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Random-Fuzzy chance-constrained programming Optimal Power Flow of Wind Integrated Power Considering Voltage Stability

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IEEE ACCESS 2020年 8卷 217957-217966页

作者： Ma, Rui Li, Xuan Gao, Weicheng Lu, Peng Wang, Tieqiang Changsha Univ Sci & Technol Coll Elect & Informat Engn Changsha 410114 Peoples R China State Grid Hebei Elect Power Co Ltd Shijiazhuang 050021 Hebei Peoples R China

Considering the random and fuzzy nature of wind speed, this paper proposes a multi-objective random-fuzzy chance-constrained programming optimal power flow (OPF) for wind integrated power systems. The proposed method is based on random-fuzzy chance-constrained programming. The optimization model aims at minimizing generation cost, carbon dioxide (CO2) emission, and system functional power loss, and P-Q-V steady-state voltage stability is included in the constraints. Based on random-fuzzy chance-constrained programming, the corresponding solution process of the proposed multi-objective OPF is proposed, which is a hybrid of random-fuzzy simulation, non-dominated sorting genetic algorithm-II (NSGA-II), and fuzzy satisfaction-maximizing decision-making method. The proposed approach is simulated on the IEEE 30-bus system to provide an example of its application. The simulation results demonstrate that the proposed random-fuzzy chance-constrained programming OPF has higher security and more economy than dynamic stochastic optimal power flow (DSOPF) and dynamic fuzzy optimal power flow (DFOPF).

关键词： Power system stability Load flow Wind speed programming Stability criteria Load modeling Uncertainty Optimal power flow (OPF) random-fuzzy variable chance-constrained programming wind power generation

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Stochastic optimization model for the short-term joint operation of photovoltaic power and hydropower plants based on chance-constrained programming

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ENERGY 2021年 222卷 119996-119996页

作者： Yuan, Wenlin Wang, Xinqi Su, Chengguo Cheng, Chuntian Liu, Zhe Wu, Zening Zhengzhou Univ Sch Hydraul Sci & Engn Zhengzhou 450001 Peoples R China Dalian Univ Technol Inst Hydropower & Hydroinformat Dalian 116024 Peoples R China

Integrating photovoltaic (PV) power into large-capacity hydropower plants is considered as an efficient and promising approach for large-scale PV power accommodation. To improve the guidelines for the optimal operation of large-scale hydro-PV hybrid systems, this paper proposes a practical coordination mode of a PV plant and a large-capacity hydropower plant based on the negotiation mechanism between the power generation company and the power grid. A chance-constrained programming (CCP) based stochastic optimization model is then presented to determine the short-term joint operation of a hydro PV system, aiming at promoting renewable energy consumption. To improve the solution efficiency, several linearization approaches are proposed to convert the original model into a scenario-based mixed integer linear programming (MILP) problem. The real-world case studies demonstrate that the joint operation of the hydro-PV hybrid system can promote the consumption of renewable energy while making the actual total power output track the schedule submitted to the power grid. Moreover, the confidence level at which the power balance constraints can be met exceeds 90% in all weather conditions, far above the confidence level of less than 50% for the deterministic model, proving the stochastic model would be a better choice for the joint operation of a hydro-PV system. (c) 2021 Elsevier Ltd. All rights reserved.

关键词： Hydro-PV hybrid Energy system Uncertainty of PV power chance-constrained programming Mixed integer linear programming

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ICCLP: An inexact chance-constrained linear programming model for land-use management of lake areas in urban fringes

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ENVIRONMENTAL MANAGEMENT 2007年第6期40卷 966-980页

作者： Liu, Yong Qin, Xiaosheng Guo, Huaicheng Zhou, Feng Wang, Jinfeng Lv, Xiaojian Mao, Guozhu Peking Univ Coll Environ Sci Beijing 100871 Peoples R China Univ Regina Fac Engn Regina SK S4S 0A2 Canada

Lake areas in urban fringes are under increasing urbanization pressure. Consequently, the conflict between rapid urban development and the maintenance of water bodies in such areas urgently needs to be addressed. An inexact chance-constrained linear programming (ICCLP) model for optimal land-use management of lake areas in urban fringes was developed. The ICCLP model was based on land-use suitability assessment and land evaluation. The maximum net economic benefit (NEB) was selected as the objective of land-use allocation. The total environmental capacity (TEC) of water systems and the public financial investment (PFI) at different probability levels were considered key constraints. Other constraints included in the model were land-use suitability, governmental requirements on the ratios of various land-use types, and technical constraints. A case study implementing the system was performed for the lake area of Hanyang at the urban fringe of Wuhan, central China, based on our previous study on land-use suitability assessment. The Hanyang lake area is under significant urbanization pressure. A 15-year optimal model for land-use allocation is proposed during 2006 to 2020 to better protect the water system and to gain the maximum benefits of development. Sixteen constraints were set for the optimal model. The model results indicated that NEB was between $1.48 x 10(9) and $8.76 x 10(9) or between $3.98 x 10(9) and $16.7 x 10(9), depending on the different urban-expansion patterns and land demands. The changes in total developed area and the land-use structure were analyzed under different probabilities (q(i) ) of TEC. Changes in q(i) resulted in different urban expansion patterns and demands on land, which were the direct result of the constraints imposed by TEC and PFI. The ICCLP model might help local authorities better understand and address complex land-use systems and develop optimal land-use management strategies that better balance urban expansion and grassland c

