification of a rough set, obtained from the normalization of fuzzy set in a approximation of crisp value. Fuzzy is utilized for analyzing the energy consumed in the system additionally. Performance evaluation of proposed Auto-intelligent LED system is carried out based on the comparative analysis of energy consumption of ac-grid system with solar energy based dc-grid system. Result analysis shows that proposed system saves 78% of energy consumption as compared to the traditional AC power grid system. The proposed DC power grid system presents 3% of voltage drop and maximum power loss of 1.25%. The statistics of battery charger and LED drives are also represented experimentally.
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Syahwil, Muhammad, and Nasrudin Kadir. "Rancang Bangun Modul Pembangkit Listrik Tenaga Surya (PLTS) Sistem Off-grid Sebagai Alat Penunjang Praktikum Di Laboratorium." Jurnal Pengelolaan Laboratorium Pendidikan 3, no. 1 (January 24, 2021): 26–35. http://dx.doi.org/10.14710/jplp.3.1.26-35.
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This study aims to design and manufacture a practical module for a small-scale off-grid solar power system with a power capacity of 320Wp. This module consists of the main components of an off-grid type solar power system such as solar panels, Solar Charger Controller (SCC), batteries, inverters, ac/dc loads and power meter measuring instruments integrated in one module. The method used is laboratory research methods and literature study. The literature study method is to look for literature related to solar power plant as a support in making modules and laboratory methods, namely testing modules/ systems with certain conditions. Stages This research method includes identification of problems in the laboratory, literature study, design/layout of the PLTS module, determining the type and analysis of the capacity of solar panels, SCC, inverters and batteries, supplying materials/components, manufacturing modules, and testing modules in the laboratory. The output and benefits of this research are getting a practical module for the solar power plant system which makes it easier for students to understand the working principles of the PLTS system; also to optimize practicum activities in the laboratory. From the results of testing, measurement, and data analysis that have been carried out by the off-grid solar power plant (PLTS) module that has been made to function properly and works in accordance with the principle of the off-grid PLTS system, generating electricity according to the capacity of the solar panel, The solar charge controller works in accordance with its function to regulate charge and discharge of battery storage and the inverter is able to serve the load according to its capacity so that this module is ready to be used as a practical module in learning activities in the laboratory.
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Mota, Alzira, Paulo Ávila, Ricardo Albuquerque, Lino Costa, and João Bastos. "A Framework for Time-Cost-Quality Optimization in Project Management Problems Using an Exploratory Grid Concept in the Multi-Objective Simulated-Annealing." International Journal of Information Technology & Decision Making 20, no. 04 (April 21, 2021): 1095–120. http://dx.doi.org/10.1142/s0219622021500322.
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Time, cost, and quality are the three indispensable factors for the realization and success of a project. In this context, we propose a framework composed of a multi-objective approach and multi-criteria decision-making methods (MCDM) to solve time-cost-quality trade-off optimization problems. A multi-objective Simulated Annealing (MOSA) algorithm is used to compute an approximation to the Pareto optimal set. The concept of the exploratory grid is introduced in the MOSA to improve its performance. MCDM are used to assist the decision-making process. The Shannon entropy and AHP methods assign weights to criteria. The first methodology is for the inexperienced decision-makers, and the second concedes a personal and flexible weighting of the criteria weights, based on the project manager’s assessment. The TOPSIS and VIKOR methods are considered to rank the solutions. Although they have the same purpose, the rankings achieved are different. A tool is implemented to solve a time-cost-quality trade-off problem on a project activities network. The computational experiments are analyzed and the results with the exploratory grid in Simulated Annealing (SA) are promising. Despite the framework aims to solve multi-objective trade-off optimization problems, supporting the decisions of the project manager, the methodologies used can also be applied in other areas.
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Veviurko, Grigorii, Wendelin Böhmer, Laurens Mackay, and Mathijs de Weerdt. "Surrogate DC Microgrid Models for Optimization of Charging Electric Vehicles under Partial Observability." Energies 15, no. 4 (February 14, 2022): 1389. http://dx.doi.org/10.3390/en15041389.
