Using Anisotropic Diffusion for Coherence Estimation

In this paper we will present a new coherence estimation technique for SAR interferometry products that adapts the estimation window size and shape during processing. This is of particular interest for sensors with medium spatial resolution, like the ASAR WS mode, where the estimator shall cope with the spatial variability of the targets in the imaged area. This method is designed to remove low coherence magnitude bias while keeping a good spatial resolution. Finally, this new approach will be compared to an existing algorithm for quantifying resulting quality improvement

Decarbonizing Western Europe: Extension of the Model 'EnergyScope MultiCell' for the Analysis of Renewable Fuel Potential.

peer reviewe

A Robust Self-calibrating Transmission Scheme for On-Chip Networks

Systems-on-Chip (SoC) design involves several challenges, stemming from the extreme miniaturization of the physical features and from the large number of devices and wires on a chip. Since most SoCs are used within embedded systems, specific concerns are increasingly related to correct, reliable, and robust operation. We believe that in the future most SoCs will be assembled by using large-scale macro-cells and interconnected by means of on-chip networks. We examine some physical properties of on-chip interconnect busses, with the goal of achieving fast, reliable, and low-energy communication. These objectives are reached by dynamically scaling down the voltage swing, while ensuring data integrity-in spite of the decreased signal to noise ratio-by means of encoding and retransmission schemes. In particular, we describe a closed-loop voltage swing controller that samples the error retransmission rate to determine the operational voltage swing. We present a control policy which achieves our goals with minimal complexity; such simplicity is demonstrated by implementing the policy in a synthesizable controller. Such a controller is an embodiment of a self-calibrating circuit that compensates for significant manufacturing parameter deviations and environmental variations. Experimental results show that energy savings amount up to 42%, while at the same time meeting performance requirements

Multi-objective near-optimal necessary conditions for multi-sectoral planning

In the energy transition context, restructuring energy systems and making informed decisions on the optimal energy mix and technologies is crucial. Energy system optimisation models (ESOMs) are commonly used for this purpose. However, their focus on cost minimisation limits their usefulness in addressing other factors like environmental sustainability and social equity. Moreover, by searching for only one global optimum, they overlook diverse alternative solutions. This paper aims to overcome these limitations by exploring near-optimal spaces in multi-objective optimisation problems, providing valuable insights for decision-makers. The authors extend the concepts of epsilon-optimality and necessary conditions to multi-objective problems. They apply this methodology to a case study of the Belgian energy transition in 2035 while considering both cost and energy invested as objectives. The results reveal opportunities to reduce dependence on endogenous resources while requiring substantial reliance on exogenous resources. They demonstrate the versatility of potential exogenous resources and provide insights into objective trade-offs. This paper represents a pioneering application of the proposed methodology to a real-world problem, highlighting the added value of near-optimal solutions in multi-objective optimisation. Future work could address limitations, such as approximating the epsilon-optimal space, investigating parametric uncertainty, and extending the approach to other case studies and objectives, enhancing its applicability in energy system planning and decision-making.2ème révision7. Affordable and clean energ

Modeling the impact of energy sufficiency measures in European integrated energy systems using PyPSA-Eur

peer reviewedThe Paris Agreement, in which most countries set the goal to limit global warming to 1.5°C, calls for extensive coordinated efforts across multiple energy sectors. The EU aims at a net-zero greenhouse gas economy by 2050. The two primary focus areas to meet this target are deploying renewable technologies in the energy mix and increasing energy efficiency. Energy sufficiency is an essential aspect of the energy transition that is often overlooked or confused with energy efficiency. It refers to the reduction of energy consumption on individual and societal levels by adopting behaviors and practices that are less energy intensive. The adoption of energy-sufficiency measures can have significant benefits for the energy transition by reducing the overall energy demand, which can, in turn, reduce the need for new energy infrastructure and lower the system costs. In this study, PyPSA-Eur, a generation and transmission optimal expansion and dispatch model, is used to study the energy system of five interconnected countries while accounting for energy sufficiency measures across multiple energy sectors. The outcomes are then compared to a reference case and business-as-usual (BAU) scenario. The sufficiency measures assumed in this study lead to less investment costs in generation technologies and grid expansion compared to the BAU scenario. The findings suggest that energy-sufficiency measures can result in significant cost savings and emission reductions, and energy sufficiency combined with energy efficiency and VRE integration can play a crucial role in the energy transition compared to the pathways considering only energy efficiency and VRE integration.13. Climate actio

The energy return on investment of whole energy systems: application to Belgium

peer reviewedPlanning the defossilization of energy systems by facilitating high penetration of renewables and maintaining access to abundant and affordable primary energy resources is a nontrivial multi-objective problem. However, so far, most long-term policies to decrease the carbon footprint of our societies consider the cost of the system as the leading indicator in the energy system models. This paper is the first to develop a novel approach by adding the energy return on investment (EROI) to a whole energy system optimization model. We built the database with all EROI technologies and resources considered. In addition, moving away from fossil-based to carbon-neutral energy systems raises the issue of the uncertainty of low-carbon technologies and resource data. Thus, we conducted a global sensitivity analysis to identify the main parameters driving the variations in the EROI of the system. This novel approach can be applied to any energy system, and we use a real-world case study to illustrate the model: the 2035 Belgian energy system for several greenhouse gas emissions targets. The main results are threefold: (i) the EROI of the system decreases from 8.9 to 3.9 when greenhouse gas emissions are reduced by 5; (ii) the renewable fuels - mainly imported renewable gas - represent the largest share of the system primary energy mix; (iii) in the sensitivity analysis, the renewable fuels drive 67% of the variation of the EROI of the system for low greenhouse gas emissions scenarios. The decrease in the EROI raises questions about meeting the climate targets without adverse socio-economic impact. Most countries rely massively on fossil fuels, and they could encounter an EROI decline when shifting to carbon neutrality. Thus, this study demonstrates the importance of considering other criteria, such as EROI, in energy system models.7. Affordable and clean energ

Validation of Methods to Select a Priori the Number of Typical Days for Energy System Optimisation Models

Studying a large number of scenarios is necessary to consider the uncertainty inherent to the energy transition. Typical Days (TDs) clustering is a commonly used technique to ensure the computational tractability of energy system optimisation models. Its capability to approximate accurately the full-year time series with a reduced number of days has been demonstrated. However, its impact on the results of the energy system model is rarely studied and has never been studied on a multi-regional whole-energy system. To address this issue, we analyse the sensitivity of the energy system strategy to reach 90% direct emission reduction for Atlantic European countries. For each number of TDs, the technologies sizes and primary energy uses with an error below 5% are considered as well approximated. At 36 TDs, they cover more than 79.5% of the system’s total cost. This is the best trade-off found and it divides the computational cost by 6.3. Finally, we validate the classical method to select a priori the number of TDs by showing its strong correlation of -0.92 with the developed a posteriori metric