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Conceptual study on incorporating user information into forecasting systems

Jiarui HAN, Qian YE, Zhongwei YAN, Meiyan JIAO, Jiangjiang XIA

《环境科学与工程前沿（英文）》 2011年第5卷第4期页码 533-542 doi: 10.1007/s11783-010-0246-6

摘要： The purpose of improving weather forecast is to enhance the accuracy in weather prediction. An ideal forecasting system would incorporate user-end information. In recent years, the meteorological community has begun to realize that while general improvements to the physical characteristics of weather forecasting systems are becoming asymptotically limited, the improvement from the user end still has potential. The weather forecasting system should include user interaction because user needs may change with different weather. A study was conducted on the conceptual forecasting system that included a dynamic, user-oriented interactive component. This research took advantage of the recently implemented TIGGE (THORPEX interactive grand global ensemble) project in China, a case study that was conducted to test the new forecasting system with reservoir managers in Linyi City, Shandong Province, a region rich in rivers and reservoirs in eastern China. A self-improving forecast system was developed involving user feedback throughout a flood season, changing thresholds for flood-inducing rainfall that were responsive to previous weather and hydrological conditions, and dynamic user-oriented assessments of the skill and uncertainty inherent in weather prediction. This paper discusses ideas for developing interactive, user-oriented forecast systems.

关键词： user-end information user-oriented interactive forecasting system TIGGE (THORPEX interactive grand global ensemble)

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美国NRC颠覆性技术持续预测系统浅析

张晓林

《中国工程科学》 2018年第20卷第6期页码 117-121 doi: 10.15302/J-SSCAE-2018.06.019

摘要：

美国国家研究委员会（NRC）发布的《颠覆性技术持续性预测》（Persistent Forecasting of Disruptive Technologies

关键词：颠覆性技术持续预测理想系统

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A novel methodology for forecasting gas supply reliability of natural gas pipeline systems

Feng CHEN, Changchun WU

《能源前沿（英文）》 2020年第14卷第2期页码 213-223 doi: 10.1007/s11708-020-0672-5

摘要： In this paper, a novel systematic and integrated methodology to assess gas supply reliability is proposed based on the Monte Carlo method, statistical analysis, mathematical-probabilistic analysis, and hydraulic simulation. The method proposed has two stages. In the first stage, typical scenarios are determined. In the second stage, hydraulic simulation is conducted to calculate the flow rate in each typical scenario. The result of the gas pipeline system calculated is the average gas supply reliability in each typical scenario. To verify the feasibility, the method proposed is applied for a real natural gas pipelines network system. The comparison of the results calculated and the actual gas supply reliability based on the filed data in the evaluation period suggests the assessment results of the method proposed agree well with the filed data. Besides, the effect of different components on gas supply reliability is investigated, and the most critical component is identified. For example, the 48th unit is the most critical component for the SH terminal station, while the 119th typical scenario results in the most severe consequence which causes the loss of 175.61×10 m gas when the 119th scenario happens. This paper provides a set of scientific and reasonable gas supply reliability indexes which can evaluate the gas supply reliability from two dimensions of quantity and time.

关键词： natural gas pipeline system gas supply reliability evaluation index Monte Carlo method hydraulic simulation

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INTERACTIVE KNOWLEDGE LEARNING BY ARTIFICIAL INTELLIGENCE FOR SMALLHOLDERS

《农业科学与工程前沿（英文）》 2023年第10卷第4期页码 648-653 doi: 10.15302/J-FASE-2023505

摘要：

Enhancement of farming management relies heavily on enhancing farmer knowledge. In the past, both the direct learning approach and the personnel extension system for improving fertilization practices of smallholders has proven insufficiently effective. Therefore, this article proposes an interactive knowledge learning approach using artificial intelligence as a promising alternative. The system consists of two parts. The first is a dialog interface that accepts information from farmers about their current farming practices. The second part is an intelligent decision system, which categorizes the information provided by farmers in two categories. The first consists of on-farm constraints, such as fertilizer resources, split application times and seasons. The second comprises knowledge-based practices by farmers, such as nutrient in- and output balance, ratios of different nutrients and the ratios of each split nutrient amount to the total nutrient input. The interactive knowledge learning approach aims to identify and rectify incorrect practices in the knowledge-based category while considering the farmer’s available finance, labor, and fertilizer resources. Investigations show that the interactive knowledge learning approach can make a strong contribution to prevention of the overuse of nitrogen and phosphorus fertilizers, and mitigating agricultural non-point source pollution.

