Millimeter wave(mmWave)massive multiple-input multiple-output(MIMO)plays an important role in the fifth-generation(5G)mobile communications and beyond wireless communication systems owing to its potential of high capa...Millimeter wave(mmWave)massive multiple-input multiple-output(MIMO)plays an important role in the fifth-generation(5G)mobile communications and beyond wireless communication systems owing to its potential of high capacity.However,channel estimation has become very challenging due to the use of massive MIMO antenna array.Fortunately,the mmWave channel has strong sparsity in the spatial angle domain,and the compressed sensing technology can be used to convert the original channel matrix into the sparse matrix of discrete angle grid.Thus the high-dimensional channel matrix estimation is transformed into a sparse recovery problem with greatly reduced computational complexity.However,the path angle in the actual scene appears randomly and is unlikely to be completely located on the quantization angle grid,thus leading to the problem of power leakage.Moreover,multiple paths with the random distribution of angles will bring about serious interpath interference and further deteriorate the performance of channel estimation.To address these off-grid issues,we propose a parallel interference cancellation assisted multi-grid matching pursuit(PIC-MGMP)algorithm in this paper.The proposed algorithm consists of three stages,including coarse estimation,refined estimation,and inter-path cyclic iterative inter-ference cancellation.More specifically,the angular resolution can be improved by locally refining the grid to reduce power leakage,while the inter-path interference is eliminated by parallel interference cancellation(PIC),and the two together improve the estimation accuracy.Simulation results show that compared with the traditional orthogonal matching pursuit(OMP)algorithm,the normalized mean square error(NMSE)of the proposed algorithm decreases by over 14dB in the case of 2 paths.展开更多
传统压缩感知(CS,Compressive Sensing)成像方法一般假定目标精确位于事先划定的成像网格上,实际中由于散射点空间位置是连续分布的,因此偏离网格(Off-grid)问题必然存在.这会引起真实回波测量值与默认系统观测矩阵之间失配,导致传统CS...传统压缩感知(CS,Compressive Sensing)成像方法一般假定目标精确位于事先划定的成像网格上,实际中由于散射点空间位置是连续分布的,因此偏离网格(Off-grid)问题必然存在.这会引起真实回波测量值与默认系统观测矩阵之间失配,导致传统CS成像方法性能恶化.本文基于频率分集多输入多输出(FD-MIMO,Frequency Diverse Multiple-Input Multiple-Output)雷达,针对Off-grid目标提出了一种基于贝叶斯压缩感知的稀疏自聚焦(SAF-BCS,Sparse Autofocus Imaging Method Based on Bayesian Compressive Sensing)成像算法.该算法依据最大后验(MAP,Maximum A Posteriori)准则,利用变分贝叶斯学习技术求解含有Off-grid目标的稀疏像.与传统稀疏重构方法相比,所提方法充分利用了目标先验信息,可自适应调整参数,能够更好地反演稀疏目标,同时具有校正Off-grid目标的网格位置偏差以及估计噪声功率等优势.仿真结果表明SAF-BCS算法对网格划分不敏感,具有稳健的成像性能.展开更多
Rural electrification remains a great challenge for Sub-Saharan Africa (SSA) as access to electricity is a prerequisite to accelerate its development. The present paper reviews the measures adopted to promote access t...Rural electrification remains a great challenge for Sub-Saharan Africa (SSA) as access to electricity is a prerequisite to accelerate its development. The present paper reviews the measures adopted to promote access to electricity in rural and remote areas of SSA. The main barriers to rural electrification in these developing countries are presented before showing technologies used for the aforementioned purpose. Then, adopted methods for enhancing the use of renewable energy in SSA are shown. Moreover, the policy adopted by decision makers and project planners are also highlighted. In addition, the optimal solutions proposed by researchers are given such as the cost-effective off-grid system type that might be a viable alternative to diesel power generation.展开更多
Domestic off-grid renewable energy systems have become common place in many areas of the world, as humanity seeks to keep abreast with global technological changes and advancements. This paper aims to present a cost-e...Domestic off-grid renewable energy systems have become common place in many areas of the world, as humanity seeks to keep abreast with global technological changes and advancements. This paper aims to present a cost-effective energy monitoring system which may be used to analyze and evaluate the operation of a domestic off-grid PV system. Parameters which are monitored include the output voltage and current from a 55 W polycrystalline PV panel. The output voltage and current from a power regulation circuit (which could be a DC-DC converter, solar charger or MPPT) is also monitored with this singular system which incorporates a data logging interface circuit, a data logger and a personal computer.展开更多
