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IEEE International Conference on Smart Energy Grid Engineering (SEGE)

作者： Sindi, Hatem Shaaban, Mostafa El-Saadany, Ehab Univ Waterloo Dept Elect & Comp Engn Waterloo ON Canada Independent Elect Syst Operator Toronto ON Canada

ISBN: (纸本)9781467379335

An algorithm to maximize distributed generation (DG) hosting capacity in a system while lowering overall system cost is proposed in this paper. This algorithm considers several realistic aspects of long-term DG planning, such as cost effective design of feeder reinforcement. It allocates DGs and provides the type, size, location, and year of installation. Both dispatchable and non-dispatchable DG technologies are used. The complexity of the problem necessitates modeling the problem as mixed integer nonlinear programming. This is performed while considering the daily optimal operation of the allocated DGs. A case study of a test system was conducted over a planning period of 20 years, with every year consisting of eight-day patterns and each day having 24 varying hours.

关键词： distributed power generation integer programming nonlinear programming power generation planning daily optimal operation distributed generation long-term planning feeder reinforcement mixed integer nonlinear programming smart distribution systems Distributed power generation Fuels Indexes Planning Reactive power Resource management Yttrium distributed power generation dispensing system Power generation planning Nonlinear programming Reactive power Rare earths yttrium integer programming management of resources Fuels Optimal operation mixed integer linear programming

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An integrated model of land-use trade-offs and expanding agricultural processing centres 21

An integrated model of land-use trade-offs and expanding agr...

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21st International Congress on Modelling and Simulation (MODSIM) held jointly with the 23rd National Conference of the Australian-Society-for-Operations-Research / DSTO led Defence Operations Research Symposium (DORS

作者： Nazari, A. Penazzi, S. Ernst, A. T. Dunstall, S. Bryan, B. Connor, J. Nolan, M. CSIRO Melbourne Vic Australia Bologna Univ Dept Ind Engn Bologna Italy CSIRO Adelaide SA Australia

ISBN: (纸本)9780987214355

Climate change and demand for greener energy alternatives are putting increased pressure on the use of agricultural land for not just for food and fibre production but also biofuels, carbon sequestration, biodiversity and other non-traditional uses. A key question is how this competition might impact on not only future land use but also on the composition of the supply chains that process the products of the land. In this paper we address a major part of this question by considering the location of processing centres alongside land use change in an integrated optimisation model. CSIRO has previously developed a model of landuse trade-offs that considers the possible evolution of agricultural land areas in Australia over the next 40 years. This can be modelled as a large scale multi-stage linear programming problem. Here we consider in addition the construction of some processing centres for bio-fuel, bio-energy, livestock facilities and so forth, which introduces a new combinatorial aspect to the model. The decisions of land use and the location of processing centres are interlinked, because transport costs based on distances are often instrumental in determining the economic viability of some of the land uses and conversely economies of scale are necessary to justify investment in processing plants. In this paper we introduce a model containing both problems of a land allocation and a facility location simultaneously which results in a large scale mixed integer linear programming (MILP) problem and therefore is computationally difficult to solve. We suggest an algorithm to solve the problem which utilises some decomposition techniques including aggregation and disaggregation, column generation and a concept of clustering. Furthermore, some numerical results are provide to empirically show the computational feasibility of the suggested solution methodology.

关键词： mixed integer linear programming land use management facility location

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Reconfiguration-aware Task Graph Scheduling 13

Reconfiguration-aware Task Graph Scheduling

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13th International Conference on Embedded and Ubiquitous Computing (EUC 2015)

作者： Kooti, Hessam Bozorgzadeh, Eli Google Inc Mountain View CA 94043 USA Univ Calif Irvine Dept Comp Sci Irvine CA USA

ISBN: (纸本)9781467382991

Due to increasing demand for reconfigurability in embedded systems, real-time task scheduling is challenged by non-negligible reconfiguration overheads. We introduce the problem of real-time task scheduling under reconfiguration overhead on heterogeneous reconfigurable systems while considering the data dependencies and data communication overhead. We introduce a novel graph representation which captures the delay overhead due to data dependencies and reconfiguration. We formulate the problem as a network flow problem and provide a mixed integer linear programming solution to minimize the completion time so called makespan. Results show that our proposed scheduling improves the makespan by 24.20% (on average) in comparison with maximum-transition-overhead scheduling.

关键词： partial reconfiguration real time systems task scheduling TASK SCHEDULING real-time systems data dependency Reconfiguration task graphs network flow Graph representations data communication mixed integer linear programming Completion time

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Optimal Number, Type and Location of Remotely Controlled and Supervised Devices in Distribution Networks

Optimal Number, Type and Location of Remotely Controlled and...

