CNRS Urban Systems Engineering

Compiegne, France

CNRS Urban Systems Engineering

Compiegne, France
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Sechilariu M.,CNRS Urban Systems Engineering | Wang B.C.,CNRS Urban Systems Engineering | Locment F.,CNRS Urban Systems Engineering | Jouglet A.,Compiègne University of Technology
Energy Conversion and Management | Year: 2014

Urban areas have great potential for photovoltaic (PV) generation, however, direct PV power injection has limitations for high level PV penetration. It induces additional regulations in grid power balancing because of lacking abilities of responding to grid issues such as reducing grid peak consumption or avoiding undesired injections. The smart grid implementation, which is designed to meet these requirements, is facilitated by microgrids development. This paper presents a DC microgrid (PV array, storage, power grid connection, DC load) with multi-layer supervision control which handles instantaneous power balancing following the power flow optimization while providing interface for smart grid communication. The optimization takes into account forecast of PV power production and load power demand, while satisfying constraints such as storage capability, grid power limitations, grid time-of-use pricing and grid peak hour. Optimization, whose efficiency is related to the prediction accuracy, is carried out by mixed integer linear programming. Experimental results show that the proposed microgrid structure is able to control the power flow at near optimum cost and ensures self-correcting capability. It can respond to issues of performing peak shaving, avoiding undesired injection, and making full use of locally produced energy with respect to rigid element constraints. © 2014 Elsevier Ltd. All rights reserved.

Abdallah N.B.,CNRS Heuristic and Diagnostic Methods for Complex Systems | Mouhous-Voyneau N.,CNRS Urban Systems Engineering | Denoeux T.,CNRS Heuristic and Diagnostic Methods for Complex Systems
Proceedings of the 16th International Conference on Information Fusion, FUSION 2013 | Year: 2013

We present a methodology based on Dempster-Shafer theory to represent, combine and propagate statistical and epistemic uncertainties. This approach is first applied to estimate, via a semi-empirical model, the future sea level rise induced by global warming at the end of the century. Projections are affected by statistical uncertainties originating from model parameter estimation and epistemic uncertainties due to lack of knowledge of model inputs. We then study the overtopping response of a typical defense structure due to (1) uncertain elevation of the mean water level and (2) uncertain level of storm surges and waves. Statistical evidence is described by likelihood-based belief functions while imprecise evidence is modeled by subjective possibility distributions. Uncertain inputs are propagated by Monte Carlo simulation and interval analysis and the output belief function can be summarized by upper and lower cumulative distribution functions. © 2013 ISIF ( Intl Society of Information Fusi.

Ben Abdallah N.,CNRS Heuristic and Diagnostic Methods for Complex Systems | Mouhous-Voyneau N.,CNRS Urban Systems Engineering | Denoeux T.,CNRS Heuristic and Diagnostic Methods for Complex Systems
International Journal of Approximate Reasoning | Year: 2014

Estimation of extreme sea levels for high return periods is of prime importance in hydrological design and flood risk assessment. Common practice consists of inferring design levels from historical observations and assuming the distribution of extreme values to be stationary. However, in recent years, there has been a growing awareness of the necessity to integrate the effects of climate change in environmental analysis. In this paper, we present a methodology based on belief functions to combine statistical judgements with expert evidence in order to predict the future centennial sea level at a particular location, taking into account climate change. Likelihood-based belief functions derived from statistical observations are combined with random intervals encoding expert assessments of the 21st century sea level rise. Monte Carlo simulations allow us to compute belief and plausibility degrees for various hypotheses about the design parameter. © 2013 Elsevier Inc. All rights reserved.

