Secure and reliable operation of power system in normal and contingency conditions is of great importance for system operator. Natural disasters can seriously threaten power systems' normal operation with catastro...
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Secure and reliable operation of power system in normal and contingency conditions is of great importance for system operator. Natural disasters can seriously threaten power systems' normal operation with catastrophic consequences. While hardening approaches may be considered for resiliency improvement, an application of a new and cost-effective technology is proposed in this study. A planning procedure is proposed for integrating distributed series reactors (DSR)into transmission grids for improving the resiliency against these disasters. DSRs are able to control power flows through meshed transmission grids and thus improve the power transfer capability and the penetration level of renewable generation. The problem of integrating DSRs into transmission grids is formulated as a mixed integer linear programming problem. Different load and wind profiles and a predefined number of disaster scenarios are considered in evaluating the impacts of DSRs on system's operational costs, wind curtailment and load shedding during disasters and normal condition. The uncertainty of wind generation can affect economic viability of DSRs deployment which is handled using information gap decision theory. It is implemented on the IEEE-RTS 24-bus test system and results show the functionality of DSRs in converting the conventional transmission grid into a flexible and dispatchable asset.
This paper proposes a scheme, called the disaster-risk-weighted damage inequality, for a customer to perform introductory planning for a distributed generation system considering business continuity planning in a disa...
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This paper proposes a scheme, called the disaster-risk-weighted damage inequality, for a customer to perform introductory planning for a distributed generation system considering business continuity planning in a disaster case. To calculate this inequality, the relevant disaster risks are surveyed and system operating simulations for target buildings such as a hotel, a hospital, a large-scale office, and a collective housing building are performed by solving a mixed integer linear programming problem under the assumption that a cogeneration system is installed as a distributed generation system. Next, we determined the probabilities of a disaster occurrence and business interruption due to a disaster, the initial cost of the equipment, the running cost, and the reduction in running cost due to a cogeneration system installation. The cogeneration system was found to effectively reduce the running cost. Finally, the suggested inequality is calculated and determined whether it is satisfied. The result Showed that cogeneration system installation very effectively reduces the running cost for a hotel, a hospital, and a large-scale office, compared to the tolerable amount of loss that is preliminarily determined by a customer. (C) 2016 Elsevier Ltd. All rights reserved.
The power system is continuously evolving towards a smarter grid by adding intelligent electrical devices that leverage communication technologies to provide visualisation, control and automation. The integration of p...
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The power system is continuously evolving towards a smarter grid by adding intelligent electrical devices that leverage communication technologies to provide visualisation, control and automation. The integration of power system and communication network has brought challenges into the resilience of interdependent networks. Following an outage or blackout, system operators cannot only restore one network while simply ignoring the interconnection with the other network. Effective restoration strategies that involve co-ordination between power system and communication network have become critical in enhancing the resilience. An optimisation-based restoration strategy is developed to coordinate the restoration actions between two networks. The problem is modelled as a mixed integer linear programming problem, with the objective of activating every node in both networks with the minimum number of activation/energisation of branches. The developed strategies are tested on the modified IEEE 14-bus system incorporating communication network. Simulation results demonstrate that the coordinated restoration strategies are effective and critical in the successful recovery of interdependent networks. The developed model could also provide insights in network design and planning to enhance the resilience of interdependent power system and communication network.
The paper is devoted to solving the two-stage problem of stochastic programming with quantile criterion. It is assumed that the loss function is bilinear in random parameters and strategies, and the random vector has ...
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The paper is devoted to solving the two-stage problem of stochastic programming with quantile criterion. It is assumed that the loss function is bilinear in random parameters and strategies, and the random vector has a normal distribution. Two algorithms are suggested to solve the problem, and they are compared. The first algorithm is based on the reduction of the original stochastic problem to a mixed integer linear programming problem. The second algorithm is based on the reduction of the problem to a sequence of convex programmingproblems. Performance characteristics of both the algorithms are illustrated by an example. A modification of both the algorithms is suggested to reduce the computing time. The new algorithm uses the solution obtained by the second algorithm as a starting point for the first algorithm. Copyright (c) 2015 John Wiley & Sons, Ltd.
Timber extraction is based on two transportation modes-off-road and on-road-that are connected by a set of landing nodes. Forest operations planning that is oriented toward harvesting consists of concurrently locating...
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Timber extraction is based on two transportation modes-off-road and on-road-that are connected by a set of landing nodes. Forest operations planning that is oriented toward harvesting consists of concurrently locating a truck road network, designating landing/loading sites along that network, and allocating stands to specific harvest technologies (e.g., cable roads). In central Europe, this problem has, until recently, been solved primarily with rules of thumb. By contrast, only a few attempts, designed for plantation systems, have been made to find the mathematical optima. Here, we present a modeling approach to identify a minimal-cost solution for this problem of laying out truck roads and cable roads when the terrain is steep. This technique is based on a mixedintegerlinearprogramming formulation. Our approach is as good as or better than state-of-the-art methods. Here, the overall costs of harvesting and roading were decreased by about 7 % compared with techniques that called for a heuristic solution only. Depending upon parameter choices, we also determined that a computing time ranging from 4 min to 8 hrs was required when assessing a logging area of 4.3 km(2).
