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5th IEEE International Conference on Engineering Technologies and Applied Sciences (IEEE ICETAS)

作者： Farizal Ariva Dachyar, M. Rahman, A. Univ Indonesia Dept Ind Engn Kampus Baru UI Depok 16424 Indonesia

ISBN: (纸本)9781538679661

Geothermal is believed a cleaner and more environmentally friendly energy source than fossil fuel. Indonesia whose has the largest geothermal potency in the world just be able to utilize around 5% of her potency. This research is about geothermal power plant area layout optimization considering one of process safety aspect, i.e. toxic gas dispersion particularly H2S gas spreading. Results of this study hopefully can be used to promote geothermal energy utlilization further especially at Indonesia. For the purpose, the optimization problem was formulated as a mixed integer non linear programming and solved with excel solver using GRG non linear algorithm. The objective function of the model is to minimize total plant layout cost yet still to take into consideration toxic gas dispersion. In this case, H2S gas dispersion was computed through computational fluid dynamic simulation. To show the applicability of the model, layout of two geothermal power plants, with and without following process safety standard spacing requirements, have been optimized. The results show that this proposed model is capable to reduce total plant layout cost of existing layouts up to 36%.

关键词： Geothermal Power Plant toxic gas dispersion H2S mixed integer non linear programming

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Simplified Optimal Scheduling (SOS) for Network Coded Wireless Multicast 88

Simplified Optimal Scheduling (SOS) for Network Coded Wirele...

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88th IEEE Vehicular Technology Conference (VTC-Fall)

作者： Moghadam, Nadieh Zhang, Guomei Li, Hongxiang Ivani LLC Dardenne Prairie MO 63368 USA Xi An Jiao Tong Univ Louisville KY USA Univ Louisville Louisville KY 40292 USA

ISBN: (纸本)9781538663585

A Simplified Optimal Scheduling (SOS) scheme for network coded wireless multicast is studied in this paper. Specifically, a complexity reduction method proposed to make the existing algorithms more practical. Our objective is to remove redundancy while maintaining the maximum throughput. We formulate it as a mixed integer non linear programming (MINLP) problem and propose a network coding based packet scheduling scheme that finds the optimal solution. Finally, the simulation results corroborate our method.

关键词： Multicast network coding queueing stability mixed integer non linear programming

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Minimum Spanning Trees with neighborhoods: Mathematical programming formulations and solution methods

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EUROPEAN JOURNAL OF OPERATIONAL RESEARCH 2017年第3期262卷 863-878页

作者： Blanco, Victor Fernandez, Elena Puerto, Justo Univ Granada Dept Quantitat Methods Econ & Business Granada 18011 Spain Univ Politecn Cataluna Dept Stat & Operat Res ES-08034 Barcelona Spain Univ Seville Dept Stat & Operat Res E-41012 Seville Spain

This paper studies Minimum Spanning Trees under incomplete information assuming that it is only known that vertices belong to some neighborhoods that are second order cone representable and distances are measured with a l(q)-norm. Two mixed integer non linear mathematical programming formulations are presented, based on alternative representations of subtour elimination constraints. A solution scheme is also proposed, resulting from a reformulation suitable for a Benders-like decomposition, which is embedded within an exact branch-and-cut framework. Furthermore, a mathheuristic is developed, which alternates in solving convex subproblems in different solution spaces, and is able to solve larger instances. The results of extensive computational experiments are reported and analyzed. (C) 2017 Elsevier B.V. All rights reserved.

