Multi-objective non-weighted optimization to explore new efficient design of electrical microgrids

Centralized electrical networks induce a dependency of local territories for their power supply. However, thanks to microgrids, territories can increase their decision-making autonomy to design a network that matches their values. Technological and management choices are critical to minimize microgrids negative impacts on their environment. Influence of the latter on the design space is rarely discussed whereas extending the design space would help to find innovative microgrids. The purpose of this paper is to find several microgrids with various performances and parameters that are compromises between economic, technical and environmental objectives. The solutions’ variety therefore extends the decision-makers’ design space. A tool has been developed to answer this goal. Design parameters are both technological and management parameters. A physical modelling is implemented in a sequential simulation of the microgrid operation. The performance of the simulation allows to use genetic algorithms to perform multi-objective non-weighted optimizations. Two twoobjective optimizations are performed. Results show how the solutions’ diversity in terms of performances and parameters helps the user choosing innovative microgrids. Especially, it underlines the potential of this approach to find microgrids with close performances but different parameters.This work was supported by the Region Provence-Alpes-Côte d’Azur, Franc

Systemic Approach for Local Energy Mix Assessment

Whereas energy mainly comes from main national power plants, distributed energy resources and storage technologies would allow local territories to choose their energy sources and increase their autonomy. This paper presents a decision-support tool that propose to find new system architecture based compromises between economic, technical and environmental objectives. Based on a systemic approach, it takes into account a broad range of technologies and assesses multi-scale territories thanks to a physical modelling. Numerical simulations show the influence of different parameters on the ability of a system to balance power demand.This work was supported by the Region Provence-Alpes-Côte d’Azur, Franc

Efficient energy system modelling for multi-objective optimisation

Energy systems, on which our modern society rely, are in constant transformation. Technological evolution, climate change or the finitude of fossil fuels are some reasons to rethink the centralized, carbon-based energy networks. This way, the design of future energy systems have to take into account multiple concerns, such as local resilience, in addition to technical and economic ones. This paper presents a decision-support tool for the conception of energy systems focusing on the electric vector. The tool was designed using an energy system model implemented in an optimisation algorithm. It takes into account several constraints simultaneously – equilibrium between production and consumption as well as resources availability – and assess the influence of technical parameters on the global performances of the system. An energy system is considered as a combination of production, storage and transport technologies with their operating strategies. The tool’s modularity allows to choose the models adapted to a quick optimisation of energy systems or to an analysis of technical parameters. The second part of the paper presents the optimisation of a local energy system. Search space is composed of production and storage technologies’ number and their operating strategies. Main goals are to find trade-offs between different economic and technical objective-functions – such as levelized cost of energy or local autonomy. Therefore, a genetic algorithm method was used to perform a multi-objective optimisation based on the model. The impact of the operating strategy adopted is underlined.This work was supported by the Region Provence-Alpes-Côte d’Azur, France

Modélisation systémique pour l'optimisation multi-objectifs de systèmes énergétiques – Application aux micro-réseaux électriques isolés.

Climate change and the depletion of some natural resources are leading to changes in social expectations toward the energy production. The development of new power supply systems must therefore take into account various impacts. One of the evolutions of the electrical mix consists in the gathering of production (conventional and renewable) and storage technologies inside a local network : a microgrid. This PhD thesis proposes to design microgrids by considering several economic, technical and environmental objectives. The developed approach consists in the consideration of management aspects in the design parameters of microgrids and the integration of the modelling into a non-weighted multi-objective optimization algorithm.A decision-support tool has been developed. After identifying the stakes of energy system modelling and optimization, a sequential simulation of microgrids operation has been set up, enhanced with various performance indicators (technical, environmental and economic) and implemented in a genetic algorithm. The sequential simulation has been carried out on a representative period of twelve typical days, while guarantying the reliability of of the performances assessment on a longer operation period. Several solutions, trade-offs between the objectives, have been found. Their diversity in terms of performances and parameters allows to extend the design space. Furthermore, the impact of the consideration of several management strategies allows to find more diverses combinations of technologies. These results have been analyzed and the assessment and optimization requirements have been checked on a realistic case study. Eventually, the performance of the approach has been validated by comparison with other software (HOMER and iHOGA/MHOGA).Le changement climatique et la raréfaction de certaines ressources fossiles sont à l'origine d'une évolution des attentes de la société à propos de la production énergétique. Le développement de nouveaux systèmes d'approvisionnement électrique doit prendre en compte différents impacts. Une des évolutions du mix électrique consiste à regrouper des technologies de production (conventionnelles ou renouvelables) et de stockage dans un sous-réseau local : un microgrid. Cette thèse propose de dimensionner les microgrids en considérant plusieurs objectifs économiques, techniques et environnementaux. La proposition de ce travail consiste en la prise en compte des aspects de pilotage dans les paramètres de conception des microgrids et l'intégration de cette modélisation dans un algorithme d'optimisation multi-objectifs sans pondération.Un outil d'aide à la décision a ainsi été développé. Après avoir identifié les enjeux de modélisation et d'optimisation des systèmes énergétiques, une simulation séquentielle de l'opération des microgrids a été mise en place, enrichie de divers indicateurs de performances (techniques, environnementaux et économiques) et implémentée dans un algorithme génétique. La simulation a été effectuée sur une période représentative de douze jours types tout en garantissant la fiabilité de l’évaluation des performances par rapport à une période d’opération réelle plus longue. Plusieurs solutions, compromis entre les objectifs, ont alors été trouvées. Leur diversité en termes de performances et de paramètres permet bien d'élargir l'espace de conception. De plus l’impact de la prise en compte de plusieurs stratégies de pilotage permet de trouver des combinaisons de technologies plus diverses. Ces résultats ont été analysés et les exigences d'évaluation et d'optimisation ont été vérifiées sur un cas d'étude réaliste. Finalement, la performance de l'approche a été validée par comparaison avec d'autres logiciels de référence (HOMER et iHOGA/MHOGA)