关键词： artificial intelligence extension system non-point source pollution control smallholders fertilization

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Regional wind power forecasting model with NWP grid data optimized

Zhao WANG, Weisheng WANG, Bo WANG

《能源前沿（英文）》 2017年第11卷第2期页码 175-183 doi: 10.1007/s11708-017-0471-9

摘要： Unlike the traditional fossil energy, wind, as the clean renewable energy, can reduce the emission of the greenhouse gas. To take full advantage of the environmental benefits of wind energy, wind power forecasting has to be studied to overcome the troubles brought by the variable nature of wind. Power forecasting for regional wind farm groups is the problem that many power system operators care about. The high-dimensional feature sets with redundant information are frequently encountered when dealing with this problem. In this paper, two kinds of feature set construction methods are proposed which can achieve the proper feature set either by selecting the subsets or by transforming the original variables with specific combinations. The former method selects the subset according to the criterion of minimal-redundancy-maximal-relevance (mRMR), while the latter does so based on the method of principal component analysis (PCA). A locally weighted learning method is also proposed to utilize the processed feature set to produce the power forecast results. The proposed model is simple and easy to use with parameters optimized automatically. Finally, a case study of 28 wind farms in East China is provided to verify the effectiveness of the proposed method.

关键词： regional wind power forecasting feature set minimal-redundancy-maximal-relevance (mRMR) principal component analysis (PCA) locally weighted learning model

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A comprehensive review and analysis of solar forecasting techniques

Pardeep SINGLA, Manoj DUHAN, Sumit SAROHA

《能源前沿（英文）》 2022年第16卷第2期页码 187-223 doi: 10.1007/s11708-021-0722-7

摘要： In the last two decades, renewable energy has been paid immeasurable attention to toward the attainment of electricity requirements for domestic, industrial, and agriculture sectors. Solar forecasting plays a vital role in smooth operation, scheduling, and balancing of electricity production by standalone PV plants as well as grid interconnected solar PV plants. Numerous models and techniques have been developed in short, mid and long-term solar forecasting. This paper analyzes some of the potential solar forecasting models based on various methodologies discussed in literature, by mainly focusing on investigating the influence of meteorological variables, time horizon, climatic zone, pre-processing techniques, air pollution, and sample size on the complexity and accuracy of the model. To make the paper reader-friendly, it presents all-important parameters and findings of the models revealed from different studies in a tabular mode having the year of publication, time resolution, input parameters, forecasted parameters, error metrics, and performance. The literature studied showed that ANN-based models outperform the others due to their nonlinear complex problem-solving capabilities. Their accuracy can be further improved by hybridization of the two models or by performing pre-processing on the input data. Besides, it also discusses the diverse key constituents that affect the accuracy of a model. It has been observed that the proper selection of training and testing period along with the correlated dependent variables also enhances the accuracy of the model.