Sechilariu M.,CNRS Urban Systems Engineering | Locment F.,CNRS Urban Systems Engineering | Wang B.,Harbin Institute of Technology
Energies | Year: 2015

In the context of sustainable buildings, this paper investigates power flow management for an isolated DC microgrid and focuses on efficiency and energy cost reduction by optimal scheduling. Aiming at high efficiency, the local produced power has to be used where, when, and how it is generated. Thus, based on photovoltaic sources, storage, and a biofuel generator, the proposed DC microgrid is coupled with the DC distribution network of the building. The DC bus distribution maximizes the efficiency of the overall production-consumption system by avoiding some energy conversion losses and absence of reactive power. The isolated DC microgrid aims to minimize the total energy cost and thus, based on forecasting data, a cost function is formulated. Using a mixed integer linear programming optimization, the optimal power flow scheduling is obtained which leads to an optimization-based strategy for real-time power balancing. Three experimental tests, operated under different meteorological conditions, validate the feasibility of the proposed control and demonstrate the problem formulation of minimizing total energy cost. © 2015 by the authors.

Hissel F.,WaterWays | Hissel F.,Common Research Team CETMEF Avenues GSU | Morel G.,Common Research Team CETMEF Avenues GSU | Morel G.,CNRS Urban Systems Engineering | And 5 more authors.
Coastal Engineering | Year: 2014

The FP7 Theseus research project (2009-2013) aims to develop and assess innovative technologies and methodologies for coastal protection against erosion, flooding and environmental damages. While protection structures may help to reduce the level of hazard and the expected degree of loss, some danger of technical failures or human errors will always remain. For extreme events, the implementation of non-structural measures as early warning systems and disaster management practices is required to ensure the protection of population.During Theseus, a methodology for helping the local authorities to prepare an action plan in case of coastal flooding was developed and tested on the estuary of Gironde in France. The methodology builds over the return of experience from past events and tries to clearly identify all the stages of an evacuation and the thinking process that can lead to a robust evacuation plan. It relies on a conceptual framework - SADT - which helps to understand how data should be processed from its collection to its use in the plan. The risk scenarios were calculated for current and future conditions of the XXIst century, taking into account the effects of climate change. The methodology is supported by the OSIRIS software, prototyped during the FP5 eponymous project and later distributed by CETMEF and the French basin authorities of Loire and Meuse.The methodology for the preparation of evacuation plans was applied on a pilot city of Theseus, Bordeaux on the estuary of Gironde (France), and the software used to calculate evacuation times was tried out on Cesenatico near the Adriatic coast (Italy). This comparison verified the replicability of methodological guidelines in two different European contexts. The cultural and organizational differences and the different number of people involved underlined strong questions to be addressed when applying them. In order to assess the efficiency of an evacuation strategy and to compute the number of people successfully evacuated over time, a macroscopic model (not representing each individual vehicle but only flows of vehicles in congestion points) for the simulation of traffic congestion was used, based on the work of the University of Twente, Rijkswaterstaat and INFRAM. This model will be integrated in the Theseus decision support system for helping coastal managers to select their strategy for risk mitigation. © 2013 Elsevier B.V.

Vermeulen T.,CNRS Urban Systems Engineering | Knopf-Lenoir C.,CNRS Roberval Laboratory (Mechanical Research Unit) | Villon P.,CNRS Roberval Laboratory (Mechanical Research Unit) | Beckers B.,CNRS Urban Systems Engineering
Computers, Environment and Urban Systems | Year: 2015

The need to save energy at the urban level leads to study how numerical simulations and optimization methods can help the architects to design buildings and districts with the best possible energetic performances, regarding daylight, warming or cooling, and photovoltaic capabilities.This work presents a study of solar potential maximization over a district and its relation with urban shape. For this purpose, two geometrical models are proposed. The first one is derived from the literature and describes a grid of buildings in open area; the second one studies moderately dense urban configurations with a pre-existent urban-context. A clear sky model is considered to compute direct solar radiation and an evolutionary algorithm is used to optimize the shape and the distribution of buildings inside a fixed area.Results show some clues on the optimal distribution of buildings considering the total direct solar irradiation to be captured by an urban district for various densities and compare the solar potential at different latitudes between 40° and 60°N. © 2015 Elsevier Ltd.

