检索结果-内蒙古大学图书馆

Operational optimization of energy systems, 25 years – established and promising use cases

Energy Procedia 2018年 149卷 15-24页

作者： Peter Stange Anja Matthees Thomas Sander TU Dresden Institute of Power Engineering Chair of Building Energy Systems and Heat Supply Helmholtzstraße 14 Dresden 01069 Germany

The operation of complex energy systems for the supply of heat and electricity leads to several questions regarding their optimal control, e.g. when to use which generator, when to load or unload energy storages or when to buy or sell energy. Usually it is a complex task to answer these questions with the aim of optimizing a specific objective and respecting all arising physical, technical and economic constraints. Since 25 years we are solving this problem for an energy provider of a medium-sized city with the aim of minimizing the operational costs. For this purpose, an own modelled mixed-integer linear optimization problem (MILP) has to be solved in association to the continuous operation of the energy system. The model includes but is not limited to several combined heat and power generators, heat accumulators, steam generators and auxiliary coolers. In this presentation we will give an outline about the wide range of given conditions that are successfully implemented for this application. Further we show our approach to generate realistic heat demand and power consumption forecasts which are both essential preconditions for obtaining reliable optimization results. In addition to the well – established MILP model in this specific use case we will outline some further promising applications of mathematical optimization in the context of energy systems. This includes the more precise modelling of energy storages, the computation of the optimal design of energy systems and the consideration of different or multiple targets in optimization. Moreover, we outline the problem of uncertain boundary conditions due to the growing amount of temporally hard to predict energy production and demand.

关键词： optimization of operation mixed-integer linear programming energy supply district heating demand forecast

来源：评论

学校读者我要写书评

暂无评论

Performance comparison of energy supply systems under uncertain energy demands based on a mixed-integer linear model

引用

ENERGY 2017年 137卷 878-887页

作者： Yokoyama, Ryohei Nakamura, Ryo Wakui, Tetsuya Osaka Prefecture Univ Dept Mech Engn Naka Ku 1-1 Gakuen Cho Sakai Osaka 5998531 Japan

In designing energy supply systems, several alternatives for design specifications are proposed, and their performances are evaluated and compared. In this paper, a method of comparing performances of two energy supply systems under uncertain energy demands is proposed based on a mixed-integer linear model. Uncertain energy demands are expressed by intervals. The minimum and maximum, and consequently their interval of the difference in the value of a performance criterion are evaluated for all the possible energy demands within their intervals. An optimization problem for this evaluation is formulated as a minimax mixed-integer linear programming one with integer and continuous operation variables. The problem is solved by evaluating upper and lower bounds for the optimal value of the difference in the value of the performance criterion repeatedly. In a case study, the minimum and maximum of the reduction in the annual total cost of a cogeneration system in comparison with a conventional energy supply system are evaluated, and the corresponding energy demands and operational strategies are identified. The influence of the uncertainty in energy demands on these results is also examined. Through the case study, the validity and effectiveness of the proposed method are clarified. (C) 2017 Elsevier Ltd. All rights reserved.

关键词： Energy supply Performance difference Uncertainty Minimax optimization mixed-integer linear programming

来源：评论

学校读者我要写书评

暂无评论

A unified MILP model for topological structure of production well gathering pipeline network

引用

JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING 2017年 152卷 284-293页

作者： Zhang, Haoran Liang, Yongtu Zhang, Wan Wang, Bohong Yan, Xiaohan Liao, Qi China Univ Petr Beijing Key Lab Urban Oil & Gas Distribut Technol Beijing 102249 Peoples R China

Production well gathering pipeline network, usually characterized by various and complex structure and high investment, is one of significant parts of oil-gas field construction. Optimization of production well fluid gathering system is critical to reducing development cost. A variety of previous research focused on the issue. However, those methods were less applicable for dealing with the challenges of compatibility to various structures, integral optimization and finding the optimum. This paper focuses on stellated pipeline network, cascade dendritic pipeline network and insertion dendritic pipeline network, three common connection structures of gathering pipeline, and establishes a versatile mixed-integer linear programming model with considering terrain and obstacle conditions. Minimizing the total investment is the object of this model. Constraints of central processing facility, manifolds, flow rate, pipeline construction and connection mode are taken into consideration in the model. The optimal topological structure, position of central processing facility, diameter and route of each pipeline are obtained integrally by solving this model with GUROBI solver. Finally, two virtual oil-gas fields and a real-world gas field are taken as examples to verify the reliability and practicality of the model.