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Many electric vehicles (EVs) are using today’s distribution grids, and their flexibility can be highly beneficial for the grid operators. This flexibility can be best exploited by DC power networks, as they allow charging and discharging without extra power electronics and transformation losses. From the grid control perspective, algorithms for planning EV charging are necessary. This paper studies the problem of EV charging planning under limited grid capacity and extends it to the partially observable case. We demonstrate how limited information about the EV locations in a grid may disrupt the operation planning in DC grids with tight constraints. We introduce two methods to change the grid topology such that partial observability of the EV locations is resolved. The suggested models are evaluated on the IEEE 16 bus system and multiple randomly generated grids with varying capacities. The experiments show that these methods efficiently solve the partially observable EV charging planning problem and offer a trade-off between computational time and performance.
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Egwebe, Augustine, Meghdad Fazeli, Petar Igic, and Paul Holland. "Load sharing methods for inverter-based systems in islanded microgrids: A review." Facta universitatis - series: Electronics and Energetics 30, no. 2 (2017): 145–60. http://dx.doi.org/10.2298/fuee1702145e.
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This paper explores and discusses various design considerations for inverter-based systems. Different load sharing techniques are presented for the integration of renewable energy sources within islanded microgrids. In off-grid connection, renewable energy sources are often configured to share power based on their rated capacity. This paper explores both conventional and dynamic load sharing interaction between distributed generation units, both in an inductive (high voltage) and resistive (low voltage) networks. Load sharing based on the proper design of virtual impedance is also reviewed.
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Luo, Fuli, Xuesheng Zhao, Wenbin Sun, Yalu Li, and Yuanzheng Duan. "An Overall Uniformity Optimization Method of the Spherical Icosahedral Grid Based on the Optimal Transformation Theory." Atmosphere 12, no. 11 (November 17, 2021): 1516. http://dx.doi.org/10.3390/atmos12111516.
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The improvement of overall uniformity and smoothness of spherical icosahedral grids, the basic framework of atmospheric models, is a key to reducing simulation errors. However, most of the existing grid optimization methods have optimized grid from different aspects and not improved overall uniformity and smoothness of grid at the same time, directly affecting the accuracy and stability of numerical simulation. Although a well-defined grid with more than 12 points cannot be constructed on a sphere, the area uniformity and the interval uniformity of the spherical grid can be traded off to enhance extremely the overall grid uniformity and smoothness. To solve this problem, an overall uniformity and smoothness optimization method of the spherical icosahedral grid is proposed based on the optimal transformation theory. The spherical cell decomposition method has been introduced to iteratively update the grid to minimize the spherical transportation cost, achieving an overall optimization of the spherical icosahedral grid. Experiments on the four optimized grids (the spring dynamics optimized grid, the Heikes and Randall optimized grid, the spherical centroidal Voronoi tessellations optimized grid and XU optimized grid) demonstrate that the grid area uniformity of our method has been raised by 22.60% of SPRG grid, −1.30% of HR grid, 38.30% of SCVT grid and 38.20% of XU grid, and the grid interval uniformity has been improved by 2.50% of SPRG grid, 2.80% of HR grid, 11.10% of SCVT grid and 11.00% of XU grid. Although the grid uniformity of the proposed method is similar with the HR grid, the smoothness of grid deformation has been enhanced by 79.32% of grid area and 24.07% of grid length. To some extent, the proposed method may be viewed as a novel optimization approach of the spherical icosahedral grid which can improve grid overall uniformity and smoothness of grid deformation.
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Ciller, Pedro, Fernando de Cuadra, and Sara Lumbreras. "Optimizing Off-Grid Generation in Large-Scale Electrification-Planning Problems: A Direct-Search Approach." Energies 12, no. 24 (December 6, 2019): 4634. http://dx.doi.org/10.3390/en12244634.
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Off-grid systems play a prominent role in rural electrification planning. The problem of optimizing the generation design of a single off-grid system has received a significant amount of attention in the literature, and several software tools and algorithms have addressed it. However, methods and tools designed for individual mini-grids are not directly applicable to regional planning, where it is necessary to estimate the generation cost of potentially thousands of mini-grids. Conversely, most regional planning tools estimate the generation cost of mini-grids with rules of thumb or analytical expressions. These estimations are useful, but they lack the accuracy necessary to develop a rural electrification plan. This paper presents a method to estimate the generation cost of any potential off-grid system in a large-scale rural electrification planning problem, which is currently implemented in the Reference Electrification Model (REM). The method uses a master-slave decomposition that exploits the structure of the problem and combines continuous and discrete variables. The algorithm is illustrated with a case study that shows that a direct application of a discrete model may lead to suboptimal results in large-scale planning.
