Quality assessment process for dynamic geometry resources in Intergeo project

One of the objectives of the Intergeo project was to provide European mathematics teachers with ??good quality?? pedagogical material supporting the use of dynamic geometry software in classrooms. With this aim in view, an online repository/platform was developed to gather various dynamic geometry resources, based on the idea of a teachers?? community feeding the repository, (re)using available resources and sharing practices related to the use of dynamic geometry in classrooms. The repository is thus open to contributions of any user who can deposit, browse, download and use resources, which naturally raises the question how to handle the resource quality issue in such an open environment. This paper reports on the way we tackled this issue in the Intergeo project. We first explain what we mean by a ??good quality?? dynamic geometry resource. We then provide a rationale behind the design of a questionnaire, the main tool for resource quality reviews, which are at the core of the quality assessment process implemented in the repository. Several experiments carried out with groups of teachers in order to confront our research-based view of the resource quality with the teachers?? one and to observe teachers?? usages of the quality assessment process are also reported in the paper. The outcomes of these experiments highlight strengths and limitations of the resource quality assessment process. They also tend to show that the idea of involving teachers into the resource quality assessment is a promising way of stimulating the use of dynamic geometry in classrooms, provided that teachers benefit from a support to make the quality process their own.     

Financial valuation of investments in future power generation technologies: nuclear fusion and CCS in an emissions trading system

This paper outlines a model approach for the financial valuation of future power generation technologies, such as nuclear fusion or carbon capture and storage (CCS) under an emissions trading regime. Since on imperfect markets, interdependencies between decisions inhibit the isolated valuation of an investment, we use simultaneous calculation of optimal production, sales and investment programs; these are subject to the constraints and conditions characteristic for investments in low- and zero-carbon technologies such as fusion and CCS. Duality theory allows to derive, identify and economically interpret the determinants for the price ceiling as (corrected) net present values. Sensitivity analysis shows how changes in the technical specification or environmental policies affect the maximum payable price. Particularly, tradable permits have several effects on low-carbon investments and do not always encourage CO ₂ abatement. While a zero-emissions technology like fusion always profits from a tightened emissions trading scheme, for low-carbon technology like CCS—in particular cases—this may even be counterproductive from an economic as well as an environmental point of view.     

Developing concurrent investment plans for power generation and transmission

Decisions on electric power generation and transmission investments may have crucial effects on the development of industrial and residential areas. Decisions made on the infrastructure should have economically beneficial consequences for producers and consumers. The aim of this paper is to propose a model that considers transmission and generation investments simultaneously. The proposed model fills in the gap between models for developing long-term power generation policies and instantaneous power flow models. Unlike other investment models, it explicitly takes the high voltage transmission network into account and the selection of new generation plants located on the interconnected network is made in a more realistic manner considering transmission bottlenecks.The problem subsumes the capacitated network location problem and the network design problem, the former being related to decisions on generation expansion and the latter to decisions on transmission network expansion. The integrated model becomes NP in both feasibility and optimality, because of the sub-problems it contains. Here, a practical procedure is proposed to achieve overall feasibility and also to improve investment decisions when the solution is feasible. The model is tested on the dense interconnected network of an industrialized region in Turkey. The implementation shows how future infeasibilities in the transmission network are highlighted by the model and how generation investment decisions are affected by network expansion alternatives.     

A participatory multi-criteria approach for power generation and transmission planning

It is well-known that reinsurance can be an effective risk management solution for financial institutions such as the insurance companies. The optimal reinsurance solution depends on a number of factors including the criterion of optimization and the premium principle adopted by the reinsurer. In this paper, we analyze the Value-at-Risk based optimal risk management solution using reinsurance under a class of premium principles that is monotonic and piecewise. The monotonic piecewise premium principles include not only those which preserve stop-loss ordering, but also the piecewise premium principles which are monotonic and constructed by concatenating a series of premium principles. By adopting the monotonic piecewise premium principle, our proposed optimal reinsurance model has a number of advantages. In particular, our model has the flexibility of allowing the reinsurer to use different risk loading factors for a given premium principle or use entirely different premium principles depending on the layers of risk. Our proposed model can also analyze the optimal reinsurance strategy in the context of multiple reinsurers that may use different premium principles (as attributed to the difference in risk attitude and/or imperfect information). Furthermore, by artfully imposing certain constraints on the ceded loss functions, the resulting model can be used to capture the reinsurer’s willingness and/or capacity to accept risk or to control counterparty risk from the perspective of the insurer. Under some technical assumptions, we derive explicitly the optimal form of the reinsurance strategies in all the above cases. In particular, we show that a truncated stop-loss reinsurance treaty or a limited stop-loss reinsurance treaty can be optimal depending on the constraint imposed on the retained and/or ceded loss functions. Some numerical examples are provided to further compare and contrast our proposed models to the existing models.     

