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A novel discrete network design problem formulation and its global optimization solution algorithm

TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2015年 79卷 213-230页

作者： Wang, David Z. W. Liu, Haoxiang Szeto, W. Y. Nanyang Technol Univ Sch Civil & Environm Engn Singapore 639798 Singapore Univ Hong Kong Dept Civil Engn Pok Fu Lam Hong Kong Peoples R China

Conventional discrete transportation network design problem deals with the optimal decision on new link addition, assuming the capacity of each candidate link addition is predetermined and fixed. In this paper, we address a novel yet general discrete network design problem formulation that aims to determine the optimal new link addition and their optimal capacities simultaneously, which answers the questions on whether a new link should be added or not, and if added, what should be the optimal link capacity. A global optimization method employing linearization, outer approximation and range reduction techniques is developed to solve the formulated model. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Network design problem User equilibrium mixed-integer linear programming Global optimization Range reduction

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Self-Scheduling of Generation Companies via Stochastic Optimization Considering Uncertainty of Units

Self-Scheduling of Generation Companies via Stochastic Optim...

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IEEE Power and Energy Society General Meeting

作者： Behdad Vatani Saeed Mohajeryami Shahab Dehghan Nima Amjady Energy Production and Infrastructure Center Dept. of Elect. and Comp. Engineering University of North Carolina at Charlotte Department of Electrical Biomedical and Mechatronics Qazvin Islamic Azad University Department of Electrical Engineering Semnan University

ISBN: (纸本)9781509041695

This paper provides a novel self-scheduling model for price-taker generation companies (GENCOs) participating in a day-ahead energy market. Also, this paper models the effect of uncertainty of generating units' forced outage considered by stochastic optimization approach in the self-scheduling. This approach allows the producer to maximize its profit while controlling the risk of profit variability. A scenario generation technique is considered to produce the scenarios for modeling the uncertainty source. Moreover, a well-known scenario reduction tool is applied to reduce the computational burden of the problem. A proposed methodology solves a set of stochastic mixed-integer linear programming (MILP) problems. The framework is effectively applied to a test system and the effect of GENCOs' unavailability and risk are obtained and discussed.

关键词： Stochastic self-scheduling mixed-integer linear programming Pool Forced outage Generation companies Dayahead energy market Conditional value-at-risk (CVaR) forced outage POOLS mixed integer linear programming Test systems Stochastic Companies Uncertainty

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A fast method for the unit scheduling problem with significant renewable power generation

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ENERGY CONVERSION AND MANAGEMENT 2015年 94卷 178-189页

作者： Osorio, G. J. Lujano-Rojas, J. M. Matias, J. C. O. Catalao, J. P. S. Univ Beira Interior P-6201001 Covilha Portugal INESC ID Lisbon Portugal Univ Lisbon IST P-1699 Lisbon Portugal

Optimal operation of power systems with high integration of renewable power sources has become difficult as a consequence of the random nature of some sources like wind energy and photovoltaic energy. Nowadays, this problem is solved using Monte Carlo Simulation (MCS) approach, which allows considering important statistical characteristics of wind and solar power production such as the correlation between consecutive observations, the diurnal profile of the forecasted power production, and the forecasting error. However, MCS method requires the analysis of a representative amount of trials, which is an intensive calculation task that increases considerably with the number of scenarios considered. In this paper, a model to the scheduling of power systems with significant renewable powergeneration based on scenario generation/reduction method, which establishes a proportional relationship between the number of scenarios and the computational time required to analyse them, is proposed. The methodology takes information from the analysis of each scenario separately to determine the probabilistic behaviour of each generator at each hour in the scheduling problem. Then, considering a determined significance level, the units to be committed are selected and the load dispatch is determined. The proposed technique was illustrated through a case study and the comparison with stochastic programming approach was carried out, concluding that the proposed methodology can provide an acceptable solution in a reduced computational time. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Forecasting error mixed-integer linear programming Stochastic unit commitment Renewable generation

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A MILP formulation for generalized geometric programming using piecewise-linear approximations

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2015年第2期245卷 360-370页

作者： Tseng, Chung-Li Zhan, Yiduo Zheng, Qipeng P. Kumar, Manish Univ New S Wales UNSW Australia Business Sch Sydney NSW 2052 Australia Univ Cent Florida Dept Ind Engn & Management Syst Orlando FL 32816 USA Nexant Inc San Francisco CA 94105 USA