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Yu, Siwei, Jianwei Ma, and Bangliu Zhao. "Off-the-grid vertical seismic profile data regularization by a compressive sensing method." GEOPHYSICS 85, no. 2 (February 12, 2020): V157—V168. http://dx.doi.org/10.1190/geo2019-0357.1.
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Different from the surface survey, the vertical seismic profile (VSP) survey deploys sources on the surface and geophones in a well. VSP provides higher resolution information of subsurface structures. The faults that cannot be imaged with surface seismic data may be detected with VSP data, and detailed analysis of fracture zones can be achieved with multicomponent VSP. However, one of the main problems is that the sources seldom are acquired on a regular grid in realistic VSP surveys. The irregular samplings cause serious artifacts in migration or imaging, such that data regularization must be implemented first. We have developed a compressive sensing (CS)-based method to regularize nonstationary VSP data. Our method directly operates on irregularly gridded data sets, which is a key contribution compared to the existing CS-based reconstruction methods that work on regular grids. The CS framework consists of a sparsity constraint and a penalty term. We have used the curvelet transform for sparsity constraint of nonstationary events in the regularization term and the nonequispaced Fourier transform to regularize the VSP data in a penalty term. An alternative directional method of multipliers is used for solving the optimization problem. Our method is tested on synthetic, field 2D and 3D VSP data sets. Our method obtains improved reconstructions on continuities of the events and produces fewer artifacts compared to the well-known antileaking Fourier transform method.
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Leach, Matthew, Chris Mullen, Jacquetta Lee, Bartosz Soltowski, Neal Wade, Stuart Galloway, William Coley, Shafiqa Keddar, Nigel Scott, and Simon Batchelor. "Modelling the Costs and Benefits of Modern Energy Cooking Services—Methods and Case Studies." Energies 14, no. 12 (June 8, 2021): 3371. http://dx.doi.org/10.3390/en14123371.
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Globally, 2.8 billion people still cook with biomass, resulting in health, environmental, and social challenges; electric cooking is a key option for a transition to modern energy cooking services. However, electric cooking is assumed to be too expensive, grids can be unreliable and the connection capacity of mini-grids and solar home systems is widely assumed to be insufficient. Developments in higher performance and lower cost batteries and solar photovoltaics can help, but they raise questions of affordability and environmental impacts. The range of issues is wide, and existing studies do not capture them coherently. A new suite of models is outlined that represents the technical, economic, human, and environmental benefits and impacts of delivering electric cooking services, with a life-cycle perspective. This paper represents the first time this diverse range of approaches has been brought together. The paper illustrates their use through combined application to case studies for transitions of households from traditional fuels to electric cooking: for urban grid-connected households in Zambia; for mini-grid connected households in Tanzania; and for off-grid households in Kenya. The results show that electric cooking can be cost-effective, and they demonstrate overall reductions in human and ecological impacts but point out potential impact ‘hotspots’. The network analysis shows that electric cooking can be accommodated to a significant extent on existing grids, due partly to diversity effects in the nature and timing of cooking practices.
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Park, Sang-Yong, and Hyo-Sang Choi. "Operation Characteristics of Mechanical DC Circuit Breaker Combined with LC Divergence Oscillation Circuit for High Reliability of LVDC System." Energies 14, no. 16 (August 18, 2021): 5097. http://dx.doi.org/10.3390/en14165097.