Systemic modelling for the multi-objective optimization of energy systems – Application to isolated electrical microgrids

Le changement climatique et la raréfaction de certaines ressources fossiles sont à l'origine d'une évolution des attentes de la société à propos de la production énergétique. Le développement de nouveaux systèmes d'approvisionnement électrique doit prendre en compte différents impacts. Une des évolutions du mix électrique consiste à regrouper des technologies de production (conventionnelles ou renouvelables) et de stockage dans un sous-réseau local : un microgrid. Cette thèse propose de dimensionner les microgrids en considérant plusieurs objectifs économiques, techniques et environnementaux. La proposition de ce travail consiste en la prise en compte des aspects de pilotage dans les paramètres de conception des microgrids et l'intégration de cette modélisation dans un algorithme d'optimisation multi-objectifs sans pondération.Un outil d'aide à la décision a ainsi été développé. Après avoir identifié les enjeux de modélisation et d'optimisation des systèmes énergétiques, une simulation séquentielle de l'opération des microgrids a été mise en place, enrichie de divers indicateurs de performances (techniques, environnementaux et économiques) et implémentée dans un algorithme génétique. La simulation a été effectuée sur une période représentative de douze jours types tout en garantissant la fiabilité de l’évaluation des performances par rapport à une période d’opération réelle plus longue. Plusieurs solutions, compromis entre les objectifs, ont alors été trouvées. Leur diversité en termes de performances et de paramètres permet bien d'élargir l'espace de conception. De plus l’impact de la prise en compte de plusieurs stratégies de pilotage permet de trouver des combinaisons de technologies plus diverses. Ces résultats ont été analysés et les exigences d'évaluation et d'optimisation ont été vérifiées sur un cas d'étude réaliste. Finalement, la performance de l'approche a été validée par comparaison avec d'autres logiciels de référence (HOMER et iHOGA/MHOGA).Climate change and the depletion of some natural resources are leading to changes in social expectations toward the energy production. The development of new power supply systems must therefore take into account various impacts. One of the evolutions of the electrical mix consists in the gathering of production (conventional and renewable) and storage technologies inside a local network : a microgrid. This PhD thesis proposes to design microgrids by considering several economic, technical and environmental objectives. The developed approach consists in the consideration of management aspects in the design parameters of microgrids and the integration of the modelling into a non-weighted multi-objective optimization algorithm.A decision-support tool has been developed. After identifying the stakes of energy system modelling and optimization, a sequential simulation of microgrids operation has been set up, enhanced with various performance indicators (technical, environmental and economic) and implemented in a genetic algorithm. The sequential simulation has been carried out on a representative period of twelve typical days, while guarantying the reliability of of the performances assessment on a longer operation period. Several solutions, trade-offs between the objectives, have been found. Their diversity in terms of performances and parameters allows to extend the design space. Furthermore, the impact of the consideration of several management strategies allows to find more diverses combinations of technologies. These results have been analyzed and the assessment and optimization requirements have been checked on a realistic case study. Eventually, the performance of the approach has been validated by comparison with other software (HOMER and iHOGA/MHOGA)

Modélisation systémique pour l'optimisation multi-objectifs de systèmes énergétiques – Application aux micro-réseaux électriques isolés.