关键词： Combinatorial Optimization Minimum Spanning Trees Neighborhoods mixed integer non linear programming Second order cone programming

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Development of a pricing mechanism for valuing ancillary, transportation and environmental services offered by a power to gas energy system

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ENERGY 2017年 128卷 447-462页

作者： Mukherjee, Ushnik Walker, Sean Maroufmashat, Azadeh Fowler, Michael Elkamel, Ali Univ Waterloo Dept Chem Engn 200 Univ Ave West Waterloo ON N2L 3G1 Canada Univ S Alabama Dept Chem & Biomol Engn Mobile AL 36688 USA

Power to gas is a novel energy storage concept that can help in providing energy storage and offer sustainable and efficient alternative ways to utilize the surplus electricity generated by the provincial grid of Ontario, Canada. This situation of 'surplus electricity' also exists elsewhere as there in increasing intermittent renewable power on various grids. The ability of the power to gas energy hubs to utilize the existing natural gas distribution and storage network (within the province) to distribute and store the electrolytic hydrogen produced is one of its major advantages. In this study an optimization model of a power to gas energy hub having a hydrogen production module capacity of 2 MW has been developed. The goal of the optimization study is to carry out an economic feasibility of the energy hub under existing pricing mechanisms for the three primary services that it provides, namely: 1) Offsetting CO2 emissions at natural gas end users by providing hydrogen enriched natural gas;2) Providing demand response when directed by the Independent Electricity System Operator of the province, and 3) Providing pure hydrogen to a fuel cell vehicle refueling station. It is observed that current pricing mechanisms are not valued high enough for the power to gas energy hub to be economically feasible and payback periods longer than the project lifetime (20 years) have been observed. Therefore, through a post-processing economic calculation, the additional monetary incentive required for the energy hub to achieve a NPV equal to zero for shorter project lifetimes of 8, 9 and 10 years have been calculated. The required additional monetary incentives (for the new project lifetimes) have then been split proportionally to the share of the revenues earned by the energy hub while providing each of the three services. Through this, the existing pricing mechanisms have been scaled up and a new pricing mechanism has been developed that highlights the monetary requirements of a p

关键词： Power to gas Demand response Hydrogen production mixed integer non linear programming optimization GAMS Green energy Electrolysis Fuel cell vehicles

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A sparsity-controlled vector autoregressive model

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BIOSTATISTICS 2017年第2期18卷 244-259页

作者： Carrizosa, Emilio Olivares-Nadal, Alba Ramirez-Cobo, Pepa Univ Seville Fac Matemat Dept Estadist & Invest Operat Av Reina Mercedes S-N E-41012 Seville Spain Univ Edinburgh Sch Math James Clerk Maxwell BldgPeter Guthrie Tait Rd Edinburgh EH9 3FD Midlothian Scotland Univ Cadiz Dept Estadist & Invest Operat Avd Univ S-N Jerez de la Frontera 11405 Spain

Vector autoregressive (VAR) models constitute a powerful and well studied tool to analyze multivariate time series. Since sparseness, crucial to identify and visualize joint dependencies and relevant causalities, is not expected to happen in the standard VAR model, several sparse variants have been introduced in the literature. However, in some cases it might be of interest to control some dimensions of the sparsity, as e.g. the number of causal features allowed in the prediction. To authors extent none of the existent methods endows the user with full control over the different aspects of the sparsity of the solution. In this article, we propose a versatile sparsity-controlled VAR model which enables a proper visualization of potential causalities while allows the user to control different dimensions of the sparsity if she holds some preferences regarding the sparsity of the outcome. The model coefficients are found as the solution to an optimization problem, solvable by standard numerical optimization routines. The tests performed on both simulated and real-life time series show that our approach may outperform a greedy algorithm and different Lasso approaches in terms of prediction errors and sparsity.

关键词： Causality mixed integer non linear programming Multivariate time series Sparse models Vector autoregressive process

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Simplified Optimal Scheduling (SOS) for Network Coded Wireless Multicast

Simplified Optimal Scheduling (SOS) for Network Coded Wirele...

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IEEE Vehicular Technology Conference

作者： Nadieh Moghadam Guomei Zhang Hongxiang Li Ivani LLC Xi'an Jiaotong University University of Louisville

ISBN: (纸本)9781538663592;9781538663585

关键词： Multicast Network coding Queueing Stability mixed integer non linear programming

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Addressing Short Term Voltage Stability Problem - Part II: A Case Study

Addressing Short Term Voltage Stability Problem - Part II: A...