Shaanxi province has three land forms which are Shaanxi’s northern plateau, Guanzhong plain and Qinba mountain land in the south of Shaanxi province. So the climate type is also divided into three types and the solar...Shaanxi province has three land forms which are Shaanxi’s northern plateau, Guanzhong plain and Qinba mountain land in the south of Shaanxi province. So the climate type is also divided into three types and the solar energy resources distribution has a big gap between different regions. PV modules, as the core component of off-grid home photovoltaic power system, their output power are mainly influenced by sun radiation, array tile angle, temperature and so on. Based on the reasons above, in order to apply off-grid home photovoltaic power system in Shaanxi region, this paper designs different systems with different configuration, and makes the performance prediction. The results show that the capacity of PV modules reaches to the largest in Shaanxi northern region, reach minimum in Shaanxi southern region and the output power in the winter is less than in the summer and reach minimum in the spring and autumn. In light of the characteristics above, this research select different type and configuration in different areas systematically, and the performance analysis shows that the configuration can meet the basic life demand of power to the people whose power is not available.展开更多
Because working performance of off-grid home photovoltaic power system is influenced by factors of solar radiation, ambient temperature and installation angle, this research established power supply model, analyzed wo...Because working performance of off-grid home photovoltaic power system is influenced by factors of solar radiation, ambient temperature and installation angle, this research established power supply model, analyzed working performance and optimized system configuration, by referencing weather conditions of Yulin and Yan’an and those factors. Results showed that under given solar radiation and ambient temperature, difference of installation angle can cause 30% to 40% difference of performance. In order to meet power demand, installation angles of Yulin and Yan'an were selected as 40 degree and 30 degree, and annual output power were 1.44 kWh/Wp and 1.32 kWh/Wp. Based on those results, the configuration of Yulin and Yan'an was 150 Wp and 170 Wp, and annual output power was 172.70 kWh and 179.66 kWh. Systems optimized above can meet the mid-scale demand in Shaanxi northern region and build theoretical foundation of application.展开更多
Necessity of electricity access in remote area is the main reason for expanding decentralized energy system such as stand-alone power systems. The best electrical power supply must provide a constant magnitude and fre...Necessity of electricity access in remote area is the main reason for expanding decentralized energy system such as stand-alone power systems. The best electrical power supply must provide a constant magnitude and frequency voltage. Therefore, good power quality is an important factor for the reliable operation of electrical loads in a power system. However, the current drawn by most of electronic devices and non-linear loads are non-sinusoidal, which can result in a poor power quality, especially in off-grid power systems. Poor power quality is characterized by electrical disturbances such as transients, sags, swells, harmonics and even interruptions in the power supply. Off-grid power systems worldwide often struggle with system failures and equipment damage due to poor power quality. In this paper, MAT- LAB/Simulink is used to model and analyses power quality in an off-grid renewable energy system. The results show high voltage transient when the inductive loads were switched OFF. The voltage and current harmonics are also determined and compared for various types of loads.展开更多
Roughly 99% of the demand for electricity in Brazil is supplied by a national interconnected grid. The remaining 1% is spread in several “isolated systems” of the Amazon region—mini-grids that rely on expensive die...Roughly 99% of the demand for electricity in Brazil is supplied by a national interconnected grid. The remaining 1% is spread in several “isolated systems” of the Amazon region—mini-grids that rely on expensive diesel gensets due to high commodity and transportation costs. The isolated systems also have remote communities disconnected altogether from the mini-grids with inadequate health, education and leisure services. These communities are precariously supplied by small inefficient diesel gensets that run for a few hours per day. In this article, we propose a sustainable and economic alternative for the electric supply of the remote communities of isolated systems through a combination of photovoltaic solar generation and storage. The objective is to improve access to electricity with savings for the communities. The present paper outlines a public policy to meet this objective.展开更多