Generalized geometric programming (GGP) problems are converted to mixed-integer linear programming (MILP) problems using piecewise-linear approximations. Our approach is to approximate a multiple-term log-sum function of the form log(x(1) + x(2) + ... +x(n)) in terms of a set of linear equalities or inequalities of logx(1), logx(2), ... , and logx(n), where x(1,) ... , x(n), are strictly positive. The advantage of this approach is its simplicity and readiness to implement and solve using commercial MILP solvers. While MILP problems in general are no easier than GGP problems, this approach is justified by the phenomenal progress of computing power of both personal computers and commercial MILP solvers. The limitation of this approach is discussed along with numerical tests. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Generalized geometric programming Piecewise-linear approximation mixed-integer linear programming Gglobal optimization

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RETRACTED: Robust optimization based price-taker retailer bidding strategy under pool market price uncertainty (Retracted Article)

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2015年 73卷 955-963页

作者： Nojavan, Sayyad Mohammadi-Ivatloo, Behnam Zare, Kazem Univ Tabriz Fac Elect & Comp Engn Tabriz Iran

In the restructured electricity markets, retailers purchase the required demand of its consumers from different energy resources such as self-generating facilities, bilateral contracts and pool market. In this process, the pool market price uncertainty modeling is important for obtaining the maximum profit. Therefore, in this paper, a robust optimization approach is proposed to obtain the optimal bidding strategy of retailer, which should be submitted to pool market. By the proposed method, a collection of robust mixed-integer linear programming problem (RMILP) is solved to build optimal bidding strategy for retailer. For pool market price uncertainty modeling, upper and lower limits of pool prices are considered instead of the forecasted prices. The range of pool prices are sequentially partitioned into a successive of nested subintervals, which permit formulating a collection of RMILP problems. The results of these problems give sufficient data to obtain optimal bidding strategy for submit to pool market by retailer. A detailed analysis is utilized to delineate the proposed method. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Price-taker retailers mixed-integer linear programming Optimal bidding strategy Robust optimization approach

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Performance Evaluation of Start-Up Decisions of Rapid-Start Units for AGC

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IEEE TRANSACTIONS ON POWER SYSTEMS 2015年第6期30卷 3130-3138页

作者： Saboya Bautista, Inmaculada Egido, Ignacio Lobato Miguelez, Enrique Univ Pontificia Comillas Sch Engn ICAI Madrid 28015 Spain

Generating units, participating in the secondary frequency control of a control area, are usually spinning units already connected to the network and operating outside their range of optimal performance. This paper deals with an alternative method of providing secondary frequency control called Rapid-Start (RS). It consists in assigning a regulation band to several off-line units (RS units) which are capable of being started and connected rapidly, therefore allowing the online units to operate closer to their nominal power. As RS operation may have economic benefits, an appropriate algorithm to start up an RS unit needs to be developed. This paper proposes a methodology to evaluate, compare, and choose the most appropriate RS algorithm among the ones developed for a certain AGC control area. An optimization model provides a reference by determining the hypothetically ideal start-ups and shut-downs of RS units. In addition, the definition of performance indexes to evaluate, compare, and choose the different RS algorithms is proposed. The proposed methodology is illustrated for a secondary frequency control zone within the Spanish power system by using real data signals.

关键词： mixed-integer linear programming Rapid-Start secondary regulation

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Computation of strict long-run marginal cost for different HV consumers

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ELECTRIC POWER SYSTEMS RESEARCH 2015年 128卷 66-78页

作者： Biskas, Pandelis N. Bakirtzis, Grigorios A. Chatziathanasiou, Vasilis Aristotle Univ Thessaloniki Dept Elect Engn Thessaloniki 54124 Greece

In this paper the strict long-run marginal cost (LRMC) for the ratemaking of High Voltage (HV) consumers is computed, along with the constituent parts of LRMC, namely the marginal capacity cost and the marginal operating cost. The computation is performed using the perturbation approach, employing a generation expansion planning model in order to compute the optimal generation capacity expansion program that could cover the future increased demand. The perturbation is performed using realistic data from five HV consumers in Greece, which are used as demand increments for the overall system demand. The attained LRMCs are compared and conclusions are drawn regarding the effect of the consumption profile on the LRMC. A sensitivity analysis is performed considering an increasing demand increment for each HV consumer, in order to evaluate the effect of the increment magnitude on the LRMCs. Moreover, the Marginal Capacity Cost and the Marginal Operating Cost are computed in all cases. All tests are performed using the Greek electricity market, and the planning period for the LRMC computation is 20 years. (C) 2015 Elsevier B.V. All rights reserved.

