Optimal Energy Management for IoT Connected Microgrid using MILP
Mabrouk, Ahmed (2024)
2024
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2024060119649
https://urn.fi/URN:NBN:fi:amk-2024060119649
Tiivistelmä
In this Master's thesis work, I had the honor to take part in implementing an energy optimization solution. The thesis work had as a goal to optimize the energy consumption for one of the greatest exhibitions in Vaasa region: Meteoria of Soderfjarden which is located in Sundom village. The implemented solution was developed to make the Meteoria Microgrid as autonomous in consumption as in energy generation from renewable sources. The Meteoria of Soderfjarden has already many options for generating electricity while taking advantage of wind and solar potential of Vaasa region.
The software solution was designed to solve a linear programming problem that had the objective of reducing fuel consumption. To achieve this, different software and frameworks were involved and taking advantage of the existing Novia IoT platform to collect the needed information for further computation during the optimization problem solving to find the possible optimal solutions. Following to the solution development, a visualization dashboard of the results of this optimization was tested in real-time which was then published in the novia broker as well as the command values. The optimal values resulting from the MILP solving were then populated through the MQTT agent and the graphs accordingly.
The main optimization work was developed using PuLp framework and using Gurrobi as an agent solver. The MQTT agent was developed using Paho, Flask, and Plotly and was incorporated to visualize results in the form of a real-time dashboard. The resulting work is a model and a complete data storage system that can be depicted under the Novia MQTT platform to govern in real-time the energy inputs and outputs while fostering the use of energy storage and taking advantage of green resources to minimize fuel generator consumption.
The software solution was designed to solve a linear programming problem that had the objective of reducing fuel consumption. To achieve this, different software and frameworks were involved and taking advantage of the existing Novia IoT platform to collect the needed information for further computation during the optimization problem solving to find the possible optimal solutions. Following to the solution development, a visualization dashboard of the results of this optimization was tested in real-time which was then published in the novia broker as well as the command values. The optimal values resulting from the MILP solving were then populated through the MQTT agent and the graphs accordingly.
The main optimization work was developed using PuLp framework and using Gurrobi as an agent solver. The MQTT agent was developed using Paho, Flask, and Plotly and was incorporated to visualize results in the form of a real-time dashboard. The resulting work is a model and a complete data storage system that can be depicted under the Novia MQTT platform to govern in real-time the energy inputs and outputs while fostering the use of energy storage and taking advantage of green resources to minimize fuel generator consumption.