Evolutionary hybrid approaches for generation scheduling in power systems

Generation scheduling (GS) in power systems is a tough optimisation problem which continues to present a challenge for efficient solution techniques. The solution is to define on/off decisions and generation levels for each electricity generator of a power system for each scheduling interval. The solution procedure requires simultaneous consideration of binary decision and continuous variables. In recent years researchers have focused much attention on developing new hybrid approaches using evolutionary and traditional exact methods for this type of mixed-integer problems. This paper investigates how the optimum or near optimum solution for the GS problem may be quickly identified. A design is proposed which uses a variety of metaheuristic, heuristics and mathematical programming techniques within a hybrid framework. The results obtained for two case studies are promising and show that the hybrid approach offers an effective alternative for solving the GS problems within a realistic timeframe.     

Bayesian inference for the power law process

The power law process has been used to model reliability growth, software reliability and the failure times of repairable systems. This article reviews and further develops Bayesian inference for such a process. The Bayesian approach provides a unified methodology for dealing with both time and failure truncated data. As well as looking at the posterior densities of the parameters of the power law process, inference for the expected number of failures and the probability of no failures in some given time interval is discussed. Aspects of the prediction problem are examined. The results are illustrated with two data examples.     

Quality issue in the design and use of resources by mathematics teachers

The profusion of resources, mostly on the Internet, makes the issue of their quality more and more pressing. Teachers often find themselves unable to choose from among them those that would be the most relevant to their educational goal and to the context of their classes. In our previous work, we claimed that acquiring resource analysis skills is one of the keys to the teachers’ professional development supporting the integration of dynamic geometry systems. Based on this assumption, we have designed a quality questionnaire for the i2geo repository aiming at framing the analysis of available resources by the platform users. The research reported in this paper, which is a continuation of this work, explores the way the quality criteria are taken into account in the design and use of resources by members of the community that has emerged around the repository and sheds light on possible evolutions of teachers’ and teacher educators’ professional practices due to their involvement in the resource quality evaluation.     

The economics of water resources for the generation of electricity and other uses

An optimal control approach is used to analyze the tradeoff between the use of water resources for electricity generation versus other economic uses (irrigation, industry, etc.). For that purpose, a dynamic model is presented which establishes relationships between economic growth, water resources management, and energy policy in the context of the aforementioned tradeoff, in an economy whose energy matrix is heavily dependent upon hydroelectric power. Among other results, the analysis establishes that in the market, the price of water for non-energy uses should be twice the price of the energy goods, indicating the necessity of substituting other sources of energy for hydroelectric power.     

Observational data-based quality assessment of scenario generation for stochastic programs

Computational Management Science - In minimization problems with uncertain parameters, cost savings can be achieved by solving stochastic programming (SP) formulations instead of using expected...     

The opportunity process for optimal consumption and investment with power utility

We study the utility maximization problem for power utility random fields in a semimartingale financial market, with and without intermediate consumption. The notion of an opportunity process is introduced as a reduced form of the value process of the resulting stochastic control problem. We show how the opportunity process describes the key objects: optimal strategy, value function, and dual problem. The results are applied to obtain monotonicity properties of the optimal consumption.     

Characterization of a nonlinear MEMS-based piezoelectric resonator for wideband micro power generation

Micro-scale piezoelectric unimorph beams with attached proof masses are the most prevalent structures in MEMS-based energy harvesters considering micro fabrication and natural frequency limitations. In doubly clamped beams a nonlinear stiffness is observed as a result of midplane stretching effect which leads to amplitude-stiffened Duffing resonance. In this study, a nonlinear model of a doubly clamped piezoelectric micro power generator, taking into account geometric nonlinearities including stretching and large curvatures, is investigated. The governing nonlinear coupled electromechanical partial differential equations of motion are determined by exploiting Hamilton's principle. A semi-analytical approach implementing the perturbation method of multiple scales is used to solve the nonlinear coupled differential equations and analyze the primary and superharmonic resonances. Results indicate that operational bandwidth of the nonlinear harvester is enhanced considerably with respect to linear models. Moreover considerable amount of power is generated due to occurrence of superharmonic resonances. This yields to extraction of energy at subharmonics of the natural frequency which is crucially important in MEMS-based harvesters.     

Optimal generation scheduling for constrained multi-area hydrothermal power systems with cascaded reservoirs

The optimization problem in this paper is targeted at large-scale hydrothermal power systems. The thermal part of the system is a multi-area power pool with tie-line constraints, and the hydro part is a set of cascaded hydrostations. The objective is to minimize the operation cost of the thermal subsystem. This is an integer nonlinear optimization process with a large number of variables and constraints. In order to obtain the optimal solution in a reasonable time, we decompose the problem into thermal and hydro subproblems. The coordinator between these subproblems is the system Lagrange multiplier. For the thermal subproblem, in a multi-area power pool, it is necessary to coordinate the area generations for reducing the operation cost without violating tie limits. For the hydro subsystem, network flow concepts are adopted to coordinate water usage over the entire study time span, and the reduced gradient method is used to overcome the linear characteristic of the network flow method in order to obtain the optimal solution. In this study, load forecasting errors and forced outages of generating units are incorporated in system reliability requirements. Three case studies for the proposed method are presented.     