关键词： chance-constrained programming interval lake area land-use management optimization uncertainty

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An Inexact chance-constrained Quadratic programming Model for Stream Water Quality Management

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WATER RESOURCES MANAGEMENT 2009年第4期23卷 661-695页

作者： Qin, X. S. Huang, G. H. Univ Regina Ctr Energy & Environm Studies Regina SK S4S 0A2 Canada N China Elect Power Univ Chinese Res Acad Environm Sci Beijing 100012 Peoples R China Univ Regina Fac Engn Environm Syst Engn Program Regina SK S4S 0A2 Canada

Water quality management is complicated with a variety of uncertainties and nonlinearities. This leads to difficulties in formulating and solving the resulting inexact nonlinear optimization problems. In this study, an inexact chance-constrained quadratic programming (ICCQP) model was developed for stream water quality management. A multi-segment stream water quality (MSWQ) simulation model was provided for establishing the relationship between environmental responses and pollution-control actions. The relationship was described by transformation matrices and vectors that could be used directly in a multi-point-source waste reduction (MWR) optimization model as water-quality constraints. The interval quadratic polynomials were employed to reflect the nonlinearities and uncertainties associated with wastewater treatment costs. Uncertainties associated with the water-quality parameters were projected into the transformation matrices and vectors through Monte Carlo simulation. Uncertainties derived from water quality standards were characterized as random variables with normal probability distributions. The proposed ICCQP model was applied to a water quality management problem in the Changsha section of the Xiangjiang River in China. The results demonstrated that the proposed optimization model could effectively communicate uncertainties into the optimization process, and generate inexact solutions containing a spectrum of wastewater treatment options. Decision alternatives could then be obtained by adjusting different combinations of the decision variables within their solution intervals. Solutions from the ICCQP model could be used to analyze tradeoffs between the wastewater treatment cost and system-failure risk due to inherent uncertainties. The results are valuable for supporting decision makers in seeking cost-effective water management strategies.

关键词： Interval quadratic programming chance-constrained programming Water quality management Uncertainty

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A New chance-constrained programming with Linear Combination of Possibility Measure and Necessity Measure

A New Chance-Constrained Programming with Linear Combination...

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第一届中国智能计算大会

作者： Kakuzo Iwamura Department of Mathematics Josai University Japan

Based on the possibility measure and necessity measure, m-measure is presented and some mathematical prop- erties of m-measure are also obtained,including con- tinuity,monotonicity,subadditivity,and so ***- cal values of fuzzy variable with respect to m-measure are introduced and are employed to construct the fuzzy chance-constrained programming *** solve the models,genetic algorithm based on fuzzy simulation is ***,two numerical examples are given to show applications of the models and algorithm.

关键词： Possibility Measure m_λ-Measure chance-constrained programming Fuzzy Simulation Genetic Algorithm

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Simulation-based inexact chance-constrained nonlinear programming for eutrophication management in the Xiangxi Bay of Three Gorges Reservoir

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JOURNAL OF ENVIRONMENTAL MANAGEMENT 2012年 108卷 54-65页

作者： Huang, Y. L. Huang, G. H. Liu, D. F. Zhu, H. Sun, W. Univ Regina Fac Engn & Appl Sci Regina SK S4S 0A2 Canada China Three Gorges Univ Coll Hydraul & Environm Engn Yichang City 443002 Hubei Province Peoples R China

Although integrated simulation and optimization approaches under stochastic uncertainty have been applied to eutrophication management problems, few studies are reported in eutrophication control planning where multiple formats of uncertainties and nonlinearities are addressed in forms of intervals and probabilistic distributions within an integrated framework. Since the impounding of Three Gorges Reservoir (TGR), China in 2003, the hydraulic conditions and aquatic environment of the Xiangxi Bay (XXB) have changed significantly. The resulting emergence of eutrophication and algal blooms leads to its deteriorated water quality. The XXB becomes an ideal case study area. Thus, a simulation-based inexact chance-constrained nonlinear programming (SICNP) model is developed and applied to eutrophication control planning in the XXB of the TGR under uncertainties. In the SICNP, the wastewater treatment costs for removing total phosphorus (TP) are set as the objective function;effluent discharge standards, stream water quality standards and eutrophication control standards are considered in the constraints;a steady-state simulation model for phosphorus transport and fate is embedded in the environmental standards constraints;the interval programming and chance-constrained approaches are integrated to provide interval decision variables but also the associated risk levels in violating the system constraints. The model results indicate that changes in the violating level (q) will result in different strategy distributions at spatial and temporal scales;the optimal value of cost objective is from [2.74, 13.41] million RMB to [2.25, 13.08] million RMB when q equals from 0.01 to 0.25;the required TP treatment efficiency for the Baisha plant is the most stringent, which is followed by the Xiakou Town and the Zhaojun Town, while the requirement for the Pingyikou cement plant is the least stringent. The model results are useful for making optimal policies on eutrophication control pl

关键词： The Xiangxi Bay Eutrophication management chance-constrained programming Uncertainty

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A Stochastic chance-constrained programming Model for Time-Cost Trade-off Problem

A Stochastic Chance-Constrained Programming Model for Time-C...

