Optimal economic schedule for a network of microgrids with hybrid energy storage system using distributed model predictive control
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Date
2018Subject
Distributed control, energy management, network operating systemsMETS:
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In this paper, an optimal procedure for the economic schedule of a network of interconnected microgrids with hybrid energy storage system is carried out through a control algorithm based on distributed model predictive control (DMPC). The algorithm is specifically designed according to the criterion of improving the cost function of each microgrid acting as a single system through the network mode operation. The algorithm allows maximum economical benefit of the microgrids, minimizing the degradation causes of each storage system, and fulfilling the different system constraints. In order to capture both continuous/discrete dynamics and switching between different operating conditions, the plant is modeled with the framework of mixed logic dynamic. The DMPC problem is solved with the use of mixed integer linear programming using a piecewise formulation, in order to linearize a mixed integer quadratic programming problem.
Description
The publication was pioneering in the optimization of interconnected microgrids with hybrid energy storage, especially in providing a formulation for non-cooperative microgrids that only share energy if it results in a more advantageous situation than operating without sharing energy. Similarly, it solves the problem of formulating MIQQ (Mixed Integer Quadratic Programming with Quadratic Constraints) problems by introducing a piecewise linearization technique using segments that activate the quadratic constraints and approximate them to a piecewise linear function