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IEEE International Energy Conference (ENERGYCON)

作者： Alabert, Aniol Somoza, Ana de la Hoz, Jordi Graells, Moises Univ Politecn Cataluna EUETIB Dept Chem Engn C Comte Urgell 187 E-08028 Barcelona Spain Univ Politecn Cataluna EUETIB Dept Elect Engn C Comte Urgell 187 E-08028 Barcelona Spain

ISBN: (纸本)9781467384636

Recently, energy systems have experienced a change of paradigm, from a large-scale centralized approach to the in-situ exploitation of renewable sources. Special attention has been paid to microgrids, a particular case of distributed generation where consumer nodes include generation and can be either grid-connected or isolated. This work aims to develop a general model to determine the optimal sizing of an energy system under fixed conditions and to analyze the effect of considering different cycle patterns on the solution. The mixed integer linear programming (MILP) formulation proposes allows determining the best combination of available technologies that satisfies the demand of a given set of scenarios at minimum total cost. The model has been implemented using AIMMS and applied to a case study consisting of a five-member Mediterranean house. The results obtained reveal the need to select the most convenient time cycles for defining the scenarios of the sizing model.

关键词： Distributed power generation Energy Management System Microgrid Optimal Sizing mixed-integer linear programming

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A smart pool search matheuristic for solving a multi-objective microgrid storage planning problem

A smart pool search matheuristic for solving a multi-objecti...

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Applied Energy Symposium and Submit on Renewable Energy Integration with Mini/Microgrid (REM)

作者： Coelho, Vitor N. Coelho, Igor M. Coelho, Bruno N. Souza, Marcone J. F. Gambini, Haroldo Mladenovic, N. Guimaraes, Frederico G. Univ Fed Minas Gerais Grad Program Elect Engn Belo Horizonte MG Brazil Inst Pesquisa & Desenvolvimento Tecnol Ouro Preto Brazil Univ Estado Rio De Janeiro Dept Comp Sci Rio De Janeiro Brazil Univ Fed Ouro Preto Dept Comp Sci Ouro Preto Brazil Serbian Acad Arts & Sci Math Inst Belgrade Serbia Univ Valenciennes & Hainaut Cambresis LAMIH Valenciennes France Univ Fed Minas Gerais Dept Elect Engn Belo Horizonte MG Brazil

In this paper, a multi-objective power dispatching problem that uses Plug-in Electric Vehicle (PEV) as storage units is considered. The problem involves several PEVs and a microgrid community, composed of small houses, residential areas, and different Renewable Energy Resources. Three different objectives are considered: microgrid total costs;usage of PEV batteries and maximum grid peak load. In order to find sets of non-dominated solutions, a matheuristic black box solves several mixed integer linear programming (MILP) subproblems. We improve a previously developed MILP model and design a new multi-objective matheuristic including new problem initialization mechanisms.

关键词： Microgrids Power dispatching Energy storage management Matheuristic mixed-integer linear programming Multiobjetive optimization

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Optimal Vehicle Planning and the Search Tour Problem 18

Optimal Vehicle Planning and the Search Tour Problem

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Conference on Unmanned Systems Technology XVIII

作者： Wettergren, Thomas A. Bays, Matthew J. Naval Undersea Warfare Ctr Newport Div Newport RI 02841 USA Naval Surface Warfare Ctr Panama City Div Panama City FL 32407 USA

ISBN: (纸本)9781510600782

We describe a problem of optimal planning for unmanned vehicles and illustrate two distinct procedures for its solution. The problem under consideration, which we refer to as the search tour problem, involves the determination of multi-stage plans for unmanned vehicles conducting search operations. These types of problems are important in situations where the searcher has varying performance in different regions throughout the domain due to environmental complexity. The ability to provide robust planning for unmanned systems under difficult environmental conditions is critical for their use in search operations. The problem we consider consists of searches with variable times for each of the stages, as well as an additional degree of freedom for each stage to select from one of a finite set of operational configurations. As each combination of configuration and stage time leads to a different performance level, there is a need to determine the optimal configuration of these stages. When the complexity of constraints on total time, as well as resources expended at each stage for a given configuration, are added, the problem becomes one of non-trivial search effort allocation and numerical methods of optimization are required. We show two solution approaches for this numerical optimization problem. The first solution technique is to use a mixed-integer linear programming formulation, for which commercially available solvers can find optimal solutions in a reasonable amount of time. We use this solution as a baseline and compare against a new inner/outer optimization formulation. This inner/outer optimization compares favorably to the baseline solution, but is also amenable to adaptation as the search operation progresses. Numerical examples illustrate the utility of the approach for unmanned vehicle search planning.