This paper develops a deep estimator framework of deep convolution networks(DCNs)for super-resolution direction of arrival(DOA)estimation.In addition to the scenario of correlated signals,the quantization errors of th...This paper develops a deep estimator framework of deep convolution networks(DCNs)for super-resolution direction of arrival(DOA)estimation.In addition to the scenario of correlated signals,the quantization errors of the DCN are the major challenge.In our deep estimator framework,one DCN is used for spectrum estimation with quantization errors,and the remaining two DCNs are used to estimate quantization errors.We propose training our estimator using the spatial sampled covariance matrix directly as our deep estimator’s input without any feature extraction operation.Then,we reconstruct the original spatial spectrum from the spectrum estimate and quantization errors estimate.Also,the feasibility of the proposed deep estimator is analyzed in detail in this paper.Once the deep estimator is appropriately trained,it can recover the correlated signals’spatial spectrum fast and accurately.Simulation results show that our estimator performs well in both resolution and estimation error compared with the state-of-the-art algorithms.展开更多
Due to the uncertainty of renewable energy power generation and the non-linearity of load demand,it becomes complicated to determine the capacity of each device in hybrid renewable energy power generation systems.This...Due to the uncertainty of renewable energy power generation and the non-linearity of load demand,it becomes complicated to determine the capacity of each device in hybrid renewable energy power generation systems.This work aims to optimize the capacity of two types of the off-grid hybrid wind-hydrogen energy system.We considered the maximum profit of the system and the minimum loss of power supply probability as optimization goals.Firstly,we established steady-state models of the wind turbine,alkaline electrolyzer,lead-acid battery,and proton exchange membrane fuel cell in matrix laboratory software to optimize the capacity.Secondly,we analyzed the operating mode of the system and determined two system structures(system contains batteries whether or not).Finally,according to the wind speed and load in the sample area,we compared the economics of the two systems and selected the optimal configuration for the area.In the same calculation example data,the non-dominated sorting genetic algorithm-II(NSGA-II)is used to optimize the capacity of each device in the two systems.The results showed that the profit of the without battery-equipped system is 32.38%higher than another system.But the power supply reliability is the opposite.To avoid the contingency of the calculation results,we used the traditional genetic algorithm(GA)and ant colony optimization(ACO)to calculate the same example.The results showed that NSGA-II is significantly better than GA and ACO in terms of iteration steps and calculation results.The required architecture for the System-I composes of 3 numbers of 10 kW wind turbines,61 sets of 12 V·240 Ah leadacid batteries,8 kW electrolytic cell,and 6 kW PEMFC.The net profit and LPSP are ¥44,315 and 0.01254 respectively.The required architecture for the System-II composes of 2 numbers of 10 kW wind turbines,24 kW electrolytic cells,and 18 kW PEMFC.Net profit and LPSP are ¥58,663 and 0.03244,respectively.This paper provided two schemes for the optimal configuration of the hybrid wind-hydrogen energy system in islanding mode,which provided a theoretical basis for practical engineering applications.展开更多
This paper presents a method for optimal sizing of an off-grid hybrid microgrid (MG) system in order to achieve a certain load demand. The hybrid MG is made of a solar photovoltaic (PV) system, wind turbine (TW) and e...This paper presents a method for optimal sizing of an off-grid hybrid microgrid (MG) system in order to achieve a certain load demand. The hybrid MG is made of a solar photovoltaic (PV) system, wind turbine (TW) and energy storage system (ESS). The reliability of the MG system is modeled based on the loss of power supply probability (SPSP). For optimization, an enhanced Genetic Algorithm (GA) is used to minimize the total cost of the system over a 20-year period, while satisfying some reliability and operation constraints. A case study addressing optimal sizing of an off-grid hybrid microgrid in Nigeria is discussed. The result is compared with results obtained from the Brute Force and standard GA methods.展开更多
Although renewable energy technologies applications to rural communities to improve energy access have been embraced in numerous parts of the world, sustainability of these systems is increasingly becoming critical as...Although renewable energy technologies applications to rural communities to improve energy access have been embraced in numerous parts of the world, sustainability of these systems is increasingly becoming critical as far as realization of long term benefits is concerned. The current manuscript proposes approaches deemed to provide appropriate match between technology and users in a select of Botswana’s rural communities. The methodology includes a participatory and inclusive approach in which the local community is engaged in the generation of their own energy. Available information indicates that available feedstock in selected communities is sufficient to generate and provide sustainable energy supply for the community.展开更多
