Transmission planning in a deregulated environment

The worldwide trend for the deregulation of the electricity generation and transmission industries has led to dramatic changes in system operation and planning procedures. The optimum approach to transmission-expansion planning in a deregulated environment is an open problem especially when the responsibilities of the organisations carrying out the planning work need to be addressed. To date there is a consensus that the system operator and network manager perform the expansion planning work in a centralised way. However, with an increasing input from the electricity market, the objectives, constraints and approaches toward transmission planning should be carefully designed to ensure system reliability as well as meeting the market requirements. A market-oriented approach for transmission planning in a deregulated environment is proposed. Case studies using the IEEE 14-bus system and the Australian national electricity market grid are performed. In addition, the proposed method is compared with a traditional planning method to further verify its effectiveness.

A real options based method for power system planning

A deregulated electricity market is characterized with uncertainties, with both long and short terms. As one of the major long term planning issues, the transmission expansion planning (TEP) is aiming at implementing reliable and secure network support to the market participants. The TEP covers two major issues: technical assessment and financial evaluations. Traditionally, the net present value (NPV) method is the most accepted for financial evaluations, it is simple to conduct and easy to understand. Nevertheless, TEP in a deregulated market needs a more dynamic approach to incorporate a project's management flexibility, or the managerial ability to adapt in response to unpredictable market developments. The real options approach (ROA) is introduced here, which has clear advantage on counting the future course of actions that investors may take, with understandable results in monetary terms. In the case study, a Nordic test system has been testified and several scenarios are given for network expansion planning. Both the technical assessment and financial evaluation have been conducted in the case study.

Effect of nitrogen supply on leaf appearance, leaf growth, leaf nitrogen economy and photosynthetic capacity in maize (Zea mays L.)

Leaf area growth and nitrogen concentration per unit leaf area, N-a (g m(-2) N) are two options plants can use to adapt to nitrogen limitation. Previous work indicated that potato (Solanum tuberosum L.) adapts the size of leaves to maintain Na and photosynthetic capacity per unit leaf area. This paper reports on the effect of N limitation on leaf area production and photosynthetic capacity in maize, a C4 cereal. Maize was grown in two experiments in pots in glasshouses with three (0.84-6.0 g N pot(-1)) and five rates (0.5-6.0 g pot(-1)) of N. Leaf tip and ligule appearance were monitored and final individual leaf area was determined. Changes with leaf age in leaf area, leaf N content and light-saturated photosynthetic capacity, P a,, were measured on two leaves per plant in each experiment. The final area of the largest leaf and total plant leaf area differed by 16 and 29% from the lowest to highest N supply, but leaf appearance rate and the duration of leaf expansion were unaffected. The N concentration of expanding leaves (N-a or %N in dry matter) differed by at least a factor 2 from the lowest to highest N supply. A hyperbolic function described the relation between P-max and N-a. The results confirm the 'maize strategy': leaf N content, photosynthetic capacity, and ultimately radiation use efficiency is more sensitive to nitrogen limitation than are leaf area expansion and light interception. The generality of the findings is discussed and it is suggested that at canopy level species showing the 'potato strategy' can be recognized from little effect of nitrogen supply on radiation use efficiency, while the reverse is true for species showing the 'maize strategy' for adaptation to N limitation. (c) 2004 Elsevier B.V. All rights reserved.

Managing knowledge in tourism planning: How to assess your capability

This paper explores the theme of strategic planning in a State Tourism Organization (STO) from a knowledge management perspective. It highlights the value of knowledge in strategy making and the importance of an organisation's knowledge management agenda in facilitating a strategic planning process. In particular, it considers the capability of an STO to implement knowledge management as the key to a successful strategic planning exercise. In order to develop greater insight into the factors that impact on planning competence, the key aim of this paper is to develop a framework on which the capability of a STO to implement a knowledge-based agenda in strategic planning can be assessed. Research on knowledge management in the field of tourism is limited and there is little practical account of the application of knowledge management principles in tourism planning. Further, there is no apparent tool or instrument that allows for the assessment of an STO's capability to implement knowledge management in planning initiatives. Based on a literature review, a three-point framework of assessment is developed. The three elements of the framework are identified as: 1. Integration of knowledge management objectives with strategic imperatives; 2. A planning approach that balances top-down (outcome focused) with bottom-up (process focused) planning processes; and 3. Organisational capacity, including leadership, people and culture, process, technology, content and continuous improvement. The framework is tested through application to a practical case study - a planning initiative undertaken by a leading tourism STO in Australia. The results demonstrate that the framework is a useful means to evaluate organisational capability in knowledge-led strategic planning exercises and would be of practical value as a point of reference for future knowledge- based strategic planning projects. Copyright © by The Haworth Press, Inc. All rights reserved.

Expansion-based algorithms for finding single pair shortest path on surface

Finding single pair shortest paths on surface is a fundamental problem in various domains, like Geographic Information Systems (GIS) 3D applications, robotic path planning system, and surface nearest neighbor query in spatial database, etc. Currently, to solve the problem, existing algorithms must traverse the entire polyhedral surface. With the rapid advance in areas like Global Positioning System (CPS), Computer Aided Design (CAD) systems and laser range scanner, surface models axe becoming more and more complex. It is not uncommon that a surface model contains millions of polygons. The single pair shortest path problem is getting harder and harder to solve. Based on the observation that the single pair shortest path is in the locality, we propose in this paper efficient methods by excluding part of the surface model without considering them in the search process. Three novel expansion-based algorithms are proposed, namely, Naive algorithm, Rectangle-based Algorithm and Ellipse-based Algorithm. Each algorithm uses a two-step approach to find the shortest path. (1) compute an initial local path. (2) use the value of this initial path to select a search region, in which the global shortest path exists. The search process terminates once the global optimum criteria are satisfied. By reducing the searching region, the performance is improved dramatically in most cases.