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DC systems are modernly starting to come into the spotlight again due to the carbon-neutral policy, the development of semiconductor devices for power, and the increase in digital loads. We need to prepare in advance solutions to problems that may arise from fault currents due to transients for future DC power grid models. In the case of DC, there is no current zero-point because there is no frequency. Therefore, a large switching surge is generated when the circuit breaker cuts off the fault current. The possibility of insulation breakdown is greater than that of AC in severe cases. We consider power semiconductors or superconducting current limiters as an alternative. However, DC breaking cannot be safely achieved by itself. For reliable DC breaking, mechanical circuit breakers must be used with them. Among the mechanical shut-off methods, we adopted the divergence oscillation method. It has the biggest advantage compared to other methods in that it has a simple structure by composing passive elements and can artificially create zero current. In addition, it can be applied to a power semiconductor and a superconducting current limiter to perform a high-reliability cut-off operation. In this paper, we conducted simulation analysis by configuring the DC power grid and DC cut-off system through the PSCAD/EMTDC program. Results confirmed that the application of the LC divergence oscillation circuit can reduce the cut-off time and reduce the power burden of the mechanical DC circuit breaker (MCB).
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Hou, Gui Xin, Qi Hui Liu, Fang Yu, and Ying Li. "Summary and Analysis on the Low Voltage Ride through Reformation of the Wind Power Turbine." Advanced Materials Research 608-609 (December 2012): 781–84. http://dx.doi.org/10.4028/www.scientific.net/amr.608-609.781.
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As the increasing of the wind power capability， in order to ensure the stability of the grid while the voltage dips， the LVRT ability of the wind power turbine has become necessary. Realizing LVRT， is not only the question the built and will build wind power system are facing, but also the challenge of the will build and operating ones. Actually, many connected operating wind power system can’t meet the LVRT, this is why the large scale wind power off-grid events happened frequently, so the reformation of the wind power system LVRT is an emergency question to be solved. This paper introduced the main methods for LVRT reformation, based on this, some LVRT reform equipment was summarized for the wind turbine; and further, some reform methods were introduced for wind farm.
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Chukwumaobi,, ICHIE, Ichie, Fabeku David Olalekan, Ishaya Witta Caleb, and Umukoro Pheobe Oghenetega. "Scalable and Characterization Methods and Tools for Remote Monitoring of Off Grid Technologies: Case Study of 3x15mva Power Distribution Injection Substation in Nigeria." International Journal of Engineering and Advanced Technology 11, no. 5 (June 30, 2022): 74–81. http://dx.doi.org/10.35940/ijeat.e3548.0611522.
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Remote control and monitoring of energy resources are vital for the effective management of electricity in rural areas. Access to electricity in rural areas of Nigeria has grown in recent years. Nigeria appears to be growing rapidly in the electrification of both rural and urban areas through the use of distributed energy resources using renewable energy. Nevertheless, there have been challenges in the remote monitoring of the energy resources in the rural area. The challenges include high cost of implementation, available technology, power consumption, system integration, social-Economic challenge, etc. This paper present a cost-effective concept for remote monitoring systems of distributed energy resources (off-grid/mini-grid) and on-grid/main-grid technologies based on free open-source Supervisory Control and Data Acquisition (SCADA) or vison CC software that runs on a server located at the central station and a robust interface panel where the sensors measure system parameters, which are subsequently analyzed by signal processors before being transferred to a central location, where data is stored on the server's hard drive. The remote monitoring system is for monitoring and collection of energy data such as current, voltage, power, and environmental data such as temperature and humidity. The basic remote monitoring system consists of two components: a transmitter located at a remote site (where the mini-grid is installed) and a receiver located at the central station (where the system monitoring process is done). The proposed concept comprises various means of connecting locally with the remote system, with the connection being through Universal Serial Bus (USB), RS232, RS485, or Ethernet, where this data is stored on a central relational database management system, which makes it possible for posterior analysis.
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Chen, Fang Yuan, and Jian Huang. "An Electricity Parameter Measurement for Off-Grid PWM Converter." Applied Mechanics and Materials 325-326 (June 2013): 742–46. http://dx.doi.org/10.4028/www.scientific.net/amm.325-326.742.
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The input voltage of off-grid PWM converters has a great dynamic range in amplitude and frequency. In addition, the frequent changing of these parameters also makes it hard to measure preciously via traditional ways. Details of window function are presented. A modified FFT spectrum analyzing method using interpolation is also given and checked. Finally, a feasible solution which balances both precision and real-time data processing comes up considering the speed of MCUs mainly used in industry. Simulations and experiments show that this solution settles the troubles which cant be cleared up by traditional methods.