关键词： forecasting techniques hybrid models neural network solar forecasting error metric support vector machine (SVM)

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long-term model with consideration of uncertainties for deployment of distributed energy resources using interactive

Iraj AHMADIAN,Oveis ABEDINIA,Noradin GHADIMI

《能源前沿（英文）》 2014年第8卷第4期页码 412-425 doi: 10.1007/s11708-014-0315-9

摘要： This paper presents a novel modified interactive honey bee mating optimization (IHBMO) base fuzzy stochastic long-term approach for determining optimum location and size of distributed energy resources (DERs). The Monte Carlo simulation method is used to model the uncertainties associated with long-term load forecasting. A proper combination of several objectives is considered in the objective function. Reduction of loss and power purchased from the electricity market, loss reduction in peak load level and reduction in voltage deviation are considered simultaneously as the objective functions. First, these objectives are fuzzified and designed to be comparable with each other. Then, they are introduced into an IHBMO algorithm in order to obtain the solution which maximizes the value of integrated objective function. The output power of DERs is scheduled for each load level. An enhanced economic model is also proposed to justify investment on DER. An IEEE 30-bus radial distribution test system is used to illustrate the effectiveness of the proposed method.

关键词： component distributed energy resources fuzzy optimization loss reduction interactive honey bee mating optimization (IHBMO) voltage deviation reduction stochastic programming

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仿真技术发展及应用

王子才

《中国工程科学》 2003年第5卷第2期页码 40-44

摘要：

从仿真技术的发展、成熟、再发展的观点论述了它的发展过程。介绍了仿真技术在国民经济各个领域中的应用。分析了国内外仿真技术水平及现状，展望了仿真技术的发展趋势。

关键词：仿真技术系统仿真半实物仿真分布交互仿真

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Interactive effects of high-speed rail on nodal zones in a city: exploratory study on China

Guo LIU, Kunhui YE

《工程管理前沿（英文）》 2019年第6卷第3期页码 327-335 doi: 10.1007/s42524-019-0051-2

摘要： The arrival of the high-speed rail (HSR) era has accelerated the pace of urban development, but its broad socioeconomic impact remains subject to intense debates. This research aims to propose a model for measuring the impact of HSR operation on HSR stations and the surrounding areas, which this research call the HSR-based nodal zone (HNZ). The proposed model is composed of two variables (i.e., transportation situation and vitality) and three subsystems (i.e., economic, societal, and environmental). Data were collected in China through questionnaire survey. Results indicate that the effects of HSR operation on HNZ are multidimensional, transportation vitality has an intermediary role in the effects, and the effects on the physical environment are negative. This study presents an early examination of the impact of HSR operation on the HSR stations and relevant areas and contributes new evidence to academic debates on the contribution of HSR to urban development. Accordingly, urban development policies should be built on the mechanism of HSR in driving the growth of HNZ.

关键词： high-speed rail nodal zone interactive effects sustainable urbanization China

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Day-ahead electricity price forecasting using back propagation neural networks and weighted least square

S. Surender REDDY,Chan-Mook JUNG,Ko Jun SEOG

《能源前沿（英文）》 2016年第10卷第1期页码 105-113 doi: 10.1007/s11708-016-0393-y

摘要： This paper proposes the day-ahead electricity price forecasting using the artificial neural networks (ANN) and weighted least square (WLS) technique in the restructured electricity markets. Price forecasting is very important for online trading, e-commerce and power system operation. Forecasting the hourly locational marginal prices (LMP) in the electricity markets is a very important basis for the decision making in order to maximize the profits/benefits. The novel approach proposed in this paper for forecasting the electricity prices uses WLS technique and compares the results with the results obtained by using ANNs. To perform this price forecasting, the market knowledge is utilized to optimize the selection of input data for the electricity price forecasting tool. In this paper, price forecasting for Pennsylvania-New Jersey-Maryland (PJM) interconnection is demonstrated using the ANNs and the proposed WLS technique. The data used for this price forecasting is obtained from the PJM website. The forecasting results obtained by both methods are compared, which shows the effectiveness of the proposed forecasting approach. From the simulation results, it can be observed that the accuracy of prediction has increased in both seasons using the proposed WLS technique. Another important advantage of the proposed WLS technique is that it is not an iterative method.

