Distributed Conditional Cooperation Model Predictive Control of Interconnected Microgrids
This work addresses the problem of fair and beneficial power exchange among interconnected microgrids for power system operators, but the results are incremental as they extend existing MPC methods with a conditional cooperation mechanism.
The paper proposes a distributed model predictive control strategy for interconnected microgrids that ensures each microgrid benefits from power exchange by including a condition based on islanded operation cost. The approach is validated through a case study, demonstrating performance and computational benefits.
In this paper, we propose a model predictive control based operation strategy that allows for power exchange between interconnected microgrids. Particularly, the approach ensures that each microgrid benefits from power exchange with others. This is realised by including a condition which is based on the islanded operation cost. The overall model predictive control problem is posed as a mixed-integer quadratically-constrained program and solved using a distributed algorithm that iteratively updates continuous and integer variables. For this algorithm, termination, feasibility and computational properties are discussed. The performance and the computational benefits of the proposed strategy are highlighted in an illustrative case study.