Gestion des flux énergétiques dans un système hybride de sources d’énergie renouvelable : Optimisation de la planification opérationnelle et ajustement d’un micro réseau électrique urbain

The presented research works aim to develop an energy management system for a cluster of distributed micro gas turbines and controllable PV generators called «active generators». The general principles of electricity generation from renewable and non-renewable energy sources are first presented. The operation of actual electric grids is also recalled in order to highlight the challenges and expected innovations in future Smart Grids. Then, the integration of a novel method for maximum and limited power point tracking in a PV-based active generator is presented. The modeling of micro-gas turbines in a microgrid energy management system is also presented. The main contribution of this thesis concerns the design of an operational planning of generators one day ahead by the means of a dynamic programming-based algorithm, taking into account the PV power production and the consumption forecasts. The proposed method calculates the production planning of generators by performing a global optimization of an objective function. An adjustment algorithm is proposed and executed every ½ hours through a communication network in order to take into account the uncertainty in forecasted values. An urban microgrid is used for testing the developed algorithms through Supervisory Control and Data Acquisition (SCADA) with hardware-in-the-loop and real-time simulations. Comparisons of the microgrid operation in identical situations with different objective functions are performed, as well as evaluations of economic and environmental indicatorsL’objectif est de développer un algorithme de gestion énergétique d’un parc de production comprenant de la production distribuée sous forme de micro turbines à gaz et de générateurs PV pilotables dits «actifs » en vue de minimiser le coût économique et environnemental. Les principes généraux de la production d’électricité à base d’énergie renouvelable et non renouvelable sont d’abord présentés et le fonctionnement actuel des réseaux électriques est rappelé pour situer les innovations attendues dans les futurs réseaux dits intelligents. Ensuite, un algorithme de suivi du point de puissance maximale et de puissance limitée dans un générateur actif PV est présenté. La modélisation des micro-turbines à gaz est aussi présentée. La contribution principale concerne la conception d’une planification opérationnelle des moyens de production la veille pour le lendemain à partir de prédictions de la charge et de la production PV en utilisant une programmation dynamique adaptée. La méthode proposée prédétermine le profil de production des générateurs de manière à réaliser une optimisation globale d’une fonction objective pour un réseau électrique urbain. Pour l’exploitation, un algorithme d’ajustement est proposé et intervient toutes les ½ heures de manière à prendre en compte les déviations par rapport aux prédictions en utilisant un réseau de communication. Un micro réseau urbain est utilisé pour tester les algorithmes de gestion implantés dans un superviseur interfacé à un simulateur temps réel. Des comparaisons dans des situations identiques avec différentes fonctions objectives sont réalisées ainsi que des évaluations économiques et environnementales à l’aide d’indicateur

An approach for estimation of optimal energy flows in battery storage devices for electric vehicles in the smart grid

While the number of the vehicle actuated with liquid fuels are settled, the count of electric vehicles is increasing. For the present moment most of them are scheduled for daily urban usage. This paper presents an analytical approach for estimation of the impact of electrical vehicle (EV) battery charging on the distribution grid. Based on the EV charge profile, load curve and local distributed generation the grid nodes, the time variation of grid parameters is obtained. A set of typical load profiles of EV charging modes is studied and presented. A software implementation and a 24h case study of low voltage distribution network with EV charging devices is presented in order to illustrate the approach and the impacts of EV charging on the grid. In the current paper an approach using variable nonlinear algebraic equations for dynamic time domain analysis of the charge of the electric vehicles is presented. Based on the results, the challenges due to EV charging in distribution networks including renewable energy sources are discussed. This approach is widely applicable for various EV charging and distributed energy resources studies considering control algorithms, grid stability analysis, smart grid power management and other power system analysis problems

Emission Reduction and Economical Optimization of an Urban Microgrid Operation Including Dispatched PV-Based Active Generators

In order to take full advantage of distributed generators, an evolution of the classical power system organization and management is also necessary. An aggregator of a residential urban electrical network can be considered by the distribution system operator as a stakeholder, which is able to control a cluster of local generators and loads with technical constraints for the connection with the remaining distribution grid and commercial contracts with outer electrical producers. This paper is focused on the design of the microgrid central energy management system which relies on a day-ahead operational planning and an online adjustment procedure during the operation. A dynamic programming-based algorithm is derived to solve the unit commitment problem with a multiobjective function in order to reduce the economic cost and CO2 equivalent emissions. The proposed energy management system is implemented into a supervisory control and data acquisition (SCADA) and tested by using a hardware-in-the-loop simulation of the urban network. Economic and environmental gains are evaluated

Energy management of a hybrid power system including renewable energy based generators : Optimization of the operational planning and the daily adjustment for an urban micro grid

