Estimation of a preference map of new consumers for spatial load forecasting simulation methods using a spatial analysis of points

The paper presents a spatial analysis of points especially suited to estimate a preference map for new consumers, which is then used as an analytical tool in spatial electric load forecasting. This approach is an exploratory spatial data analysis used to discover useful point patterns in the spatial location of distribution transformers to calculate a preference value for each area, rating it with respect to a hypothetical load change that may occur. We consider the locations of distribution transformers occupied land. Random points are generated in the study area where the new loads are expected; these points are referred to as unoccupied land. The method uses a generalized additive model (GAM) to estimate the probability of unoccupied land becoming occupied land. We test the approach with data from a real distribution system in a mid-size city in Brazil; the result is a preference map that shows the areas where new consumers are most likely to be allocated. The main advantage of this method is the ability work with a small-scale resolution, which enables the use of a resolution suitable for spatial load forecasting method chosen. We test the calculated probabilities in a spatial load forecasting simulation, yielding results with lower spatial error when compared with the heuristic technique.     

New concepts in biomass gasification

Gasification is considered as a key technology for the use of biomass. In order to promote this technology in the future, advanced, cost-effective, and highly efficient gasification processes and systems are required. This paper provides a detailed review on new concepts in biomass gasification.Concepts for process integration and combination aim to enable higher process efficiencies, better gas quality and purity, and lower investment costs. The recently developed UNIQUE gasifier which integrates gasification, gas cleaning and conditioning in one reactor unit is an example for a promising process integration. Other interesting concepts combine pyrolysis and gasification or gasification and combustion in single controlled stages. An approach to improve the economic viability and sustainability of the utilization of biomass via gasification is the combined production of more than one product. Polygeneration strategies for the production of multiple energy products from biomass gasification syngas offer high efficiency and flexibility.     

产融结合对上市公司经营绩效和企业价值的影响

以我国上市公司为研究样本,从金融机构参股钢铁上市公司的视角,分析不同参股比例的产融结合行为对经营绩效、企业价值的影响。经分析发现,金融机构参股超过一定比例后,产融结合对企业经营绩效和企业价值呈显著非线性相关关系。     

Seasonal hydrological and nutrient loading forecasts for watersheds over the Southeastern United States

We show useful seasonal deterministic and probabilistic prediction skill of streamflow and nutrient loading over watersheds in the Southeastern United States (SEUS) for the winter and spring seasons. The study accounts for forecast uncertainties stemming from the meteorological forcing and hydrological model uncertainty. Multi-model estimation from three hydrological models, each forced with an ensemble of forcing derived by matching observed analogues of forecasted quartile rainfall anomalies from a seasonal climate forecast is used. The attained useful hydrological prediction skill is despite the climate model overestimating rainfall by over 23% over these SEUS watersheds in December–May period. The prediction skill in the month of April and May is deteriorated as compared to the period from December–March (zero lead forecast). A nutrient streamflow rating curve is developed using a log linear tool for this purpose. The skill in the prediction of seasonal nutrient loading is identical to the skill of seasonal streamflow forecast.     

Mode-dependent stochastic stability criteria of fuzzy Markovian jumping neural networks with mixed delays

This paper investigates the stochastic stability of fuzzy Markovian jumping neural networks with mixed delays in mean square. The mixed delays include time-varying delay and continuously distributed delay. By using the Lyapunov functional method, Jensen integral inequality, the generalized Jensen integral inequality, linear convex combination technique and the free-weight matrix method, several novel sufficient conditions are derived to ensure the global asymptotic stability of the equilibrium point of the considered networks in mean square. The proposed results, which do not require the differentiability of the activation functions, can be easily checked via Matlab software. Finally, two numerical examples are given to demonstrate the effectiveness and less conservativeness of our theoretical results over existing literature.     