关键词： day-ahead electricity markets price forecasting load forecasting artificial neural networks load serving entities

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上海建设网上城市通用系统架构的实践与前景

严隽琪

《中国工程科学》 2005年第7卷第5期页码 1-8

摘要：

从方便性、协同性、共享性、开放性和安全性这五个角度出发，提出了上海建设网上城市的通用系统架构模型，阐述了实现该架构模型的相关关键技术，介绍了上海市在网上城市建设方面的工程实践，并提出了发展展望。

关键词：海网上城市系统架构信息资源互动服务工程实践

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Forecasting industrial emissions: a monetary approach

Yang DONG, Yi LIU, Jining CHEN, Yebin DONG, Benliang QU

《环境科学与工程前沿（英文）》 2012年第6卷第5期页码 734-742 doi: 10.1007/s11783-012-0451-6

摘要： Forecasts of industrial emissions provide a basis for impact assessment and development planning. To date, most studies have assumed that industrial emissions are simply coupled to production value at a given stage of technical progress. It has been argued that the monetary method tends to overestimate pollution loads because it is highly influenced by market prices and fails to address spatial development schemes. This article develops a land use-based environmental performance index (L-EPI) that treats the industrial land areas as a dependent variable for pollution emissions. The basic assumption of the method is that at a planning level, industrial land use change can represent the change in industrial structure and production yield. This physical metric provides a connection between the state-of-the-art and potential impacts of future development and thus avoids the intrinsic pitfalls of the industrial Gross Domestic Product-based approach. Both methods were applied to examine future industrial emissions at the planning area of Dalian Municipality, North-west China, under a development scheme provided by the urban master plan. The results suggested that the L-EPI method is highly reliable and applicable for the estimation and explanation of the spatial variation associated with industrial emissions.

关键词： industrial emissions environmental performance index spatial planning industrial land use

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智能预报模式与水文中长期智能预报方法

陈守煜,郭瑜,王大刚

《中国工程科学》 2006年第8卷第7期页码 30-35

摘要：

建立了以模糊优选、BP神经网络及遗传算法有机结合的智能预报模式与方法。在应用该方法进行中长期水文智能预报时，首先选取训练样本的数量，根据预报因子与预报对象的相关关系得到相对隶属度矩阵;再将其作为BP神经网络输入值以训练连接权重；最后将得到的连接权重值用于预报检验。计算结果表明，智能预报模式与方法的运行速度、精度及稳定性都达到了实际应用的要求。

关键词：模糊优选 BP神经网络遗传算法智能预报模式中长期水文智能预报

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基于BP-AGA的非线性组合预测方法研究

王硕,张有富,金菊良

《中国工程科学》 2005年第7卷第4期页码 83-87

摘要：

运用神经网络和加速遗传算法建立非线性组合预测模型，在BP算法训练网络出现收敛速度缓慢时启用加速遗传算法（AGA）来优化网络参数，把AGA的优化结果作为BP算法的初始值，再用BP算法训练网络，如此交替运行BP算法和AGA以加快网络的收敛速度，同时改善局部最小问题。最后给出实例研究，结果表明，该方法能明显提高预测精度。

关键词：神经网络加速遗传算法非线性组合预测预测精度

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高铁客站建设动态互动管理理论研究

郑健

《中国工程科学》 2011年第13卷第8期页码 31-35

摘要：

高速铁路及其客站建设是我国经济社会持续发展的必然产物，其建设与运营将促进区域经济一体化及都市圈和经济带的形成与发展，从而为经济社会发展提供动力与支撑。党的十六大以来，伴随着中国高铁的快速发展，高铁客站迎来了难得的发展机遇。截至2011年3月，共建成北京南、武汉、广州南、上海虹桥等139座高铁客站。笔者分析了高铁客站与经济社会发展之间的互动关系，结合大规模高铁客站建设实践，研究提出了以经济社会发展演化规律为指导的战略、项目集与项目的动态互动模型和管理理论，为科学制定我国高铁客站建设的战略目标体系及项目集、单项目管理提供了理论依据。

关键词：高铁客站经济社会项目集动态互动管理