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A Hybrid Stochastic/Deterministic Unit Commitment Based on Projected Disjunctive MILP Reformulation

IEEE TRANSACTIONS ON POWER SYSTEMS 2016年第6期31卷 5200-5201页

作者： Tan, Wen-Shan Shaaban, Mohamed Univ Teknol Malaysia Inst Future Energy Ctr Elect Energy Syst Utm 81310 Johor Bahru Malaysia Port Said Univ Dept Elect Engn Fac Engn Port Fouad 42523 Port Said Egypt

This letter presents a new expression of the chance constraint, representing ramping and operating reserve, in the context of the mixed integer linear programming (MILP) formulation for solving the hybrid stochastic/deterministic unit commitment (SDUC) problem. Based on projected disjunctive programming, the nonlinear chance constraint is converted into a set of linear constraints that has a more compact size. Numerical simulations highlight the primacy of the proposed MILP-SDUC reformulation as compared with other formulation approaches.

关键词： Chance-constrained optimization mixed-integer linear programming unit commitment variable renewable sources

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More MILP models for integrated process planning and scheduling

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INTERNATIONAL JOURNAL OF PRODUCTION RESEARCH 2016年第14期54卷 4387-4402页

作者： Jin, Liangliang Tang, Qiuhua Zhang, Chaoyong Shao, Xinyu Tian, Guangdong Huazhong Univ Sci & Technol State Key Lab Digital Mfg Equipment & Technol Wuhan Peoples R China Huazhong Univ Sci & Technol Sch Mech Sci & Engn Wuhan Peoples R China Wuhan Univ Sci & Technol Sch Mech Engn Wuhan Peoples R China Northeast Forestry Univ Transportat Coll Harbin Peoples R China

The integration of process planning and scheduling is important for an efficient utilisation of manufacturing resources. In general, there are two types of models for this problem. Although some MILP models have been reported, most existing models belong to the first type and they cannot realise a true integration of process planning and scheduling. Especially, they are completely powerless to deal with the cases where jobs are expressed by network graphs because generating all the process plans from a network graph is difficult and inefficient. The network graph-specific models belong to the other type, and they have seldom been deliberated on. In this research, some novel MILP models for integrated process planning and scheduling in a job shop flexible manufacturing system are developed. By introducing some network graph-oriented constraints to accommodate different operation permutations, the proposed models are able to express and utilise flexibilities contained in network graphs, and hence have the power to solve network graph-based instances. The established models have been tested on typical test bed instances to verify their correctness. Computational results show that this research achieves the anticipant purpose: the proposed models are capable of solving network graph-based instances.

关键词： flexible manufacturing mixed-integer linear programming integration of process planning and scheduling

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Comparison between Optimal Control Allocation with mixed Quadratic & linear programming Techniques

Comparison between Optimal Control Allocation with Mixed Qua...

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10th IFAC Conference on Control Applications in Marine Systems (CAMS)

作者： Grechi, Simone Caiti, Andrea Univ Pisa Dept Informat Engn Pisa Italy Univ Pisa Ctr E Piaggio Pisa Italy Interuniv Ctr Integrated Syst Marine Environm ISM Genoa Italy

The paper provides a comparison between different control allocation techniques in over-actuated Autonomous Underwater Vehicles. The pseudoinverse, linear programming (LP), Quadratic programming (QP), mixed integer linear programming (MILP) and mixed integer Quadratic programming (MIQP) are evaluated in simulation on the V-Fides vehicle model. The MILP and MIQP techniques allow to include in their implementations a more detailed characterization of the non-linear static behaviour of the actuators. This customizability can be also exploited to improve the practical stability of the system. The metrics used for comparison include the maximum attainable forces and torques, the integral of the error allocation and the required thrusters effort. Our simulation results show that, in particular with respect to thrusters effort, MILP and MIQP are the preferred allocation methods. The computational complexity associated to both methods is not such to compromise their implementation in operating vehicles;in particular, the MILP version is currently implemented in the V-Fides vehicle. (C) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Optimal Control allocation Quadratic programming linear programming mixed-integer linear programming mixed-integer Quadratic programming

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QFix: Demonstrating Error Diagnosis in Query Histories 16

QFix: Demonstrating Error Diagnosis in Query Histories

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ACM SIGMOD International Conference on Management of Data

