Operation Scheduling Optimization for Microgrids Considering Coordination of Their Components
Operation scheduling is one of the most practical optimization problems to efficiently manage the electric power supply and demand in microgrids. Although various microgrid-related techniques have been developed, there has been no established solution to the problem until now. This is because the fo...
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| Published in: | Future internet Vol. 11; no. 11; p. 223 |
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| Format: | Journal Article |
| Language: | English |
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| ISSN: | 1999-5903, 1999-5903 |
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| Abstract | Operation scheduling is one of the most practical optimization problems to efficiently manage the electric power supply and demand in microgrids. Although various microgrid-related techniques have been developed, there has been no established solution to the problem until now. This is because the formulated problem becomes a complicated mixed-integer programming problem having multiple optimization variables. The authors present a framework for this problem and its effective solution to obtain an operation schedule of the microgrid components considering their coordination. In the framework, trading electricity with traditional main power grids is included in the optimization target, and uncertainty originating from variable renewable energy sources is considered. In the solution, the formulated problem is reformulated to reduce the dimensions of its solution space, and, as a result, a combined algorithm of binary particle swarm optimization and quadratic programming is applicable. Through numerical simulations and discussions of their results, the validity of the authors’ proposal is verified. |
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| AbstractList | Operation scheduling is one of the most practical optimization problems to efficiently manage the electric power supply and demand in microgrids. Although various microgrid-related techniques have been developed, there has been no established solution to the problem until now. This is because the formulated problem becomes a complicated mixed-integer programming problem having multiple optimization variables. The authors present a framework for this problem and its effective solution to obtain an operation schedule of the microgrid components considering their coordination. In the framework, trading electricity with traditional main power grids is included in the optimization target, and uncertainty originating from variable renewable energy sources is considered. In the solution, the formulated problem is reformulated to reduce the dimensions of its solution space, and, as a result, a combined algorithm of binary particle swarm optimization and quadratic programming is applicable. Through numerical simulations and discussions of their results, the validity of the authors' proposal is verified. |
| Author | Tuyen, Nguyen Duc Takano, Hirotaka Asano, Hiroshi Goto, Ryota Soe, Thin Zar |
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| Cites_doi | 10.1109/TPWRS.1987.4335130 10.1541/ieejpes.128.388 10.1002/9780470612163 10.1109/TPWRS.2005.860922 10.1109/TPAS.1966.291678 10.1109/TPWRS.2003.821611 10.1080/22348972.2016.1173794 10.1002/eej.22687 10.1016/j.pnsc.2008.03.018 10.1007/b108628 10.1109/59.651636 10.1109/60.222703 10.1007/s11708-013-0240-3 10.1109/59.485989 10.1109/TPWRS.2005.846060 10.1109/TSTE.2015.2497470 10.1002/9781119263739 10.1109/59.801925 10.1109/TPAS.1983.317714 10.1109/TPWRS.2014.2355204 10.1109/TSG.2012.2231440 10.1016/j.tej.2012.09.013 10.1109/TPWRS.2010.2042472 10.1109/ICECE.2018.8636808 10.1016/S0142-0615(98)00013-1 10.1016/j.jare.2016.02.002 10.1109/59.119267 10.3923/ijepe.2012.51.57 10.1109/TPWRS.2003.821472 |
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| SubjectTerms | Algorithms Alternative energy sources binary particle swarm optimization (bpso) Computer simulation Consumption Coordination Distributed generation economic load dispatch (eld) Efficiency Electric power demand Electric power grids Electric power supplies Electricity Electricity distribution Expected values Integer programming Internet microgrids Operation scheduling Optimization Particle swarm optimization Power supply power supply-demand management Quadratic programming quadratic programming (qp) Renewable energy sources Schedules Scheduling Solution space Supply & demand uncertainty unit commitment (uc) Variables |
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