20 resultados para optimal power flow successive linear programming
em University of Queensland eSpace - Australia
Resumo:
This paper proposes a transmission and wheeling pricing method based on the monetary flow tracing along power flow paths: the monetary flow-monetary path method. Active and reactive power flows are converted into monetary flows by using nodal prices. The method introduces a uniform measurement for transmission service usages by active and reactive powers. Because monetary flows are related to the nodal prices, the impacts of generators and loads on operation constraints and the interactive impacts between active and reactive powers can be considered. Total transmission service cost is separated into more practical line-related costs and system-wide cost, and can be flexibly distributed between generators and loads. The method is able to reconcile transmission service cost fairly and to optimize transmission system operation and development. The case study on the IEEE 30 bus test system shows that the proposed pricing method is effective in creating economic signals towards the efficient use and operation of the transmission system. (c) 2005 Elsevier B.V. All rights reserved.
Resumo:
In this paper, a new differential evolution (DE) based power system optimal available transfer capability (ATC) assessment is presented. Power system total transfer capability (TTC) is traditionally solved by the repeated power flow (RPF) method and the continuation power flow (CPF) method. These methods are based on the assumption that the productions of the source area generators are increased in identical proportion to balance the load increment in the sink area. A new approach based on DE algorithm to generate optimal dispatch both in source area generators and sink area loads is proposed in this paper. This new method can compute ATC between two areas with significant improvement in accuracy compared with the traditional RPF and CPF based methods. A case study using a 30 bus system is given to verify the efficiency and effectiveness of this new DE based ATC optimization approach.
Resumo:
The notion of being sure that you have completely eradicated an invasive species is fanciful because of imperfect detection and persistent seed banks. Eradication is commonly declared either on an ad hoc basis, on notions of seed bank longevity, or on setting arbitrary thresholds of 1% or 5% confidence that the species is not present. Rather than declaring eradication at some arbitrary level of confidence, we take an economic approach in which we stop looking when the expected costs outweigh the expected benefits. We develop theory that determines the number of years of absent surveys required to minimize the net expected cost. Given detection of a species is imperfect, the optimal stopping time is a trade-off between the cost of continued surveying and the cost of escape and damage if eradication is declared too soon. A simple rule of thumb compares well to the exact optimal solution using stochastic dynamic programming. Application of the approach to the eradication programme of Helenium amarum reveals that the actual stopping time was a precautionary one given the ranges for each parameter.
Resumo:
This paper critically assesses several loss allocation methods based on the type of competition each method promotes. This understanding assists in determining which method will promote more efficient network operations when implemented in deregulated electricity industries. The methods addressed in this paper include the pro rata [1], proportional sharing [2], loss formula [3], incremental [4], and a new method proposed by the authors of this paper, which is loop-based [5]. These methods are tested on a modified Nordic 32-bus network, where different case studies of different operating points are investigated. The varying results obtained for each allocation method at different operating points make it possible to distinguish methods that promote unhealthy competition from those that encourage better system operation.
Resumo:
It has been established that large numbers of certain trees can survive in the beds of rivers of northeastern Australia where a strongly seasonal distribution of precipitation causes extreme variations in flow on both a yearly and longer-term basis. In these rivers, minimal flow occurs throughout much of any year and for periods of up to several years, allowing the trees to become established and to adapt their form in order to facilitate their survival in environments that experience periodic inundation by fast-flowing, debris-laden water. Such trees (notably paperbark trees of the angiosperm genus Melaleuca) adopt a reclined to prostrate, downstream-trailing habit, have a multiple-stemmed form, modified crown with weeping foliage, development of thick, spongy bark, anchoring of roots into firm to lithified substrates beneath the channel floor, root regeneration, and develop in flow-parallel, linear groves. Individuals from within flow-parallel, linear groves are preserved in situ within the alluvial deposit of the river following burial and death. Four examples of in situ tree fossils within alluvial channel deposits in the Permian of eastern Australia demonstrate that specialised riverbed plant communities also existed at times in the geological past. These examples, from the Lower Permian Carmila Beds, Upper Permian Moranbah Coal Measures and Baralaba Coal Measures of central Queensland and the Upper Permian Newcastle Coal Measures of central New South Wales, show several of the characteristics of trees described from modern rivers in northeastern Australia, including preservation in closely-spaced groups. These properties, together with independent sedimentological evidence, suggest that the Permian trees were adapted to an environment affected by highly variable runoff, albeit in a more temperate climatic situation than the modem Australian examples. It is proposed that occurrences of fossil trees preserved in situ within alluvial channel deposits may be diagnostic of environments controlled by seasonal and longer-term variability in fluvial runoff, and hence may have value in interpreting aspects of palaeoclimate from ancient alluvial successions. (C) 2001 Elsevier Science B.V. All rights reserved.
Resumo:
The principal aim of this paper is to measure the amount by which the profit of a multi-input, multi-output firm deviates from maximum short-run profit, and then to decompose this profit gap into components that are of practical use to managers. In particular, our interest is in the measurement of the contribution of unused capacity, along with measures of technical inefficiency, and allocative inefficiency, in this profit gap. We survey existing definitions of capacity and, after discussing their shortcomings, we propose a new ray economic capacity measure that involves short-run profit maximisation, with the output mix held constant. We go on to describe how the gap between observed profit and maximum profit can be calculated and decomposed using linear programming methods. The paper concludes with an empirical illustration, involving data on 28 international airline companies. The empirical results indicate that these airline companies achieve profit levels which are on average US$815m below potential levels, and that 70% of the gap may be attributed to unused capacity. (C) 2002 Elsevier Science B.V. All rights reserved.