Climate change and the depletion of some natural resources are leading to changes in social expectations toward the energy production. The development of new power supply systems must therefore take into account various impacts. One of the evolutions of the electrical mix consists in the gathering of production (conventional and renewable) and storage technologies inside a local network : a microgrid. This PhD thesis proposes to design microgrids by considering several economic, technical and environmental objectives. The developed approach consists in the consideration of management aspects in the design parameters of microgrids and the integration of the modelling into a non-weighted multi-objective optimization algorithm.A decision-support tool has been developed. After identifying the stakes of energy system modelling and optimization, a sequential simulation of microgrids operation has been set up, enhanced with various performance indicators (technical, environmental and economic) and implemented in a genetic algorithm. The sequential simulation has been carried out on a representative period of twelve typical days, while guarantying the reliability of of the performances assessment on a longer operation period. Several solutions, trade-offs between the objectives, have been found. Their diversity in terms of performances and parameters allows to extend the design space. Furthermore, the impact of the consideration of several management strategies allows to find more diverses combinations of technologies. These results have been analyzed and the assessment and optimization requirements have been checked on a realistic case study. Eventually, the performance of the approach has been validated by comparison with other software (HOMER and iHOGA/MHOGA).Le changement climatique et la raréfaction de certaines ressources fossiles sont à l'origine d'une évolution des attentes de la société à propos de la production énergétique. Le développement de nouveaux systèmes d'approvisionnement électrique doit prendre en compte différents impacts. Une des évolutions du mix électrique consiste à regrouper des technologies de production (conventionnelles ou renouvelables) et de stockage dans un sous-réseau local : un microgrid. Cette thèse propose de dimensionner les microgrids en considérant plusieurs objectifs économiques, techniques et environnementaux. La proposition de ce travail consiste en la prise en compte des aspects de pilotage dans les paramètres de conception des microgrids et l'intégration de cette modélisation dans un algorithme d'optimisation multi-objectifs sans pondération.Un outil d'aide à la décision a ainsi été développé. Après avoir identifié les enjeux de modélisation et d'optimisation des systèmes énergétiques, une simulation séquentielle de l'opération des microgrids a été mise en place, enrichie de divers indicateurs de performances (techniques, environnementaux et économiques) et implémentée dans un algorithme génétique. La simulation a été effectuée sur une période représentative de douze jours types tout en garantissant la fiabilité de l’évaluation des performances par rapport à une période d’opération réelle plus longue. Plusieurs solutions, compromis entre les objectifs, ont alors été trouvées. Leur diversité en termes de performances et de paramètres permet bien d'élargir l'espace de conception. De plus l’impact de la prise en compte de plusieurs stratégies de pilotage permet de trouver des combinaisons de technologies plus diverses. Ces résultats ont été analysés et les exigences d'évaluation et d'optimisation ont été vérifiées sur un cas d'étude réaliste. Finalement, la performance de l'approche a été validée par comparaison avec d'autres logiciels de référence (HOMER et iHOGA/MHOGA)

Approche systémique pour l'évaluation de mix énergétiques locaux

International audienceWhereas energy mainly comes from main national power plants, distributed energy resources and storage technologies would allow local territories to choose their energy sources and increase their autonomy. This paper presents a decision-support tool that propose to find new system architecture based compromises between economic, technical and environmental objectives. Based on a sys-temic approach, it takes into account a broad range of technologies and assess multi-scale territories thanks to a physical modelling. Numerical simulations show the influence of different parameters on the ability of a system to balance power demand

Approche systémique pour l'évaluation de mix énergétiques locaux

International audienceWhereas energy mainly comes from main national power plants, distributed energy resources and storage technologies would allow local territories to choose their energy sources and increase their autonomy. This paper presents a decision-support tool that propose to find new system architecture based compromises between economic, technical and environmental objectives. Based on a sys-temic approach, it takes into account a broad range of technologies and assess multi-scale territories thanks to a physical modelling. Numerical simulations show the influence of different parameters on the ability of a system to balance power demand

Modelling of Electric Bus Operation and Charging Process: Potential Contribution of Local Photovoltaic Production

The transition from diesel to electric buses allows the reduction of greenhouse gas emissions. However, the impacts of charging strategies on the quality of bus services and the utility grid must be assessed to ensure the feasibility of the energy transition in the public transportation sector. This study investigates the performances of different locations and sizes of charging infrastructures by presenting the comprehensive modelling of a bus network. It also estimates the potential benefits of a local photovoltaic (PV) production to reduce negative impacts on the utility grid. The presented approach is used for modelling one urban bus line in Compiègne, France, and simulations are performed for various case studies. The results demonstrate that the proposed method allows analysing the impact of the charging process on the quality of bus services by determining the delays of arrivals. The simulations also show the impacts of charger placement on bus on-board battery capacity, total peak power demand of battery charging, and PV self-consumption ratio. The amount of PV energy used directly to charge buses remains low, although it varies between scenarios. PV energy during winter is not sufficient to fully charge buses; however, it can be enough with additional stationary storage in the summer