Heuristiques optimisées et robustes de résolution du problème de gestion d'énergie pour les véhicules électriques et hybrides

Le système étudié durant cette thèse est un véhicule électrique hybride avec deux sources d’énergies (Pile à combustible et Super-capacité). L’objectif fixé est de minimiser la consommation du carburant tout en satisfaisant la demande instantanée en puissance sous des contraintes de puissance et de capacité et de stockage. Le problème a été modélisé sous la forme d’un problème d’optimisation globale. Nous avons développé de nouvelles méthodes heuristiques pour le résoudre et proposé le calcul d’une borne inférieure de consommation, en apportant de meilleurs résultats que ceux trouvés dans la littérature. En plus, une étude de robustesse a été réalisée afin de minimiser la consommation de pire-cas suite à une perturbation ou du fait d’incertitudes sur les données d’entrée, précisément sur la puissance demandée. Le but de cette étude est de prendre en compte les perturbations dès la construction des solutions afin d’éviter l’infaisabilité des solutions non robustes en situation perturbée. Les heuristiques de résolution du problème robuste modélisé sous la forme d’un problème de Minimax ont fourni des solutions moins sensibles aux perturbations que les solutions classiques. ABSTRACT : The system studied in this thesis is a hybrid electrical vehicle with two energy sources (fuel cell system and super-capacitor). The first goal is to minimize the fuel consumption whilst satisfying the requested power for each instant, taking into account constraints on the availability and the state of charge of the storage element. The system was modeled as a global optimization problem. The heuristics developped for obtaining the best power split between the two sources and the lower bound consumption computation proposed provide better results than those found in the literature. The second goal of the thesis is the study of the robustness of the solutions in order to minimize the worst-case consumption when perturbation happens or uncertainty is added to the input data. In this study the uncertainty concerns the power required for traction. The objective is to maintain the feasibility of solutions and limit the worst consumption that can happen due to a demand fluctuation. Dedicated heuristics are proposed for solving the identified robust variant of the problem, modeled as a Minimax problem. The solutions provided are less sensitive to the perturbations than the previous ones

A better alternative to dynamic programming for offline energy optimization in hybrid-electric vehicles

International audienceThis article focusses on the well-known problem of energy management for hybrid-electric vehicles. Although researches on this problem have recently intensified. Dynamic programming (DP) is still considered as the reference method because it obtains the best solutions of the literature so far, even though it requires a significant computational time. This article however, describes two heuristic-global-optimization-based algorithms that not only require less computational time than DP, but also produce better solutions, with significantly lower fuel consumption cost

HEURISTICS AND LOWER BOUND FOR ENERGY MANAGEMENT IN HYBRID-ELECTRIC VEHICLES

International audienc

A DSO Support Framework for Assessment of Future-Readiness of Distribution Systems: Technical, Market, and Policy Perspectives

This paper presents the initial ideas for a framework to support the distribution system operators for assessing current status of network infrastructures, market/business models, and policies applicable to distribution systems, and thus identify future-readiness of their network. The assessment framework consists of two steps as the identification of the key indicators associated with this transition and assessing the current status by evaluation of these indicators based on inputs from distribution system operators. Case studies have been carried out for distribution system operators in three European countries, i.e., G\uf6teborg Energi (Sweden), SOREA (France), and ENEXIS (The Netherlands). The key results have shown that presently the three distribution system operators have a small proportion of renewable power generation in their grids, but it is going to increase in the future. Hence, they need investments in flexibilities, generation and load forecasting, advanced network control, and protection strategies, etc. The results also suggest needs for development of novel business models for customers and changes in the policy and regulations. Finally, a comparative assessment of three distribution system operators is presented in the paper

Optimized and robust heuristics for solving the problem of energy management for hybrid electric vehicles

Le système étudié durant cette thèse est un véhicule électrique hybride avec deux sources d’énergies (Pile à combustible et Super-capacité). L’objectif fixé est de minimiser la consommation du carburant tout en satisfaisant la demande instantanée en puissance sous des contraintes de puissance et de capacité et de stockage. Le problème a été modélisé sous la forme d’un problème d’optimisation globale. Nous avons développé de nouvelles méthodes heuristiques pour le résoudre et proposé le calcul d’une borne inférieure de consommation, en apportant de meilleurs résultats que ceux trouvés dans la littérature. En plus, une étude de robustesse a été réalisée afin de minimiser la consommation de pire-cas suite à une perturbation ou du fait d’incertitudes sur les données d’entrée, précisément sur la puissance demandée. Le but de cette étude est de prendre en compte les perturbations dès la construction des solutions afin d’éviter l’infaisabilité des solutions non robustes en situation perturbée. Les heuristiques de résolution du problème robuste modélisé sous la forme d’un problème de Minimax ont fourni des solutions moins sensibles aux perturbations que les solutions classiques.The system studied in this thesis is a hybrid electrical vehicle with two energy sources (fuel cell system and super-capacitor). The first goal is to minimize the fuel consumption whilst satisfying the requested power for each instant, taking into account constraints on the availability and the state of charge of the storage element. The system was modeled as a global optimization problem. The heuristics developped for obtaining the best power split between the two sources and the lower bound consumption computation proposed provide better results than those found in the literature. The second goal of the thesis is the study of the robustness of the solutions in order to minimize the worst-case consumption when perturbation happens or uncertainty is added to the input data. In this study the uncertainty concerns the power required for traction. The objective is to maintain the feasibility of solutions and limit the worst consumption that can happen due to a demand fluctuation. Dedicated heuristics are proposed for solving the identified robust variant of the problem, modeled as a Minimax problem. The solutions provided are less sensitive to the perturbations than the previous ones

