A generalized Linear Programming based approach to optimal divisible load scheduling

In this paper we propose a general Linear Programming (LP) based formulation and solution methodology for obtaining optimal solution to the load distribution problem in divisible load scheduling. We exploit the power of the versatile LP formulation to propose algorithms that yield exact solutions to several very general load distribution problems for which either no solutions or only heuristic solutions were available. We consider both star (single-level tree) networks and linear daisy chain networks, having processors equipped with front-ends, that form the generic models for several important network topologies. We consider arbitrary processing node availability or release times and general models for communication delays and computation time that account for constant overheads such as start up times in communication and computation. The optimality of the LP based algorithms is proved rigorously.

An efficient hybrid approach for design of automotive wheel bearings

Wheel bearings play a crucial role in the mobility of a vehicle by minimizing motive power loss and providing stability in cornering maneuvers. Detailed engineering analysis of a wheel bearing subsystem under dynamic conditions poses enormous challenges due to the nonlinearity of the problem caused by multiple factional contacts between rotating and stationary parts and difficulties in prediction of dynamic loads that wheels are subject to. Commonly used design methodologies are based on equivalent static analysis of ball or roller bearings in which the latter elements may even be represented with springs. In the present study, an advanced hybrid approach is suggested for realistic dynamic analysis of wheel bearings by combining lumped parameter and finite element modeling techniques. A validated lumped parameter representation serves as an efficient tool for the prediction of radial wheel load due to ground reaction which is then used in detailed finite element analysis that automatically accounts for contact forces in an explicit formulation.

An automatable generic strategy for dynamic load balancing in parallel structured mesh CFD codes

Parallel computing is now widely used in numerical simulation, particularly for application codes based on finite difference and finite element methods. A popular and successful technique employed to parallelize such codes onto large distributed memory systems is to partition the mesh into sub-domains that are then allocated to processors. The code then executes in parallel, using the SPMD methodology, with message passing for inter-processor interactions. In order to improve the parallel efficiency of an imbalanced structured mesh CFD code, a new dynamic load balancing (DLB) strategy has been developed in which the processor partition range limits of just one of the partitioned dimensions uses non-coincidental limits, as opposed to coincidental limits. The ‘local’ partition limit change allows greater flexibility in obtaining a balanced load distribution, as the workload increase, or decrease, on a processor is no longer restricted by the ‘global’ (coincidental) limit change. The automatic implementation of this generic DLB strategy within an existing parallel code is presented in this chapter, along with some preliminary results.

Load and Season Adapted Solar Collectors

In Sweden solar irradiation and space heating loads are unevenly distributed over the year. Domestic hot water loads may be nearly constant. Test results on solar collector performance are often reported as yearly output of a certain collector at fixed temperatures, e g 25, 50 and 75 C. These data are not suitable for dimensioning of solar systems, because the actual performance of the collector depends heavily on solar fraction and load distribution over the year.At higher latitudes it is difficult to attain high solar fractions for buildings, due to overheating in summer and small marginal output for added collector area. Solar collectors with internal reflectors offer possibilities to evade overheating problems and deliver more energy at seasons when the load is higher. There are methods for estimating the yearly angular irradiation distribution, but there is a lack of methods for describing the load and the storage in such a way as to enable optical design of season and load adapted collectors.This report describes two methods for estimation of solar system performance with relevance for season and load adaption. Results regarding attainable solar fractions as a function of collector features, load profiles, load levels and storage characteristics are reported. The first method uses monthly collector output data at fixed temperatures from the simulation program MINSUN for estimating solar fractions for different load profiles and load levels. The load level is defined as estimated yearly collector output at constant collector temperature divided be yearly load. This table may examplify the results:CollectorLoadLoadSolar Improvementtypeprofile levelfractionover flat plateFlat plateDHW 75 %59 %Load adaptedDHW 75 %66 %12 %Flat plateSpace heating 50 %22 %Load adaptedSpace heating 50 %28 %29 %The second method utilises simulations with one-hour timesteps for collectors connected to a simplified storage and a variable load. Collector output, optical and thermal losses, heat overproduction, load level and storage temperature are presented as functions of solar incidence angles. These data are suitable for optical design of load adapted solar collectors. Results for a Stockholm location indicate that a solar combisystem with a solar fraction around 30 % should have collectors that reduce heat production at solar heights above 30 degrees and have optimum efficiency for solar heights between 8 and 30 degrees.