关键词： Oil-gas gathering pipeline network Topological structure Integral optimization mixed-integer linear programming

来源：评论

学校读者我要写书评

暂无评论

Optimal design of energy conversion units and envelopes for residential building retrofits using a comprehensive MILP model

引用

APPLIED ENERGY 2017年 185卷 1-15页

作者： Schuetz, Thomas Schiffer, Lutz Harb, Hassan Fuchs, Marcus Mueller, Dirk Rhein Westfal TH Aachen EON Energy Res Ctr Inst Energy Efficient Bldg & Indoor Climate Mathieustr 10 Aachen Germany

The optimal design of buildings is a complex task involving energy systems as well as construction measures. Typically, in exact optimization models, only energy systems are considered, whereas envelope components are neglected. When considering both, heuristics are commonly used, which do not guarantee optimal or close to optimal results. Thus, this paper presents the governing equations, validation and exemplary usage of a building model suitable for exact optimization problems. The developed model simultaneously considers energy systems and building envelopes. It is based on ISO 13790 and validated according to ASHRAE 140 and further compared to a more detailed model. The findings show that the developed model largely complies with the ASHRAE requirements and is able to assess buildings' dynamic behavior regarding indoor air temperatures as well as hourly, peak load, and annual heating loads. The simultaneous optimization of energy system and envelope is further demonstrated analyzing retrofitting options of a residential building. We consider solely installing additional PV units, modernizing the building envelope according to German regulations and an optimization without constraints regarding building envelope and energy system. The results indicate that installing additional PV units can moderately reduce total costs and CO2 emissions. The envelope modernization according to governmental regulations leads to largely increased costs at lower emissions, whereas the unconstrained optimization is able to simultaneously achieve significant cost and CO2 emission advantages. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Building energy systems Building envelopes German Energy Saving Ordinance ISO 13790 mixed-integer linear programming Optimal design Retrofitting

来源：评论

学校读者我要写书评

暂无评论

Adaptive Scheme for Caching YouTube Content in a Cellular Network: Machine Learning Approach

引用

IEEE ACCESS 2017年 5卷 5870-5881页

作者： Tanzil, S. M. Shahrear Hoiles, William Krishnamurthy, Vikram Univ British Columbia Dept Elect & Comp Engn Vancouver BC V6T 1Z4 Canada Cornell Tech Dept Elect & Comp Engn New York NY 10011 USA Cornell Univ New York NY 10011 USA

Content caching at base stations is a promising solution to address the large demands for mobile data services over cellular networks. Content caching is a challenging problem as it requires predicting the future popularity of the content and the operating characteristics of the cellular networks. In this paper, we focus on constructing an algorithm that improves the users' quality of experience (QoE) and reduces network traffic. The algorithm accounts for users' behavior and properties of the cellular network (e.g. cache size, bandwidth, and load). The constructed content and network aware adaptive caching scheme uses an extreme-learning machine neural network to estimate the popularity of content, and mixed-integer linear programming to compute where to place the content and select the physical cache sizes in the network. The proposed caching scheme simultaneously performs efficient cache deployment and content caching. Additionally, a simultaneous perturbation stochastic approximation method is developed to reduce the number of neurons in the extreme-learning machine method while ensuring a sufficient predictive performance is maintained. Using real-world data from YouTube and a NS-3 simulator, we demonstrate how the caching scheme improves the QoE of users and network performance compared with industry standard caching schemes.

关键词： Content caching cellular network extreme learning machines mixed-integer linear programming popularity prediction feature selection YouTube

来源：评论

学校读者我要写书评

暂无评论

Comparison of optimization solvers in the model predictive control of a PV-battery-heat pump system

引用

Energy Procedia 2018年 155卷 524-535页

作者： Ronny Gelleschus Michael Böttiger Peter Stange Thilo Bocklisch Chair of Energy Storage Systems Technische Universität Dresden Helmholtzstr. 9 01069 Dresden Germany Chair of Building Energy Systems and Heat Supply Technische Universität Dresden Helmholtzstr. 14 01069 Dresden Germany

This paper presents a model predictive control approach for a home energy system with a heat pump, a thermal storage, a photovoltaic system and a battery. The modeling of the system in the mixed-integer linear programming framework is demonstrated and results of a one-year simulation with real measured PV and electric load data are shown. Different solution strategies for the underlying optimization problem are presented. The strategies are compared with respect to their performance and reliability. In this rather complex case branch & cut-based algorithms performed best in solving the optimization problem.

关键词： Energy Management System Model Predivtive Control Energy Storage Sector Coupling mixed-integer linear programming Genetic Algorithm Dynamic programming

来源：评论

学校读者我要写书评

暂无评论

A comparative analysis of mixed-integer linear formulations for the multi-family capacitated lot-sizing problem

引用

JOURNAL OF INDUSTRIAL AND PRODUCTION ENGINEERING 2018年第4期35卷 229-242页

作者： Arias, Andrea L. Gatica, Ricardo A. Pontificia Univ Catolica Valparaiso Sch Ind Engn Ind Engn Valparaiso Chile Pontificia Univ Catolica Valparaiso Sch Ind Engn Valparaiso Chile Texas Tech Univ Dept Ind Mfg & Syst Engn Lubbock TX 79409 USA

Despite having a very broad spectrum of applicability in practice, the multi-family capacitated lot-sizing problem (MFCLSP) has been scarcely studied. The MFCLSP is an extension of the capacitated lot-sizing problem with setup times (CLST) in which items are organized into families based on similar setup structures. In this paper, we propose three formulations for the MFCLSP (MF-TRAD, MF-ARBNET, and MF-EXREQ), and develop a comprehensive comparative analysis to evaluate their performance using a generic solver (CPLEX). Solving large-scale problems to optimality has been shown to consume a great amount of computational time, which is very impractical for real-life applications. Because of that, this study focuses on analyzing the performance of these formulations in a limited, and reasonable, amount of time. The results show the MF-EXREQ model outperforms the other two models in both the time to the first feasible solution and the quality of the solutions generated throughout the solving process.