Locment F.,CNRS Urban Systems Engineering | Sechilariu M.,CNRS Urban Systems Engineering
ENERGYCON 2014 - IEEE International Energy Conference | Year: 2014

This paper presents an urban DC microgrid based on photovoltaic which allows to charge the plug-in electric vehicles and to supply a DC load. Taking into account the public grid connection, the applied local control aims to extract maximum power from photovoltaic sources and manages the power flow with respect to electric vehicles state of charge and the DC load power demand. The urban DC microgrid is modeled by using Energetic Macroscopic Representation (EMR) and Maximum Control Structure (MCS). The simulation results for ensuring the maximal utilization of produced electricity, under different conditions, show the validity of the model and the feasibility of the proposed system design. © 2014 IEEE.

Sechilariu M.,CNRS Urban Systems Engineering | Wang B.C.,CNRS Urban Systems Engineering | Locment F.,CNRS Urban Systems Engineering
International Journal of Electrical Power and Energy Systems | Year: 2014

The development of microgrids could facilitate the smart grid feasibility which is conceived to improve instantaneous grid power balancing as well as demand response. It requires microgrid control functions as power balancing, optimization, prediction, and smart grid and end-user interaction. In literature, these aspects have been studied mostly separately. However, combining them together, especially implementing optimization in real-time operation has not been reported. The difficulty is to offer resistance to optimization uncertainties in real-time power balancing. To cover the research gap, this paper presents the supervision design with predicted powers flow optimization for DC microgrid based on photovoltaic sources, storage, grid connection and DC load. The supervision control, designed as four-layer structure, takes into account forecast of power production and load power demand, storage capability, grid power limitations, grid time-of-use tariffs, optimizes energy cost, and handles instantaneous power balancing in the microgrid. Optimization aims to reduce the microgrid energy cost while meeting all constraints and is carried out by mixed integer linear programming. Simulation results, show that the proposed control is able to implement optimization in real-time power balancing with resistance to uncertainties. The designed supervision can be a solution concerning the communication between loads and smart grid. © 2014 Elsevier Ltd. All rights reserved.

Dos Santos L.T.,CNRS Urban Systems Engineering | Sechilariu M.,CNRS Urban Systems Engineering | Locment F.,CNRS Urban Systems Engineering
IEEE International Symposium on Industrial Electronics | Year: 2015

This paper presents an optimal scheduling and real-time power management for islanded microgrid. Based on prediction data, a multi-objective cost function is formulated aiming to minimize the total energy cost by reducing the diesel-generator fuel consumption and load shedding, while respecting the storage parameters and microgrid operation constraints. The problem is solved with two different optimization algorithms. Simulation results prove that the mixed integer linear programing optimization permits to obtain the lower total energy cost for real-time power balancing. © 2015 IEEE.

Locment F.,CNRS Urban Systems Engineering | Sechilariu M.,CNRS Urban Systems Engineering
Energies | Year: 2015

This paper focuses on the evaluation of theoretical and numerical aspects related to an original DC microgrid power architecture for efficient charging of plug-in electric vehicles (PEVs). The proposed DC microgrid is based on photovoltaic array (PVA) generation, electrochemical storage, and grid connection; it is assumed that PEVs have a direct access to their DC charger input. As opposed to conventional power architecture designs, the PVA is coupled directly on the DC link without a static converter, which implies no DC voltage stabilization, increasing energy efficiency, and reducing control complexity. Based on a real-time rule-based algorithm, the proposed power management allows self-consumption according to PVA power production and storage constraints, and the public grid is seen only as back-up. The first phase of modeling aims to evaluate the main energy flows within the proposed DC microgrid architecture and to identify the control structure and the power management strategies. For this, an original model is obtained by applying the Energetic Macroscopic Representation formalism, which allows deducing the control design using Maximum Control Structure. The second phase of simulation is based on the numerical characterization of the DC microgrid components and the energy management strategies, which consider the power source requirements, charging times of different PEVs, electrochemical storage ageing, and grid power limitations for injection mode. The simulation results show the validity of the model and the feasibility of the proposed DC microgrid power architecture which presents good performance in terms of total efficiency and simplified control. © 2015 by the authors.

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