检索结果-内蒙古大学图书馆

2023 IEEE PES Innovative Smart Grid Technologies - Asia, ISGT Asia 2023

作者： Tamura, Shigeru Kimura, Hiroto Meiji University Graduate School of Advanced Mathematical Sciences Tokyo Japan Financial First Systems Division Hitachi Ltd. Kawasaki Japan

ISBN: (纸本)9798350327748

EV (electric vehicle) aggregators can get more profit by buying and selling electricity from/to the market through their V2G (Vehicle to Grid) scheduling with increase of the number of EV. As EV usage for them includes uncertainty, V2G scheduling problem is formulated by stochastic programming with scenarios and their probabilities. However, the increase of number of scenarios makes a burden of computational time for EV aggregators. Then the scenario reduction techniques have been developed to shorten the computational time. This paper proposes a new method of temporal variables reduction to reduce the computational time. The proposed method is to reduce the variables related to the time slots in the problem. This paper also shows the simulation results of the new method applied to Japanese electric market and its comparison to the traditional scenario reduction method. © 2023 IEEE.

关键词： stochastic programming

来源：评论

学校读者我要写书评

暂无评论

Planning Distributed Generation Systems Powered with Wind Turbines using a stochastic programming Model

Planning Distributed Generation Systems Powered with Wind Tu...

引用

IISE Annual Conference and Expo 2023

作者： Islam, Md Fantacher Novoa, Clara Mendez, Francis A. Texas State University San MarcosTX78666 United States

ISBN: (纸本)9781713877851

This paper presents a non-linear scenario-based stochastic programming model to determine wind turbines' optimal siting and sizing in distributed generation (DG) systems powering twelve houses or industrial facilities. The model's goal is to minimize the expected DG system's annualized installation and operational costs over the system's life cycle. The model is novel because it integrates four practical aspects, wind volatility, realistic loads, system loss-of-load probability and thermal constraints, to design a real-size DG system. The model solves exactly with a relatively low computational time, providing a competitive approach to models in the literature that typically end up solved by heuristic methods or ignoring the stochastic nature of the model parameters. The model is useful to assess if the DG system needs to connect to a centrally located substation or can operate in an islanded mode. The numerical experimentation is performed in six US cities using hourly wind speed collected over thirteen years (2009-2021). The three case studies presented are industrial park, residential houses with substations, and residential houses without substations. The industrial park case results show that in cities with high wind speeds (e.g., averaging 4.6 m/s), the system costs are 7% lower than in cities with low wind speeds (e.g., averaging 2.9 m/s). Costs are highly sensitive to load increases and slightly sensitive to changes in loss-of-load probability. Results for the residential case indicate that the system can be disconnected from the substation, even assuming a low loss-of-load probability (0.001), but the system's cost rises by about 50%. © 2023 IISE Annual Conference and Expo 2023. All rights reserved.

关键词： stochastic programming

来源：评论

学校读者我要写书评

暂无评论

stochastic programming Based Objective Function Optimization for Predictive Thrust Control of Linear Induction Machine

Stochastic Programming Based Objective Function Optimization...

引用

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

作者： Tang, Lei Xu, Wei Islam, Md Rabiul Xi An Jiao Tong Univ Sch Elect Engn Sch Management Xian 710049 Peoples R China Huazhong Univ Sci & Technol Sch Elect & Elect Engn Wuhan 430074 Peoples R China Univ Wollongong Sch Elect Comp & Telecommun Engn Wollongong NSW 2522 Australia

ISBN: (纸本)9781728164014

Model predictive thrust control (MPTC) is one of the most effective approaches for linear induction motor (LIM) drive system. It can achieve the optimization of multiple objectives. However, the process of tuning the weighting factors in the objective function is the main drawback of MPTC. It greatly increases the computation burden. In this paper, the tuning process of weighting factors is regarded as a random sampling process. Then, a novel weighting factor optimization method based on the stochastic programming technique is proposed to select the suitable control action for LIM. It will optimize with flux and thrust together to avoid the adjustment of weighting factor. In this paper, the optimal model can be solved by Monte Carlo simulation. At last, the simulation results have shown better dynamic and steady state performance of the proposed method.

