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1068 full-text articles. Page 1 of 33.

Toward Scalable Stochastic Unit Commitment. Part 2: Solver Configuration And Performance Assessment, Kwok Cheung, Dinakar Gade, Cesar Silva-Monroy, Sarah M. Ryan, Jean-Paul Watson, Roger Wets, David L. Woodruff 2017 Alstom Grid

Toward Scalable Stochastic Unit Commitment. Part 2: Solver Configuration And Performance Assessment, Kwok Cheung, Dinakar Gade, Cesar Silva-Monroy, Sarah M. Ryan, Jean-Paul Watson, Roger Wets, David L. Woodruff

Sarah M. Ryan

In this second portion of a two-part analysis of a scalable computa- tional approach to stochastic unit commitment, we focus on solving stochastic mixed-integer programs in tractable run-times. Our solution technique is based on Rockafellar and Wets' progressive hedging algorithm, a scenario-based decomposi- tion strategy for solving stochastic programs. To achieve high-quality solutions in tractable run-times, we describe critical, novel customizations of the progressive hedging algorithm for stochastic unit commitment. Using a variant of the WECC- 240 test case with 85 thermal generation units, we demonstrate the ability of our approach to solve realistic, moderate-scale stochastic unit commitment problems with ...


Optimal Replacement In The Proportional Hazards Model With Semi-Markovian Covariate Process And Continuous Monitoring, Xiang Wu, Sarah M. Ryan 2017 Iowa State University

Optimal Replacement In The Proportional Hazards Model With Semi-Markovian Covariate Process And Continuous Monitoring, Xiang Wu, Sarah M. Ryan

Sarah M. Ryan

Motivated by the increasing use of condition monitoring technology for electrical transformers, this paper deals with the optimal replacement of a system having a hazard function that follows the proportional hazards model with a semi-Markovian covariate process, which we assume is under continuous monitoring. Although the optimality of a threshold replacement policy to minimize the long-run average cost per unit time was established previously in a more general setting, the policy evaluation step in an iterative algorithm to identify optimal threshold values poses computational challenges. To overcome them, we use conditioning to derive an explicit expression of the objective in ...


Statistical Metrics For Assessing The Quality Of Wind Power Scenarios For Stochastic Unit Commitment, Didem Sari, Youngrok Lee, Sarah M. Ryan, David L. Woodruff 2017 Iowa State University

Statistical Metrics For Assessing The Quality Of Wind Power Scenarios For Stochastic Unit Commitment, Didem Sari, Youngrok Lee, Sarah M. Ryan, David L. Woodruff

Sarah M. Ryan

In power systems with high penetration of wind generation, probabilistic scenarios are generated for use in stochastic formulations of day-ahead unit commitment problems. To minimize the expected cost, the wind power scenarios should accurately represent the stochastic process for available wind power. We employ some statistical evaluation metrics to assess whether the scenario set possesses desirable properties that are expected to lead to a lower cost in stochastic unit commitment. A new mass transportation distance rank histogram is developed for assessing the reliability of unequally likely scenarios. Energy scores, rank histograms and Brier scores are applied to alternative sets of ...


Toward Scalable Stochastic Unit Commitment. Part 1: Load Scenario Generation, Yonghan Feng, Ignacio Rios, Sarah M. Ryan, Kai Spurkel, Jean-Paul Watson, Roger Wets, David L. Woodruff 2017 Iowa State University

Toward Scalable Stochastic Unit Commitment. Part 1: Load Scenario Generation, Yonghan Feng, Ignacio Rios, Sarah M. Ryan, Kai Spurkel, Jean-Paul Watson, Roger Wets, David L. Woodruff

Sarah M. Ryan

Unit commitment decisions made in the day-ahead market and during subsequent reliability assessments are critically based on forecasts of load. Tra- ditional, deterministic unit commitment is based on point or expectation-based load forecasts. In contrast, stochastic unit commitment relies on multiple load sce- narios, with associated probabilities, that in aggregate capture the range of likely load time-series. The shift from point-based to scenario-based forecasting necessi- tates a shift in forecasting technologies, to provide accurate inputs to stochastic unit commitment. In this paper, we discuss a novel scenario generation method- ology for load forecasting in stochastic unit commitment, with application to ...


