Maestro: A Python library for multi-carrier energy district optimal control design

TL;DR

Maestro is a Python library that simplifies the design and testing of predictive controllers for multi-carrier energy networks, enabling non-experts to optimize energy dispatch and costs.

Contribution

The paper introduces Maestro, a user-friendly Python library for modeling and controlling multi-carrier energy networks using mixed-integer linear programming.

Findings

Enables non-expert users to model complex energy networks.

Supports multiple energy carriers and components.

Facilitates simulation and optimization of energy dispatch.

Abstract

This paper introduces the Maestro library. This library for Python focuses on the design of predictive controllers for small to medium-scale energy networks. It allows non-expert users to describe multi-carrier (electricity, heat, gas) energy networks with a range of energy production, conversion, and storage component classes; together with consumption patterns. Based on this description a predictive controller can be synthesized and tested in simulation. This controller manages the dispatch of energy in the network, making sure that the demands are met, while minimizing the total energy cost. Alternative objectives can be specified. The library uses a mixed-integer linear modelling framework to describe the network and can be used in stand-alone based on standardized input files or as part of the larger energy network control platform PENTAGON.