The need for renewable energy sources is quickly growing in order to reduce the greenhouse gas emissions. Moreover, Navarre, a European region located in Northern Spain is, currently, a global leader in the production...
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The need for renewable energy sources is quickly growing in order to reduce the greenhouse gas emissions. Moreover, Navarre, a European region located in Northern Spain is, currently, a global leader in the production and use of renewable energy. Actually, more than 80% of its electricity production comes from renewable sources (mainly wind and water). Then, having the purpose of increasing the renewable energy sources diversification, the region aims to locate a biorefinery plant which mainly serves Northern Spain. Locating decisions are considered strategic, immobilizing a large amount of resources and involving an important group of industrial actors. Therefore, they initially show a significant impact on investment costs, and later, on the operating costs when the facility is already running. This location activity has also important environmental influence due to the usual performance of the biorefinery, involving also the transportation and logistic activities because of the supply chain procurement. Once the biorefinery has been located, another problem arises: the design of the supply chain with its classical operational decisions: which crops are going to be harvested, when they are going to be collected and how we should transport the feedstock to the biorefinery. Apart from this, dealing with farms production is always dealing with uncertainty. Thus, climate and weather, competitors and alternate uses, are key factors which influence the availability of biomass. For that reason, uncertainty must be taken into account in order to avoid stockouts that allow us the optimization of the total expected cost. Moreover, estimated feedstock availability is crucial to determine the optimal plant size. Therefore, the results provide us not only the best location of the biorefinery from the economic point of view, but also the variation on feedstock disposal that eventually the biorefinery could intake along with its final size.
We devise a new formulation for the vertex coloring problem. Different from other formulations, decision variables are associated with pairs of vertices. Consequently, colors will be distinguishable. Although the obje...
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We devise a new formulation for the vertex coloring problem. Different from other formulations, decision variables are associated with pairs of vertices. Consequently, colors will be distinguishable. Although the objective function is fractional, it can be replaced by a piece-wise linear convex function. Numerical experiments show that our formulation has significantly good performance for dense graphs. (C) 2014 Elsevier B.V. All rights reserved.
This paper describes parallel processor architecture for a mixedintegerlinearprogramming (MILP) solver to realize motion planning and hybrid system control in robot applications. It features pipeline architecture w...
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ISBN:
(纸本)9781424453092
This paper describes parallel processor architecture for a mixedintegerlinearprogramming (MILP) solver to realize motion planning and hybrid system control in robot applications. It features pipeline architecture with an MILP-specific configuration and two-port SRAM. Based on the architecture, both FPGA and VLSI implementations have been done to solve sample problems including 16 variables. The FPGA implementation can reduce the power consumption to 13 W: an 85.4% reduction compared to a 3.0-GHz processor (Pentium 4;Intel Corp.). The VLSI solver further reduces the power to 6.4 W using 0.18-mu m CMOS technology.
Optimization of thermal process scheduling in plants producing canned food is of great interest because canning is a dominant operation within the food processing sector. Batch processing has been widely practiced but...
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Optimization of thermal process scheduling in plants producing canned food is of great interest because canning is a dominant operation within the food processing sector. Batch processing has been widely practiced but scarcely analyzed in the context of plants producing canned food. The objective of this research study was to solve the problem of optimizing scheduling for the case where given amounts of different canned food products, with specific quality requirements, would be sterilized within a minimum plant operation time. The proposed solution is based on simultaneous sterilization implementation, using the revisited general method (RGM) procedure for process calculations, and developing a mixedintegerlinearprogramming (MILP) model to optimize autoclave scheduling with the purpose of minimizing plant operation time. In order to maximize the output from a specific plant processing different products and container sizes, isolethal processes were identified for various products/containers from which a common set of process conditions could be chosen for simultaneous sterilization of different product lots in the same retort. An example involving the sterilization of 16 different products was solved to illustrate the MILP model developed here. The methodology proposed here is of special relevance to small and medium size canneries, normally processing many different products at the same time. (c) 2008 Published by Elsevier Ltd.
As genome-scale metabolic reconstructions emerge, tools to manage their size and complexity will be increasingly important. Flux balance analysis (FBA) is a constraint-based approach widely used to study the metabolic...
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As genome-scale metabolic reconstructions emerge, tools to manage their size and complexity will be increasingly important. Flux balance analysis (FBA) is a constraint-based approach widely used to study the metabolic capabilities of cellular or subcellular systems. FBA problems are highly under determined and many different phenotypes can satisfy any set of constraints through which the metabolic system is represented. Two of the main concerns in FBA are exploring the space of solutions for a given metabolic network and finding a specific phenotype which is representative for a given task such as maximal growth rate. Here, we introduce a recursive algorithm suitable for overcoming both of these concerns. The method proposed is able to find the alternate optimal patterns of active reactions of an FBA problem and identify the minimal subnetwork able to perform a specific task as optimally as the whole. Our method represents an alternative to and an extension of other approaches conceived for exploring the space of solutions of an FBA problem. It may also be particularly helpful in defining a scaffold of reactions upon which to build up a dynamic model, when the important pathways of the system have not yet been well-defined. (C) 2009 Elsevier Ltd. All rights reserved.
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