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López-Castrillón, William, Héctor H. Sepúlveda, and Cristian Mattar. "Off-Grid Hybrid Electrical Generation Systems in Remote Communities: Trends and Characteristics in Sustainability Solutions." Sustainability 13, no. 11 (May 23, 2021): 5856. http://dx.doi.org/10.3390/su13115856.
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The objective of this review is to present the characteristics and trends of hybrid renewable energy systems for remote off-grid communities. Traditionally, remote off-grid communities have used diesel oil-based systems to generate electricity. Increased technological options and lower costs have resulted in the adoption of hybrid renewable energy-based systems. The evaluated 168 studies from the period 2002–2019 considered energy developments in Asia, northern Europe, Africa and South America, with the great majority in the northern hemisphere (n = 152, 90.5%). Many of the studied systems were located in tropical (44.1%) and subtropical areas (31.0%). Our review shows that most of the studied approaches combined photovoltaic (PV) and wind energy and that diesel generators are the preferred backup system (61.3%), while batteries are the preferred method of energy storage (80.4%). Communities far from coasts have more options for renewable energy sources, such as biogas. Although half the studies were related to communities with access to marine-based renewable energy resources, their use was only referred to in fifteen studies. In terms of trends, the studies show a mature development of PV and wind-power technology for off-grid hybrid systems independent of the latitude, which is preferred as they are proven and accessible methods. The preferred storage method is batteries, and diesel is the preferred backup system given the low efficiency of PV and the intermittent character of wind power.
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Cai, Wenchao, Chenglong Li, Kodjo Agbossou, Pierre Bénard, and Jinsheng Xiao. "A review of hydrogen-based hybrid renewable energy systems: Simulation and optimization with artificial intelligence." Journal of Physics: Conference Series 2208, no. 1 (March 1, 2022): 012012. http://dx.doi.org/10.1088/1742-6596/2208/1/012012.
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Abstract With the massive use of traditional fossil fuels, greenhouse gas emissions are increasing, and environmental pollution is becoming an increasingly serious problem, which led to an imminent energy transition. Therefore, the development and application of renewable energy are particularly important. This paper reviews a wide range of issues associated with hybrid renewable energy systems (HRESs). The issues concerning system configurations, energy storage options, simulation and optimization with artificial intelligence are discussed in detail. Storage technology options are introduced for stand-alone (off-grid) and grid-connected (on-grid) HRESs. Different optimization methodologies, including classical techniques, intelligent techniques, hybrid techniques and software tools for sizing system components, are presented. Besides, the artificial intelligence methods for optimizing the solar/wind HRESs are discussed in detail.
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Habachi, Rachid, Achraf Touil, Abdellah Boulal, Abdelkabir Charkaoui, and Abdelwahed Echchatbi. "Comparative study of metaheuristics methods applied to smart grid network in Morocco." International Journal of Power Electronics and Drive Systems (IJPEDS) 11, no. 1 (March 1, 2020): 487. http://dx.doi.org/10.11591/ijpeds.v11.i1.pp487-495.
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The economic dispatch problem of power plays a very important role in the exploitation of electro-energy systems to judiciously distribute power generated by all plants. The Unit commitment problem (UCP) is mainly finding the minimum cost schedule to a set of generators by turning each one either on or off over a given time horizon to meet the demand load and satisfy different operational constraints, This research article integrates the crow search algorithm (CSA) as a local optimizer of Eagle strategy (ES) to solve economic dispatch and unit commitment problem in smart grid system of two electricity networks: a testing system 7 units and the Moroccan network.. The results obtained by ES- CSA are compared with various results obtained in the literature. Simulation results show that using ES-CSA can lead to finding stable and adequate power generated that can fulfill the need of both the civil and industrial areas<em>.</em>
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Gossard, Alban, Frédéric de Gournay, and Pierre Weiss. "Bayesian Optimization of Sampling Densities in MRI." Machine Learning for Biomedical Imaging 2, June 2023 (June 15, 2023): 253–87. http://dx.doi.org/10.59275/j.melba.2023-8172.
