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Proposal of a decision scheme for installing a cogeneration system considering disaster risks

APPLIED THERMAL ENGINEERING 2017年 114卷 1414-1423页

作者： Nagao, Hiroshi Uemichi, Akane Yamasaki, Yudai Kaneko, Shigehiko Univ Tokyo Dept Mech Engn Bunkyo Ku 7-3-1 Hongo Tokyo 1138656 Japan

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.

关键词： Business continuity planning Distributed generation system Cogeneration system Disaster risk Customer mixed integer linear programming problem

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Fractional programming formulation for the vertex coloring problem

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INFORMATION PROCESSING LETTERS 2014年第12期114卷 706-709页

作者： Matsui, Tomomi Sukegawa, Noriyoshi Miyauchi, Atsushi Tokyo Inst Technol Grad Sch Decis Sci & Technol Meguro Ku Tokyo 1528552 Japan

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.

关键词： Combinatorial problems Vertex coloring Fractional programming formulation mixed integer linear programming problem

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Concurrent optimization of harvesting and road network layouts under steep terrain

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ANNALS OF OPERATIONS RESEARCH 2015年第1期232卷 41-64页

作者： Bont, Leo Gallus Heinimann, Hans Rudolf Church, Richard L. ETH Inst Terr Ecosyst CH-8092 Zurich Switzerland Univ Calif Santa Barbara Dept Geog Santa Barbara CA 93106 USA

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 mixed integer linear programming 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).

关键词： Cable-yarding Forest road network mixed integer linear programming problem Steep terrain

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Optimal distribution system restoration using PHEVs

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IET SMART GRID 2019年第1期2卷 42-49页

作者： Sun, Wei Kadel, Nemica Alvarez-Fernandez, Inalvis Nejad, Reza Roofegari Golshani, Amir Univ Cent Florida Elect & Comp Engn Dept Orlando FL 32816 USA Elect Reliabil Council Texas Transmiss Planning Austin TX USA

Power outages cost billions of dollars every year and jeopardise the lives of hospital patients. Traditionally, power distribution system takes a long time to recover after a major blackout, due to its top-down operation strategy. New technologies in modern distribution systems bring opportunities and challenges to distribution system restoration. As fast response energy resources, plug-in hybrid electric vehicles (PHEVs) can accelerate the load pickup by compensating the imbalance between available generation and distribution system load. This study provides a bottom-up restoration strategy to use PHEVs for reliable load pickup and faster restoration process. The optimisation problem of finding load pickup sequence to maximise restored energy is formulated as a mixed integer linear programming (MILP) problem. Moreover, the coordination between transmission and distribution restoration is developed to efficiently restore the entire system back to normal operating conditions. Simulation results on one 100-feeder test system demonstrate the efficiency of MILP-based restoration strategy and the benefit from PHEVs to restore more energy in given restoration time. The proposed restoration strategy has great potential to facilitate system operators to achieve efficient system restoration plans. It also provides incentives to deploy a large amount of PHEVs to improve system resiliency.

关键词： power system restoration linear programming integer programming power distribution faults optimisation hybrid electric vehicles power system reliability normal operating conditions 100-feeder test system MILP-based restoration strategy PHEVs system operators efficient system restoration system resiliency optimal distribution system restoration power outages hospital patients power distribution system operation strategy modern distribution systems fast response energy resources hybrid electric vehicles available generation distribution system load reliable load pickup faster restoration process load pickup sequence restored energy mixed integer linear programming problem restoration time transmission restoration distribution system restoration bottom-up restoration strategy

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Online Optimization of Pickup and Delivery problem Considering Feasibility

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FUTURE INTERNET 2024年第2期16卷 64页

作者： Matsuoka, Ryo Kobayashi, Koichi Yamashita, Yuh Hokkaido Univ Grad Sch Informat Sci & Technoloty Sapporo 0600814 Japan

A pickup and delivery problem by multiple agents has many applications, such as food delivery service and disaster rescue. In this problem, there are cases where fuels must be considered (e.g., the case of using drones as agents). In addition, there are cases where demand forecasting should be considered (e.g., the case where a large number of orders are carried by a small number of agents). In this paper, we consider an online pickup and delivery problem considering fuel and demand forecasting. First, the pickup and delivery problem with fuel constraints is formulated. The information on demand forecasting is included in the cost function. Based on the orders, the agents' paths (e.g., the paths from stores to customers) are calculated. We suppose that the target area is given by an undirected graph. Using a given graph, several constraints such as the moves and fuels of the agents are introduced. This problem is reduced to a mixed integer linear programming (MILP) problem. Next, in online optimization, the MILP problem is solved depending on the acceptance of orders. Owing to new orders, the calculated future paths may be changed. Finally, by using a numerical example, we present the effectiveness of the proposed method.