For domestic consumers in the rural areas of northern Kenya, as in other developing countries, the typical source of electrical supply is diesel generators. However, diesel generators are associated with both CO2 emis...For domestic consumers in the rural areas of northern Kenya, as in other developing countries, the typical source of electrical supply is diesel generators. However, diesel generators are associated with both CO2 emissions, which adversely affect the environment and increase diesel fuel prices, which inflate the prices of consumer goods. The Kenya government has taken steps towards addressing this issue by proposing The Hybrid Mini-Grid Project, which involves the installation of 3 MW of wind and solar energy systems in facilities with existing diesel generators. However, this project has not yet been implemented. As a contribution to this effort, this study proposes, simulates and analyzes five different configurations of hybrid energy systems incorporating wind energy, solar energy and battery storage to replace the stand-alone diesel power systems servicing six remote villages in northern Kenya. If implemented, the systems proposed here would reduce Kenya’s dependency on diesel fuel, leading to reductions in its carbon footprint. This analysis confirms the feasibility of these hybrid systems with many configurations being profitable. A Multi-Attribute Trade-Off Analysis is employed to determine the best hybrid system configuration option that would reduce diesel fuel consumption and jointly minimize CO2 emissions and net present cost. This analysis determined that a wind-diesel-battery configuration consisting of two 500 kW turbines, 1200 kW diesel capacity and 95,040 Ah battery capacity is the best option to replace a 3200 kW stand-alone diesel system providing electricity to a village with a peak demand of 839 kW. It has the potential to reduce diesel fuel consumption and CO2 emissions by up to 98.8%.展开更多
With the increasingly fierce competition among communication operators,it is more and more important to make an accurate prediction of potential off grid users.To solve the above problem,it is inevitable to consider t...With the increasingly fierce competition among communication operators,it is more and more important to make an accurate prediction of potential off grid users.To solve the above problem,it is inevitable to consider the effectiveness of learning algo rithms,the efficiency of data processing,and other factors.Therefore,in this paper,we,from the practical application point of view,propose a potential customer off grid predic tion system based on Spark,including data pre processing,feature selection,model build ing,and effective display.Furthermore,in the research of off grid system,we use the Spark parallel framework to improve the gcForest algorithm which is a novel decision tree ensemble approach.The new parallel gcForest algorithm can be used to solve practical problems,such as the off grid prediction problem.Experiments on two real world datasets demonstrate that the proposed prediction system can handle large scale data for the off grid user prediction problem and the proposed parallel gcForest can achieve satisfying per formance.展开更多
基金supported in part by the Beijing Natural Science Foundation under Grant No.L202003the National Natural Science Foundation of China under Grant U22B2001 and 62271065the Project of China Railway Corporation under Grant N2022G048.
文摘Millimeter wave(mmWave)massive multiple-input multiple-output(MIMO)plays an important role in the fifth-generation(5G)mobile communications and beyond wireless communication systems owing to its potential of high capacity.However,channel estimation has become very challenging due to the use of massive MIMO antenna array.Fortunately,the mmWave channel has strong sparsity in the spatial angle domain,and the compressed sensing technology can be used to convert the original channel matrix into the sparse matrix of discrete angle grid.Thus the high-dimensional channel matrix estimation is transformed into a sparse recovery problem with greatly reduced computational complexity.However,the path angle in the actual scene appears randomly and is unlikely to be completely located on the quantization angle grid,thus leading to the problem of power leakage.Moreover,multiple paths with the random distribution of angles will bring about serious interpath interference and further deteriorate the performance of channel estimation.To address these off-grid issues,we propose a parallel interference cancellation assisted multi-grid matching pursuit(PIC-MGMP)algorithm in this paper.The proposed algorithm consists of three stages,including coarse estimation,refined estimation,and inter-path cyclic iterative inter-ference cancellation.More specifically,the angular resolution can be improved by locally refining the grid to reduce power leakage,while the inter-path interference is eliminated by parallel interference cancellation(PIC),and the two together improve the estimation accuracy.Simulation results show that compared with the traditional orthogonal matching pursuit(OMP)algorithm,the normalized mean square error(NMSE)of the proposed algorithm decreases by over 14dB in the case of 2 paths.
