Stochastic-based scheduling of the microgrid operation including wind turbines, photovoltaic cells, energy storages and responsive loads

Microgrids with different technologies in distributed generations (DGs), different control facilities and power electronic interfaces require proper management and operation strategies. In these strategies, in order to reach the optimum scheduling, the stochastic nature of some decision variables sh...

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Veröffentlicht in:IET generation, transmission & distribution Jg. 9; H. 12; S. 1498 - 1509
Hauptverfasser: Talari, Saber, Yazdaninejad, Mohsen, Haghifam, Mahmoud-Reza
Format: Journal Article
Sprache:Englisch
Veröffentlicht: The Institution of Engineering and Technology 04.09.2015
Schlagworte:
Computer simulation
demand response
demand side management
DG dispatch
Distributed generation
distributed power generation
economic efficiency
Energy storage
integer programming
linear programming
linear two‐stage stochastic model
load curtailment
Mathematical models
microgrid operation
mixed‐integer linear programming
Monte Carlo methods
Monte Carlo simulation
photovoltaic cell
photovoltaic power systems
power electronic interface
power generation dispatch
power generation economics
power generation scheduling
renewable energy source
RES availability
Scheduling
solar cells
stochastic processes
stochastic scheduling
stochastic variable computation module
Stochasticity
Strategy
Uncertainty
wind turbine
wind turbines
integer programming
wind turbine
linear programming
distributed power generation
linear two-stage stochastic model
power generation scheduling
RES availability
power generation economics
Monte Carlo methods
DG dispatch
energy storage
stochastic variable computation module
stochastic processes
load curtailment
photovoltaic power systems
photovoltaic cell
microgrid operation
stochastic scheduling
economic efficiency
power generation dispatch
distributed generation
mixed-integer linear programming
wind turbines
demand side management
solar cells
power electronic interface
Monte Carlo simulation
renewable energy source
demand response
ISSN:1751-8687, 1751-8695
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Zusammenfassung:Microgrids with different technologies in distributed generations (DGs), different control facilities and power electronic interfaces require proper management and operation strategies. In these strategies, in order to reach the optimum scheduling, the stochastic nature of some decision variables should be considered. Subsequently, it will lead to a decrease in the forced load curtailment and an increase in the economic efficiency from the perspective of both the maingrid and the microgrid owner. In this study, the availability of dispatchable DGs, energy storage, renewable energy sources (RESs) and the maingrid as well as the power generation of RESs and load are studied through their uncertainty natures. For dealing with these uncertainties, stochastic variables computation module is designed which generates several scenarios by Monte Carlo simulation at each hour. The microgrid operation is optimised in uncertainty environment through a linear two-stage stochastic model. The stochastic scheduling model which is solved by mixed-integer linear programming is compared with a deterministic model through three different cases in presence of demand response on a sample microgrid. The results explicitly show benefits of the proposed stochastic model since it provides accuracy in scheduling and decreases the operation cost.
Bibliographie:Now also with IAEW (Institue of Power Systems and Power Economics), RWTH Aachen University, Aachen, Germany, as Alexander von Humboldt Research Fellow
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ISSN:1751-8687
1751-8695
DOI:10.1049/iet-gtd.2014.0040