关键词： Linear induction machine (LIM) stochastic programming model predictive control (MPC) weighting factors fuzzy optimization

来源：评论

学校读者我要写书评

暂无评论

stochastic programming-based mathematical model and solution strategy for chemical production scheduling with processing time uncertainty

引用

COMPUTERS & CHEMICAL ENGINEERING 2022年 168卷

作者： Gao, Jingxing Liu, Linlin Dong, Yachao Zhang, Lei Zhuang, Yu Du, Jian Dalian Univ Technol Frontiers Sci Ctr Smart Mat Oriented Chem Engn Sch Chem Engn Inst Chem Proc Syst Engn Dalian 116024 Peoples R China

Scheduling of multipurpose batch chemical plant is always affected by uncertain factors, including processing time of tasks. When the processing time deviates from its nominal value, the task sequence and executing time based upon the original schedule may become suboptimal or even infeasible. To address this issue, an optimization model based on stochastic programming is proposed for the short-term scheduling of multipurpose batch chemical plant, by introducing task sequence variables and new logical constraints relating multiple binary variables. Additionally, a network-based decomposition solution strategy, accounting for different situations of profits and shared units, is proposed to solve the large-scale problems, which has been shown to provide high quality solutions while consuming substantially less solution time than solving the entire process directly.

关键词： Multipurpose batch scheduling stochastic programming Processing time uncertainty Decomposition solution strategy

来源：评论

学校读者我要写书评

暂无评论

Power Control in Local 5G/Beyond Systems Utilizing Spectrum Database and Monte Carlo stochastic programming 12

Power Control in Local 5G/Beyond Systems Utilizing Spectrum ...

引用

IEEE 12th Annual Computing and Communication Workshop and Conference (CCWC)

作者： Taniguchi, Tetsuki Fujii, Takeo Univ Electrocommun UEC Adv Wireless & Commun Res Ctr AWCC Tokyo 1828585 Japan

ISBN: (纸本)9781665483032

In 5G / beyond, local communication systems with small cells managed by micro operators are collecting attentions, where interference mitigation and power saving is considered as an important topic. This paper presents an interference management method aided by spectrum database based on stochastic programming assuming non-line of sight (NLOS) environment. Regarding analysis of signal to interference plus noise ratio (SINR) under multiuser Rayleigh channel, density functions of SINR are approximated by exponential distributions. Then chance constraints in stochastic programming concerning outage SINR which are hard to deal with are converted to Monte Carlo expression for approximating predetermined outage SINR inequalities to improve the feasibility of the problem. Computer simulations show the proposed approach utilizing spectrum database is effective for performance improvement in small cellular system by micro operator.

关键词： spectrum database micro operator small cell local 5G stochastic programming Monte Carlo

来源：评论

学校读者我要写书评

暂无评论

Convex relaxation of two-stage network-constrained stochastic programming for CHP microgrid optimal scheduling

引用

ENERGY 2024年 308卷

作者： Mohtavipour, Seyed Saeid Univ Guilan Dept Elect Engn Rasht Iran

Different from most studies only incorporating economic aspect into operation scheduling, this paper develops a novel network-constrained framework that can address both economic and secure issues for combined heating and power (CHP) microgrids integrated with wind power considering uncertainties. According to quadratically constrained programs, a two-stage network-constrained stochastic programming (TSNCSP) model is formulated to improve economic benefits and meanwhile capture active/reactive power and off-nominal bus voltage constraints in the full decision variable domain. In the first stage, namely day-ahead, the schedule of transacted electricity with the upstream power grid and the generation cost of heat is determined according to the forecast information. In the second stage, namely real-time, a recourse function of adjustable resources is defined to reduce the expected cost incurred by the perturbation of random wind power outputs. Moreover, the original non-convex problem is innovatively transformed into a semidefinite programming through incorporation of demand response program (DRP), duality, complementary slackness, and relaxation techniques to improve the solving efficiency. Finally, a proposition is presented and proved that provides a sufficient condition for the exactness of the proposed convex relaxation. Numerical simulations on the 33-bus test system verify the effectiveness of the proposed framework in multi-period scenario-based scheduling problems.