Resumo:
In a deregulated electricity market, optimizing dispatch capacity and transmission capacity are among the core concerns of market operators. Many market operators have capitalized on linear programming (LP) based methods to perform market dispatch operation in order to explore the computational efficiency of LP. In this paper, the search capability of genetic algorithms (GAs) is utilized to solve the market dispatch problem. The GA model is able to solve pool based capacity dispatch, while optimizing the interconnector transmission capacity. Case studies and corresponding analyses are performed to demonstrate the efficiency of the GA model.
Resumo:
It has been established that large numbers of certain trees can survive in the beds of rivers of northeastern Australia where a strongly seasonal distribution of precipitation causes extreme variations in flow on both a yearly and longer-term basis. In these rivers, minimal flow occurs throughout much of any year and for periods of up to several years, allowing the trees to become established and to adapt their form in order to facilitate their survival in environments that experience periodic inundation by fast-flowing, debris-laden water. Such trees (notably paperbark trees of the angiosperm genus Melaleuca) adopt a reclined to prostrate, downstream-trailing habit, have a multiple-stemmed form, modified crown with weeping foliage, development of thick, spongy bark, anchoring of roots into firm to lithified substrates beneath the channel floor, root regeneration, and develop in flow-parallel, linear groves. Individuals from within flow-parallel, linear groves are preserved in situ within the alluvial deposit of the river following burial and death. Four examples of in situ tree fossils within alluvial channel deposits in the Permian of eastern Australia demonstrate that specialised riverbed plant communities also existed at times in the geological past. These examples, from the Lower Permian Carmila Beds, Upper Permian Moranbah Coal Measures and Baralaba Coal Measures of central Queensland and the Upper Permian Newcastle Coal Measures of central New South Wales, show several of the characteristics of trees described from modern rivers in northeastern Australia, including preservation in closely-spaced groups. These properties, together with independent sedimentological evidence, suggest that the Permian trees were adapted to an environment affected by highly variable runoff, albeit in a more temperate climatic situation than the modem Australian examples. It is proposed that occurrences of fossil trees preserved in situ within alluvial channel deposits may be diagnostic of environments controlled by seasonal and longer-term variability in fluvial runoff, and hence may have value in interpreting aspects of palaeoclimate from ancient alluvial successions. (C) 2001 Elsevier Science B.V. All rights reserved.
Resumo:
1. Establishing biological control agents in the field is a major step in any classical biocontrol programme, yet there are few general guidelines to help the practitioner decide what factors might enhance the establishment of such agents. 2. A stochastic dynamic programming (SDP) approach, linked to a metapopulation model, was used to find optimal release strategies (number and size of releases), given constraints on time and the number of biocontrol agents available. By modelling within a decision-making framework we derived rules of thumb that will enable biocontrol workers to choose between management options, depending on the current state of the system. 3. When there are few well-established sites, making a few large releases is the optimal strategy. For other states of the system, the optimal strategy ranges from a few large releases, through a mixed strategy (a variety of release sizes), to many small releases, as the probability of establishment of smaller inocula increases. 4. Given that the probability of establishment is rarely a known entity, we also strongly recommend a mixed strategy in the early stages of a release programme, to accelerate learning and improve the chances of finding the optimal approach.
Resumo:
This paper is devoted to the problems of finding the load flow feasibility, saddle node, and Hopf bifurcation boundaries in the space of power system parameters. The first part contains a review of the existing relevant approaches including not-so-well-known contributions from Russia. The second part presents a new robust method for finding the power system load flow feasibility boundary on the plane defined by any three vectors of dependent variables (nodal voltages), called the Delta plane. The method exploits some quadratic and linear properties of the load now equations and state matrices written in rectangular coordinates. An advantage of the method is that it does not require an iterative solution of nonlinear equations (except the eigenvalue problem). In addition to benefits for visualization, the method is a useful tool for topological studies of power system multiple solution structures and stability domains. Although the power system application is developed, the method can be equally efficient for any quadratic algebraic problem.
Resumo:
1. A model of the population dynamics of Banksia ornata was developed, using stochastic dynamic programming (a state-dependent decision-making tool), to determine optimal fire management strategies that incorporate trade-offs between biodiversity conservation and fuel reduction. 2. The modelled population of B. ornata was described by its age and density, and was exposed to the risk of unplanned fires and stochastic variation in germination success. 3. For a given population in each year, three management strategies were considered: (i) lighting a prescribed fire; (ii) controlling the incidence of unplanned fire; (iii) doing nothing. 4. The optimal management strategy depended on the state of the B. ornata population, with the time since the last fire (age of the population) being the most important variable. Lighting a prescribed fire at an age of less than 30 years was only optimal when the density of seedlings after a fire was low (< 100 plants ha(-1)) or when there were benefits of maintaining a low fuel load by using more frequent fire. 5. Because the cost of management was assumed to be negligible (relative to the value of the persistence of the population), the do-nothing option was never the optimal strategy, although lighting prescribed fires had only marginal benefits when the mean interval between unplanned fires was less than 20-30 years.