Marginal cost and congestion in the Italian electricity market: An indirect estimation approach

In this paper we construct an indirect measure of the supply marginal cost function for the main generators from the observed bid data in the Italian electricity market in the period 2004–2007. We compute the residual demand function for each generator, taking explicitly into account the issue of transmission line congestion. This procedure allows recovering correct zonal Lerner index and the implied measure of the marginal cost function. We find evidence of a stable U-shaped marginal cost function for three main Italian generators, but a flat function for ENEL, the former national monopolist. The policy relevance of our approach lies in the possibility to offer some empirical knowledge of the marginal cost function of each generator to the regulator to design appropriate policy measures geared to the promotion of competitive market conditions. We propose a new market surveillance mechanism, which is based on the principle of sanctioning excessive deviations from the estimated measure of the marginal cost function presented in this work.     

管道风险管理方法研究

按照管道风险管理的流程分别对管道风险评价、风险控制和决策支持、效能测试和响应进行了论述。针对目前国内管道行业的情况，提出了进行管道风险评价的有效方法及维护措施。着重介绍了国外管道风险可接受标准的情况，作为国内制定管道风险评价标准的参考。     

Forecasting based on sectoral energy consumption of GHGs in Turkey and mitigation policies

Recently, global warming and its effects have become one of the most important themes in the world. Under the Kyoto Protocol, the EU has agreed to an 8% reduction in its greenhouse gas (GHG) emissions by 2008–2012. The GHG emissions (total GHG, CO₂, CO, SO₂, NO₂, E (emissions of non-methane volatile organic compounds)) covered by the Protocol are weighted by their global warming potentials (GWPs) and aggregated to give total emissions in CO₂ equivalents. The main subject in this study is to obtain equations by the artificial neural network (ANN) approach to predict the GHGs of Turkey using sectoral energy consumption. The equations obtained are used to determine the future level of the GHG and to take measures to control the share of sectors in total emission. According to ANN results, the maximum mean absolute percentage error (MAPE) was found as 0.147151, 0.066716, 0.181901, 0.105146, 0.124684, and 0.158157 for GHG, SO₂, NO₂, CO, E, and CO₂, respectively, for the training data with Levenberg–Marquardt (LM) algorithm by 8 neurons. R² values are obtained very close to 1. Also, this study proposes mitigation policies for GHGs.     

Reducing energy-related CO2 emissions using accelerated weathering of limestone

The use and impacts of accelerated weathering of limestone (AWL; reaction: CO₂+H₂O+CaCO₃→Ca²⁺+2(HCO₃⁻) is explored as a CO₂ capture and sequestration method. It is shown that significant limestone resources are relatively close to a majority of CO₂-emitting power plants along the coastal US, a favored siting location for AWL. Waste fines, representing more than 20% of current US crushed limestone production (>10⁹ tonnes/yr), could provide an inexpensive or free source of AWL carbonate. With limestone transportation then as the dominant cost variable, CO₂ mitigation costs of $3-$4/tonne appear to be possible in certain locations. Perhaps 10–20% of US point–source CO₂ emissions could be mitigated in this fashion. It is experimentally shown that CO₂ sequestration rates of 10⁻⁶ to 10⁻⁵ moles/sec per m² of limestone surface area are achievable, with reaction densities on the order of 10⁻² tonnes CO₂ m⁻³day⁻¹, highly dependent on limestone particle size, solution turbulence and flow, and CO₂ concentration. Modeling shows that AWL would allow carbon storage in the ocean with significantly reduced impacts to seawater pH relative to direct CO₂ disposal into the atmosphere or sea. The addition of AWL-derived alkalinity to the ocean may itself be beneficial for marine biota.     