关键词： CHP microgrid stochastic programming Demand response program Convex relaxation Wind power

来源：评论

学校读者我要写书评

暂无评论

Emergency materials management of petrochemical accidents considering the randomness and uncertainty base on stochastic programming

引用

FRONTIERS IN ENERGY RESEARCH 2024年 12卷

作者： Jiang, Wei Yang, Yuxiang Hu, Ansen Liu, Yulin Hong, Siyan Dongying Hualian Petrochem Plant Co Ltd Dongying Shandong Peoples R China China Univ Petr Coll Safety & Ocean Engn Beijing Peoples R China Zhejiang Ocean Univ Sch Shipping & Maritime Zhoushan Zhejiang Peoples R China Zhejiang Ocean Univ Natl & Local Joint Engn Res Ctr Harbor Oil & Gas S Zhejiang Key Lab Petrochem Environm Pollut Control Zhoushan Peoples R China

Petroleum is the pillar industry of the national economy, but safety accidents are frequent all over the world. The government attaches more importance to the safety production management of enterprises to reduce the occurrence of accidents that infringe on personal safety. The management of emergency supplies, which can effectively respond to the occurrence of safety production accidents, is a key measure for handling emergency accidents. Rapid response to accidents means reducing accident rescue costs and protecting personal and property safety. This paper proposes a material stochastic model with the randomness of accident demand for materials. The enterprise and the government can obtain the material management scheme and the quantitative evaluation standard of accident preventive measures from the model results respectively. The model covers as many accident scenarios as possible through multi-scenario modeling to reduce the impact of accident uncertainty. Finally, the feasibility is proved by an example of a petroleum enterprise in Zhoushan City. When the accident demand fluctuates randomly between 80% and 120%, the model proposes a material management scheme that the dispatching time of materials and the cost in rescue work do not exceed 31.33 min and 11.68 million CNY respectively. With the assistance of the model, the enterprise saves the cost of safe production and improves the efficiency of rescue. The government has strengthened the supervision and evaluation of enterprise safety production management. Finally, the mission of protecting the property and life safety of the people will be realized.

关键词： emergency logistics stochastic programming multi-scenario modeling petrochemical accident disaster accident frequency

来源：评论

学校读者我要写书评

暂无评论

Predictive stochastic programming

引用

COMPUTATIONAL MANAGEMENT SCIENCE 2022年第1期19卷 65-98页

作者： Deng, Yunxiao Sen, Suvrajeet Univ Southern Calif Daniel J Epstein Dept Ind & Syst Engn Los Angeles CA 90089 USA

Several emerging applications call for a fusion of statistical learning and stochastic programming (SP). We introduce a new class of models which we refer to as Predictive stochastic programming (PSP). Unlike ordinary SP, PSP models work with datasets which represent random covariates, often refered to as predictors (or features) and responses (or labels) in the machine learning literature. As a result, these PSP models call for methodologies which borrow relevant concepts from both learning and optimization. We refer to such a methodology as Learning Enabled Optimization (LEO). This paper sets forth the foundation for such a framework by introducing several novel concepts such as statistical optimality, hypothesis tests for model-fidelity, generalization error of PSP, and finally, a non-parametric methodology for model selection. These new concepts, which are collectively referred to as LEO, provide a formal framework for modeling, solving, validating, and reporting solutions for PSP models. We illustrate the LEO framework by applying it to a production-marketing coordination model based on combining a pedagogical production planning model with an advertising dataset intended for sales prediction.

