Towards a Sustainable, Intelligent, and Energy-autonomous Nanogrid Buildings: a Holistic Systemic Multi-objective Optimization Approach

**Towards a Sustainable, Intelligent, and Energy-Autonomous Nanogrid Buildings: A Holistic Systemic Multi-Objective Optimization Approach**:

- Réf **ABG-131278**
- Sujet de Thèse
- 18/04/2025
- Financement public/privé
- CESI/LINEACT
- Lieu de travail- Brest - Bretagne - France
- Intitulé du sujet- Towards a Sustainable, Intelligent, and Energy-Autonomous Nanogrid Buildings: A Holistic Systemic Multi-Objective Optimization Approach
- Champs scientifiques- Sciences de l’ingénieur
- Energie
- Informatique
- Mots clés- Energy efficient buildings, Multi-objective controllers, Nanogrids, Optimization, Renewable energies

**Description du sujet**:
**Thesis abstract**

Buildings energy autonomy has become a major issue, motivating numerous research and development efforts, mainly in energy management, particularly through ICT in smart buildings. To achieve sustainable, intelligent, and energy-autonomous nanogrid buildings, it is essential to implement multi-objective controllers. These controllers must consider various factors, including renewable energy sources (i.e., PV, geothermal, fuel cell) and peak shaving (i.e., storage), to optimize energy consumption and comfort via a holistic and systematic approach.

**Thesis scientific context**

France’s carbon neutrality objective for 2050 aims to align the country with the 1.5°C target. This goal is defined as achieving a balance between the greenhouse gases (GHG) emitted each year and the quantity of GHGs absorbed by ”carbon sinks” within the national territory. Buildings are key components of society as they host human activity, but they are also a major contributor to its environmental footprint [1]. Brittany is a region that suffers from energy insecurity and is highly dependent on energy imports: it produces only about 12% of its consumption. Faced with this critical issue, the Region and other partners (State, ADEME, RTE, and ANAH) signed the Breton Electricity Pact 9 years ago, which aims to secure the electricity supply in Brittany. Moreover, Brittany has real opportunities [2]: significant potential in terms of energy savings and the development of renewable energies, particularly marine ones, which in short term could cover more than 20% of the region energy consumption and 34% of electricity consumption alone. Brittany wishes to position itself as one of the major French regions in the building and smart grid market (i.e. Smile project).

The current state of building management highlights the necessity for a transformation towards intelligent buildings. An optimal trade-off is necessary between comfort and energy savings by optimizing the multiobjectives of buildings [3]. Traditional Building Energy Management Systems (BEMS) are primarily used as automation and simulation platform tools for simple optimization operations. However, these conventional controllers do not consider all the dynamics of the buildings, particularly occupancy factors [4]. Their performance is also heavily dependent on the accuracy of building models. In literature, there are mainly three types of models that are used: 1) white-box (physics-based) models, 2) black-box (data-based), and 3) grey-box (hybrid) models [5]. Both the black-box and grey-box models have shown promising results with low computational costs and design simplicity [6].

The occupants of the building are active participants in the system, and their interaction with the building, like HVAC (heating, ventilation, air conditioning) control, plug-loads, lighting, etc., significantly influences the overall performance of the buildings [7]. Additionally, integrating renewable energy sources into buildings to reduce their grid dependency positively influences sustainable development. However, this integration complicates optimization challenges for BEMS, making their operation increasingly difficult. Traditional interaction between occupants and buildings tends to be unidirectional, with manual regulation by the occupants. In contrast, the concept of intelligent buildings has evolved. Unlike automated systems that merely regulate based on monitoring, an intelligent system is based on several agents that are able to communicate with each other, learn, and act adaptively [8].

The emergence of cost-effective IoT systems, coupled with the availability of data and advanced computational power, has created the way for the implementation of data-driven or hybrid approaches. Intelligent control systems can be categorized into several levels of intelligence based on their functionality and services: from basic monitoring, where users control the environment based on their needs, to advanced systems that monitor, propose solutions, and act autonomously, continuously learning from new patterns and interactions [9, 10].

The objective of this research work is therefore to:

- Develop an occupancy-centric and hybrid energy systems multi-objective intelligent controller for the buildings,
- Integrate the dynamic information of th