Possibilities and problems with the use of models as a communication tool in water resource management

Politicians and policy-makers, as well as modellers, often nurses an expectation that model derived results is an objective source of information that can be used to support decisions. However, several prerequisites have to be dealt with in order to ensure that models can be used as legitimate and efficient tools in water resource management. Based on empirical material from recent studies on the use of models in stakeholder dialogues, mainly focusing on catchment nutrient transport, two central problems are identified: (a) Models are laden with choices and thus depend on assumptions and priorities of modellers. (b) There are several factors that influence ability and willingness of stakeholders (as information recovers) to criticize or accept results of the modelling exercise. Recognized factors likely to influence stakeholders' acceptance of model derived results include issues at stake, stakeholders' ability to criticize model derived information, and their trust in the institutions that have developed or applied the used models. Identified prerequisites for successful use of models in integrated water resource management include: consideration of user relevance, awareness of and preparedness to handle constraints linked to communication of model-based results, transparency of used models and data and of involved uncertainties, mutual respect between experts and stakeholders and between involved stakeholder groups, a robust institutional network, and sufficient time for dialogues. Development and use of strategies for participatory modelling, based on a continuous dialogue between experts and stakeholders is recommended as a way to facilitate that the prerequisites for a successful use of models in water resource management are fulfilled.     

组合预测模型在电力系统负荷预测中的应用研究

本文基于灰色预测模型、滑动平均模型和指数平滑模型这三种单一预测模型,采用方差-协方差策略,建立组合预测模型。然后结合老挝电力系统的概况,对老挝的全国年用电量进行预测和分析。结果表明,组合预测模型的预测精度明显高于各单一预测模型,即组合预测模型的相对误差小于各单一预测模型的相对误差,说明组合预测模型具有相当的适用性和优越性。     

Selection of a dynamic supply portfolio in make-to-order environment withrisks

The problem of a multi-period supplier selection and order allocation in make-to-order environment in the presence of supply chain disruption and delay risks is considered. Given a set of customer orders for finished products, the decision maker needs to decide from which supplier and when to purchase product-specific parts required for each customer order to meet customer requested due date at a low cost and to mitigate the impact of supply chain risks. The selection of suppliers and the allocation of orders over time is based on price and quality of purchased parts and reliability of supplies. For selection of dynamic supply portfolio a mixed integer programming approach is proposed to incorporate risk that uses conditional value-at-risk via scenario analysis. In the scenario analysis, the low-probability and high-impact supply disruptions are combined with the high probability and low impact supply delays. The proposed approach is capable of optimizing the dynamic supply portfolio by calculating value-at-risk of cost per part and minimizing expected worst-case cost per part simultaneously. Numerical examples are presented and some computational results are reported.     

Performance analysis of security aspects by weaving scenarios extracted from UML models

Aspect-oriented modeling (AOM) allows software designers to describe features that address pervasive concerns separately as aspects, and to systematically incorporate the features into a design model using model composition techniques. The goal of this paper is to analyze the performance effects of different security features that may be represented as aspect models. This is part of a larger research effort to integrate methodologies and tools for the analysis of security and performance properties early in the software development process. In this paper, we describe an extension to the AOM approach that provides support for performance analysis. We use the performance analysis techniques developed previously in the PUMA project, which take as input UML models annotated with the standard UML Profile for Schedulability, Performance and Time (SPT), and transform them first into Core Scenario Model (CSM), and then into different performance models. The composition of the aspects with the primary (base) model is performed at the CSM level. A new formal definition of CSM properties and operations is described as a foundation for scenario-based weaving. The proposed approach is illustrated with an example that utilizes two standards, TPC-W and SSL.     

Modeling and evaluating information leakage caused by inferences in supply chains

While information sharing can benefit supply chains significantly, it may also have an adverse effect, namely, information leakage. A limitation common to many existing solutions for preventing information leakage in supply chains is that they rely, either implicitly or explicitly, upon two unrealistic assumptions. First, what information is confidential is well known. Second, confidential information will not be revealed, if only it is not shared, regardless of how much other information is being shared. As we shall show in this paper, those assumptions are not always true due to potential information leakage caused by inferences. Specifically, we propose a conceptual model of such information leakage. The model will enable companies in a supply chain to better understand how their confidential information may be leaked through inferences. On the basis of the proposed conceptual model, we then devise a quantitative approach to evaluating the risk of information leakage caused by inferences when a given amount of information is shared. The quantitative approach will allow companies in a supply chain to measure and consequently mitigate the risk of information leakage. Finally, we discuss a case study to illustrate how the proposed approaches work in practice.     

川藏公路工程病害减灾决策支持系统

川藏公路工程病害减灾决策支持系统以地理信息系统、遥感和数据库为技术支撑，以灾害数据库和环境背景数据库为基础，其核心是建立灾害分析模型，以辅助决策部门制定科学合理的减灾规划。系统今后的目标是建立川藏公路数字减灾系统。