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IEEE/PES Transmission and Distribution Conference and Exposition (T&D)

作者： Tiwari, Ashutosh Ajjarapu, Venkataramana Iowa State Univ Dept ECPE Ames IA USA

ISBN: (纸本)9781509021574

This paper is second of a two-part paper and proposes a framework for optimal allocation of dynamic VAR device and demonstrates its application. This paper presents a complete framework to solve this complex problem. First, to filter out severe contingencies out of all credible ones severity indices are proposed. Second, a method based upon trajectory sensitivity analysis is used to determine the best candidate dynamic VAR locations. Third, the overall optimization problem is formulated as mixed integer Dynamic Optimization (MIDO). To reduce the complexity of optimization problem due to consideration of system dynamics and multiple contingencies, a novel methodology is proposed, where the overall problem is solved in two phases. Further, the MIDO problem is solved by the state of art solvers. The effectiveness of the proposed approach is illustrated using the 75 bus system.

关键词： Branch and Bound dynamic VAR allocation mixed integer dynamic optimization mixed integer non linear programming multiple contingency

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Joint location-inventory problem with differentiated service levels using critical level policy

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TRANSPORTATION RESEARCH PART E-LOGISTICS AND TRANSPORTATION REVIEW 2015年 83卷 141-157页

作者： Escalona, P. Ordonez, F. Marianov, V. Univ Tecn Federico Santa Maria Dept Ind Engn Valparaiso Chile Univ Chile Dept Ind Engn Santiago Chile Pontificia Univ Catolica Chile Dept Elect Engn Santiago Chile

This paper analyzes the design of a distribution network for fast-moving items able to provide differentiated service levels in terms of product availability for two demand classes (high and low priority) using a critical level policy. The model is formulated as a MINLP with chance constraints for which we propose a heuristic to solve it. Although the heuristic does not guarantee an optimal solution, our computational experiments have shown that it provides good-quality solutions that are on average 0.8% and at worst 2.7% from the optimal solution. (C) 2015 Elsevier Ltd. All rights reserved.

关键词： Location-inventory model Two demand classes Critical level rationing Fast-moving items mixed integer non linear programming

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A Computer Package for Multi-Contingency Constrained Reactive Power Planning

A Computer Package for Multi-Contingency Constrained Reactiv...

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General Meeting of the IEEE-Power-and-Energy-Society

作者： Tiwari, Ashutosh Ajjarapu, Venkataramana Iowa State Univ Dept Elect & Comp Engn Ames IA USA

ISBN: (纸本)9781467380409

Reactive power planning or VAR planning is critical to ensure acceptable power quality and system robustness. While addressing var planning, the key issue is optimal allocation i.e. location and size of reactive power sources. Security of power systems is a major concern during contingencies. So, consideration of all plausible contingencies during planning process is important. However, consideration of such a large number of contingencies makes the problem size big hence complex to solve. This paper presents a computer package for solving multiple contingency constrained reactive power planning. To reduce the complexity of optimization problem due to consideration of multiple contingencies a new methodology is proposed, where the overall problem is solved in two phases. The optimization problem is formulated as mixed integer non linear programming (MINLP) optimization problem, which is solved by the state of art solvers. Further the efficiency of integer optimization is increased by incorporating system based knowledge. The effectiveness of the proposed approach is illustrated using the 75 bus system.

关键词： Branch and Bound mixed integer non linear programming multiple contingency reactive power planning

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A Computer Package for Multi-Contingency Constrained Reactive Power Planning

A Computer Package for Multi-Contingency Constrained Reactiv...

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IEEE Power and Energy Society General Meeting

作者： Ashutosh Tiwari Venkataramana Ajjarapu Electrical and Computer Engineering Dept. Iowa State University

ISBN: (纸本)9781467380416

关键词： Branch and Bound mixed integer non linear programming Multiple contingency Reactive power planning Power system planning Reactive power contingency Power system security encapsulating Planning process optimal allocation Variance Power quality Computers

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