An approach based on neural networks for identification of fault sections in radial distribution systems

The main objective involved with this paper consists of presenting the results obtained from the application of artificial neural networks and statistical tools in the automatic identification and classification process of faults in electric power distribution systems. The developed techniques to treat the proposed problem have used, in an integrated way, several approaches that can contribute to the successful detection process of faults, aiming that it is carried out in a reliable and safe way. The compilations of the results obtained from practical experiments accomplished in a pilot radial distribution feeder have demonstrated that the developed techniques provide accurate results, identifying and classifying efficiently the several occurrences of faults observed in the feeder.

Integrated planning of electric power distribution networks

In this work, a heuristic model for integrated planning of primary distribution network and secondary distribution circuits is proposed. A Tabu Search (TS) algorithm is employed to solve the planning of primary distribution networks. Evolutionary Algorithms (EA) are used to solve the planning model of secondary networks. The planning integration of both networks is carried out by means a constructive heuristic taking into account a set of integration alternatives between these networks. These integration alternatives are treated in a hierarchical way. The planning of primary networks and secondary distribution circuits is carried out based on assessment of the effects of the alternative solutions in the expansion costs of both networks simultaneously. In order to evaluate this methodology, tests were performed for a real-life distribution system taking into account the primary and secondary networks.

On the efficiency of an alternative codification for multiobjective service restoration in electric distribution networks

This paper proposes an alternative codification to solve the service restoration in electric power distribution networks using a SPEA2 multiobjective evolutionary algorithm, assuming the minimization of both the load not supplied and the number of switching operations involved in the restoration plan. Constrains as the line, power source and voltage drop limits in order to avoid the activation of protective devices are all included in the proposed algorithm. Experimental results have shown the convenience on considering these new representations in the sense of feasibility maintenance and also in the sense of better approximation to the Pareto set. ©2009 IEEE.

Spatial electric load forecasting using a local movement approach

An agent based model for spatial electric load forecasting using a local movement approach for the spatiotemporal allocation of the new loads in the service zone is presented. The density of electrical load for each of the major consumer classes in each sub-zone is used as the current state of the agents. The spatial growth is simulated with a walking agent who starts his path in one of the activity centers of the city and goes to the limits of the city following a radial path depending on the different load levels. A series of update rules are established to simulate the S growth behavior and the complementarity between classes. The results are presented in future load density maps. The tests in a real system from a mid-size city show a high rate of success when compared with other techniques. The most important features of this methodology are the need for few data and the simplicity of the algorithm, allowing for future scalability. © 2009 IEEE.

Optimal phasor measurement units placement for fault location on overhead electric power distribution feeders

This paper proposes a new approach for optimal phasor measurement units placement for fault location on electric power distribution systems using Greedy Randomized Adaptive Search Procedure metaheuristic and Monte Carlo simulation. The optimized placement model herein proposed is a general methodology that can be used to place devices aiming to record the voltage sag magnitudes for any fault location algorithm that uses voltage information measured at a limited set of nodes along the feeder. An overhead, three-phase, three-wire, 13.8 kV, 134-node, real-life feeder model is used to evaluate the algorithm. Tests show that the results of the fault location methodology were improved thanks to the new optimized allocation of the meters pinpointed using this methodology. © 2011 IEEE.

Spatial load forecasting using a demand propagation approach

A method for spatial electric load forecasting using multi-agent systems, especially suited to simulate the local effect of special loads in distribution systems is presented. The method based on multi-agent systems uses two kinds of agents: reactive and proactive. The reactive agents represent each sub-zone in the service zone, characterizing each one with their corresponding load level, represented in a real number, and their relationships with other sub-zones represented in development probabilities. The proactive agent carry the new load expected to be allocated because of the new special load, this agent distribute the new load in a propagation pattern. The results are presented with maps of future expected load levels in the service zone. The method is tested with data from a mid-size city real distribution system, simulating the effect of a load with attraction and repulsion attributes. The method presents good results and performance. © 2011 IEEE.