关键词： pickup and delivery problem online optimization mixed integer linear programming problem fuel constraints demand forecasting

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Capturing the essence of a metabolic network: A flux balance analysis approach

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JOURNAL OF THEORETICAL BIOLOGY 2009年第3期260卷 445-452页

作者： Murabito, Ettore Simeonidis, Evangelos Smallbone, Kieran Swinton, Jonathan Univ Manchester Manchester Interdisciplinary Bioctr Doctoral Training Ctr Integrat Syst Biol Mol Life Manchester M1 7DN Lancs England Univ Manchester Sch Chem Engn & Analyt Sci Manchester M60 1QD Lancs England Univ Manchester Manchester Ctr Integrat Syst Biol Manchester Interdisciplinary Bioctr Manchester M1 7DN Lancs England Univ Manchester Sch Math Manchester M13 9PL Lancs England AstraZeneca Computat Biol Adv Sci & Technol Lab Wilmington DE USA

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.

关键词： mixed integer linear programming problem Alternate optimal solutions Alternate optimal patterns Minimal optimal subnetwork Minimal effort principle

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Framework of intentional islanding operation of active distribution network based on self-healing perspective

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IET RENEWABLE POWER GENERATION 2018年第2期12卷 219-226页

作者： Oboudi, Mohammad Hossein Hooshmand, Rahmat-Allah Faramarzi, Farshad Boushehri, Mohammad Javad Amroony Univ Isfahan Dept Elect Engn Esfahan Iran

Intentional islanding operation (IIO) is a feasible solution to improve the reliability of active distribution network (ADN) by supplying critical loads through the local DG when a fault occurs. Aiming at this goal, a new two-stage methodology is proposed to supply critical loads based on cost-effective improvement. In the first stage, the interruption cost is proposed as the load priority and the ON/OFF status of switches are considered as the binary decision variables. Therefore, IIO is considered as a mixed integer linear programming (MILP) problem to minimise the interruption cost. At the second stage, the power flow calculation is performed on the initial islands for the real-time operation. The proposed method can be utilised for both long- and short-term studies. In the long-term study, the inherent uncertainty of ADN is considered in MILP by using a Monte-Carlo simulation. This concept is used for clustering ADN into self-sufficient microgrids. Moreover, by taking a snapshot of the ADN status and performing operational feasibility, the proposed method can be considered as a real-time power regulation method. The proposed methodology is implemented on the IEEE 33-bus distribution network, and the results are discussed in detail.

关键词： power distribution reliability distributed power generation integer programming linear programming costing power distribution economics Monte Carlo methods intentional islanding operation active distribution network self-healing perspective ADN reliability local DG two-stage methodology interruption cost load priority switch on-off status binary decision variables mixed integer linear programming problem MILP problem power flow calculation inherent uncertainty Monte-Carlo simulation ADN clustering self-sufficient microgrids real-time power regulation method IEEE 33-bus distribution network

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Optimizing private and public mode of operation in major ports of India for better customer service

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INDIAN GROWTH AND DEVELOPMENT REVIEW 2019年第1期12卷 2-37页

作者： Sinha, Deepankar Chowdhury, Shuvo Roy Indian Inst Foreign Trade IIFT Kolkata Campus Kolkata India

Purpose The Government of India announced its liberalization policy in the year 1991. Since then, the major ports in India introduced privatization in various forms into their operations. However, the share of total traffic (cargo) handled by major ports fell from 90 per cent in 1991 to around 70 per cent in 2015, losing share to minor ports. These major ports, except for the port of Kamarajar, are governed by the Major Port Trust Act, 1961. None of the Indian ports feature amongst the top 20 ports of the world. Interestingly, several ports in Asia, namely, seven ports from China, Singapore, Hong Kong and Malaysia are on that list. Several studies and reports have shown that privatization in India did not yield the desired results. Ports in India have adopted a hybrid mode of governance, aligned between a landlord port model and a service port model. This paper aims to address the question - What is the optimal way to mix privatisation and government control in the operations of major ports of India. Design/methodology/approach In this paper, the authors attempt to develop an optimization model for port planners to decide on the optimum mix of privatized and self-managed operations so as to maintain efficiency and maximize revenue. Findings The model tested on a major port in the country shows that the present privatization policy followed by the port needs revision. A similar plan to revise their policies can be carried out for other major ports in the country. Originality/value The model is generic and can be used by any port in the world operating under conditions similar to those in India.

关键词： Optimization Customer Privatization Cost-revenue dynamics Indian major ports mixed integer linear programming problem

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Locating and Designing a Biorefinery Supply Chain under Uncertainty in Navarre: A Stochastic Facility Location problem Case

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Transportation Research Procedia 2015年 10卷 704-713页

作者： Adrián Serrano Javier Faulin Pablo Astiz Mercedes Sánchez Javier Belloso Interdisciplinary Group of Logistics and Transportation- GILT Public University of Navarre Spain

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.

关键词： Facility Location problem Biorefinery Uncertainty mixed integer linear programming problem Biomass.

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Effective restoration strategies of interdependent power system and communication network

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The Journal of Engineering 2018年第13期2017卷 1760-1764页

作者： Prabin M. Baidya Wei Sun Department of Electrical and Computer Engineering University of Central Florida Orlando FL 32816 USA

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.

关键词： power system restoration power system reliability smart power grids telecommunication networks communication technologies optimisation-based restoration strategy mixed integer linear programming problem modified IEEE 14-bus system coordinated restoration strategies network design network planning intelligent electrical devices smart grid communication network interdependent power system effective restoration strategies

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