文摘传统压缩感知(CS,Compressive Sensing)成像方法一般假定目标精确位于事先划定的成像网格上,实际中由于散射点空间位置是连续分布的,因此偏离网格(Off-grid)问题必然存在.这会引起真实回波测量值与默认系统观测矩阵之间失配,导致传统CS成像方法性能恶化.本文基于频率分集多输入多输出(FD-MIMO,Frequency Diverse Multiple-Input Multiple-Output)雷达,针对Off-grid目标提出了一种基于贝叶斯压缩感知的稀疏自聚焦(SAF-BCS,Sparse Autofocus Imaging Method Based on Bayesian Compressive Sensing)成像算法.该算法依据最大后验(MAP,Maximum A Posteriori)准则,利用变分贝叶斯学习技术求解含有Off-grid目标的稀疏像.与传统稀疏重构方法相比,所提方法充分利用了目标先验信息,可自适应调整参数,能够更好地反演稀疏目标,同时具有校正Off-grid目标的网格位置偏差以及估计噪声功率等优势.仿真结果表明SAF-BCS算法对网格划分不敏感,具有稳健的成像性能.
文摘Rural electrification remains a great challenge for Sub-Saharan Africa (SSA) as access to electricity is a prerequisite to accelerate its development. The present paper reviews the measures adopted to promote access to electricity in rural and remote areas of SSA. The main barriers to rural electrification in these developing countries are presented before showing technologies used for the aforementioned purpose. Then, adopted methods for enhancing the use of renewable energy in SSA are shown. Moreover, the policy adopted by decision makers and project planners are also highlighted. In addition, the optimal solutions proposed by researchers are given such as the cost-effective off-grid system type that might be a viable alternative to diesel power generation.
文摘Domestic off-grid renewable energy systems have become common place in many areas of the world, as humanity seeks to keep abreast with global technological changes and advancements. This paper aims to present a cost-effective energy monitoring system which may be used to analyze and evaluate the operation of a domestic off-grid PV system. Parameters which are monitored include the output voltage and current from a 55 W polycrystalline PV panel. The output voltage and current from a power regulation circuit (which could be a DC-DC converter, solar charger or MPPT) is also monitored with this singular system which incorporates a data logging interface circuit, a data logger and a personal computer.
文摘Shaanxi province has three land forms which are Shaanxi’s northern plateau, Guanzhong plain and Qinba mountain land in the south of Shaanxi province. So the climate type is also divided into three types and the solar energy resources distribution has a big gap between different regions. PV modules, as the core component of off-grid home photovoltaic power system, their output power are mainly influenced by sun radiation, array tile angle, temperature and so on. Based on the reasons above, in order to apply off-grid home photovoltaic power system in Shaanxi region, this paper designs different systems with different configuration, and makes the performance prediction. The results show that the capacity of PV modules reaches to the largest in Shaanxi northern region, reach minimum in Shaanxi southern region and the output power in the winter is less than in the summer and reach minimum in the spring and autumn. In light of the characteristics above, this research select different type and configuration in different areas systematically, and the performance analysis shows that the configuration can meet the basic life demand of power to the people whose power is not available.
文摘Because working performance of off-grid home photovoltaic power system is influenced by factors of solar radiation, ambient temperature and installation angle, this research established power supply model, analyzed working performance and optimized system configuration, by referencing weather conditions of Yulin and Yan’an and those factors. Results showed that under given solar radiation and ambient temperature, difference of installation angle can cause 30% to 40% difference of performance. In order to meet power demand, installation angles of Yulin and Yan'an were selected as 40 degree and 30 degree, and annual output power were 1.44 kWh/Wp and 1.32 kWh/Wp. Based on those results, the configuration of Yulin and Yan'an was 150 Wp and 170 Wp, and annual output power was 172.70 kWh and 179.66 kWh. Systems optimized above can meet the mid-scale demand in Shaanxi northern region and build theoretical foundation of application.
