无烟煤制工业燃气项目原料煤价与经济性的关系分析

针对我国建材行业传统使用的常压固定床煤气发生炉及化肥行业固定床间歇气化炉面临淘汰,无烟煤市场萎缩的情况,提出以晋城无烟煤为原料,利用赛鼎碎煤加压气化技术,生产适合建材行业大规模使用的工业燃气。以无烟煤为原料的河北沙河年产26亿m^3工业清洁燃气项目为基础,对无烟煤与天然气价格、项目经济性的关系进行了分析,结果表明,以晋城无烟块煤运到河北沙河的到厂价935元/t计算,盈亏平衡天然气价约2.26元/m^3;以沙河工业天然气到户售价2.5元/m^3计算,盈亏平衡到厂煤价约1 077元/t,项目经济性较好。     

基于峰谷分时电价的虚拟电厂日前申报及运行优化

鉴于分布式能源的出力性质为间歇性和波动性,影响电网安全高效运行,而虚拟电厂可解决此问题。对虚拟电厂进行申报-调度两阶段建模,以包含分布式电源(光电、风电和燃气轮机)和储能系统(储能电池)两大类分布式能源的虚拟电厂为例,基于光照强度及风速等不确定因素,研究峰谷分时电价下日前市场虚拟电厂的出力申报和运行调度策略并利用风险价值模型进行风险管理。结果表明,申报出力时,当电价激励足够高时储能电池方会参与出力,成功起到削峰填谷的作用;运行调度时,平衡出力偏差方面,储能电池发挥主要作用,且虚拟电厂运行调度策略具有一定的经济效益。     

矿山工程建设项目造价管理信息系统设计

为提高矿山工程建设项目造价管理水平,设计了矿山工程建设项目造价管理系统。通过分析矿山工程项目的造价组成,并采用三层B/S架构设计系统硬件框架,运用Web服务器传输矿山工程项目各项数据,划分系统功能子系统,并对矿山工程建设项目造价额与价差预备费进行计算,完成系统软件设计。结果表明,该系统能够有效管理矿山工程建设项目造价,并对外部的恶意攻击进行及时报警,系统具有有效性与安全性。     

Quality improvement and backorder price discount under controllable lead time in an inventory model

The proposed study investigates a continuous review inventory model with order quantity, reorder point, backorder price discount, process quality, and lead time as decision variables. An investment function is used to improve the process quality. Two models are developed based on the probability distribution of lead time demand. The lead time demand follows a normal distribution in the first model and in the second model it does not follow any specific distribution but mean and standard deviation are known. We prove two lemmas to obtain optimal solutions for the normal distribution model and distribution free model. Finally, some numerical examples are given to illustrate the model.     

Geospatial analysis for utilizing the marginal land in regional biofuel industry: A case study in Guangdong Province,China

Due to the intensive and exhaustive land use in China, the so-called marginal land is expected to play a major role in supporting the biofuel industry of the country. We developed a regional-level framework of using geospatial information technologies to achieve an optimal utilization of the marginal land for biofuel production. The framework includes identifying marginal lands, evaluating optimality of the land for growing certain bioenergy crops, estimating local potential feedstock production, and finally selecting optimal sites for biofuel factories. We present a case study of farming Jatropha (Jatropha curcas L.) and Cassava (Manihot esculenta Crantz) in Guangdong, China. The marginal land was identified from satellite imageries at a 30-m resolution. The optimality for growing the two species was evaluated using the Ecological Niche Models (ENMs), which incorporates local temperature, precipitation, soil, and terrain. The optimality value was then converted into potential feedstock production using a conversion model. The site selection for the factories incorporated the local potential feedstock production, the transportation cost measured by road distance, and the farming cost related to the land patch geometry. Each candidate site received an overall optimality score derived based on those factors. We identified five sites that have high scores and also minimal or none spatial overlaps of their supporting areas. Three of them (Zhanjiang, Yunfu, and Jieyang) are for Cassava, located on in southern Guangdong. Two (Qingyuan and Meizhou) are for Jatropha in northern Guangdong.     