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PowerTech, 2015 IEEE Eindhoven

作者： Popovic, Zeljko Knezevic, Stanko Brbaklic, Branislav Univ Novi Sad Fac Tech Sci Novi Sad Serbia Schneider Elect DMS NS Novi Sad Serbia

ISBN: (纸本)9781479976959

This paper presents the mixed integer linear programming model for determining optimal number, type and location of remotely controlled and supervised devices in distribution networks in the presence of distributed generators. The proposed model enables consideration of a number of different devices simultaneously (remotely controlled circuit breakers/reclosers, sectionalizing switches, remotely supervised fault passage indicators) along with all costs and benefits relevant for determining the best network automation strategy. The obtained numerical results emphasize the importance of consideration of different types of automation devices simultaneously and show that the proposed approach has a potential to improve the process of determining of the best automation strategy in real life distribution networks.

关键词： automation distribution networks mixed integer linear programming

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A MILP Approach to Accommodate More Building Integrated Photovoltaic System in Distribution Network

A MILP Approach to Accommodate More Building Integrated Phot...

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General Meeting of the IEEE-Power-and-Energy-Society

作者： Wang, Haiming Meng, Ke Dong, Zhao Yang Xu, Zhao Luo, Fengji Wong, Kit Po Univ Newcastle Ctr Intelligent Elect Networks Callaghan NSW 2308 Australia Univ Sydney Sch Elect & Informat Engn Sydney NSW 2006 Australia Univ Western Australia Sch Elect Elect & Comp Engn Perth WA 6009 Australia

ISBN: (纸本)9781467380409

This paper proposes a mixed integer linear programming (MILP) framework to accommodate more Building Integrated Photovoltaic (BIPV) System in distribution networks. The proposed framework is introduced to efficiently manage energy consumption of building equipped with a Battery Energy Storage System (BESS) and BIPV system. Models of distributed energy resources (DERs) in a building are investigated. The MILP algorithm is solved by an academically-free software platform-MOSEK. Case studies are conducted to validate the performance of the algorithm. It is observed that proposed algorithm could efficiently accommodate BIPV in distribution networks in the context of smart grid.

关键词： Demand Response mixed integer linear programming Building Integrated Photovoltaic System Smart Building Energy Management System

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Cutting plane algorithms for mean-CVaR portfolio optimization with nonconvex transaction costs

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COMPUTATIONAL MANAGEMENT SCIENCE 2015年第2期12卷 319-340页

作者： Takano, Yuichi Nanjo, Keisuke Sukegawa, Noriyoshi Mizuno, Shinji Senshu Univ Sch Network & Informat Tama Ku 2-1-1 Higashimita Kawasaki Kanagawa 2148580 Japan Tokyo Inst Technol Dept Ind Engn & Management Meguro Ku Tokyo 1528552 Japan Tokyo Inst Technol Dept Ind Engn & Management Meguro Ku Tokyo 1528552 Japan

This paper studies the mean-risk portfolio optimization problem with nonconvex transaction costs. We employ the conditional value-at-risk (CVaR) as a risk measure. There are a number of studies that aim at efficiently solving large-scale CVaR minimization problems. None of these studies, however, take into account nonconvex transaction costs, which are present in practical situations. To make a piecewise linear approximation of the transaction cost function, we utilized special ordered set type two constraints. Moreover, we devised a subgradient-based cutting plane algorithm to handle a large number of scenarios. This cutting plane algorithm needs to solve a mixed integer linear programming problem in each iteration, and this requires a substantial computation time. Thus, we also devised a two-phase cutting plane algorithm that is even more efficient. Numerical experiments demonstrated that our algorithms can attain near-optimal solutions to large-scale problems in a reasonable amount of time. Especially when rebalancing a current portfolio that is close to an optimal one, our algorithms considerably outperform other solution methods.

关键词： Portfolio optimization Conditional value-at-risk Cutting plane algorithm Transaction costs mixed integer linear programming

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Incremental, Distributed and Concurrent Scheduling in Systems-of-Systems with Real-Time Requirements 15

Incremental, Distributed and Concurrent Scheduling in System...

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IEEE International Conference on Computer and Information

作者： Obermaisser, Roman Murshed, Ayman Univ Siegen D-57068 Siegen Germany

ISBN: (纸本)9781509001545

Systems-of-Systems (SoS) are large-scale networked embedded systems that are characterized by operational and managerial independence of constituent systems, geographical distribution, emergent behavior and evolutionary development processes. This paper introduces a conceptual model and a scheduling algorithm for supporting real-time requirements in SoS. Real-time support is essential in many safety-relevant application areas such medical, military and industrial SoS. The search for a feasible schedule is computed incrementally upon the introduction of new applications in the SoS. The distributed computation of the schedule using the different constituent systems considers the lack of global knowledge and control in the SoS, while also reducing the overall scheduling time. Concurrent scheduling activities are supported to deal with the uncoordinated and possibly simultaneous introduction of multiple applications. The paper introduces a high-level scheduling algorithm for the SoS as well as a low-level scheduling problem for individual constituent systems. The incremental scheduling problem for the constituent systems is formulated using IBM CPLEX. An experimental evaluation with automatically generated examples demonstrates the feasibility of the proposed solution.