Incorporating both undesirable outputs and uncontrollable variables into DEA: The performance of Chinese coal-fired power plants

There are two difficulties in doing an objective evaluation of the performance of decision making units (DMUs). The first one is how to treat undesirable outputs jointly produced with the desirable outputs, and the second one is how to treat uncontrollable variables, which often capture the impact of the operating environment. Given difficulties in both model construction and data availability, very few published papers simultaneously consider the above two problems. This article attempts to do so by proposing six DEA-based performance evaluation models based on a research sample of the Chinese coal-fired power plants. The finding of this paper not only contributes for the performance measurement methodology, but also has policy implications for the Chinese coal-fired power sector.     

The water resources assessment based on resource exergy for the mainstream Yellow River

Based on the resource exergy theory, a unified exergetic index is proposed to assess both the quantity and quality of the water of the mainstream Yellow River, thus verifying the real available quantity of the river water in an ecological thermodynamics view. The chemical exergy, thermal exergy, potential exergy and sediment exergy of the river water as partial exergies are, respectively, calculated with the field river water intake data of the mainstream Yellow River. Exergetic potential is also defined to describe different working capacities of the river water along the mainstream. Finally, the temporal and spatial variation of the water resources of the mainstream Yellow River is illuminated with the proposed exergetic measure.     

A programming model for the economic use of power cables

Summary An attempt is made here to implicate the technical problem of power cables into programming language. Economic use of power cables demand consideration of various cost-factors, both of technical and commercial character. The problem is mathematically solved to derive the condition for minimum of costs or — in other words — for optimum use of a cable. Graphical exhibits clearly demarcate the optimum use of cables under changes in cost-factors. The problem simultaneously tries to differentiate between the criterions of technical maximum and economic optimum.

---

Zusammenfassung Es wird das technische Problem elektrischer Kabel als ein solches der Programmierung formuliert. Der ökonomische Einsatz von Kabeln verlangt die Heranziehung der verschiedenen Kostenfaktoren sowohl technischen wie kommerziellen Charakters. Die Bedingungen für minimale Kosten, d. h. optimalen Einsatz eines Kabels, werden hergeleitet. Die graphischen Darstellungen lassen die optimale Verwendung bei Veränderung der Kostenfaktoren erkennen. Gleichzeitig wird der Unterschied zwischen technischem Maximum und wirtschaftlichem Optimum herausgearbeitet.This study in its technical form was originally carried out in 1957 by the joint author AmritlalGosalia while undergoing a training course at Drammens Elektrisitets Verk, Drammen, Norway. The cost analysis was to provide an idea as to the proper choice of cables for house-hold and commercial supply of electric power in the city of Drammen. The numerical values of different cost-factors as well as prices of cables for calculations in Dia. 5 and 6 therefore correspond to the normal market level of 1957 in Norway. These two diagrams have been reproduced in the text by the kind permission of DEV, Drammen, Norway. The original drawings have been altered as required for the easy explanation of the subject.

---

---

Vorgel. v.:J. Nitsche.     

Optimization of power production through coordinated use of hydroelectric and conventional power units

In the present work a methodology to tackle the problem of simultaneous utilization of hydroelectric and conventional power units with the goal of optimizing power production operations over the short term is presented. Most problem formulations found in the literature result in the development of nonlinear optimization programs, which are solved with stochastic methods. The methodology presented in this paper leads to the development of a convex mixed integer quadratic programming (MIQP) model, which is a special type of nonlinear model that enables reaching the global optimum solution in short computational time. The efficiency of the proposed approach is demonstrated by its application to a realistic power production system.     

New opportunities for encouraging higher level mathematical learning by creative use of emerging computer aided assessment

This article defines ‘higher level mathematical skills’ and details an important class: that of constructing instances of mathematical objects satisfying certain properties. Comment is made on the frequency of higher level tasks in undergraduate work. We explain how such questions may be assessed in practice without the imposition on staff of an onerous marking load. Included are examples which have been implemented on a free computer aided assessment system. Lastly we report an investigation of students’ reactions to these questions and discuss their design and impact.     

Radial basis neural tree model for improving waste recovery process in a paper industry

In this article, we propose a novel hybridization of regression trees (RTs) and radial basis function networks, namely, radial basis neural tree model, for waste recovery process (WRP) improvement in a paper industry. As a by‐product of the paper manufacturing process, a lot of waste along with valuable fibers and fillers come out from the paper machine. The WRP involves separating the unwanted materials from the valuable ones so that the recovered fibers and fillers can be further reused in the production process. This job is done by fiber‐filler recovery equipment (FFRE). The efficiency of FFRE depends on several crucial process parameters, and monitoring them is a difficult proposition. The proposed model can be useful to find the essential parameters from the set of available data and to perform prediction task to improve WRP efficiency. An idea of parameter optimization along with regularity conditions for the universal consistency of the proposed model is given. The proposed model has the advantages of easy interpretability and excellent performance when applied to the FFRE efficiency improvement problem. Improved waste recovery will help the industry to become environmentally friendly with less ecological damage apart from being cost‐effective.