Nadia Maïzi

Key features of the electricity production sector through long-term planning : the French case

We present a view of a long-term French electricity production sector with a MARKAL approach. The aim of MARKAL is to optimise energy systems in the long- mid- term with an explicit description of the technologies used. Using the example of French electricity supply, we will illustrate the tools potential and provide the necessary technical information for assessing the extent to which MARKAL models provide a good opportunity for helping industry leaders and decision-makers who are involved in the electricity sector to make energy strategy choices-at regional, national and international level

Long-term planning and the sustainable power system: A focus on flexibility needs and network reliability

Long-term planning models are useful to describe future energy and technology options and to analyze environmental issues. They propose solutions for meeting future energy consumption. Focusing on the electricity sector, we argue that in order to provide a more relevant assessment of the power supply system ahead we need to tackle both flexibility needs and network reliability.

Optimal Passive Source Localization

In order to optimize the estimation of an objects position, this paper proposes a procedure for placing acoustical sensors in 3D space, using passive source localization. A standard performance measure in estimation theory is the Cramer-Rao Lower Bound (CRLB), which describes the lower bound of the variance of unbiased estimators. In the case of passive source localization, this bound depends on the sensor and source positions, as well as on the propagation speed and the assumptions made about the disturbance noise. A procedure for an optimal sensor placement, using this CRLB as the objective function, is described. In order to assure optimal coverage of a surveillance area, the average CRLB of multiple source positions (in this area) is minimized.

Optimal sensor configuration for passive position estimation

The goal of passive source localization is to acoustically detect objects producing noises by multiple sensors (e.g. microphones, hydrophones) and to estimate their position using only the sound information. While within the last four decades a lot of work was carried out on how to best measure the time delay of arrivals (TDOAs) and on finding an optimal location estimator, relatively little work can be found on how to best place the sensors. However, the performance of such estimators is strongly correlated to the sensor configuration. Therefore, we propose a procedure for an optimal sensor setup minimizing the condition numbers of an analytic linear least-squares (LLS) estimator and an iterative, linearized model (LM) estimator. An advantage of using the condition number as the cost function is that, unlike the Cramer Rao Lower Bound, it defines an upper bound for the estimation error. Further, no assumptions about the disturbance noise need to be made and a robust sensor configuration will be found, which is invariant to rotation and dilatation. The two condition numbers of the presented passive source localization algorithms are independent of the number of sensors. However, it will be shown, that the estimation error decreases proportionally to the inverse of the square-root of the number of sensors. Some analytical forms of optimal sensor configurations will be derived, which attain the global minimum of the condition number of the LLS estimator or which minimize the condition number of the LM estimator. Further, a sensor geometry using a minimum number of sensors is derived, which forces the condition numbers of both estimators equal to one. The interest of such a setup lies in a possible combination of both estimators. The LM estimator might then be initialized by the position estimate found by the LLS estimator. A variety of alternative estimators are closely related to the LLS estimator. Their performances will be compared, and it will be shown, that the optimal sensor geometry specially derived for the LLS estimator also increases their accuracies.

A Global Renewable Energy Roadmap: Comparing Energy Systems Models with IRENA’s REmap 2030 Project

In 2014, the International Renewable Energy Agency (IRENA) published a global renewable energy roadmap—called REmap 2030—to double the share of renewables in the global energy mix by 2030 compared to 2010 (IRENA, A Renewable Energy Roadmap, 2014a). A REmap tool was developed to facilitate a transparent and open framework to aggregate the national renewable energy plans and/or scenarios of 26 countries. Unlike the energy systems models by IEA-ETSAP teams, however, the REmap tool does not account for trade-offs between renewable energy and energy efficiency activities, system planning issues like path dependency and investments in the grid infrastructure, competition for scarce resources—e.g. biomass—in the commodity prices, or dynamic cost developments as technologies get deployed over time. This chapter compares the REmap tool with the IEA-ETSAP models at two levels: the results and the insights. Based on the results comparison, it can be concluded that the REmap tool can be used as a way to explicitly engage national experts, to scope renewable energy options, and to compare results across countries. However, the ETSAP models provide detailed insights into the infrastructure requirements, competition between technologies and resources, and the role of energy efficiency needed for planning purposes. These insights are particularly relevant for countries with infrastructure constraints and/or ambitious renewable energy targets. As more and more countries are turning to renewables to secure their energy future, the REmap tool and the ETSAP models have complementary roles to play in engaging policy makers and national energy planners to advance renewables.

