Optimal dispatch of spinning reserve in a competitive electricity market using genetic algorithms

Ancillary service plays a key role in maintaining operation security of the power system in a competitive electricity market. The spinning reserve is one of the most important ancillary services that should be provided effectively. This paper presents the design of an integrated market for energy and spinning reserve service with particular emphasis on coordinated dispatch of bulk power and spinning reserve services. A new market dispatching mechanism has been developed to minimize the cost of service while maintaining system security. Genetic algorithms (GA) are used for finding the global optimal solutions for this dispatch problem. Case studies and corresponding analyses have been carried out to demonstrate and discuss the efficiency and usefulness of the proposed method.

A genetic algorithm based method for deregulated electricity market dispatch

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.

An optimal sequential procedure for a buying-selling problem with independent observations

We consider a buying-selling problem when two stops of a sequence of independent random variables are required. An optimal stopping rule and the value of a game are obtained.

Differential evolution based total transfer capability assessment with optimal dispatch

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.

Generalized optimal lattice covering of finite-dimensional Euclidean space

A generalization of the classical problem of optimal lattice covering of R-n is considered. Solutions to this generalized problem are found in two specific classes of lattices. The global optimal solution of the generalization is found for R-2. (C) 1998 Elsevier Science Inc. All rights reserved.

Numerical modelling of double diffusion driven reactive flow transport in deformable fluid-saturated porous media with particular consideration of temperature-dependent chemical reaction rates

Numerical methods ave used to solve double diffusion driven reactive flow transport problems in deformable fluid-saturated porous media. in particular, thp temperature dependent reaction rate in the non-equilibrium chemical reactions is considered. A general numerical solution method, which is a combination of the finite difference method in FLAG and the finite element method in FIDAP, to solve the fully coupled problem involving material deformation, pore-fluid flow, heat transfer and species transport/chemical reactions in deformable fluid-saturated porous media has been developed The coupled problem is divided into two subproblems which are solved interactively until the convergence requirement is met. Owing to the approximate nature of the numerical method, if is essential to justify the numerical solutions through some kind of theoretical analysis. This has been highlighted in this paper The related numerical results, which are justified by the theoretical analysis, have demonstrated that the proposed solution method is useful for and applicable to a wide range of fully coupled problems in the field of science and engineering.

Optimal estimation of one-parameter quantum channels

We explore the task of optimal quantum channel identification and in particular, the estimation of a general one-parameter quantum process. We derive new characterizations of optimality and apply the results to several examples including the qubit depolarizing channel and the harmonic oscillator damping channel. We also discuss the geometry of the problem and illustrate the usefulness of using entanglement in process estimation.

The application of adaptive partitioned random search in feature selection problem

Feature selection is one of important and frequently used techniques in data preprocessing. It can improve the efficiency and the effectiveness of data mining by reducing the dimensions of feature space and removing the irrelevant and redundant information. Feature selection can be viewed as a global optimization problem of finding a minimum set of M relevant features that describes the dataset as well as the original N attributes. In this paper, we apply the adaptive partitioned random search strategy into our feature selection algorithm. Under this search strategy, the partition structure and evaluation function is proposed for feature selection problem. This algorithm ensures the global optimal solution in theory and avoids complete randomness in search direction. The good property of our algorithm is shown through the theoretical analysis.

Hemiplegic shoulder pain: defining the problem and its management

Purpose: Hemiplegic shoulder pain can affect up to 70% of stroke patients and can have an adverse impact on rehabilitation outcomes. This article aims to review the literature on the suggested causes of hemiplegic shoulder pain and the therapeutic techniques that can be used to prevent or treat it. On the basis of this review, the components of an optimal management programme for hemiplegic shoulder pain are explored. Method: English language articles in the CINAHL and MEDLINE databases between 1990 and 2000 were reviewed. These were supplemented by citation tracking and manual searches. Results: A management programme for hemiplegic shoulder pain could comprise the following components: provision of an external support for the affected upper limb when the patient is seated, careful positioning in bed, daily static positional stretches, motor retraining and strapping of the scapula to maintain postural tone and symmetry. Conclusions: Research is required to evaluate the effectiveness of the components of the proposed management programme for the prevention and treatment of hemiplegic shoulder pain and to determine in what combination they achieve the best outcomes.