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Data-driven optimization of sampling patterns in MRI has recently received a significant attention. Following recent observations on the combinatorial number of minimizers in off-the-grid optimization, we propose a framework to globally optimize the sampling densities using Bayesian optimization. Using a dimension reduction technique, we optimize the sampling trajectories more than 20 times faster than conventional off-the-grid methods, with a restricted number of training samples. This method – among other benefits – discards the need of automatic differentiation. Its performance is slightly worse than state-of-the-art learned trajectories since it reduces the space of admissible trajectories, but comes with significant computational advantages. Other contributions include: i) a careful evaluation of the distance in probability space to generate trajectories ii) a specific training procedure on families of operators for unrolled reconstruction networks and iii) a gradient projection based scheme for trajectory optimization.
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Skwame, Y., J. Sabo, and T. Kyagya. "The Construction of Implicit One-step Block Hybrid Methods with Multiple Off-grid Points for the Solution of Stiff Differential Equations." Journal of Scientific Research and Reports 16, no. 1 (January 10, 2017): 1–7. http://dx.doi.org/10.9734/jsrr/2017/36187.
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Surinsky, Dmitry, Sergey Egorov, and Ilya Shchinnikov. "Investigation of methods of rodent control and analysis of existing devices constructed based on electrophysical control method." АгроЭкоИнфо 6, no. 48 (November 16, 2021): 5. http://dx.doi.org/10.51419/20216605.
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This article is considered used and newly developed rodent control devices, taking into account operating experience with patented structures, and analyzes the options for their use to control the pests. The analysis of the currently used methods for protection showed that there is a need not only to use devices for scaring and destruction, but also to design a device for research is required taking electrophysical methods for consideration. As a result, a model of an electrocontact grid has been proposed that plays the role of a stun gun to scare off rodents. Keywords: DERATIZATION, DERATIZER, ULTRASOUND, RODENTS, METHODS OF CONTROL, STUN GUN
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Kasprzyk, Leszek, Andrzej Tomczewski, Robert Pietracho, Agata Mielcarek, Zbigniew Nadolny, Krzysztof Tomczewski, Grzegorz Trzmiel, and Juan Alemany. "Optimization of a PV-Wind Hybrid Power Supply Structure with Electrochemical Storage Intended for Supplying a Load with Known Characteristics." Energies 13, no. 22 (November 23, 2020): 6143. http://dx.doi.org/10.3390/en13226143.
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An important aspect of the off-grid utilization of hybrid generation systems is the integration of energy storage facilities into their structures, which allows for improved power supply reliability. However, this results in a significant increase in the cost of such systems. Therefore, it is justified to use optimization resulting in the minimization of the selected economic indicator taking into account the most important technical constraints. For this reason, this work proposes an algorithm to optimize the structure of a hybrid off-grid power distribution system (with electrochemical energy storage), designed to supply a load with known daily energy demand. The authors recommend genetic algorithm utilization as well as a modified criterion for evaluating the quality of solutions based on the Levelized Cost of Energy (LCOE) index. Several technical and economic analyses were presented, including unit costs, power distribution of the wind and solar sections, nominal battery capacity, SSSI index (System Self-Sufficiency Index), etc. The model of the system includes durability of the elements which have a significant impact on the periodic battery replacement. The tests were carried out for two types of loads and two types of electrochemical batteries (NMC—Lithium Nickel Manganese Cobalt Oxide; and PbO2—Lead-Acid Battery), taking into account the forecast of an increased lifetime of NMC type batteries and decreasing their price within five years. The proposed synthesis method of photovoltaic-wind (PV-wind) hybrid off-line systems leads to limiting the energy capacity of electrochemical storages. Based on the analyses, the authors proposed recommended methods to improve (reduce) the value of the criterion index (LCOE) for PV-wind off-grid systems while maintaining the assumed level of power supply reliability.
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Hussain, Irshad, Majid Ullah, Ibrar Ullah, Asima Bibi, Muhammad Naeem, Madhusudan Singh, and Dhananjay Singh. "Optimizing Energy Consumption in the Home Energy Management System via a Bio-Inspired Dragonfly Algorithm and the Genetic Algorithm." Electronics 9, no. 3 (February 28, 2020): 406. http://dx.doi.org/10.3390/electronics9030406.