Assessing the Impact of Smart Building Techniques: a Prospective Study for France

Saving energy is an essential lever in cutting our greenhouse gases emissions. Worldwide, the building sector is responsible for 40% of energy consumption. We focus on the French commercial sector in order to assess the gains that could be made by using smart building techniques over the long term (2030-2050). We use a long-term planning model based on a Markal/Times approach. We develop a specific way of modeling energy savings potential and energy conservation techniques. The commercial sectors energy consumption, sorted by energy carrier, sub-sector and end-use, is determined for the baseline year (2000). It is then extrapolated to 2050, using existing French prospective studies. Assumptions are made on the value of other external parameters, such as energy prices, technological evolution, etc. The model shows that smart building helps to reduce the commercial sectors overall consumption by 8%. This result remains stable when external parameters are modified: smart building solutions are robust. These solutions are complementary to passive (insulation) solutions, and they result in a reduction of the global cost of the energy system.

Multiobjective Robust Control via Youla Parametrization

Using Youla Parametrization and Linear Matrix Inequalities (LMI) a Multiobjective Robust Control (MRC) design for continuous linear time invariant (LTI) systems with bounded uncertainties is described. The design objectives can be a combination of H∞-, H2-performances, constraints on the control signal, etc.. Based on an initial stabilizing controller all stabilizing controllers for the uncertain system can be described by the Youla parametrization. Given this representation, all objectives can be formulated by independent Lyapunov functions, increasing the degree of freedom for the control design.

Modeling Ship Behavior based on Hidden Markov Models

Since 2001, works in the field of security have been considerably growing. All over the word, public places as markets, parkings, hotels, metro and train stations are permanently threatened by terroristic events. For this reason, researches are working every day to meet the need of security. In this article, we have been interested in securing harbors, equipements and people from any threatening event by studying, classifying and recognizing ships behaviors. We propose to use the probabilistic approach Hidden Markov Models (HMM) because of its promising performance in the field of behaviors learning and recognition. The idea is to gather the map of the port as well as ships trajectories in order to construct a set of models of all ships behaviors. Then, this set is exploited to classify every new ship trajectory moving in the harbor. Map of the harbor allowed the initialization of HMM models of ships behaviors, then the well-known Baum-Welch algorithm was chosen to learn models from ships trajectories obtained from port and finally the forward algorithm was used to classify and recognize every new ship behavior.

Electricity Prices in a Game Theory Context

We consider a model of an electricity market in which S suppliers offer electricity: each supplier Si offers a maximum quantity qi at a fixed price pi. The response of the market to these offers is the quantities bought from the suppliers. The objective of the market is to satisfy its demand at minimal price.

Long-Term Water and Energy Issues in European Power Systems

Abstract European countries are highly diverse in terms of their socioeconomic development, energy sources, power mixes, water access, and availability. At the same time, they need to develop their power systems and satisfy their water requirements. We propose to take a journey through this European diversity, crossing the Balkans, Norway, France, and southern Europe, to understand how water and power interweave. To do so, we focus on the following generation technologies: thermoelectric plants that use water to discharge waste heat and hydropower for its direct link with water (dam needs and evaporation) and also as a way of balancing the significant integration of intermittent renewable sources (solar and wind). We also look at how water constraints will impact future investments in the European power system on the 2050 horizon.