A Comparative Study of Optimization- and Rule-Based Control for Microgrid Operation
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Date
2015-01-14
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Abstract
As local renewable energy based generation units
are being deployed worldwide, distribution grids are facing integration
challenges. Here, microgrids provide a solution, by allowing
intentional islanding and connection to the public distribution
grid depending upon its current state. Microgrids may consist of
loads, generation units and storages which can be operated as
a single controllable entity. This paper investigates two control
approaches for cost-efficient operation of grid-connected microgrids:
optimization- and rule-based control. For optimizationbased
control, a model predictive control algorithm with mixed
integer linear programming formulation is used. A case study
for a microgrid in an office building consisting of distributed
generation units and different storage units is presented to assess
the performance of the two control approaches. The simulation
results show the effectiveness of the optimization-based approach
and a potential for lower microgrid operating costs compared to
the rule-based approach.
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Keywords
microgrids, energy storage, model predictive control (MPC), moving horizon control, mixed integer linear programming (MILP), energy management system (EMS), grid-connected