Scenario Construction And Reduction Applied To Stochastic Power Generation Expansion Planning, Yonghan Feng, Sarah M. Ryan 2017 Iowa State University

Scenario Construction And Reduction Applied To Stochastic Power Generation Expansion Planning, Yonghan Feng, Sarah M. Ryan

Sarah M. Ryan

A challenging aspect of applying stochastic programming in a dynamic setting is to construct a set of discrete scenarios that well represents multivariate stochastic processes for uncertain parameters. Often this is done by generating a scenario tree using a statistical procedure and then reducing its size while maintaining its statistical properties. In this paper, we test a new scenario reduction heuristic in the context of long-term power generation expansion planning. We generate two different sets of scenarios for future electricity demands and fuel prices by statistical extrapolation of long-term historical trends. The cardinality of the first set is controlled by ...


Obtaining Lower Bounds From The Progressive Hedging Algorithm For Stochastic Mixed-Integer Programs, Dinakar Gade, Gabriel Hackebeil, Sarah M. Ryan, Jean-Paul Watson, Roger J-B Wets, David L. Woodruff 2017 Sabre Holdings

Obtaining Lower Bounds From The Progressive Hedging Algorithm For Stochastic Mixed-Integer Programs, Dinakar Gade, Gabriel Hackebeil, Sarah M. Ryan, Jean-Paul Watson, Roger J-B Wets, David L. Woodruff

Sarah M. Ryan

We present a method for computing lower bounds in the progressive hedging algorithm (PHA) for two-stage and multi-stage stochastic mixed-integer programs. Computing lower bounds in the PHA allows one to assess the quality of the solutions generated by the algorithm contemporaneously. The lower bounds can be computed in any iteration of the algorithm by using dual prices that are calculated during execution of the standard PHA. We report computational results on stochastic unit commitment and stochastic server location problem instances, and explore the relationship between key PHA parameters and the quality of the resulting lower bounds.


Optimal Price And Quantity Of Refurbished Products, Jumpol Vorasayan, Sarah M. Ryan 2017 Iowa State University

Optimal Price And Quantity Of Refurbished Products, Jumpol Vorasayan, Sarah M. Ryan

Sarah M. Ryan

Many retail product returns can be refurbished and resold, typically at a reduced price. The price set for the refurbished products affects the demands for both new and refurbished products, while the refurbishment and resale activities incur costs. To maximize profit, a manufacturer in a competitive market must carefully choose the proportion of returned products to refurbish and their sale price. We model the sale, return, refurbishment, and resale processes in an open queueing network and formulate a mathematical program to find the optimal price and proportion to refurbish. Examination of the optimality conditions reveals the different situations in which ...


Temporal Vs. Stochastic Granularity In Thermal Generation Capacity Planning With Wind Power, Shan Jin, Audun Botterud, Sarah M. Ryan 2017 Iowa State University

Temporal Vs. Stochastic Granularity In Thermal Generation Capacity Planning With Wind Power, Shan Jin, Audun Botterud, Sarah M. Ryan

Sarah M. Ryan

We propose a stochastic generation expansion model, where we represent the long-term uncertainty in the availability and variability in the weekly wind pattern with multiple scenarios. Scenario reduction is conducted to select a representative set of scenarios for the long-term wind power uncertainty. We assume that the short-term wind forecast error induces an additional amount of operating reserves as a predefined fraction of the wind power forecast level. Unit commitment (UC) decisions and constraints for thermal units are incorporated into the expansion model to better capture the impact of wind variability on the operation of the system. To reduce computational ...


Total Wip And Wip Mix For A Conwip Controlled Job Shop, Sarah M. Ryan, F. Fred Choobineh 2017 Iowa State University

Total Wip And Wip Mix For A Conwip Controlled Job Shop, Sarah M. Ryan, F. Fred Choobineh

Sarah M. Ryan

A planning procedure to set the constant level of Work-In-Process (WIP) for each product type in a job shop operated under CONWIP control is developed. We model the job shop as a single chain multiple class closed queuing network. Given a specified product mix and a total WIP, a nonlinear program bounds the throughput of the network and optimizes the WIP mix. We identify the minimum total WIP that is guaranteed to yield throughput near the maximum possible for the specified product mix and set individual WIP levels by multiplying the optimal WIP mix proportions by the minimum total WIP ...


Robust Design Of A Closed-Loop Supply Chain Network For Uncertain Carbon Regulations And Random Product Flows, Nan Gao, Sarah M. Ryan 2017 Iowa State University

Robust Design Of A Closed-Loop Supply Chain Network For Uncertain Carbon Regulations And Random Product Flows, Nan Gao, Sarah M. Ryan

Sarah M. Ryan

This paper addresses a multi-period capacitated closed-loop supply chain (CLSC) network design problem subject to uncertainties in the demands and returns as well as the potential carbon emission regulations. Two promising regulatory policy settings are considered: namely, (a) a carbon cap and trade system, or (b) a tax on the amount of carbon emissions. A traditional CLSC network design model using stochastic programming is extended to integrate robust optimization to account for regulations of the carbon emissions caused by transportation. We propose a hybrid model to account for both regulatory policies and derive tractable robust counterparts under box and ellipsoidal ...