L’objectif est de développer un algorithme de gestion énergétique d’un parc de production comprenant de la production distribuée sous forme de micro turbines à gaz et de générateurs PV pilotables dits «actifs » en vue de minimiser le coût économique et environnemental. Les principes généraux de la production d’électricité à base d’énergie renouvelable et non renouvelable sont d’abord présentés et le fonctionnement actuel des réseaux électriques est rappelé pour situer les innovations attendues dans les futurs réseaux dits intelligents. Ensuite, un algorithme de suivi du point de puissance maximale et de puissance limitée dans un générateur actif PV est présenté. La modélisation des micro-turbines à gaz est aussi présentée. La contribution principale concerne la conception d’une planification opérationnelle des moyens de production la veille pour le lendemain à partir de prédictions de la charge et de la production PV en utilisant une programmation dynamique adaptée. La méthode proposée prédétermine le profil de production des générateurs de manière à réaliser une optimisation globale d’une fonction objective pour un réseau électrique urbain. Pour l’exploitation, un algorithme d’ajustement est proposé et intervient toutes les ½ heures de manière à prendre en compte les déviations par rapport aux prédictions en utilisant un réseau de communication. Un micro réseau urbain est utilisé pour tester les algorithmes de gestion implantés dans un superviseur interfacé à un simulateur temps réel. Des comparaisons dans des situations identiques avec différentes fonctions objectives sont réalisées ainsi que des évaluations économiques et environnementales à l’aide d’indicateursThe presented research works aim to develop an energy management system for a cluster of distributed micro gas turbines and controllable PV generators called «active generators». The general principles of electricity generation from renewable and non-renewable energy sources are first presented. The operation of actual electric grids is also recalled in order to highlight the challenges and expected innovations in future Smart Grids. Then, the integration of a novel method for maximum and limited power point tracking in a PV-based active generator is presented. The modeling of micro-gas turbines in a microgrid energy management system is also presented. The main contribution of this thesis concerns the design of an operational planning of generators one day ahead by the means of a dynamic programming-based algorithm, taking into account the PV power production and the consumption forecasts. The proposed method calculates the production planning of generators by performing a global optimization of an objective function. An adjustment algorithm is proposed and executed every ½ hours through a communication network in order to take into account the uncertainty in forecasted values. An urban microgrid is used for testing the developed algorithms through Supervisory Control and Data Acquisition (SCADA) with hardware-in-the-loop and real-time simulations. Comparisons of the microgrid operation in identical situations with different objective functions are performed, as well as evaluations of economic and environmental indicator

Energy management and operational planning of a microgrid with a PV-based active generator for Smart Grid Applications

The development of energy management tools for consumers and next generation PV installations, including storage units, provides flexibility to distribution system operators. In this paper the aggregation and implementation of this new energy management method for business customers in a microgrid power system is presented. The proposed energy management system is organized according to different functions and is implemented in two parts: a central energy management of the microgrid and a local power management at the customer side. The central and local management systems exchange data and orders through a communication network. The power planning is designed according to the prediction for PV power production and the load forecasting by taking into account the capabilities of dispatched customers. According to received grid power references, additional functions are also designed to manage locally the power flows between the various sources. Application to the case of a hybrid supercapacitor battery based PV active generator is presented

An approach for estimation of optimal energy flows in battery storage devices for electric vehicles in the smart grid

While the number of the vehicle actuated with liquid fuels are settled, the count of electric vehicles is increasing. For the present moment most of them are scheduled for daily urban usage. This paper presents an analytical approach for estimation of the impact of electrical vehicle (EV) battery charging on the distribution grid. Based on the EV charge profile, load curve and local distributed generation the grid nodes, the time variation of grid parameters is obtained. A set of typical load profiles of EV charging modes is studied and presented. A software implementation and a 24h case study of low voltage distribution network with EV charging devices is presented in order to illustrate the approach and the impacts of EV charging on the grid. In the current paper an approach using variable nonlinear algebraic equations for dynamic time domain analysis of the charge of the electric vehicles is presented. Based on the results, the challenges due to EV charging in distribution networks including renewable energy sources are discussed. This approach is widely applicable for various EV charging and distributed energy resources studies considering control algorithms, grid stability analysis, smart grid power management and other power system analysis problems

An approach for estimation of optimal energy flows in battery storage devices for electric vehicles in the smart grid

While the number of the vehicle actuated with liquid fuels are settled, the count of electric vehicles is increasing. For the present moment most of them are scheduled for daily urban usage. This paper presents an analytical approach for estimation of the impact of electrical vehicle (EV) battery charging on the distribution grid. Based on the EV charge profile, load curve and local distributed generation the grid nodes, the time variation of grid parameters is obtained. A set of typical load profiles of EV charging modes is studied and presented. A software implementation and a 24h case study of low voltage distribution network with EV charging devices is presented in order to illustrate the approach and the impacts of EV charging on the grid. In the current paper an approach using variable nonlinear algebraic equations for dynamic time domain analysis of the charge of the electric vehicles is presented. Based on the results, the challenges due to EV charging in distribution networks including renewable energy sources are discussed. This approach is widely applicable for various EV charging and distributed energy resources studies considering control algorithms, grid stability analysis, smart grid power management and other power system analysis problems

Day-ahead probabilistic forecast of solar irradiance: a Stochastic Differential Equation approach

International audienceIn this work, we derive a probabilistic forecast of the solar irradiance during a day at a given location, using a stochastic differential equation (SDE for short) model. We propose a procedure that transforms a deterministic forecast into a proba-bilistic forecast: the input parameters of the SDE model are the Arome deterministic forecast computed at day D-1 for the day D. The model also accounts for the maximal irradiance from the clear sky model. The SDE model is mean-reverting towards the deterministic forecast and the instantaneous amplitude of the noise depends on the clear sky index, so that the fluctuations vanish as the index is close to 0 (cloudy) or 1 (sunny), as observed in practice. Our tests show a good adequacy of the confidence intervals of the model with the measurement