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Due to the exponential increase in the human population of this bio-sphere, energy resources are becoming scarce. Because of the traditional methods, most of the generated energy is wasted every year in the distribution network and demand side. Therefore, researchers all over the world have taken a keen interest in this issue and finally introduced the concept of the smart grid. Smart grid is an ultimate solution to all of the energy related problems of today’s modern world. In this paper, we have proposed a meta-heuristic optimization technique called the dragonfly algorithm (DA). The proposed algorithm is to a real-world problem of single and multiple smart homes. In our system model, two classes of appliances are considered; Shiftable appliances and Non-shiftable appliances. Shiftable appliances play a significant role in demand side load management because they can be scheduled according to real time pricing (RTP) signal from utility, while non-shiftable appliances are not much important in load management, as these appliances are fixed and cannot be scheduled according to RTP. On behalf of our simulation results, it can be concluded that our proposed algorithm DA has achieved minimum electricity cost with a tolerable waiting time. There is a trade-off between electricity cost and waiting time because, with a decrease in electricity cost, waiting time increases and vice versa. This trade-off is also obtained by our proposed algorithm DA. The stability of the grid is also maintained by our proposed algorithm DA because stability of the grid depends on peak-to-average ratio (PAR), while PAR is reduced by DA in comparison with an unscheduled case.
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Rajanna, B. V., Ganta Joga Rao, and S. K. Shrivastava. "Defining Control Strategies for Micro Grids Islanded Operation with Maximum Power Point Tracking using a Fuzzy Logic Control Scheme." International Journal of Power Electronics and Drive Systems (IJPEDS) 7, no. 3 (September 1, 2016): 723. http://dx.doi.org/10.11591/ijpeds.v7.i3.pp723-733.
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<p>This paper explains about an intelligent control method for the maximum power point tracking (MPPT) of a photo voltaic system with different temperature and insolation conditions. This method uses a fuzzy logic controller applied to a DC-DC converter. The different steps of the design of this controller are presented together with its simulation and the feasibility of control methods to be adopted for the operation of a micro grid when it becomes isolated. Normally, the micro grid operates in interconnected mode with the medium voltage network; however, scheduled or forced isolation can take place. In such conditions, the micro grid must have the ability to operate stably and autonomously. An evaluation of the need of storage devices and load to take off strategies is included in this paper. The MPPT of a photovoltaic system for Micro Grid operaion using a Fuzzy logic control scheme is successfully designed and simulated by using MATLAB/Simulink Software.</p>
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Gitifar, Siavash, Rahim Zahedi, Saba Ziaie, Amir Mohammad Mirzaei, and Mohammad Mahdi Forootan. "Review of different vertical axis wind turbine modeling methods." Future Energy 3, no. 1 (February 15, 2024): 23–33. http://dx.doi.org/10.55670/fpll.fuen.3.1.4.
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Wind energy can be used as an inexhaustible option for human consumption. Wind turbines offer a promising solution for off-grid areas. Darrieus turbine is one of the types of turbines that can be more efficient than other types if it is used by knowing its characteristics. The complex dynamic mechanism of the flow around the machine has led to its aerodynamic optimization problems remaining complex. This article reviews the applied methods in modeling vertical axis turbines and implicitly shows the turbine operation by presenting the results of these methods. Knowing these methods is important because each has its advantages and disadvantages and should be selected depending on the purpose of the research. One of the problems with Darrieus turbines is their poor start-up, which has been little researched so far. Finally, a suitable method that can model the start-up is introduced.
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Qian, Jianliang, and William W. Symes. "An adaptive finite‐difference method for traveltimes and amplitudes." GEOPHYSICS 67, no. 1 (January 2002): 167–76. http://dx.doi.org/10.1190/1.1451472.
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The point‐source traveltime field has an upwind singularity at the source point. Consequently, all formally high‐order, finite‐difference eikonal solvers exhibit first‐order convergence and relatively large errors. Adaptive upwind finite‐difference methods based on high‐order Weighted Essentially NonOscillatory (WENO) Runge‐Kutta difference schemes for the paraxial eikonal equation overcome this difficulty. The method controls error by automatic grid refinement and coarsening based on a posteriori error estimation. It achieves prescribed accuracy at a far lower cost than does the fixed‐grid method. Moreover, the achieved high accuracy of traveltimes yields reliable estimates of auxiliary quantities such as take‐off angles and geometric spreading factors.