文摘Necessity of electricity access in remote area is the main reason for expanding decentralized energy system such as stand-alone power systems. The best electrical power supply must provide a constant magnitude and frequency voltage. Therefore, good power quality is an important factor for the reliable operation of electrical loads in a power system. However, the current drawn by most of electronic devices and non-linear loads are non-sinusoidal, which can result in a poor power quality, especially in off-grid power systems. Poor power quality is characterized by electrical disturbances such as transients, sags, swells, harmonics and even interruptions in the power supply. Off-grid power systems worldwide often struggle with system failures and equipment damage due to poor power quality. In this paper, MAT- LAB/Simulink is used to model and analyses power quality in an off-grid renewable energy system. The results show high voltage transient when the inductive loads were switched OFF. The voltage and current harmonics are also determined and compared for various types of loads.
文摘Roughly 99% of the demand for electricity in Brazil is supplied by a national interconnected grid. The remaining 1% is spread in several “isolated systems” of the Amazon region—mini-grids that rely on expensive diesel gensets due to high commodity and transportation costs. The isolated systems also have remote communities disconnected altogether from the mini-grids with inadequate health, education and leisure services. These communities are precariously supplied by small inefficient diesel gensets that run for a few hours per day. In this article, we propose a sustainable and economic alternative for the electric supply of the remote communities of isolated systems through a combination of photovoltaic solar generation and storage. The objective is to improve access to electricity with savings for the communities. The present paper outlines a public policy to meet this objective.
文摘This paper develops a deep estimator framework of deep convolution networks(DCNs)for super-resolution direction of arrival(DOA)estimation.In addition to the scenario of correlated signals,the quantization errors of the DCN are the major challenge.In our deep estimator framework,one DCN is used for spectrum estimation with quantization errors,and the remaining two DCNs are used to estimate quantization errors.We propose training our estimator using the spatial sampled covariance matrix directly as our deep estimator’s input without any feature extraction operation.Then,we reconstruct the original spatial spectrum from the spectrum estimate and quantization errors estimate.Also,the feasibility of the proposed deep estimator is analyzed in detail in this paper.Once the deep estimator is appropriately trained,it can recover the correlated signals’spatial spectrum fast and accurately.Simulation results show that our estimator performs well in both resolution and estimation error compared with the state-of-the-art algorithms.
基金supported by the Inner Mongolia Science and Technology Program under Grant 2021GG0336by the Open Fund of Key Laboratory of Wind Energy and Solar Energy Technology(Inner Mongolia University of Technology),Ministry of Education(No.2020ZD01)in China.
文摘Due to the uncertainty of renewable energy power generation and the non-linearity of load demand,it becomes complicated to determine the capacity of each device in hybrid renewable energy power generation systems.This work aims to optimize the capacity of two types of the off-grid hybrid wind-hydrogen energy system.We considered the maximum profit of the system and the minimum loss of power supply probability as optimization goals.Firstly,we established steady-state models of the wind turbine,alkaline electrolyzer,lead-acid battery,and proton exchange membrane fuel cell in matrix laboratory software to optimize the capacity.Secondly,we analyzed the operating mode of the system and determined two system structures(system contains batteries whether or not).Finally,according to the wind speed and load in the sample area,we compared the economics of the two systems and selected the optimal configuration for the area.In the same calculation example data,the non-dominated sorting genetic algorithm-II(NSGA-II)is used to optimize the capacity of each device in the two systems.The results showed that the profit of the without battery-equipped system is 32.38%higher than another system.But the power supply reliability is the opposite.To avoid the contingency of the calculation results,we used the traditional genetic algorithm(GA)and ant colony optimization(ACO)to calculate the same example.The results showed that NSGA-II is significantly better than GA and ACO in terms of iteration steps and calculation results.The required architecture for the System-I composes of 3 numbers of 10 kW wind turbines,61 sets of 12 V·240 Ah leadacid batteries,8 kW electrolytic cell,and 6 kW PEMFC.The net profit and LPSP are ¥44,315 and 0.01254 respectively.The required architecture for the System-II composes of 2 numbers of 10 kW wind turbines,24 kW electrolytic cells,and 18 kW PEMFC.Net profit and LPSP are ¥58,663 and 0.03244,respectively.This paper provided two schemes for the optimal configuration of the hybrid wind-hydrogen energy system in islanding mode,which provided a theoretical basis for practical engineering applications.
