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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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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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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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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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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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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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A general MILP model for the sizing of islanded/grid-connected microgrids

A general MILP model for the sizing of islanded/grid-connect...

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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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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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