Mixed-Integer Convex Optimization for DC Microgrid Droop Control
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Institute of Electrical and Electronics Engineers Inc.
Abstract
Droop control is a viable method for the operation of island DC microgrids in a decentralized architecture. This paper presents a mixed-integer conic optimization formulation for the design of generator droop control, comprising the parameters of a piecewise linear droop curve. The mixed-integer formulation originates from a stochastic optimization framework that considers several operating scenarios for finding the optimal design. The convexity of the mixed-integer problem continuous relaxation gives global optimality guarantees for the design problem. The paper presents computational results using a tight polyhedral approximation of the conic program, leading to a mixed-integer linear programming (MILP) problem that is solved using a state-of-the-art commercial solver. The results from the proposed approach are contrasted with both a classic linear droop control design and a recent piecewise linear formulation. The Monte-Carlo simulation results quantify the extent to which the MILP solution is superior in reducing voltage violations and power loss, and the degree to which the loss is close to that from a conic optimal power flow solution. © 1969-2012 IEEE.
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Keywords
Dc microgrids, Droop control, Optimization methods, Power-sharing, Voltage control, Convex optimization, Curve fitting, Electric load flow, Microgrids, Monte carlo methods, Piecewise linear techniques, Computational results, Continuous relaxation, Decentralized architecture, Mixed integer problems, Mixed-integer linear programming, Optimal power flows, Polyhedral approximation, Stochastic optimizations, Integer programming