Accuracy of wind energy forecasts in Great Britain and prospects for improvement

The metric representing the wind energy forecast error, when reported as a percent, is calculated quite differently than the error metrics for electricity transmission, electricity load, or in other industries such as manufacturing when they are also reported as a percent. The resulting calculated metric is quite different from what would be reported if the method utilized elsewhere was employed. This paper examines the possible forecast assessment and operational challenges associated with this finding. Concerning the prospects for improvement, the errors reported in MW of energy have a systematic component. With this insight, we developed a model to improve accuracy.     

Quantitative analysis of semiconductor supply chain contracts with order flexibility under demand uncertainty: A case study

The evidence base for the configuration of rolling horizon flexibility (RHF) contracts (a type of quantity flexibility contract) used in the semiconductor industry to coordinate production and demand remains meagre, more art than science. Informed by the characteristics of actual clauses and demand behaviors drawn from a company’s experience, a discrete-event simulation model is developed to represent the company’s supply chain. It comprises of three parties: a customer, a supplier (semiconductor manufacturer), and a capacity provider. Through analysis of customer forecasted demand the paper characterizes forecast demand as being under, over or unbiased. Models of these forecasted demands drives both long and short term planning. In long term planning, which is given twelve months before an order is delivered, capacity at the capacity provider is booked. Short term planning is also driven by this forecast which, within a binding period, is governed by an RHF contract. Results from the model report inventory levels, and delivery compliance, namely Delivery Performance (DP) and Delivery Reliability (DR), measures widely used in this sector. It is concluded from this work that on the balance of performance measures RHF contracts with asymmetrical flexibility bounds are substantially better than those with symmetrical boundaries, and that this conclusion is robust with regard to both over-planning and under-planning behaviors. This robustness is a critical attribute with respect to the endemic medium-term vacillation between both states experienced in practice in this sector.     

城市地震灾害经济损失预测方法综述

本文结合城市地震灾害损失大、牵连性强的特点,对现有地震灾害损失的预测方法进行了讨论和评述,认为在地震灾害损失预测时应把受灾城市看作一个灾场,充分考虑城市各系统之间的相互影响和作用,最后指出了进一步研究的方向和内容。     

Prediction of dynamic voltage stability status based on Hopf and limit induced bifurcations using extreme learning machine

Evaluation of voltage stability status considering its dynamic boundaries is a key issue for saving global stability of power systems. However, this evaluation is a computationally demanding task and its implementation is very hard (if not impossible) for on-line environments such as dispatching centers of power systems. In this paper, a new viewpoint for the problem based on modeling it as a forecast process is proposed, which can be implemented with a low computation burden for practical power systems. For this purpose, a voltage stability classification model considering Hopf and limit induced bifurcations is proposed and a new forecast strategy to predict voltage stability class label based on the proposed classification is suggested. The suggested forecast strategy is composed of an information theoretic feature selection technique, extreme learning machine (ELM) as the forecast engine and a line search procedure to fine-tune the settings. The effectiveness of the proposed classification model and forecast strategy is extensively illustrated on the New England 39-bus and IEEE 145-bus test systems.     

Forecasting conditional climate-change using a hybrid approach

A novel approach is proposed to forecast the likelihood of climate-change across spatial landscape gradients. This hybrid approach involves reconstructing past precipitation and temperature using the self-organizing map technique; determining quantile trends in the climate-change variables by quantile regression modeling; and computing conditional forecasts of climate-change variables based on self-similarity in quantile trends using the fractionally differenced auto-regressive integrated moving average technique. The proposed modeling approach is applied to states (Arizona, California, Colorado, Nevada, New Mexico, and Utah) in the southwestern U.S., where conditional forecasts of climate-change variables are evaluated against recent (2012) observations, evaluated at a future time period (2030), and evaluated as future trends (2009–2059). These results have broad economic, political, and social implications because they quantify uncertainty in climate-change forecasts affecting various sectors of society. Another benefit of the proposed hybrid approach is that it can be extended to any spatiotemporal scale providing self-similarity exists.     