关键词： Planning algorithms mixed-integer linear programming inner/outer optimization unmanned vehicles search and rescue vehicle control

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Formulations and algorithms for the multiple depot, fuel-constrained, multiple vehicle routing problem

Formulations and algorithms for the multiple depot, fuel-con...

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American Control Conference (ACC)

作者： Sundar, Kaarthik Venkatachalam, Saravanan Rathinam, Sivakumar Texas A&M Univ Dept Mech Engn College Stn TX 77843 USA Wayne State Univ Dept Ind & Syst Engn Detroit MI 48202 USA

ISBN: (纸本)9781467386821

We consider a multiple depot, multiple vehicle routing problem with fuel constraints. We are given a set of targets, a set of depots and a set of homogeneous vehicles, one for each depot. The depots are also allowed to act as refueling stations. The vehicles are allowed to refuel at any depot, and our objective is to determine a route for each vehicle with a minimum total cost such that each target is visited at least once by some vehicle, and the vehicles never run out fuel as it traverses its route. We refer to this problem as the Multiple Depot, Fuel-Constrained, Multiple Vehicle Routing Problem (FCMVRP). This paper presents four new mixed integer linear programming formulations to compute an optimal solution for the problem. Extensive computational results for a large set of instances are also presented.

关键词： fuel constraints green vehicle routing electric vehicles mixed-integer linear programming unmanned vehicle routing

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Analysis of Singapore Electricity Market Clearing Model with Transmission Network Consideration

Analysis of Singapore Electricity Market Clearing Model with...

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IEEE Region 10 Conference (TENCON)

作者： Shu, Zhen Zhou, Shengfeng Hock, Kelvin Tan Kian Beng, Gooi Hoay DN GL Energy R&D 16 Sci Pk Dr Singapore 118227 Singapore Nanyang Technol Univ Sch Elect & Elect Engn 50 Nanyang Ave Singapore 639798 Singapore

ISBN: (纸本)9781509025978

The analysis of electricity market model plays a very important role in power system planning and market design. It is usually established based on economic deliberation and reliability requirement. This paper investigates the electricity market clearing model (MCM) of Singapore as a representative of Southeast Asia countries. The MCM is formulated as an optimization framework, where the system network topology is properly incorporated. The market clearing policies for energy and ancillary services are explicitly included in the mathematical model. Case studies have been performed on a transmission test system based on local market data. The optimal dispatch for generation production, as well as the locational marginal prices are achieved, providing effective decision-making support for power system planners and operators.

关键词： Singapore wholesale electricity market power system market clearing process electric generation dispatch mixed-integer linear programming

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A Hybrid Genetic Algorithm for the Interaction of Electricity Retailers with Demand Response 19th

A Hybrid Genetic Algorithm for the Interaction of Electricit...

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19th European Conference on the Applications of Evolutionary Computation (EvoApplications)

作者： Alves, Maria Joao Antunes, Carlos Henggeler Carrasqueira, Pedro Univ Coimbra INESC Coimbra Fac Econ Coimbra Portugal Univ Coimbra INESC Coimbra Dept Elect Engn & Comp Coimbra Portugal INESC Coimbra Coimbra Portugal

ISBN: (纸本)9783319312040

In this paper a bilevel programming model is proposed for modeling the interaction between electricity retailers and consumers endowed with energy management systems capable of providing demand response to variable prices. The model intends to determine the optimal pricing scheme to be established by the retailer (upper level decision maker) and the optimal load schedule adopted by the consumer (lower level decision maker) under this price setting. The lower level optimization problem is formulated as a mixed-integer linear programming (MILP) problem. A hybrid approach consisting of a genetic algorithm and an exact MILP solver is proposed. The individuals of the population represent the retailer's choices (electricity prices). For each price setting, the exact optimal solution to the consumer's problem is obtained in a very efficient way using the MILP solver. An illustrative case is analyzed and discussed.

关键词： Genetic algorithm Bilevel problem mixed-integer linear programming Demand response Electricity retail market

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A Domain Specific Language for Optimal Pumping Systems 1

A Domain Specific Language for Optimal Pumping Systems

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1st Industry Track for Software Language Engineering Workshop (ITSLE)

作者： Saul, Benjamin Berg, Christian Zimmermann, Wolf Martin Luther Univ Halle Wittenberg Von Seckendorff Pl 1 D-06120 Halle Saale Germany

ISBN: (纸本)9781450346467

This paper discusses the design and implementation of a domain-specific language for modelling energy optimal pumping systems (realizing specific flows and pressures). The domain model is transformed into a corresponding mixed-integer linear program which can be solved by standard solvers. The solution together with the original model are transformed into executable simulation models (e.g. MODELICA or MATLAB SIMULINK).