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第七届中国不确定系统年会

作者： Hua Ke,Weimin Ma School of Economics and Management,Tongji University,Shanghai 200092,China

In real projects,both the trade-off between the project cost and the project completion time,and the uncertainty of the environment are considerable for *** the existing models for the stochastic time-cost trade-off problem,optimizing the expected value of the objective is the exclusive decision-making *** this paper,an alternative stochastic model is proposed,in which the philosophy of chance-constrained programming is adopted for decision *** addition,stochastic simulation and genetic algorithm are integrated to design a hybrid intelligent algorithm to search the quasi-optimal schedule.

关键词： Time-cost trade-off chance-constrained programming Genetic algorithm

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Solving for Power system economic dispatch with wind power integration based on chance-constrained programming 19

Solving for Power system economic dispatch with wind power i...

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Proceedings of the 4th International Conference on Intelligent Information Processing

作者： Yaming Ren College of Mechanical and Control Engineering Guilin University of Technology Guilin China

ISBN: (纸本)9781450361910

In today's world, with the rapid development of green and clean energy, the comparison of wind power in power network has been gradually improved. However, wind power has also brought new challenges to the stable operation of power system due to its inherent volatility and randomness. In this paper, the economic dispatching model of power system including wind power grid connection is studied. On the basis of stochastic expectation and chance-constrained programming, the specific economic dispatch model with wind power integration is given. The core of this paper is that we simulate the degree of wind power output fluctuation by setting different confidence levels. Simulation results show that a larger confidence interval can achieve better security, while a smaller confidence interval can achieve better economy.

关键词： chance-constrained programming Stochastic expectation Wind

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A chance constrained programming approach for uncertain p-hub center location problem

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COMPUTERS & INDUSTRIAL ENGINEERING 2016年 102卷 10-20页

作者： Gao, Yuan Qin, Zhongfeng Beijing Jiaotong Univ State Key Lab Rail Traff Control & Safety Beijing 100044 Peoples R China Beihang Univ Sch Econ & Management Beijing 100191 Peoples R China

The p-hub center location problem aims to locate p hubs and allocate other nodes to these hub nodes in order to minimize the maximal travel time. It is more important for time-sensitive distribution systems. Due to the presence of uncertainty, more researches are recently focused on the problem in non deterministic environment. This paper joins the research stream by considering travel times as uncertain variables instead of random variables or fuzzy ones. The goal is to model the p-hub center problem based on experts' subjective belief in the case of lack of data. The uncertain distribution of the maximal travel time is first derived and then a chance constrained programming model is formulated. The deterministic equivalent forms are further given when the information of uncertainty distributions is provided. A hybrid intelligent algorithm is designed to solve the proposed models and numerical examples are presented to illustrate the application of this approach and the effectiveness of the algorithm. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Uncertainty modelling p-hub center location problem Uncertain variable Uncertain measure chance-constrained programming

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COTS products selection using fuzzy chance-constrained multiobjective programming

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APPLIED INTELLIGENCE 2015年第4期43卷 732-751页

作者： Mehlawat, Mukesh Kumar Gupta, Pankaj Univ Delhi Dept Operat Res Delhi 110007 India

In this paper, we study the commercial off-the-shelf (COTS) products selection problem in COTS-based modular software systems with fuzzy parameters using chance-constrained multiobjective programming. The criteria used in this work are total cost, size, execution time, software reliability, delivery time, and compatibility issues among available COTS products. The COTS selection model presented herein simultaneously minimizes the total cost, size, and execution time of the modular software system at a credibility that is no less than pre-determined confidence levels. We propose a hybrid approach that combines the technique for order preference by similarity to ideal solution (TOPSIS) and the compensatory fuzzy approach based on the "fuzzy and" aggregation operator. TOPSIS is used to reduce the multiobjective problem with conflicting and non-commensurable objective functions to a bi-objective problem with conflicting but commensurable objective functions. The resulting bi-objective problem is solved using the compensatory fuzzy approach. The obtained compromise solutions are both compensatory and pareto-optimal for the multiobjective COTS products selection problem. A small-scale real-life case study of modular software development is presented to demonstrate the applicability of the proposed model and solution approach in real-life applications of COTS selection. A detailed performance analysis and comparison with some existing related fuzzy programming approaches are performed using distance measures to illustrate the superiority of the proposed hybrid interactive fuzzy-programming approach over existing approaches.

关键词： COTS selection chance-constrained programming Credibility theory Fuzzy sets Multiobjective optimization

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