关键词： Generation expansion planning Long-run marginal cost Marginal capacity cost Marginal operating cost mixed-integer linear programming Perturbation approach

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The aircraft routing problem with refueling

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OPTIMIZATION LETTERS 2015年第8期9卷 1609-1624页

作者： Kannon, Tanya E. Nurre, Sarah G. Lunday, Brian J. Hill, Raymond R. Air Force Inst Technol Dept Operat Sci ENS Wright Patterson AFB OH 45433 USA US Air Force Dept Strateg Plans & Programs Headquarters Washington DC 20330 USA

In this paper, we present, test, and compare two novel methods to solve the aircraft routing problem with aerial refueling with a multicriteria objective function. We present a mixed-integer linear program (MILP) that utilizes a combination of a network transformation and a formulation that creatively decouples refueling decisions from the nodes within the network. We also present a dynamic program (DP) that, when coupled with an alternative network transformation to account for the multiple criteria within the objective function, applies a node-labeling approach based on a modification of Dijkstra's algorithm. We test and compare these alternative solution methods on a set of 264 synthetically-generated instances representing 66 combinations of network size and the frequency of aerial refueling point availability. Invoking CPLEX using the C++ callable library to solve the MILP and applying the DP in C++, we found that the application of the DP yields a 98.97 % reduction in the required computational effort, on average, relative to the MILP;the MILP fails to find an optimal solution within a 3,600-s time limit for selected instances of networks having at least 80 nodes and for all instances of networks having at least 350 nodes. In contrast, the DP is more robust than the MILP, as it only requires longer than 3,600 s to solve selected instances of networks having more than 3,000 nodes.

关键词： Aircraft routing Network routing Node splitting mixed-integer linear programming Dynamic programming

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Single-Car Routing in Rail Freight Transport

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TRANSPORTATION SCIENCE 2015年第1期49卷 130-148页

作者： Fuegenschuh, Armin Homfeld, Henning Schuelldorf, Hanno Helmut Schmidt Univ Univ Fed Armed Forces Hamburg Dept Mech Engn D-22043 Hamburg Germany Univ Erlangen Nurnberg Lehrstuhl Wirtschaftsmath D-91058 Erlangen Germany DB Mobil Logist AG Transportat Network Dev & Transport Models GSV D-60326 Frankfurt Germany

Single cars in rail freight service are bundled into trains at classification yards. On the way from their respective origins via intermediate yards to their destinations, they are reclassified several times, which is a time-consuming and personally consuming procedure. The single-car routing problem asks for the design of such routes for a given set of orders (origin-destination pairs with associated data) on an infrastructure network, such that the number of trains and their travel distances are minimal. A number of hard restrictions must be obeyed, such as restrictions for the train length and weight, and capacity restrictions for the yards, as well as further operational rules. We present a mixed-integer linear programming (MILP) formulation for this car-routing problem arising at Deutsche Bahn, one of the largest European railway companies. In a further step, we refine the handling of the turnover waiting time for the cars in the yards, which leads to the inclusion of nonlinear constraints in the model. Using adequate linearization techniques, this model can be reduced to a MILP again. Instances of this model turn out to be hard to solve. Further techniques are thus presented to speed up the numerical solution process, among them a tree-based reformulation and heuristic cuts. The different model formulations are computationally compared on a test set of randomly generated instances whose sizes are comparable to real-world instances. Using state-of-the-art MILP solvers, optimal or near-optimal solutions can be computed within a reasonable time frame.

关键词： single-car rail freight transport mixed-integer linear programming modeling nonlinear constraints lifting network design

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Multi-objective, multi-period optimization of district energy systems: IV - A case study

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ENERGY 2015年 84卷 365-381页

作者： Fazlollahi, Samira Becker, Gwenaelle Ashouri, Araz Marechal, Francois Veolia Environm Rech & Innovat F-78520 Limay France Ecole Polytech Fed Lausanne Ind Proc & Energy Syst Engn CH-1015 Lausanne Switzerland

A multi-objective, multi-period model for optimizing the design and operating strategy of district energy systems is proposed by authors [1]. In the developed model the process and energy integration techniques are principally investigated. In the present work, a case study is discussed to demonstrate the proposed model. The results illustrate that by selecting the adequate resources, centralized and decentralized conversion technologies and distribution networks, the environmental impacts can be reduced down to 50-65% and the total annual costs down to 22-27%. In addition, 75% efficiency is obtained due to the integration of co-generation technologies, endogenous resources and the waste heat recovery. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： District energy systems mixed-integer linear programming Evolutionary algorithm Multi-objective optimization Case study

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