Investigation of boundary‐layer wind predictions during nocturnal low‐level jet events using the Weather Research and Forecasting model

The accuracy of boundary‐layer wind profiles occurring during nocturnal low‐level jet (LLJ) events, and their sensitivities to variations of user‐specifiable model configuration parameters within the Weather Research and Forecasting model, was investigated. Simulations were compared against data from a wind‐profiling lidar, deployed to the Northern Great Plains during the U.S. Department of Energy‐supported Weather Forecast Improvement Project. Two periods during the autumn of 2011 featuring LLJs of similar magnitudes and durations occurring during several consecutive nights were selected for analysis. Simulated wind speed and direction at 80 and 180 m above the surface, the former a typical wind turbine hub height, bulk vertical gradients between 40 and 120 m, a typical rotor span, and the maximum wind speeds occurring at 80 and 180 m, and their times of occurrence, were compared with the observations. Sensitivities of these parameters to the horizontal and vertical grid spacing, planetary boundary layer and land surface model physics options, and atmospheric forcing dataset, were assessed using ensembles encompassing changes of each of these configuration parameters. Each simulation captured the diurnal cycle of wind speed and stratification, producing LLJs during each overnight period; however, large discrepancies in relation to the observations were frequently observed, with each ensemble producing a wide range of distributions, reflecting highly variable representations of stratification during the weakly stable overnight conditions. Root mean square error and bias values computed over the LLJ cycle (late evening through the following morning) revealed that, while some configurations performed better or worse in different aspects and at different times, none exhibited definitively superior performance. The considerable root mean square error and bias values, even among the ‘best’ performing simulations, underscore the need for improved simulation capabilities for the prediction of near‐surface winds during LLJ conditions. Copyright © 2015 John Wiley & Sons, Ltd.     

An application of OWA operators in fuzzy business diagnosis

The paper aims to develop an adjustment index based on OWA operators to enrich the results of diagnostic fuzzy models of business failure. A proposal to verify the diseases prediction accuracy of the models is also added. This allows a reduction of the map of causes or diseases detected in strategic defined areas. At the same time, these key areas can be disaggregated when an alert indicator is identified, and shows which of the causes need special attention. This application of OWA can encourage the development of suitable computer systems for monitoring companies’ problems, warn of failures and facilitate decision-making. In addition, taking Vigier and Terceño’s 2008 model as a benchmark, causes aggregation operators are introduced to evaluate alternative groupings, and the adjustment measure using approximate solutions is proposed to test the model’s prediction.The empirical estimation and the verification of the improvement proposals in a set of small and medium- sized enterprises (SMEs) in the construction industry are also presented. The functionality and the prediction capacity are thus measured and detected by monitoring key areas that warn about insolvency situations in the firm.     

Research on the energy-saving and revenue sharing strategy of ESCOs under the uncertainty of the value of Energy Performance Contracting Projects

Under the uncertainty of the value of Energy Performance Contracting Projects (EPCPs), this paper develops a revenue-sharing bargaining model between an Energy Service Company (ESCO) and an Energy-Using Organization (EU). Based on the model the paper analyzes the impacts of energy prices, risk-adjusted discount rates and accidents on the ESCO’s bargaining strategies. The research shows that the greater the probability of adverse circumstances is, the higher is the revenue share (of the EU), and the more disadvantageous is the ESCO’s position in the game. Furthermore, we design a forecast–commitment contract between an ESCO and an EU and analyze the optimal product’s energy savings commitment strategy of the ESCO to cope with uncertain energy savings and contract risk. The research illustrates that by introducing penalties and commitments, the contract can eliminate the impact of the uncertain energy savings on the contract execution to a certain extent; when the EU takes a greater commitment risk, the ESCO is willing to provide a higher commitment, thus enhancing the strategy value of the bilateral relationship and reducing the contract risk. Finally, the policy recommendations about improving shared savings contract standard, third-party energy savings measurement and verification mechanism and arbitration mechanism of EPCs are provided.     

“十一五”中国电解金属锰工业的发展和“十二五”展望

中国电解金属锰工业在“十一五”取得了很大发展,对其在各个方面取得的主要成绩进行了介绍,分析了在发展过程中存在的主要问题,同时也展望了电解金属锰在“十二五”发展态势。     

非圆信号多级维纳滤波MUSIC测向算法

为降低非圆信号的MUSIC(记为NC-MUSIC)测向算法的计算量,提出了基于多级维纳滤波的NC-MUSIC算法.首先,该算法将非圆信号特性用于多级维纳滤波算法,构造出扩展阵列输出矩阵,利用多级维纳滤波的递推特性求出信号子空间,而不需要估计样本协方差矩阵和对其特征值分解;其次,为了进一步降低算法的计算量,推导出信号子空间的谱峰一维搜索公式进行非圆信号谱峰搜索的计算,快速估算出目标的方位值.仿真结果和计算复杂度分析表明,新算法不但在均方根误差性能上与其他快速算法相似,均接近于NC-MUSIC算法,具有良好的估计性能,而且降低了NC-MUSIC算法的计算最,使其计算复杂度小于非圆信号扩展传播算子快速测向算法的计算复杂度.证实了新算法快速有效的估计性能.