有机-无机联合矿井突水水源判别方法

溶解性有机质(Dissolved Organic Matter,DOM)在随地下水运移过程中,不同含水层水中DOM含量、类别、荧光强度等均存在较明显差异,因此结合无机水化学,开展了有机-无机联合的矿井突水水源判别方法研究,结果表明:地下水中无机组分浓度分布具有垂向分带性,利用pH、矿化度(TDS),HCO3,SO4等无机指标,可以判别浅部含水层和深部含水层水化学特征差异; DOM进入含水层后发生氧化还原反应强烈,其浓度(TOC含量和UV254)变化快、差异大,可以识别地表水与第四系水的水化学特征;第四系与白垩系含水层,以及覆岩破坏范围内的细分含水层,水中无机组分和有机组分含量非常接近,而荧光指纹技术灵敏度高,可以根据3DEEM光谱图分析DOM类型和荧光峰强度等差异,区分相邻含水层的水化学特征差异。陷落柱等地质异常体作为特殊的地质环境体,其内部水体中DOM相对丰富,其DOM含量和荧光指纹特征与奥灰水差异显著。将有机-无机联合开展不同含水层水化学特征分析,能够很好地区分不同水源,为矿井突水事故发生时快速判别水源提供科学依据。     

基于深度脊波神经网络的电力系统短期负荷预测模型

针对电力系统负荷的非线性预测问题,本文构造了一种基于深度脊波神经网络的电力系统短期负荷预测模型。该模型的隐含层采用脊波神经元,神经元的激励函数采用脊波变换函数。对该预测模型采用受限的玻尔兹曼机学习原理进行预训练,最后利用粒子群优化算法对其进行深度优化精调。通过对某地区实际电网负荷系统进行仿真预测,结果表明,与传统的BP神经网络、脊波神经网络和常规深度神经网络模型相对比,深度脊波神经网络预测模型的日平均绝对误差百分比分别降低了1.96%、1.12%和0.3%,日最大绝对误差分别降低了3.91%、2.19%和1.78%,验证了深度脊波神经网络预测模型具有较好的预测准确度和稳定性。     

Thermo-economic analysis and optimization of a combined Organic Rankine Cycle (ORC) system with LNG cold energy and waste heat recovery of dual-fuel marine engine

A combined Organic Rankine Cycle (ORC) system with liquefied nature gas (LNG) cold energy and dual-fuel (DF) marine engine waste heat utilization was proposed. Engine exhaust gas and engine jacket cooling water were adopted as parallel heat sources. Thermo-economic analyses of the proposed system with 32 working fluids combinations were performed. Two objective functions covering thermal efficiencies and economic index were employed for performance evaluation. Afterward, the effects of operation pressure on the objective functions were investigated. Finally, the optimal conditions were obtained from the Pareto front with the Non-dominated Sorting Genetic Algorithm-II (NSGA-II) method. The results show that the proposed ORC system has better energy recovery performances than the parallel ORC system. R1150-R600a-R290, R1150-R601a-R600a, and R170-R601-R290 are determined as the three most promising working fluids combinations. Under optimized conditions, the output power range is 199.97 to 218.51 kW, the energy efficiency range is 13.64% to 15.62%, and the exergy efficiency range is 25.29% to 27.3%. The payback period ranges from 8.36 to 8.74 years. The working fluids selection helps to reduce the exergy destruction of intermediate heat exchanger, which could be up to 30.59%.     

多晶硅生产中残液搅拌罐密封结构的改造

在处理多晶硅生产中产生的残液时,残液搅拌罐填料密封出现泄漏,针对此问题提出了优化措施,达到了预期效果。     

An optimal integrated lot sizing and maintenance strategy for multi-machines system with energy consumption

This paper proposes an integrated model for multi-machines dynamic lot sizing aiming to produce a single item, considering the energy consumption during the production horizon. The objective is to find, firstly, the optimal lot size as well as the number of machines that satisfy a random demand under given service level and secondly, maintenance plan depended to production planning to minimise the total production, energy and maintenance costs. In fact, the problem of energy consumption is one of the most evoked topics especially with the decision of many governments to reduce theirs (For example France is willing to reduce the total consumption by 20% by 2020). The keys of this study are to consider, firstly, the correlation between the forecasting of demand, the variation of the working machines as well as their production rates under energy constraint and secondly the correlation between the production cadences and the maintenance strategy of all machines.