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Online optimal power management considering electric vehicles, load curtailment and grid trade in a microgrid energy market
Published in Institute of Electrical and Electronics Engineers Inc.
2016
Abstract
This paper proposes an online optimal power management problem for microgrid energy market considering electric vehicle (EV) charging/discharging, load curtailment and grid power transactions. Fuel and emission costs of conventional sources, hourly profits, incentives for load curtailment, revenue/cost of grid power trade and charging/discharging price of electric vehicles (EV) are considered by the microgrid central controller (MGCC) for the dispatch. A realistic model for EV is considered with its state of charge (SOC), age/life, charging/discharging rate limits, trip period and number of switching. Two different objectives of the MGCC viz. operational cost minimization and overall profit maximization are compared in the CIGRE LV benchmark microgrid in terms of revenue, expense, node voltage, curtailed load, EV power, grid trade and overall execution time. Particle swarm optimization with time varying acceleration co-efficient (PSO-TVAC) and modified backward forward sweep (BFS) based optimal power flow (OPF) method is used to optimize the benefits. © 2015 IEEE.
Concepts (25)
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    Battery management systems
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    Commerce
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    Costs
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    Electric load flow
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    Electric machine control
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    Electric power measurement
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    Electric power system control
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    Electric vehicles
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    Energy management
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    Optimization
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    Particle swarm optimization (pso)
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    Power management
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    Power markets
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    Profitability
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    Smart power grids
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    Vehicles
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    ACCELERATION COEFFICIENTS
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    Charging/discharging
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    Cost minimization
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    Demand response
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    Micro grid
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    OPTIMAL POWER FLOWS
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    OVERALL EXECUTION
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    Profit maximization
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    Electric power transmission networks