作者： Wang, Xiaolan Meliou, Alexandra Wu, Eugene Univ Massachusetts Sch Comp Sci Amherst MA 01003 USA Columbia Univ Comp Sci New York NY 10027 USA

ISBN: (纸本)9781450335317

An increasing number of applications in all aspects of society rely on data. Despite the long line of research in data cleaning and repairs, data correctness has been an elusive goal. Errors in the data, can be extremely disruptive, and are detrimental to the effectiveness and proper function of data-driven applications. Even when data, is cleaned, new errors can be introduced by applications and users who interact with the data. Subsequent valid updates can obscure these errors and propagate them through the dataset causing more discrepancies. Any discovered errors tend to be corrected superficially, on a case-by-case basis, further obscuring the true underlying cause, and snaking detection of the remaining errors harder. In this demo proposal, we outline the design of QFix, a query-centric framework that derives explanations and repairs for discrepancies in relational data based on potential errors in the queries that operated on the data. This is a marked departure from traditional data-centric techniques that directly fix the data. We then describe how users will use QFix in a demonstration scenario. Participants will be able to select from a number of transactional benchmarks, introduce errors into the queries that are executed, and compare the fixes to the queries proposed by QFix as well as existing alternative algorithms such as decision trees.

关键词： query provenance data cleaning mixed-integer linear programming

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An MILP Model for the Analysis of Operation of Energy Storage Devices in Distribution Systems

An MILP Model for the Analysis of Operation of Energy Storag...

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IEEE PES Transmission & Distribution Conference and Exposition-Latin America (PES T&D-LA)

作者： Macedo, Leonardo H. Franco, John F. Romero, Ruben Rider, Marcos J. Sao Paulo State Univ Dept Elect Engn Ilha Solteira Brazil Univ Estadual Campinas Dept Syst & Energy Campinas SP Brazil

ISBN: (纸本)9781509028757

This paper presents a mixed-integer linear programming model to define the optimal operation of energy storage devices in radial distribution systems. The objective considered is the reduction of the energy purchase cost from the distribution substation. The modeling of the energy storage devices determines both the charging and discharging periods, and the injected and extracted power. In addition, the number of daily charge/discharge cycles of the storage devices is limited to avoid an excessive reduction of their lifespan. The proposed model was used to analyze the influence of the location of energy storage devices in the operation of a system. The efficiency of the methodology was tested in several cases, using a 136-node distribution system.

关键词： Energy storage devices mixed-integer linear programming operation of distribution systems

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Optimal Operational State Scheduling of Wind Turbines for Lower Battery Capacity in Renewable Power Systems in Islands 5

Optimal Operational State Scheduling of Wind Turbines for Lo...

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5th IEEE International Conference on Renewable Energy Research and Applications (ICRERA)

作者： Song, Jeonghun Song, Seung Jin Oh, Si-Deok Yoo, Yungpil Seoul Natl Univ Sch Mech & Aerosp Engn Seoul South Korea Blue Econ Strategy Inst Co Ltd Seoul South Korea

ISBN: (纸本)9781509033881

To cover a large portion of annual electricity demand of an island with renewable power sources, battery capacity should be high because of temporal inconsistency between renewable power generation and power demand. But such high battery capacity is practically infeasible because battery forms the greatest part of the cost of the renewable power system. As an alternative solution, wind turbines can he in idle state when overall renewable power generation is high, to reduce the required battery capacity. This paper investigates the optimal operational state scheduling of wind turbines for battery capacity reduction and its effect to reduction of renewable power generation and cost. A mixed-integer linear programming problem is formulated for the scheduling. A case study shows that the decrease of renewable power generation due to idle state of wind turbines is small, even if the battery capacity heroines significantly lower.

关键词： renewable energy island wind turbine power system scheduling mixed-integer linear programming

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Security-Constrained Unit Commitment Considering Demand Response Resource as Virtual Power Plant

Security-Constrained Unit Commitment Considering Demand Resp...

