IEEE Transactions on Smart Grid · 2016 · 88 citations · 35 references
Distributed Energy SystemEngineeringEnergy EfficiencyIndividual Microgrids/nanogridsDistributed Energy GenerationPower System EconomicsEnergy OptimizationSystems EngineeringRenewable Energy SystemsEnergy NetworkElectrical EngineeringDc MicrogridsMicrogrids/nanogrids Cost VectorPower System OptimizationMicrogridsEnergy System OperationSmart GridEnergy ManagementGrid OptimizationEnergy EconomicsExternal Electricity Grid
A new multi-objective optimization model is proposed for efficient integration of a group of microgrids/nanogrids with local energy storage devices into the power grid. In this model, the individual microgrids/nanogrids can exchange power locally among each other as well as with the external electricity grid. A pricing regime is introduced in which differences in the local and grid buy and sell time-of-use prices of electricity incentivize local inter-microgrid/nanogrid exchanges of power over power exchange with the grid. A novel formulation of a multiple-objective constrained optimization is presented for solving the microgrids/nanogrids energy management problem under the proposed electricity pricing regime. This approach is based on minimization of l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> or l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> distances of the microgrids/nanogrids cost vector to a utopia point in the solution space. Components of the utopia point are defined as the minimum cost achievable by the corresponding microgrid/nanogrid when it always uses the favorable local buy/sell prices. The proposed optimization models are in the form of convex linear/quadratic programs without any binary or integer variables for l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1</sub> /l <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> norms. Results of numerical simulations with on-line rolling horizon optimization of the storage device power flow decisions demonstrate the effectiveness of the proposed methods.
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Hristiyan Kanchev, Di Lu, Frédéric Colas et al. · IEEE Transactions on Industrial Electronics · 2011 · 975 citations · Full text
Distributed Energy System, Electrical Engineering, Operational Planning +13