关键词： stochastic programming Fusion with statistical learning Model assessment

来源：评论

学校读者我要写书评

暂无评论

A two-stage stochastic programming approach for dynamic OD estimation using LBSN data

引用

TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES 2024年 158卷

作者： Lu, Qing-Long Qurashi, Moeid Antoniou, Constantinos Tech Univ Munich Chair Transportat Syst Engn Munich Germany Tech Univ Dresden Chair Transport Modeling & Simulat Dresden Germany

Estimating origin-destination (OD) demand is essential for urban transport management and traffic control systems. With the ubiquity of smartphones, location based social networks (LBSN) data has emerged as a new rich data source with broad urban spatial and temporal coverage highly suitable for OD estimation. Its nature of confirmed trip purpose (activity) and activity chain host makes it more advantageous than other data (e.g., household travel surveys and traffic network detection). On the other hand, LBSN data is a more direct and accurate representation of demand patterns and can remove the significant burden of developing traffic models and estimating simulation-based objective functions. However, thus far, most LBSN-based estimation models only focus on static (day-level) OD estimation, making less use of those characteristics. To this end, this paper establishes a two-stage stochastic programming (TSSP) framework integrating the activity chains to model activity-level dynamic mobility flows using LBSN data. The first-stage model aims to minimize the errors introduced by the inter-zone OD flows alongside the expected errors of the check-in patterns. The second-stage model attempts to minimize the errors produced by the considered check-in pattern scenarios. Markov chain Monte Carlo (MCMC) sampling is used to generate plausible check-in scenarios. A generalized Benders decomposition (GBD) algorithm is presented to solve the two-stage stochastic programming model. We conduct the experiments on the case study of Tokyo, Japan, under the employment of the generalized least squares (GLS) estimator. The results show that algorithm convergence can be guaranteed within several iterations. The approach can provide satisfactory estimations of check-in patterns, zonal production and attraction, and OD flows. Furthermore, multiple objective function states are tested for evaluating the completeness of the proposed framework and exploring its potential for simplification a

关键词： OD estimation Demand estimation stochastic programming LBSN data Activity chain

来源：评论

学校读者我要写书评

暂无评论

A two-stage stochastic programming approach for electric energy procurement of EV charging station integrated with BESS and PV

引用

ELECTRIC POWER SYSTEMS RESEARCH 2024年 232卷

作者： Kazemtarghi, Abed Mallik, Ayan Arizona State Univ Polytech Sch 6075 Innovat Way W Mesa AZ 85212 USA

Energy procurement of an electric vehicle charging station (EVCS) needs medium-term decisions, which depend on the short-term energy transactions of the EVCS in real-time market. However, the energy exchange in real-time operation is affected by uncertainties related to the pool prices, electric vehicle (EV) load demand, and photovoltaic (PV) generation level. To comprehensively include the real-time considerations in the decision framework, this paper proposes a two-stage stochastic programming approach to formulate EVCS energy procurement and optimal equipment dispatch as a single problem. The objective is to minimize the total operational cost of EVCS. First, a decision-making framework is developed that integrates EVCS energy procurement, charging pricing, and equipment dispatch in order to make energy procurement decisions based on random nature of electricity pool prices, EV loads, and PV generation in real-time operations. Next, the developed decision framework is formulated as a two-stage stochastic program with risk modeling using Conditional value-at-risk (CVaR) index. The first-stage variables include medium-term bilateral contracts and EV charging prices, while the second-stage variables encompass energy dispatch of battery energy storage systems (BESS) and energy transactions with the main grid in real-time pool. In addition, uncertainties related to electricity pool prices, EV loads, and PV generation levels are characterized by stochastic scenarios generated based on historical data. The simulation results for an EVCS equipped with DC fast chargers and integrated with BESS and PV generation demonstrate the effectiveness of the proposed approach in achieving efficient and profitable EVCS energy procurement. It is observed that expected profit for beta = 0 is $11,308 while none of the bilateral contracts are selected in this case because the pool prices are expected to be cheaper. On the other hand, expected profit for beta = 100 is $9900 where some par

关键词： Conditional value-at-risk (CVaR) Electric energy procurement Electric vehicle charging station stochastic programming

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：