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IFAC Workshop on Control of Transmission and Distribution Smart Grids (CTDSG)

作者： Lee, Dongyeon Park, Daehyun Park, Jong-Bae Lee, Kwang-Y. Konkuk Univ Energy Syst Lab Seoul South Korea Baylor Univ Elect & Comp Engn Waco TX 76798 USA

This paper presents a new methodology to security-constrained unit commitment (SCUC) problem with demand response resource (DRR) which is regarded as virtual power plant (VPP). In this paper, based on DRR bids information submitted to Korea Power Exchange (KPX), price elasticity and peak load are calculated and DRR cost function is obtained. The scheduling includes generator characteristics, DRR and reliability constraints Cost functions for generator and DRR are modeled as a piecewise linear function and an mixed integer linear programming (MILP) based method is applied to solve the optimization problem. Proposed methodology is tested and validated on The IEEE RTS-24 system. Through numerical simulation, DRR has demonstrated the decrease in the total operation cost as well as the curtailment of peak load. (c) 2016, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved.

关键词： Demand response resource(DRR) demand response resource cost function security-constrained unit commitment (SCUC) virtual power plant (VPP) mixed-integer linear programming

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Decomposition for adjustable robust linear optimization subject to uncertainty polytope

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COMPUTATIONAL MANAGEMENT SCIENCE 2016年第2期13卷 219-239页

作者： Ayoub, Josette Poss, Michael CDS Consultant Murex Murex Lebanon Univ Montpellier CNRS LIRMM UMR 5506 Rue Ada 161 F-34095 Montpellier 5 France

We present in this paper a general decomposition framework to solve exactly adjustable robust linear optimization problems subject to polytope uncertainty. Our approach is based on replacing the polytope by the set of its extreme points and generating the extreme points on the fly within row generation or column-and-row generation algorithms. The novelty of our approach lies in formulating the separation problem as a feasibility problem instead of a max-min problem as done in recent works. Applying the Farkas lemma, we can reformulate the separation problem as a bilinear program, which is then linearized to obtained a mixed-integer linear programming formulation. We compare the two algorithms on a robust telecommunications network design under demand uncertainty and budgeted uncertainty polytope. Our results show that the relative performance of the algorithms depend on whether the budget is integer or fractional.

关键词： Adjustable robust optimization Uncertainty polytope Benders decomposition mixed-integer linear programming Network design

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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 (PESGM)

作者： Vatani, Behdad Mohajeryami, Saeed Dehghan, Shahab Amjady, Nima Univ N Carolina Dept Elect & Comp Engn Energy Prod & Infrastruct Ctr Charlotte NC 28223 USA Qazvin Islamic Azad Univ Dept Elect Biomed & Mechatron Qazvin Iran Semnan Univ Dept Elect Engn Semnan Iran

ISBN: (纸本)9781509041688

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)

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MILP-based Deadline Assignment for End-to-End Flows in Distributed Real-Time Systems 16

MILP-based Deadline Assignment for End-to-End Flows in Distr...

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24th International Conference on Real-Time Networks and Systems (RTNS)

作者： Peng, Bo Fisher, Nathan Chantem, Thidapat Wayne State Univ Dept Comp Sci Detroit MI 48202 USA Virginia Tech Dept Elect & Comp Engn Arlington VA USA

ISBN: (纸本)9781450347877

End-to-end flows, which have a set of chainlike subtasks, are widely used in distributed real-time systems. For instance, multimedia and automative applications require that subtasks finish executing on a chain of processors before their end-to-end deadlines. The scheduling of such chained subtasks decides the schedulability of a distributed real-time system. Since the subtask priority assignment problem is NP-hard in general, most heuristics are presented to schedule end-to-end flows in two separate steps. The first step calculates intermediate relative deadlines for frames, and the second step makes scheduling decisions under EDF scheduling. Because the quality of the priority assignment of subtasks will directly affect the schedulability of the distributed systems, the two separate steps may cause pessimism in schedulability analysis. To reduce potential pessimism, we combine the two steps in our novel dGMF-PA (distributed generalized multiframe tasks with parameter adaption) model. We present an algorithm based on mixed-integer linear programming for optimally selecting frame relative deadlines in the dGMF-PA model. An approximation algorithm is also proposed to reduce computational running time. Our approximation algorithm has a tunable speed-up factor of 1 + epsilon where epsilon can be arbitrarily small, with respect to the exact schedulability test of dGMF-PA tasks under EDF scheduling. Extensive experiments have shown that our approximation algorithm (which is a sufficient schedulability test) can schedule at most 44 % more than HOSPA, an existing state-of-the-art algorithm.

关键词： distributed generalized multiframe tasks with parameter adaption model distributed real-time system scheduling mixed-integer linear programming approximation algorithms EDF scheduling end-to-end flows

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