A Predictive Operation Controller for an Electro-Thermal Microgrid Utilizing Variable Flow Temperatures

TL;DR

This paper introduces a model predictive control strategy for electro-thermal microgrids that leverages variable flow temperatures to enhance flexibility and optimize operation, explicitly utilizing the thermal network's storage capacity.

Contribution

It presents a novel control approach that integrates a multi-layer network model with variable flow temperatures, enabling more flexible and efficient microgrid management.

Findings

Improved operational flexibility through variable flow temperature control.

Effective optimization of thermal and electrical layers in microgrids.

Validated control scheme via numerical case study.

Abstract

We propose an optimal operation control strategy for an electro-thermal microgrid. Compared to existing work, our approach increases flexibility by operating the thermal network with variable flow temperatures and in that way explicitly exploits its inherent storage capacities. To this end, the microgrid is represented by a multi-layer network composed of an electrical and a thermal layer. We show that the system behavior can be represented by a discrete-time state model derived from DC power flow approximations and 1d incompressible Euler equations. Both layers are interconnected via heat pumps. By combining this model with desired operating objectives and constraints, we obtain a constrained convex optimization problem. This is used to derive a model predictive control scheme for the optimal operation of electro-thermal microgrids. The performance of the proposed operation control algorithm is demonstrated in a numerical case study.