文摘This paper presents a method for optimal sizing of an off-grid hybrid microgrid (MG) system in order to achieve a certain load demand. The hybrid MG is made of a solar photovoltaic (PV) system, wind turbine (TW) and energy storage system (ESS). The reliability of the MG system is modeled based on the loss of power supply probability (SPSP). For optimization, an enhanced Genetic Algorithm (GA) is used to minimize the total cost of the system over a 20-year period, while satisfying some reliability and operation constraints. A case study addressing optimal sizing of an off-grid hybrid microgrid in Nigeria is discussed. The result is compared with results obtained from the Brute Force and standard GA methods.
文摘Although renewable energy technologies applications to rural communities to improve energy access have been embraced in numerous parts of the world, sustainability of these systems is increasingly becoming critical as far as realization of long term benefits is concerned. The current manuscript proposes approaches deemed to provide appropriate match between technology and users in a select of Botswana’s rural communities. The methodology includes a participatory and inclusive approach in which the local community is engaged in the generation of their own energy. Available information indicates that available feedstock in selected communities is sufficient to generate and provide sustainable energy supply for the community.
文摘For domestic consumers in the rural areas of northern Kenya, as in other developing countries, the typical source of electrical supply is diesel generators. However, diesel generators are associated with both CO2 emissions, which adversely affect the environment and increase diesel fuel prices, which inflate the prices of consumer goods. The Kenya government has taken steps towards addressing this issue by proposing The Hybrid Mini-Grid Project, which involves the installation of 3 MW of wind and solar energy systems in facilities with existing diesel generators. However, this project has not yet been implemented. As a contribution to this effort, this study proposes, simulates and analyzes five different configurations of hybrid energy systems incorporating wind energy, solar energy and battery storage to replace the stand-alone diesel power systems servicing six remote villages in northern Kenya. If implemented, the systems proposed here would reduce Kenya’s dependency on diesel fuel, leading to reductions in its carbon footprint. This analysis confirms the feasibility of these hybrid systems with many configurations being profitable. A Multi-Attribute Trade-Off Analysis is employed to determine the best hybrid system configuration option that would reduce diesel fuel consumption and jointly minimize CO2 emissions and net present cost. This analysis determined that a wind-diesel-battery configuration consisting of two 500 kW turbines, 1200 kW diesel capacity and 95,040 Ah battery capacity is the best option to replace a 3200 kW stand-alone diesel system providing electricity to a village with a peak demand of 839 kW. It has the potential to reduce diesel fuel consumption and CO2 emissions by up to 98.8%.
基金supported by ZTE Industry-Academia-Research Cooperationthe National Key Research and Development Program of China under Grant No.2017YFB1002104+1 种基金the National Natural Science Foundation of China under Grant Nos.U1836206,U1811461,and 61773361the Project of Youth Innovation Promotion Association CAS under Grant No.2017146
文摘With the increasingly fierce competition among communication operators,it is more and more important to make an accurate prediction of potential off grid users.To solve the above problem,it is inevitable to consider the effectiveness of learning algo rithms,the efficiency of data processing,and other factors.Therefore,in this paper,we,from the practical application point of view,propose a potential customer off grid predic tion system based on Spark,including data pre processing,feature selection,model build ing,and effective display.Furthermore,in the research of off grid system,we use the Spark parallel framework to improve the gcForest algorithm which is a novel decision tree ensemble approach.The new parallel gcForest algorithm can be used to solve practical problems,such as the off grid prediction problem.Experiments on two real world datasets demonstrate that the proposed prediction system can handle large scale data for the off grid user prediction problem and the proposed parallel gcForest can achieve satisfying per formance.
