Download the full-sized PDF of Stochastic Modeling and Optimization for Community Energy Storage SystemsDownload the full-sized PDF



Permanent link (DOI):


Export to: EndNote  |  Zotero  |  Mendeley


This file is in the following communities:

Graduate Studies and Research, Faculty of


This file is in the following collections:

Theses and Dissertations

Stochastic Modeling and Optimization for Community Energy Storage Systems Open Access


Other title
Community Energy Storage System
Smart grid
General Robust Optimization
Type of item
Degree grantor
University of Alberta
Author or creator
Wang, Weiran
Supervisor and department
Jie, Chen (Electrical and Computer Engineering)
Hao, Liang (Electrical and Computer Engineering)
Examining committee member and department
Di, Niu (Electrical and Computer Engineering)
Petr, Musilek (Electrical and Computer Engineering)
Department of Electrical and Computer Engineering
Energy Systems
Date accepted
Graduation date
2017-06:Spring 2017
Master of Science
Degree level
Due to the integration of renewable energy sources such as wind turbines, significant technical challenge exists for the energy management in the future power distribution systems and/or microgrids. The efficiency and reliability of the energy management may be jeopardized by the randomness of the power production from renewable energy sources. In order to address this challenge and to harness renewable power, community energy storage (CES) systems with dispatchable capacities can be installed to buffer the intermittent supply from renewable energy sources In Part I, we focus on the stochastic model of CES system with wind power generation. The power generation of each wind turbine is modeled using a Markov modulated rate process (MMRP), while the CES system is modeled as a queuing system. Based on a diffusion approximation of the queue length, a closed-form representation of the cumulative distribution function (CDF) of the SoC of the CES system can be derived. In Part II, we focus on the optimal energy management of the CES systems in a microgrid. During the normal operation of the microgrid, the dispatchable outputs of the CES systems are controlled to minimize the overall operation cost of the microgrid. When a fault occurs in the main grid, the microgrid operates in an islanded mode, and energy stored in the CES systems can be utilized to supply the loads in the microgrid for reliability improvement. To control the amount of energy stored in the CES systems, two kinds of SoC thresholds are introduced, which correspond to hard reservation and soft reservation of energy. Accordingly, the stochastic model of the CES system developed in Part I is extended to embed the impact of the two kinds of thresholds. To take account of the potential bias in the forecast of wind power generation, the energy management problem is solved based on a general robust optimization technique. The performance of the stochastic model and optimization technique is evaluated based on the IEEE 123 bus test feeder as well as the wind power generation data of Changling Wind Farm.
This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for the purpose of private, scholarly or scientific research. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.
Citation for previous publication

File Details

Date Uploaded
Date Modified
Audit Status
Audits have not yet been run on this file.
File format: pdf (PDF/A, PDF/X)
Mime type: application/pdf
File size: 2570710
Last modified: 2017:06:13 12:23:02-06:00
Filename: Wang_Weiran_201701_MSc.pdf
Original checksum: aea64987959d381f7e975b29513eea9e
Well formed: true
Valid: true
Page count: 73
Activity of users you follow
User Activity Date