RSA-Grid: A grid computing based framework for power system reliability and security analysis

Grid computing is an emerging technology for providing the high performance computing capability and collaboration mechanism for solving the collaborated and complex problems while using the existing resources. In this paper, a grid computing based framework is proposed for the probabilistic based power system reliability and security analysis. The suggested name of this computing grid is Reliability and Security Grid (RSA-Grid). Then the architecture of this grid is presented. A prototype system has been built for further development of grid-based services for power systems reliability and security assessment based on probabilistic techniques, which require high performance computing and large amount of memory. Preliminary results based on prototype of this grid show that RSA-Grid can provide the comprehensive assessment results for real power systems efficiently and economically.

A cognitive genetic algorithm for power distribution system planning

Power systems are large scale nonlinear systems with high complexity. Various optimization techniques and expert systems have been used in power system planning. However, there are always some factors that cannot be quantified, modeled, or even expressed by expert systems. Moreover, such planning problems are often large scale optimization problems. Although computational algorithms that are capable of handling large dimensional problems can be used, the computational costs are still very high. To solve these problems, in this paper, investigation is made to explore the efficiency and effectiveness of combining mathematic algorithms with human intelligence. It had been discovered that humans can join the decision making progresses by cognitive feedback. Based on cognitive feedback and genetic algorithm, a new algorithm called cognitive genetic algorithm is presented. This algorithm can clarify and extract human's cognition. As an important application of this cognitive genetic algorithm, a practical decision method for power distribution system planning is proposed. By using this decision method, the optimal results that satisfy human expertise can be obtained and the limitations of human experts can be minimized in the mean time.

Computation of bifurcation boundaries for power systems: A new Delta-plane method

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.

Satellite observation and climate system model simulation of the St. Lawrence Island polynya

The St. Lawrence Island polynya (SLIP) is a commonly occurring winter phenomenon in the Bering Sea, in which dense saline water produced during new ice formation is thought to flow northward through the Bering Strait to help maintain the Arctic Ocean halocline. Winter darkness and inclement weather conditions have made continuous in situ and remote observation of this polynya difficult. However, imagery acquired from the European Space Agency ERS-1 Synthetic Aperture Radar (SAR) has allowed observation of the St. Lawrence Island polynya using both the imagery and derived ice displacement products. With the development of ARCSyM, a high resolution regional model of the Arctic atmosphere/sea ice system, simulation of the SLIP in a climate model is now possible. Intercomparisons between remotely sensed products and simulations can lead to additional insight into the SLIP formation process. Low resolution SAR, SSM/I and AVHRR infrared imagery for the St. Lawrence Island region are compared with the results of a model simulation for the period of 24-27 February 1992. The imagery illustrates a polynya event (polynya opening). With the northerly winds strong and consistent over several days, the coupled model captures the SLIP event with moderate accuracy. However, the introduction of a stability dependent atmosphere-ice drag coefficient, which allows feedbacks between atmospheric stability, open water, and air-ice drag, produces a more accurate simulation of the SLIP in comparison to satellite imagery. Model experiments show that the polynya event is forced primarily by changes in atmospheric circulation followed by persistent favorable conditions: ocean surface currents are found to have a small but positive impact on the simulation which is enhanced when wind forcing is weak or variable.

Optimization of pipeline transport for CO2 sequestration

Coal fired power generation will continue to provide energy to the world for the foreseeable future. However, this energy use is a significant contributor to increased atmospheric CO2 concentration and, hence, global warming. Capture and disposal Of CO2 has received increased R&D attention in the last decade as the technology promises to be the most cost effective for large scale reductions in CO2 emissions. This paper addresses CO2 transport via pipeline from capture site to disposal site, in terms of system optimization, energy efficiency and overall economics. Technically, CO2 can be transported through pipelines in the form of a gas, a supercritical. fluid or in the subcooled liquid state. Operationally, most CO2 pipelines used for enhanced oil recovery transport CO2 as a supercritical fluid. In this paper, supercritical fluid and subcooled liquid transport are examined and compared, including their impacts on energy efficiency and cost. Using a commercially available process simulator, ASPEN PLUS 10.1, the results show that subcooled liquid transport maximizes the energy efficiency and minimizes the Cost Of CO2 transport over long distances under both isothermal and adiabatic conditions. Pipeline transport of subcooled liquid CO2 can be ideally used in areas of cold climate or by burying and insulating the pipeline. In very warm climates, periodic refrigeration to cool the CO2 below its critical point of 31.1 degrees C, may prove economical. Simulations have been used to determine the maximum safe pipeline distances to subsequent booster stations as a function of inlet pressure, environmental temperature and ground level heat flux conditions. (c) 2005 Published by Elsevier Ltd.

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.

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 hybrid probabilistic criterion for market-based transmission expansion planning

Market-based transmission expansion planning gives information to investors on where is the most cost efficient place to invest and brings benefits to those who invest in this grid. However, both market issue and power system adequacy problems are system planers’ concern. In this paper, a hybrid probabilistic criterion of Expected Economical Loss (EEL) is proposed as an index to evaluate the systems’ overall expected economical losses during system operation in a competitive market. It stands on both investors’ and planner’s point of view and will further improves the traditional reliability cost. By applying EEL, it is possible for system planners to obtain a clear idea regarding the transmission network’s bottleneck and the amount of losses arises from this weak point. Sequentially, it enables planners to assess the worth of providing reliable services. Also, the EEL will contain valuable information for moneymen to undertake their investment. This index could truly reflect the random behaviors of power systems and uncertainties from electricity market. The performance of the EEL index is enhanced by applying Normalized Coefficient of Probability (NCP), so it can be utilized in large real power systems. A numerical example is carried out on IEEE Reliability Test System (RTS), which will show how the EEL can predict the current system bottleneck under future operational conditions and how to use EEL as one of planning objectives to determine future optimal plans. A well-known simulation method, Monte Carlo simulation, is employed to achieve the probabilistic characteristic of electricity market and Genetic Algorithms (GAs) is used as a multi-objective optimization tool.

Using the canonical modelling approach to simplify the simulation of function in functional-structural plant models

Functional-structural plant models that include detailed mechanistic representation of underlying physiological processes can be expensive to construct and the resulting models can also be extremely complicated. On the other hand, purely empirical models are not able to simulate plant adaptability and response to different conditions. In this paper, we present an intermediate approach to modelling plant function that can simulate plant response without requiring detailed knowledge of underlying physiology. Plant function is modelled using a 'canonical' modelling approach, which uses compartment models with flux functions of a standard mathematical form, while plant structure is modelled using L-systems. Two modelling examples are used to demonstrate that canonical modelling can be used in conjunction with L-systems to create functional-structural plant models where function is represented either in an accurate and descriptive way, or in a more mechanistic and explanatory way. We conclude that canonical modelling provides a useful, flexible and relatively simple approach to modelling plant function at an intermediate level of abstraction.