A hierarchical optimization model for energy data flow in smart grid power systems |
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| Affiliation: | 1. School of Computer Engineering, Nanyang Technological University, Singapore;2. Department of Computer Science, Jordan University of Science and Technology, 22110, Jordan;3. Department of Computer Engineering, Jordan University of Science and Technology, 22110, Jordan;4. Qatar Environment and Energy Research Institute, Doha, Qatar;1. Department of Software Engineering, Hashemite University, Zarka, Jordan;2. Department of Computer Science, Colorado State University, USA;3. Department of Computer Information Systems, Colorado State University, USA;1. Centre of Electrical Energy Systems (CEES), Faculty of Electrical Engineering (FKE), Universiti Teknologi Malaysia (UTM), 81310 Skudai, Johor, Malaysia;2. Young Researchers and Elites Club, Saveh Branch, Islamic Azad University, Saveh, Iran;1. SFR NSSS System Design Division, Korea Atomic Energy Research Institute (KAERI), 111, Daedeok-daero 989 Beon-gil, Yuseong-gu, Daejeon 305-353, South Korea;2. Automotive Components and Materials R&D Group, Korea Institute of Industrial Technology (KITECH), 6 Cheomdan-gwagiro 208 beon-gil, Buk-gu, Gwangju 500-408, South Korea;3. School of Mechatronics, Gwangju Institute of Science and Technology (GIST), 123 Cheomdan-gwagiro, Buk-gu, Gwangju 500-712, South Korea;1. The School of Electrical Engineering and Computer Science, University of Ottawa, 25 Templeton Ave., Ottawa K1N 6X1, Canada;2. Telfer School of Management, University of Ottawa, 55 Laurier Ave. E, Ottawa K1N 6N5, Canada |
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| 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. |
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| Keywords: | Smart grid Central power management Linear programming Renewable energy Energy storage |
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