A hierarchical optimization model for energy data flow in smart grid power systems. (October 2015)
- Record Type:
- Journal Article
- Title:
- A hierarchical optimization model for energy data flow in smart grid power systems. (October 2015)
- Main Title:
- A hierarchical optimization model for energy data flow in smart grid power systems
- Authors:
- Jarrah, Moath
Jaradat, Manar
Jararweh, Yaser
Al-Ayyoub, Mahmoud
Bousselham, Abdelkader - Abstract:
- 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. Abstract : Highlights: We examine the three scopes of smart grid systems. We write mathematical models to cover the different aspects in SG. We use linear optimization toAbstract: 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. Abstract : Highlights: We examine the three scopes of smart grid systems. We write mathematical models to cover the different aspects in SG. We use linear optimization to solve the equations and yield optimal solutions. Hierarchical method achieves better distribution and cooperative scenario. … (more)
- Is Part Of:
- Information systems. Volume 53(2015)
- Journal:
- Information systems
- Issue:
- Volume 53(2015)
- Issue Display:
- Volume 53, Issue 2015 (2015)
- Year:
- 2015
- Volume:
- 53
- Issue:
- 2015
- Issue Sort Value:
- 2015-0053-2015-0000
- Page Start:
- 190
- Page End:
- 200
- Publication Date:
- 2015-10
- Subjects:
- Smart grid -- Central power management -- Linear programming -- Renewable energy -- Energy storage
Database management -- Periodicals
Electronic data processing -- Periodicals
Bases de données -- Gestion -- Périodiques
Informatique -- Périodiques
Database management
Electronic data processing
Periodicals
005.7 - Journal URLs:
- http://www.sciencedirect.com/science/journal/03064379 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.is.2014.12.003 ↗
- Languages:
- English
- ISSNs:
- 0306-4379
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 4496.367300
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 6668.xml