DG planning with amalgamation of economic and reliability considerations

Distributed generation has been playing a vital role in dealing with issues related to distribution systems. This paper presents an approach which provides the distribution system operator with a set of solutions for DG placement to optimize reliability and total cost of power consumed by the distribution system. Optimal location of a Distributed Generator is evaluated based on the performance indices derived for reliability index and total cost of power consumed by the system. The proposed approach is applied to a 15-bus radial distribution system and a 18-bus radial distribution system and the results are analyzed.     

Mixed coordination mechanisms for scheduling games on hierarchical machines

In this paper, we study scheduling games under mixed coordination mechanisms on hierarchical machines. The two scheduling policies involved are ‐ and ‐, where ‐ (resp., ‐) policy sequences jobs in nondecreasing order of their hierarchies, and jobs of the same hierarchy in nonincreasing (resp., nondecreasing) order of their processing times. We first show the existence of a Nash equilibrium. Then we present the price of anarchy and the price of stability for the games with social costs of minimizing the makespan and maximizing the minimum machine load. All the bounds given in this paper are tight.     

两阶段领域自适应学习

针对领域自适应问题中源域和目标域的联合分布差异最小化问题,提出两阶段领域自适应学习方法.在第一阶段考虑样本标签和数据结构的判别信息,通过学习一个共享投影变换,使投影后的共享空间中边缘分布的差异最小.第二阶段利用源域标记数据和目标域非标记数据学习一个带结构风险的自适应分类器,不仅能最小化源域和目标域条件分布差异,还能进一步保持源域和目标域边缘分布的流形一致性.在3个基准数据集上的实验表明,文中方法在平均分类准确率和Kappa系数两项评价指标上均表现较优.     

A bat-neural network multi-agent system (BNNMAS) for stock price prediction: Case study of DAX stock price

Creating an intelligent system that can accurately predict stock price in a robust way has always been a subject of great interest for many investors and financial analysts. Predicting future trends of financial markets is more remarkable these days especially after the recent global financial crisis. So traders who access to a powerful engine for extracting helpful information throw raw data can meet the success. In this paper we propose a new intelligent model in a multi-agent framework called bat-neural network multi-agent system (BNNMAS) to predict stock price. The model performs in a four layer multi-agent framework to predict eight years of DAX stock price in quarterly periods. The capability of BNNMAS is evaluated by applying both on fundamental and technical DAX stock price data and comparing the outcomes with the results of other methods such as genetic algorithm neural network (GANN) and some standard models like generalized regression neural network (GRNN), etc. The model tested for predicting DAX stock price a period of time that global financial crisis was faced to economics. The results show that BNNMAS significantly performs accurate and reliable, so it can be considered as a suitable tool for predicting stock price specially in a long term periods.     

Industrial sugar beets to biofuel: Field to fuel production system and cost estimates

Specialized varieties of sugar beets (Beta vulgaris L.) may be an eligible feedstock for advanced biofuel designation under the USA Energy Independence and Security Act of 2007. These non-food industrial beets could double ethanol production per hectare compared to alternative feedstocks. A mixed-integer mathematical programming model was constructed to determine the breakeven price of ethanol produced from industrial beets, and to determine the optimal size and biorefinery location. The model, based on limited field data, evaluates Southern Plains beet production in a 3-year crop rotation, and beet harvest, transportation, and processing. The optimal strategy depends critically on several assumptions including a just-in-time harvest and delivery system that remains to be tested in field trials. Based on a wet beet to ethanol conversion rate of 110 dm³ Mg⁻¹ and capital cost of 128 M$ for a 152 dam³ y⁻¹ biorefinery, the estimated breakeven ethanol price was 507 $ m⁻³. The average breakeven production cost of corn (Zea mays L.) grain ethanol ranged from 430 to 552 $ m⁻³ based on average net corn feedstock cost of 254 and 396 $ m⁻³ in 2014 and 2013, respectively. The estimated net beet ethanol delivered cost of 207 $ m⁻³ was lower than the average net corn feedstock cost of 254–396$ m⁻³ in 2013 and 2014. If for a mature industry, the cost to process beets was equal to the cost to process corn, the beet breakeven ethanol price would be $387 m^-3 (587 $ m⁻³ gasoline equivalent).