关键词： mixed-integer linear programming production planning mathematical modeling multi-family lot-sizing solver performance

来源：评论

学校读者我要写书评

暂无评论

Dual Pricing Algorithm in ISO Markets

引用

IEEE TRANSACTIONS ON POWER SYSTEMS 2017年第4期32卷 3308-3310页

作者： O'Neill, Richard P. Castillo, Anya Eldridge, Brent Hytowitz, Robin Broder Fed Energy Regulatory Commiss Washington DC 20426 USA Sandia Natl Labs POB 5800 Albuquerque NM 87185 USA Johns Hopkins Univ Baltimore MD 21218 USA

The challenge to create efficient market clearing prices in centralized day-ahead electricity markets arises from inherent nonconvexities in unit commitment problems. When this aspect is ignored, marginal prices may result in economic losses to market participants who are part of the welfare maximizing solution. In this essay, we present an axiomatic approach to efficient prices and cost allocation for a revenue neutral and nonconfiscatory day-ahead market. Current cost allocation practices do not adequately attribute costs based on transparent cost causation criteria. Instead we propose an ex post multipart pricing scheme, which we refer to as the dual pricing algorithm. Our approach can be incorporated into current day-ahead markets without altering the market equilibrium.

关键词： Centralized day-ahead electricity market mixed-integer linear programming non-convex pricing power system economics

来源：评论

学校读者我要写书评

暂无评论

On optimizing the deployment cost of visual sensor networks

引用

JOURNAL OF HIGH SPEED NETWORKS 2017年第1期24卷 17-30页

作者： Mehdi, Rouan-Serik Mejdi, Kaddour Univ Oran 1 Lab LITIO Ahmed Ben Bella Algeria

We study in this paper the problem of minimizing the number and the locations of deployed cameras in visual sensor networks where to objective is to monitor a set of targets with a predefined quality level. To this end, we first propose a mathematical programming formulation, based on mixed-integer linear programming (MILP), which is designed to provide optimal solutions in case where the deployment area is represented through a set of discrete potential locations of the cameras. Due to the combinatorial nature of such problems, finding exact solutions entails a tremendous computational cost. Consequently, we introduce various suboptimal solution approaches, based on a number of well-known metaheuristics, such as particle swarm optimization (PSO) and genetic algorithms. Numerical results show PSO succeeds to find the best solutions in the majority of considered scenarios. Furthermore, even for large instances, it provides better feasible solutions than those returned the MILPs after a significant amount of time.

关键词： Visual sensor networks deployment problem mixed-integer linear programming particle swarm optimization genetic algorithms greedy algorithms simulated annealing target coverage

来源：评论

学校读者我要写书评

暂无评论

Frequency constrained unit commitment

引用

ENERGY SYSTEMS-OPTIMIZATION MODELING SIMULATION AND ECONOMIC ASPECTS 2017年第1期8卷 31-56页

作者： Cardozo, Carmen Capely, Laurent Dessante, Philippe UPMC Univ Paris 06 Sorbonne Univ Univ Paris SudCentraleSupelec GeePs Grp Elect Engn Paris UMR CNRS 8507 3-11 Rue Joliot Curie F-91192 Gif Sur Yvette France EFESE EDF R&D 1 Ave Gen Gaulle F-92141 Clamart France

The unit commitment (UC) problem deals with the short-term schedule of the electrical generation to meet the power demand. The main objective is to minimize the production cost, while respecting technical and security constraints. In addition to the system load, a specific amount of spare capacity is committed to cope with uncertainties, such as forecasting errors and unit outages;this is called reserve and it has been traditionally specified following a static reliability criterion. In a system with a conventional generation mix, this security constraint allows one to obtain UC solutions that naturally provide an acceptable transient response. However, the increasing penetration of variable generation sources, such as wind and solar, can lead to UC solutions that no longer ensure system security. Thus, enhanced security constraints have been proposed to consider the power system dynamics when optimising the dayahead generation schedule. Some published works are focused on the formulation of these constraints in amixed-integer linear programming structure to apply classic optimisation techniques. Nevertheless, power system dynamics is a non-linear problem, and, to the authors' knowledge, the limits of these linear approximations have not been discussed in literature. This work examines the ability of different UC models to produce secure schedules when facing unit outages, through the implementation of a set of primary reserve and energy co-optimisation models. These models are built based on linear approximations of dynamic constraints that are available in recent literature. Then, dynamic simulations are performed for every conceivable outage to observe the transient response of a test system and to quantify the risk of under frequency load shedding. It is shown that the system's need for frequency regulation depends on the operating point and that enforcing a fixed reserve, inertia or maximal frequency slope constraint is not cost/ effective to limit the dynamic

关键词： Unit commitment Primary reserve optimisation Under frequency load shedding mixed-integer linear programming Variable generation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：