The modeling of turbulent reactive flows based on multiple mapping conditioning

A new modeling approach-multiple mapping conditioning (MMC)-is introduced to treat mixing and reaction in turbulent flows. The model combines the advantages of the probability density function and the conditional moment closure methods and is based on a certain generalization of the mapping closure concept. An equivalent stochastic formulation of the MMC model is given. The validity of the closuring hypothesis of the model is demonstrated by a comparison with direct numerical simulation results for the three-stream mixing problem. (C) 2003 American Institute of Physics.

Discoloration and mineralization of Reactive Red HE-3B by heterogeneous photo-Fenton reaction

Discoloration and mineralization of Reactive Red HE-3B were studied by using a laponite clay-based Fe nanocomposite (Fe-Lap-RD) as a heterogeneous catalyst in the presence of H2O2 and UV light. Our experimental results clearly indicate that Fe-Lap-RD mainly consists of Fe2O3 (meghemite) and Fe2Si4O10(OH)2 (iron silicate hydroxide) which have tetragonal and monoclinic structures, respectively, and has a high specific surface area (472m(2) / g) as well as a high total pore volume (0.547 cm(3)/g). It was observed that discoloration of HE-3B undergoes a much faster kinetics than mineralization of HE-3B. It was also found that initial HE-3B concentration, H2O2 concentration, UV light wavelength and power, and Fe-Lap-RD catalyst loading are the four main factors that can significantly influence the mineralization of HE-3B. At optimal conditions, complete discoloration of 100 mg/L HE-3B can be achieved in 30 min and the total organic carbon removal ratio can attain 76% in 120 min, illustrating that Fe-Lap-RD has a high photo-catalytic activity in the photo-assisted discoloration and mineralization of HE-3B in the presence of UV light (254nm) and H2O2. (C) 2003 Elsevier Science Ltd. All rights reserved.

Modelling the population cost-effectiveness of current and evidence-based optimal treatment for anxiety disorders

Background. The present paper describes a component of a large Population cost-effectiveness study that aimed to identify the averted burden and economic efficiency of current and optimal treatment for the major mental disorders. This paper reports on the findings for the anxiety disorders (panic disorder/agoraphobia, social phobia, generalized anxiety disorder, post-traumatic stress disorder and obsessive-compulsive disorder). Method. Outcome was calculated as averted 'years lived with disability' (YLD), a population summary measure of disability burden. Costs were the direct health care costs in 1997-8 Australian dollars. The cost per YLD averted (efficiency) was calculated for those already in contact with the health system for a mental health problem (current care) and for a hypothetical optimal care package of evidence-based treatment for this same group. Data sources included the Australian National Survey of Mental Health and Well-being and published treatment effects and unit costs. Results. Current coverage was around 40% for most disorders with the exception of social phobia at 21%. Receipt of interventions consistent with evidence-based care ranged from 32% of those in contact with services for social phobia to 64% for post-traumatic stress disorder. The cost of this care was estimated at $400 million, resulting in a cost per YLD averted ranging from $7761 for generalized anxiety disorder to $34 389 for panic/agoraphobia. Under optimal care, costs remained similar but health gains were increased substantially, reducing the cost per YLD to < $20 000 for all disorders. Conclusions. Evidence-based care for anxiety disorders would produce greater population health gain at a similar cost to that of current care, resulting in a substantial increase in the cost-effectiveness of treatment.

Genetic algorithm-based spinning reserve dispatching in a competitive electricity market

Power systems rely greatly on ancillary services in maintaining operation security. As one of the most important ancillary services, spinning reserve must be provided effectively in the deregulated market environment. This paper focuses on the design of an integrated market for both electricity and spinning reserve service with particular emphasis on coordinated dispatch of bulk power and spinning reserve services. A new market dispatching mechanism has been developed to minimize the ISO's total payment while ensuring system security. Genetic algorithms are used in the finding of the global optimal solutions for this dispatching problem. Case studies and corresponding analyses haw been carried out to demonstrate and discuss the efficiency and usefulness of the proposed market.

Application of the cross-entropy method to the buffer allocation problem in a simulation-based environment

The buffer allocation problem (BAP) is a well-known difficult problem in the design of production lines. We present a stochastic algorithm for solving the BAP, based on the cross-entropy method, a new paradigm for stochastic optimization. The algorithm involves the following iterative steps: (a) the generation of buffer allocations according to a certain random mechanism, followed by (b) the modification of this mechanism on the basis of cross-entropy minimization. Through various numerical experiments we demonstrate the efficiency of the proposed algorithm and show that the method can quickly generate (near-)optimal buffer allocations for fairly large production lines.