关键词： Constituent System Manager Embedded Systems mixed integer linear programming Network Management System Systems of System Time Division Multiple Access

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MILP for the Multi-objective VM Reassignment Problem 27

MILP for the Multi-objective VM Reassignment Problem

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27th IEEE International Conference on Tools with Artificial Intelligence (ICTAI)

作者： Saber, Takfarinas Ventresque, Anthony Marques-Silva, Joao Thorburn, James Murphy, Liam Univ Coll Dublin Sch Comp Sci & Informat Lero UCD Dublin Ireland IBM Res Dublin Ireland Inst Super Tecn Lisbon Portugal IBM Software Grp Toronto ON Canada

ISBN: (纸本)9781509001637

Machine Reassignment is a challenging problem for constraint programming (CP) and mixed integer linear programming (MILP) approaches, especially given the size of data centres. The multi-objective version of the Machine Reassignment Problem is even more challenging and it seems unlikely for CP or MILP to obtain good results in this context. As a result, the first approaches to address this problem have been based on other optimisation methods, including metaheuristics. In this paper we study under which conditions a mixed integer optimisation solver, such as IBM ILOG CPLEX, can be used for the Multi-objective Machine Reassignment Problem. We show that it is useful only for small or medium scale data centres and with some relaxations, such as an optimality tolerance gap and a limited number of directions explored in the search space. Building on this study, we also investigate a hybrid approach, feeding a metaheuristic with the results of CPLEX, and we show that the gains are important in terms of quality of the set of Pareto solutions (+ 126.9% against the metaheuristic alone and + 17.8% against CPLEX alone) and number of solutions (8.9 times more than CPLEX), while the processing time increases only by 6% in comparison to CPLEX for execution times larger than 100 seconds.

关键词： Multi-objective Optimisation VM/Machine Reassignment mixed integer linear programming Hybrid-Metaheuristics

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Short Term Self Scheduling of Hydro Power Plants with Intra-day Regulation Capacity. Case study of Los Molles and Sauzal in Chile

Short Term Self Scheduling of Hydro Power Plants with Intra-...

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General Meeting of the IEEE-Power-and-Energy-Society

作者： Villavicencio, Jorge Ramirez, Rodolfo Pereira-Bonvallet, Eduardo Endesa Chile Santiago Chile

ISBN: (纸本)9781467380409

A mixed integer linear programming (MILP) model for scheduling of the short-term operation of a price-taker hydroelectric plant is presented. The objective of the model is to maximize the profit of energy production in the next hours' operations. Non-linear production curves of hydro power units are considered through a piecewise representation. A detailed modeling of the hydro network is also described. Realistic test-cases of Los Molles and Sauzal-Sauzalito power plants, both part of the Enel group operations in Chile, are analyzed in detail. Results of real operation are compared to the schedules produced with the model showing the potential of the proposed approach in the industry.

关键词： Hydroelectric power generation Unit commitment mixed integer linear programming Optimal scheduling

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Optimal Charging Coordination of Electric Vehicles in Unbalanced Electrical Distribution System Considering Vehicle-to-Grid Technology 3

Optimal Charging Coordination of Electric Vehicles in Unbala...

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3rd International Istanbul Smart Grid Congress and Fair (ICSG)

作者： Sabillon A, Carlos F. Franco, John F. Rider, Marcos J. Romero, Ruben UNESP Dept Elect Engn Ilha Solteira Brazil

ISBN: (纸本)9781467366250

A mixed integer linear programming (MILP) formulation is proposed in this paper to solve the problem of optimal charging coordination of electric vehicle (EVs) in unbalanced electrical distribution system (EDS) considering vehicle-to-grid (V2G) technology. The imbalance of the system circuits and loads has been taken into account. The developed method defines an optimal charging schedule for the EVs which considers the EVs arrival and departure times and their arrival state of charge;the energy contribution of EVs equipped with vehicle-to-grid technology and distributed generators are considered as well. The classical optimization techniques used to solve the MILP formulation guarantee the optimal solution of the problem. The model was written in the mathematical modeling language AMPL and solved using the commercial solver CPLEX. The presented formulation was tested in a 34-node distribution system and a comparison of the obtained charging schedule on scenarios with V2G and distributed generation was made.

关键词： Charging Coordination Problem Electric Vehicles mixed integer linear programming Vehicle-to-Grid

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