关键词： domain specific language mixed-integer linear programming model to model transformation

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A Multi-layer Optimal Chiller Operation Management Framework 52

A Multi-layer Optimal Chiller Operation Management Framework

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52nd Annual Meeting of the IEEE-Industry-Applications-Society (IAS)

作者： Ye, Yanzhu Sharma, Ratnesh Guo, Feng NEC Labs Amer Inc Dept Energy Management Princeton NJ 08540 USA

ISBN: (纸本)9781479983971

This work targets on the chiller plant operation management for a large campus building cooling load. In this paper a multi-layer optimal chiller operation management framework is proposed to operate various chiller units to meet the system cooling load while reduce the system operation cost. The first layer is the day-ahead 24-hour chiller operation planning layer which optimizes multiple chiller sequencing and chillers loading. The second real-time dispatching layer effectively addresses load forecasting uncertainties in real-time. The load uncertainty is solved hierarchically through two steps of approaches. An efficient and accurate system modeling framework for optimization is formulated with mixed-integer linear expressions to reduce the computational complexity. The effectiveness of this proposed management framework is demonstrated for an actual chiller plant operation in university campus. Simulation analyses validate that the proposed method can effectively address various levels of forecast uncertainty and reduce the operation cost.

关键词： chiller operation multi-layer mixed-integer linear programming optimization cost minimization

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Parameter Adaption for Generalized Multiframe Tasks and Applications to Self-Suspending Tasks 22

Parameter Adaption for Generalized Multiframe Tasks and Appl...

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22nd IEEE International Conference on Embedded and Real-Time Computing Systems and Applications (RTSCA)

作者： Peng, Bo Fisher, Nathan Wayne State Univ Dept Comp Sci Detroit MI 48202 USA

ISBN: (纸本)9781509024797

The generalized multiframe task model (GMF) extends the sporadic task model and multiframe task model. Each frame in the GMF model contains an execution time, a relative deadline, and a minimum inter-arrival time. These parameters are fixed after task specification time in the GMF model. However, multimedia and adaptive control systems may be overloaded and no longer stabilized when the task parameters in such systems are not flexible. In order to address this problem, deadlines and periods may change to alleviate temporal overload, for example in the parameter adaption and elastic scheduling model. In this paper, we propose a new model GMF-PA (the GMF model with parameter adaption). This model allows task parameters to be flexible in arbitrary-deadline systems. A necessary schedulability test based on mixed-integer linear programming (MILP) is given to check the schedulability under EDF scheduling and optimally assign deadlines and periods at the same time. We also prove that the test is a sufficient and necessary schedulability test when task parameters must be integers. An approximation algorithm is also deployed to reduce computational running time. The speed-up factor of our approximation algorithm is 1+is an element of where is an element of can be arbitrarily small, with respect to the exact schedulability test of GMF-PA tasks under EDF. We also apply the GMF model to self-suspending tasks. By extending recent work on scheduling self-suspending tasks, we remove the assumption that deadlines are equally assigned in self-suspending tasks, and the system is extended from constrained-deadline systems to arbitrary-deadline systems. We have done exhaustive experiments to show that the schedulability ratio is improved using our techniques in our GMF-PA model.

关键词： generalized multiframe task model multisegment self-suspending tasks uniprocessor scheduling mixed-integer linear programming approximation algorithms

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Network Interdiction through Length-Bounded Critical Disruption Paths: A Bi-Objective Approach

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Electronic Notes in Discrete Mathematics 2016年 52卷 375-382页

作者： Granata, Donatella Sgalambro, Antonino Istituto per le Applicazioni del Calcolo Mauro Picone National Research Council of Italy Italy

In this paper the Bi-Objective k-Length-Bounded Critical Disruption Path (BO-kLB-CDP) optimization problem is proposed, aimed at maximizing the interdiction effects provided on a network by removing a simple path connecting a given source and destination whose length does not exceed a certain threshold. The BO-kLB-CDP problem extends the Critical Disruption Path (CDP) problem introduced by Granata et al. in [Granata, D. and Steeger, G. and Rebennack, S., Network interdiction via a Critical Disruption Path: Branch-and-Price algorithms, Computers & Operations Research, Volume 40, Issue 11, November 2013, Pages 2689-2702]. Several real applications of this class of optimization problems arise in the field of security, surveillance, transportation and evacuation operations. In order to overcome some limits of the original CDP problem and increase its suitability for practical purposes, first we consider a length limitation for Critical Disruption Paths. Second, we generalize the concept of network interdiction considered in the CDP: beside minimizing the cardinality of the maximal connected component after the removal of the CDP, now we are also interested in maximizing the number of connected components in the residual graph. A mixed integer programming formulation for the BO-kLB-CDP problem is therefore proposed and discussed, presenting the results of a multiple objective analysis performed through a computational experience on a large set of instances. © 2016 Elsevier B.V.

关键词： Connected Components Critical Disruption Path mixed-integer linear programming Multi-Objective Network interdiction

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