A Hierarchical Algorithm for Vehicle-to-Grid Integration under Line Capacity Constraints

This work deals with the coordinated charging/discharging of a population of plug-in electric vehicles (PEVs) under energy efficiency, SOC, battery capacity, and power-line capacity constraints, to minimize energy cost. To address this, we introduce a framework in which the power grid is modeled as...

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Vydáno v:European journal of control Ročník 47; s. 53 - 63
Hlavní autoři: Cortés, Andres, Martínez, Sonia
Médium: Journal Article
Jazyk:angličtina
Vydáno: Philadelphia Elsevier Ltd 01.05.2019
Elsevier Limited
Témata:
Algorithms
Batteries
Capacity Constraints
Computational geometry
Computer simulation
Convergence
Convexity
Demand
Electric vehicle charging
Electric Vehicles
Energy conservation
Energy conversion efficiency
Energy costs
Energy management
Hierarchical optimization
Nodes
Optimization
Power efficiency
Power management
Transactive Energy
Upper bounds
Vehicle-to-grid
Capacity Constraints
Hierarchical optimization
Transactive Energy
Electric Vehicles
ISSN:0947-3580, 1435-5671
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Shrnutí:This work deals with the coordinated charging/discharging of a population of plug-in electric vehicles (PEVs) under energy efficiency, SOC, battery capacity, and power-line capacity constraints, to minimize energy cost. To address this, we introduce a framework in which the power grid is modeled as an undirected rooted tree, the root of this tree represents the generation/transmission side of the system and the leaves represent PEVs. Due to the several constraints, we are led to a non-convex optimization problem formulation subject to a complementarity constraint. We then show how a relaxed version of the problem can capture a wide set of optimal solutions for the original problem. After this, we propose a hierarchical algorithm for the computation of the PEVs’ charging/discharging profiles based on the relaxed problem formulation. The root generates a control signal based on the price per unit of power according to the demand for each time. Intermediate nodes represent congestible elements on the distribution side (e.g., transformers), which have a bound on the demand they can satisfy. In the proposed algorithm, intermediate nodes modify the control signal according to the difference between the demand they take care of, and its capacity upper bound. PEVs update their charging/discharging strategies according to this pricing signal. A proof of algorithm convergence to the optimizer of the problem is provided. Simulations demonstrate the algorithm performance and convergence rate.
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ISSN:0947-3580
1435-5671
DOI:10.1016/j.ejcon.2018.07.003