Abstract
Environmental concerns and high prices of fossil fuels increase the feasibility of using renewable energy sources in smart grid. Smart grid technologies are currently being developed to provide efficient and clean power systems. Communication in smart grid allows different components to collaborate and exchange information. Traditionally, the utility company uses a central management unit to schedule energy generation, distribution, and consumption. Using centralized management in a very large scale smart grid forms a single point of failure and leads to serious scalability issues in terms of information delivery and processing. In this paper, a three-level hierarchical optimization approach is proposed to solve scalability, computational overhead, and minimize daily electricity cost through maximizing the used percentage of renewable energy. At level one, a single home or a group of homes are combined to form an optimized power entity (OPE) that satisfies its load demand from its own renewable energy sources (RESs). At level two, a group of OPEs satisfies energy requirements of all OPEs within the group. At level three, excess in renewable energy from different groups along with the energy from the grid is used to fulfill unsatisfied demands and the remaining energy are sent to storage devices.
| Original language | English |
|---|---|
| Pages (from-to) | 190-200 |
| Number of pages | 11 |
| Journal | Information Systems |
| Volume | 53 |
| DOIs | |
| Publication status | Published - 1 Oct 2015 |
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Keywords
- Central power management
- Energy storage
- Linear programming
- Renewable energy
- Smart grid
ASJC Scopus subject areas
- Hardware and Architecture
- Information Systems
- Software
Cite this
A hierarchical optimization model for energy data flow in smart grid power systems. / Jarrah, Moath; Jaradat, Manar; Jararweh, Yaser; Al-Ayyoub, Mahmoud; Bousselham, Abdelkader.
In: Information Systems, Vol. 53, 01.10.2015, p. 190-200.Research output: Contribution to journal › Article
}
TY - JOUR
T1 - A hierarchical optimization model for energy data flow in smart grid power systems
AU - Jarrah, Moath
AU - Jaradat, Manar
AU - Jararweh, Yaser
AU - Al-Ayyoub, Mahmoud
AU - Bousselham, Abdelkader
PY - 2015/10/1
Y1 - 2015/10/1
N2 - Environmental concerns and high prices of fossil fuels increase the feasibility of using renewable energy sources in smart grid. Smart grid technologies are currently being developed to provide efficient and clean power systems. Communication in smart grid allows different components to collaborate and exchange information. Traditionally, the utility company uses a central management unit to schedule energy generation, distribution, and consumption. Using centralized management in a very large scale smart grid forms a single point of failure and leads to serious scalability issues in terms of information delivery and processing. In this paper, a three-level hierarchical optimization approach is proposed to solve scalability, computational overhead, and minimize daily electricity cost through maximizing the used percentage of renewable energy. At level one, a single home or a group of homes are combined to form an optimized power entity (OPE) that satisfies its load demand from its own renewable energy sources (RESs). At level two, a group of OPEs satisfies energy requirements of all OPEs within the group. At level three, excess in renewable energy from different groups along with the energy from the grid is used to fulfill unsatisfied demands and the remaining energy are sent to storage devices.
AB - Environmental concerns and high prices of fossil fuels increase the feasibility of using renewable energy sources in smart grid. Smart grid technologies are currently being developed to provide efficient and clean power systems. Communication in smart grid allows different components to collaborate and exchange information. Traditionally, the utility company uses a central management unit to schedule energy generation, distribution, and consumption. Using centralized management in a very large scale smart grid forms a single point of failure and leads to serious scalability issues in terms of information delivery and processing. In this paper, a three-level hierarchical optimization approach is proposed to solve scalability, computational overhead, and minimize daily electricity cost through maximizing the used percentage of renewable energy. At level one, a single home or a group of homes are combined to form an optimized power entity (OPE) that satisfies its load demand from its own renewable energy sources (RESs). At level two, a group of OPEs satisfies energy requirements of all OPEs within the group. At level three, excess in renewable energy from different groups along with the energy from the grid is used to fulfill unsatisfied demands and the remaining energy are sent to storage devices.
KW - Central power management
KW - Energy storage
KW - Linear programming
KW - Renewable energy
KW - Smart grid
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U2 - 10.1016/j.is.2014.12.003
DO - 10.1016/j.is.2014.12.003
M3 - Article
AN - SCOPUS:84933674544
VL - 53
SP - 190
EP - 200
JO - Information Systems
JF - Information Systems
SN - 0306-4379
ER -