Reliability Of Wind Power Scenarios And Stochastic Unit Commitment Cost, Didem Sari, Sarah M. Ryan 2017 Iowa State University

Reliability Of Wind Power Scenarios And Stochastic Unit Commitment Cost, Didem Sari, Sarah M. Ryan

Sarah M. Ryan

Probabilistic wind power scenarios constitute a crucial input for stochastic day-ahead unit commitment in power systems with deep penetration of wind generation. To minimize the expected cost, the scenario time series of wind power amounts available should accurately represent the stochastic process for available wind power as it is estimated on the day ahead. The high computational demands of stochastic programming motivate a search for ways to evaluate scenarios without extensively simulating the stochastic unit commitment procedure. Reliability of wind power scenario sets can be assessed by statistical verification approaches. In this study, we examine the relationship between the statistical ...


Value Of Condition Monitoring For Optimal Replacement In The Proportional Hazards Model With Continuous Degradation, Xiang Wu, Sarah M. Ryan 2017 Iowa State University

Value Of Condition Monitoring For Optimal Replacement In The Proportional Hazards Model With Continuous Degradation, Xiang Wu, Sarah M. Ryan

Sarah M. Ryan

This article investigates the value of perfect monitoring information for optimal replacement of deteriorating systems in the Proportional Hazards Model (PHM). A continuous-time Markov chain describes the condition of the system. Although the form of an optimal replacement policy for system under periodic monitoring in the PHM was developed previously, an approximation of the Markov process as constant within inspection intervals led to a counter intuitive result that less frequent monitoring could yield a replacement policy with lower average cost. This article explicitly accounts for possible state transitions between inspection epochs to remove the approximation and eliminate the cost anomaly ...


Welfare Effects Of Expansions In Equilibrium Models Of An Electricity Market With Fuel Network, Sarah M. Ryan, Anthony Downward, Andrew Philpott, Golbon Zakeri 2017 Iowa State University

Welfare Effects Of Expansions In Equilibrium Models Of An Electricity Market With Fuel Network, Sarah M. Ryan, Anthony Downward, Andrew Philpott, Golbon Zakeri

Sarah M. Ryan

The welfare of electricity producers and consumers depends on congestion in the transmission grid, generation costs that consist mainly of fuel costs, and strategic behavior. We formulate a game theoretic model of an oligopolistic electricity market where generation costs are derived from a fuel supply network. The game consists of a fuel dispatcher that transports fuels at minimum cost to meet generator demands, generators that maximize profit in Cournot competition, and an independent system operator (ISO) that sets nodal prices to balance electricity supply with linear demand functions. We prove the existence of an equilibrium. If fuel supplies are unlimited ...


Impact Of Demand Response On Thermal Generation Investment With High Wind Penetration, Shan Jin, Audun Botterud, Sarah M. Ryan 2017 Iowa State University

Impact Of Demand Response On Thermal Generation Investment With High Wind Penetration, Shan Jin, Audun Botterud, Sarah M. Ryan

Sarah M. Ryan

We present a stochastic programming model for investments in thermal generation capacity to study the impact of demand response (DR) at high wind penetration levels. The investment model combines continuous operational constraints and wind scenarios to represent the implications of wind variability and uncertainty at the operational level. DR is represented in terms of linear price-responsive demand functions. A numerical case study based on load and wind profiles of Illinois is constructed with 20 candidate generating units of various types. Numerical results show the impact of DR on both investment and operational decisions. We also propose a model in which ...


Joint Optimization Of Asset And Inventory Management In A Product–Service System, Xiang Wu, Sarah M. Ryan 2017 Iowa State University

Joint Optimization Of Asset And Inventory Management In A Product–Service System, Xiang Wu, Sarah M. Ryan

Sarah M. Ryan

We propose an integrated model of the asset management decisions for a fleet of identical product units and the inventory management decisions for a closed-loop supply chain in the context of a product-service system, in which the two types of decisions are closely coupled. A joint optimization technique is developed to obtain the parameters of the operational policy for the integrated model that minimize the long run average cost rate. A numerical example is provided to illustrate the computational procedures. In addition, the effect of a simplifying assumption that the replaced products have no quality difference is evaluated and the ...


