- Permanent Link:
- https://ufdc.ufl.edu/UFE0049134/00001
Material Information
- Title:
- Stochastic Optimization and Control with Applications in PHEV and Inventory Management
- Creator:
- Wei, Lai
- Place of Publication:
- [Gainesville, Fla.]
Florida
- Publisher:
- University of Florida
- Publication Date:
- 2015
- Language:
- english
- Physical Description:
- 1 online resource (315 p.)
Thesis/Dissertation Information
- Degree:
- Doctorate ( Ph.D.)
- Degree Grantor:
- University of Florida
- Degree Disciplines:
- Industrial and Systems Engineering
- Committee Chair:
- GUAN,YONGPEI
- Committee Co-Chair:
- GEUNES,JOSEPH PATRICK
- Committee Members:
- RICHARD,JEAN-PHILIPPE P
CARRILLO,JANICE ELLEN
- Graduation Date:
- 8/8/2015
Subjects
- Subjects / Keywords:
- Carrying costs ( jstor )
Cost control ( jstor )
Cost functions ( jstor )
Electricity ( jstor )
Inventory control ( jstor )
Market prices ( jstor )
Optimal control ( jstor )
Optimal policy ( jstor )
Prices ( jstor )
Search services ( jstor )
Industrial and Systems Engineering -- Dissertations, Academic -- UF
impulse -- inventory -- phev
- Genre:
- bibliography ( marcgt )
theses ( marcgt )
government publication (state, provincial, terriorial, dependent) ( marcgt )
born-digital ( sobekcm )
Electronic Thesis or Dissertation
Industrial and Systems Engineering thesis, Ph.D.
Notes
- Abstract:
- In this dissertation, we address problems related to electricity storage control policies to manage charging and discharging activities for plug-in hybrid electric vehicles. We start with the trading strategies for plug-in hybrid electric vehicles in day-ahead and real-time markets. For this topic, we first develop models for both risk-neutral and risk-averse aggregators to participate only in a real-time market. The proposed models capture the impact of the charging and discharging activities on real-time electricity prices. Then, we extend our study to the case in which aggregators participate in both the real-time and day-ahead markets. For each developed model,
we analyze the properties of the optimal objective value function, prove the existence and uniqueness of the optimal policy, and explore the corresponding optimal policy structure. Moreover, through numerical studies, we explore insights on how electricity prices are influenced by charging and discharging activities. In particular, we observe that aggregated charging/discharging activities with market-impact consideration could reduce the variance of the real-time electricity prices more efficiently, as compared to individual activities. In addition, considering market impact, an aggregator tends to use less electricity storage. Finally, it is beneficial to let an aggregator control the electricity storage and participate in both the real-time and day-ahead markets, instead of participating only in the real-time market.
Then, we study the electricity storage control policies for electricity reserve markets. We start with general inventory control models. We explore the optimal inventory control problem where the inventory evolves as a Brownian motion and each order has to be integral times of a fixed quantity. Under the assumption that the holding and penalty costs are convex functions, we prove that the (R,Q) policy is optimal and we further provide explicit expressions of R and Q. We also provide more general verification theorems that can be used to verify the guessed function is the optimal value function for a general class of stochastic inventory control problems.
Next, we study the Brownian inventory control problem where the inventory can be both increased and decreased by integer times of a fixed based quantity Q. Under
reasonable assumptions, we prove that the optimal control policy is an (S,D,Q) policy and provide explicit expressions of S, D, and the value function.
Furthermore, we study the Brownian inventory control problem with piecewise linear concave control cost. The objective is to derive a control policy to minimize the discounted total costs including holding cost and control costs. We show that, depending on the basic parameters, the optimal policy is either an (s, S) policy or a new type of policy which is different from traditional ones. The new policy looks like a combination of two (s, S) policies with two waiting areas. The challenging part is to prove the existence and uniqueness of the smooth solution for a free boundary problem associated with one waiting area.
Finally, we discuss how to optimally control the PHEV battery storage in electricity reserve market based on the results obtained in stochastic inventory control model. ( en )
- General Note:
- In the series University of Florida Digital Collections.
- General Note:
- Includes vita.
- Bibliography:
- Includes bibliographical references.
- Source of Description:
- Description based on online resource; title from PDF title page.
- Source of Description:
- This bibliographic record is available under the Creative Commons CC0 public domain dedication. The University of Florida Libraries, as creator of this bibliographic record, has waived all rights to it worldwide under copyright law, including all related and neighboring rights, to the extent allowed by law.
- Thesis:
- Thesis (Ph.D.)--University of Florida, 2015.
- Local:
- Adviser: GUAN,YONGPEI.
- Local:
- Co-adviser: GEUNES,JOSEPH PATRICK.
- Electronic Access:
- RESTRICTED TO UF STUDENTS, STAFF, FACULTY, AND ON-CAMPUS USE UNTIL 2016-08-31
- Statement of Responsibility:
- by Lai Wei.
Record Information
- Source Institution:
- UFRGP
- Rights Management:
- Applicable rights reserved.
- Embargo Date:
- 8/31/2016
- Classification:
- LD1780 2015 ( lcc )
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