Heuristiques optimisées et robustes pour la résolution du problème de gestion d'énergie pour véhicules électriques et hybrides

Le système étudié durant cette thèse est un véhicule électrique hybride avec deux sources d énergies (Pile à combustible et Super-capacité). L objectif fixé est de minimiser la consommation du carburant tout en satisfaisant la demande instantanée en puissance sous des contraintes de puissance et de capacité et de stockage. Le problème a été modélisé sous la forme d un problème d optimisation globale. Nous avons développé de nouvelles méthodes heuristiques pour le résoudre et proposé le calcul d une borne inférieure de consommation, en apportant de meilleurs résultats que ceux trouvés dans la littérature. En plus, une étude de robustesse a été réalisée afin de minimiser la consommation de pire-cas suite à une perturbation ou du fait d incertitudes sur les données d entrée, précisément sur la puissance demandée. Le but de cette étude est de prendre en compte les perturbations dès la construction des solutions afin d éviter l infaisabilité des solutions non robustes en situation perturbée. Les heuristiques de résolution du problème robuste modélisé sous la forme d un problème de Minimax ont fourni des solutions moins sensibles aux perturbations que les solutions classiques.The system studied in this thesis is a hybrid electrical vehicle with two energy sources (fuel cell system and super-capacitor). The first goal is to minimize the fuel consumption whilst satisfying the requested power for each instant, taking into account constraints on the availability and the state of charge of the storage element. The system was modeled as a global optimization problem. The heuristics developped for obtaining the best power split between the two sources and the lower bound consumption computation proposed provide better results than those found in the literature. The second goal of the thesis is the study of the robustness of the solutions in order to minimize the worst-case consumption when perturbation happens or uncertainty is added to the input data. In this study the uncertainty concerns the power required for traction. The objective is to maintain the feasibility of solutions and limit the worst consumption that can happen due to a demand fluctuation. Dedicated heuristics are proposed for solving the identified robust variant of the problem, modeled as a Minimax problem. The solutions provided are less sensitive to the perturbations than the previous ones.TOULOUSE-INP (315552154) / SudocSudocFranceF

Impact of consumer profiles and forecast accuracy on day-ahead scheduling of household appliances

International audienceDue to the increasing profitability of photovoltaic systems, the penetration of decentralized domestic photovoltaic energy sources is growing. Contrarily to conventional energy sources, photovoltaic systems cannot be scheduled to meet the consumption. This prompts the need to shift the energy consumption towards times with high photovoltaic production. Indeed, local consumption of the produced energy allows the prosumer to increase the profitability of its photovoltaic system and decreases the impact of high photovoltaic penetration on the distribution grid. To this end, energy management methods are investigated. However, the benefits of the methods are inherently dependent on the study case. This paper presents a sensitivity analysis based on a demand response method, investigating its dependency with the prosumer load profile and with the production forecast accuracy. The demand response method introduces flexibility in the time-of-use of electricity consuming devices in order to increase the profitability of photovoltaic systems, but also to reduce the peak power exchanged with the distribution grid

Establishing DSOso-specific scenarios for future electrical distribution grids

International audienceThe evolution of electrical distribution grids requires the Distribution System Operators to be ready for a more complex and flexible grid. This paper explores the use of scenario analysis as a useful tool that the operators can use to foresee and hedge against any upcoming challenges. However, available energy transition scenarios in literature predominantly focus on a large scale in their projections and hence may not be the best fit for this task. This paper proposes an approach to break down the projections of these scenarios to the level of a specific distribution grid, taking into account the current state of the system and its specificities. A study case with a distribution system operator and the electricity system in France is also presented. The work demonstrates how applying scenario analysis to an individual distribution system operator can be beneficial in exploring multiple possible futures and determining future challenges and requirements

Heuristics and lower bounds for minimizing fuel consumption in hybrid-electrical vehicles

International audienceIn hybrid electric vehicles, the electrical powertrain system has multiple energy sources that it can gather power from to satisfy the propulsion power requested by the vehicle at each instant. This paper focusses on the minimization of the fuel consumption of such a vehicle, taking advantage of the different energy sources. Based on global optimization approaches, the proposed heuristics find solutions that best split the power requested between the multi-electrical sources available. A lower bounding procedure is introduced to validate the quality of the solutions. Computational results show a significant improvement over previous results from the literature in both the computing time and the quality of the solutions

Implementation of a Coordinated Voltage Control Algorithm for a Microgrid via SCADAas-a-service approach

International audienceThe massive penetration of distributed renewable energy resources (DRES) at low voltage distribution network poses challenging power quality issues. Coordinated voltage control is necessary in microgrid with high DRES rate to keep the voltage in required range and to optimize the grid performance. This paper presents the implementation of a coordinated voltage control algorithm on a real world microgrid via SCADA-as-a-service (SCADA-aaS) method. The SCADA-aaS approach provides the interoperability framework for the network operators to provide their CVC algorithm to microgrid owners or to implement a third party CVC. This real world implementation demonstrates the feasibility of the SCADA-aaS approach. Experiences and lessons learned from the implementation are discussed