On The Validity Of The Geometric Brownian Motion Assumption, Rahul Ratnakar Marathe, Sarah M. Ryan 2017 Iowa State University

On The Validity Of The Geometric Brownian Motion Assumption, Rahul Ratnakar Marathe, Sarah M. Ryan

Sarah M. Ryan

The geometric Brownian motion (GBM) process is frequently invoked as a model for such diverse quantities as stock prices, natural resource prices and the growth in demand for products or services. We discuss a process for checking whether a given time series follows the GBM process. Methods to remove seasonal variation from such a time series are also analyzed. Of four industries studied, the historical time series for usage of established services meet the criteria for a GBM; however, the data for growth of emergent services do not.


Hybrid Robust And Stochastic Optimization For Closed-Loop Supply Chain Network Design Using Accelerated Benders Decomposition, Esmaeil Keyvanshokooh, Sarah M. Ryan, Elnaz Kabir 2017 University of Michigan-Ann Arbor

Hybrid Robust And Stochastic Optimization For Closed-Loop Supply Chain Network Design Using Accelerated Benders Decomposition, Esmaeil Keyvanshokooh, Sarah M. Ryan, Elnaz Kabir

Sarah M. Ryan

Environmental, social and economic concerns motivate the operation of closed-loop supply chain networks (CLSCN) in many industries. We propose a novel profit maximization model for CLSCN design as a mixed-integer linear program in which there is flexibility in covering the proportions of demand satisfied and returns collected based on the firm's policies. Our major contribution is to develop a novel hybrid robust-stochastic programming (HRSP) approach to simultaneously model two different types of uncertainties by including stochastic scenarios for transportation costs and polyhedral uncertainty sets for demands and returns. Transportation cost scenarios are generated using a Latin Hypercube Sampling method ...


Integration Of Progressive Hedging And Dual Decomposition In Stochastic Integer Programs, Ge Guo, Gabriel Hackebeil, Sarah M. Ryan, Jean-Paul Watson, David L. Woodruff 2017 Iowa State University

Integration Of Progressive Hedging And Dual Decomposition In Stochastic Integer Programs, Ge Guo, Gabriel Hackebeil, Sarah M. Ryan, Jean-Paul Watson, David L. Woodruff

Sarah M. Ryan

We present a method for integrating the Progressive Hedging (PH) algorithm and the Dual Decomposition (DD) algorithm of Carøe and Schultz for stochastic mixed-integer programs. Based on the correspondence between lower bounds obtained with PH and DD, a method to transform weights from PH to Lagrange multipliers in DD is found. Fast progress in early iterations of PH speeds up convergence of DD to an exact solution. We report computational results on server location and unit commitment instances.


The Effect Of Technological Improvement On Capacity Expansion For Uncertain Exponential Demand With Lead Times, Dohyun Pak, Nattapol Pornsalnuwat, Sarah M. Ryan 2017 University of Michigan - Ann Arbor

The Effect Of Technological Improvement On Capacity Expansion For Uncertain Exponential Demand With Lead Times, Dohyun Pak, Nattapol Pornsalnuwat, Sarah M. Ryan

Sarah M. Ryan

We formulate a model of capacity expansion that is relevant to a service provider for whom the cost of capacity shortages would be considerable but difficult to quantify exactly. Due to demand uncertainty and a lead time for adding capacity, not all shortages are avoidable. In addition, technological innovations will reduce the cost of adding capacity but may not be completely predictable. Analytical expressions for the infinite horizon expansion cost and shortages are optimized numerically. Sensitivity analyses allow us to determine the impact of technological change on the optimal timing and sizes of capacity expansions to account for economies of ...


Capacity Expansion Under A Service-Level Constraint For Uncertain Demand With Lead Times, Rahul R. Marathe, Sarah M. Ryan 2017 Indian Institute of Technology Madras

Capacity Expansion Under A Service-Level Constraint For Uncertain Demand With Lead Times, Rahul R. Marathe, Sarah M. Ryan

Sarah M. Ryan

For a service provider facing stochastic demand growth, expansion lead times and economies of scale complicate the expansion timing and sizing decisions. We formulate a model to minimize the infinite horizon expected discounted expansion cost under a service-level constraint. The service level is defined as the proportion of demand over an expansion cycle that is satisfied by available capacity. For demand that follows a geometric Brownian motion process, we impose a stationary policy under which expansions are triggered by a fixed ratio of demand to the capacity position, i.e., the capacity that will be available when any current expansion ...


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