A proposal for reliability evaluation of components on electric power distribution system integrating probabilistic models and fuzzy inference systems

The system reliability depends on the reliability of its components itself. Therefore, it is necessary a methodology capable of inferring the state of functionality of these components to establish reliable indices of quality. Allocation models for maintenance and protective devices, among others, have been used in order to improve the quality and availability of services on electric power distribution systems. This paper proposes a methodology for assessing the reliability of distribution system components in an integrated way, using probabilistic models and fuzzy inference systems to infer about the operation probability of each component. © 2012 IEEE.

Electrical Power Distribution System modeling with VHDL-AMS for the construction of a Real-Time Digital Simulator using FPGAS devices

This paper presents a distribution feeder simulation using VHDL-AMS, considering the standard IEEE 13 node test feeder admitted as an example. In an electronic spreadsheet all calculations are performed in order to develop the modeling in VHDL-AMS. The simulation results are compared in relation to the results from the well knowing MatLab/Simulink environment, in order to verify the feasibility of the VHDL-AMS modeling for a standard electrical distribution feeder, using the software SystemVision™. This paper aims to present the first major developments for a future Real-Time Digital Simulator applied to Electrical Power Distribution Systems. © 2012 IEEE.

Improving the grid operation and reliability cost of distribution systems with dispersed generation

In this work, a mathematical model to analyze the impact of the installation and operation of dispersed generation units in power distribution systems is proposed. The main focus is to determine the trade-off between the reliability and operational costs of distribution networks when the operation of isolated areas is allowed. In order to increase the system operator revenue, an optimal power flow makes use of the different energy prices offered by the dispersed generation connected to the grid. Simultaneously, the type and location of the protective devices initially installed on the protection system are reconfigured in order to minimize the interruption and expenditure of adjusting the protection system to conditions imposed by the operation of dispersed units. The interruption cost regards the unsupplied energy to customers in secure systems but affected by the normal tripping of protective devices. Therefore, the tripping of fuses, reclosers, and overcurrent relays aims to protect the system against both temporary and permanent fault types. Additionally, in order to reduce the average duration of the system interruption experienced by customers, the isolated operation of dispersed generation is allowed by installing directional overcurrent relays with synchronized reclose capabilities. A 135-bus real distribution system is used in order to show the advantages of using the mathematical model proposed. © 1969-2012 IEEE.

Multiobjective short-term planning of electric power distribution systems using NSGA-II

This paper presents a mixed integer nonlinear programming multiobjective model for short-term planning of distribution networks that considers in an integrated manner the following planning activities: allocation of capacitor banks; voltage regulators; the cable replacement of branches and feeders. The objective functions considered in the proposed model are: to minimize operational and investment costs and minimize the voltage deviations in the the network buses, subject to a set of technical and operational constraints. A multiobjective genetic algorithm based on a Non-Dominated Sorting Genetic Algorithm (NSGA-II) is proposed to solve this model. The proposed mathematical model and solution methodology is validated testing a medium voltage distribution system with 135 buses. © 2013 Brazilian Society for Automatics - SBA.

A load-balancing spare capacity reallocation approach in service-rich SONET metro mesh networks

The next-generation SONET metro network is evolving into a service-rich infrastructure. At the edge of such a network, multi-service provisioning platforms (MSPPs) provide efficient data mapping enabled by Generic Framing Procedure (GFP) and Virtual Concatenation (VC). The core of the network tends to be a meshed architecture equipped with Multi-Service Switches (MSSs). In the context of these emerging technologies, we propose a load-balancing spare capacity reallocation approach to improve network utilization in the next-generation SONET metro networks. Using our approach, carriers can postpone network upgrades, resulting in increased revenue with reduced capital expenditures (CAPEX). For the first time, we consider the spare capacity reallocation problem from a capacity upgrade and network planning perspective. Our approach can operate in the context of shared-path protection (with backup multiplexing) because it reallocates spare capacity without disrupting working services. Unlike previous spare capacity reallocation approaches which aim at minimizing total spare capacity, our load-balancing approach minimizes the network load vector (NLV), which is a novel metric that reflects the network load distribution. Because NLV takes into consideration both uniform and non-uniform link capacity distribution, our approach can benefit both uniform and non-uniform networks. We develop a greedy loadbalancing spare capacity reallocation (GLB-SCR) heuristic algorithm to implement this approach. Our experimental results show that GLB-SCR outperforms a previously proposed algorithm (SSR) in terms of established connection capacity and total network capacity in both uniform and non-uniform networks.