Data-Driven Regionalization of Decarbonized Energy Systems for Reflecting Their Changing Topologies in Planning and Optimization

The decarbonization of energy systems has led to a fundamental change in their topology since generation is shifted to locations with favorable renewable conditions. In planning, this change is reflected by applying optimization models to regions within a country to optimize the distribution of generation units and to evaluate the resulting impact on the grid topology. This paper proposes a globally applicable framework to find a suitable regionalization for energy system models with a data-driven approach. Based on a global, spatially resolved database of demand, generation, and renewable profiles, hierarchical clustering with fine-tuning is performed. This regionalization approach is applied by modeling the resulting regions in an optimization model including a synthesized grid. In an exemplary case study, South Africa’s energy system is examined. The results show that the data-driven regionalization is beneficial compared to the common approach of using political regions. Furthermore, the results of a modeled 80% decarbonization until 2045 demonstrate that the integration of renewable energy sources fundamentally changes the role of regions within South Africa’s energy system. Thereby, the electricity exchange between regions is also impacted, leading to a different grid topology. Using clustered regions improves the understanding and analysis of regional transformations in the decarbonization process

Electrification seeds-A fiexible approach for decentralized electricity supply in developing countries

There are currently more than 500 million people without access to electricity on the African continent alone. With an expected strong population growth and the global goals for reducing carbon emissions, the challenge of providing electricity for all is tremendous. We present an approach that tackles electrification bottom-up in a decentral approach from so-called electrification seeds: Business owners or public institutions that invest in an electricity system to ensure reliable electricity supply for themselves may serve as a seed by also selling elec-tricity in their surroundings via mini-or microgrids. This approach will allow for cheaper solutions due to economies of scale. While private households can also be addressed by simple solutions e.g. solar home systems, the power of the electrification seed approach is that it can also provide enough secure power for small and medium enterprises (SME) and thus drive economic development. It is important to address the individual environment of the respective electrification seed, since there is no standard solution. To do so, the method includes an entire toolchain from estimating demands and structures with satellite data and Geographic Information System (GIS) software over employing an energy system model for finding the optimal technological design. As a last step, the viability of the electrification seed concept is verified with an exemplary business plan. The results show positive business cases for the electrification seed and a reduction of electricity costs for end-customers by 11.3 %. Altogether, this gives a very optimistic outlook of the suggested approach to support the great challenge of sustainable electrification for economic growth in developing countries. (c) 2021 International Energy Initiative. Published by Elsevier Inc. All rights reserved

Data-Driven Regionalization of Decarbonized Energy Systems for Reflecting Their Changing Topologies in Planning and Optimization

The decarbonization of energy systems has led to a fundamental change in their topology since generation is shifted to locations with favorable renewable conditions. In planning, this change is reflected by applying optimization models to regions within a country to optimize the distribution of generation units and to evaluate the resulting impact on the grid topology. This paper proposes a globally applicable framework to find a suitable regionalization for energy system models with a data-driven approach. Based on a global, spatially resolved database of demand, generation, and renewable profiles, hierarchical clustering with fine-tuning is performed. This regionalization approach is applied by modeling the resulting regions in an optimization model including a synthesized grid. In an exemplary case study, South Africa’s energy system is examined. The results show that the data-driven regionalization is beneficial compared to the common approach of using political regions. Furthermore, the results of a modeled 80% decarbonization until 2045 demonstrate that the integration of renewable energy sources fundamentally changes the role of regions within South Africa’s energy system. Thereby, the electricity exchange between regions is also impacted, leading to a different grid topology. Using clustered regions improves the understanding and analysis of regional transformations in the decarbonization process

Pathways toward a Decarbonized Future—Impact on Security of Supply and System Stability in a Sustainable German Energy System

Pathways leading to a carbon neutral future for the German energy system have to deal with the expected phase-out of coal-fired power generation, in addition to the shutdown of nuclear power plants and the rapid ramp-up of photovoltaics and wind power generation. An analysis of the expected impact on electricity market, security of supply, and system stability must consider the European context because of the strong coupling—both from an economic and a system operation point of view—through the cross-border power exchange of Germany with its neighbors. This analysis, complemented by options to improve the existing development plans, is the purpose of this paper. We propose a multilevel energy system modeling, including electricity market, network congestion management, and system stability, to identify challenges for the years 2023 and 2035. Out of the results, we would like to highlight the positive role of innovative combined heat and power (CHP) solutions securing power and heat supply, the importance of a network congestion management utilizing flexibility from sector coupling, and the essential network extension plans. Network congestion and reduced security margins will become the new normal. We conclude that future energy systems require expanded flexibilities in combination with forward planning of operation

Medical history of coronary artery disease and time to electrocardiogram in the emergency department: a real-life, single-center, retrospective analysis

Background Timely acquisition of 12-lead Electrocardiogram (ECG) in the emergency department (ED) is crucial and recommended by current guidelines. Objectives To evaluate the association of medical history of coronary artery disease (hCAD) on door-to-ECG time in the ED. Methods In this single center, retrospective cohort study, patients admitted to ED for cardiac evaluation were grouped according to hCAD and no hCAD. The primary outcome was door-to-ECG time. A multivariate analysis adjusted for the cofounders sex, age, type of referral and shift was performed to evaluate the association of hCAD with door-to-ECG time. Results 1101 patients were included in this analysis. 362 patients (33%) had hCAD. Patients with hCAD had shorter door-to-ECG time (20 min. [Inter Quartile Range [IQR] 13-30] vs. 22 min. [IQR 14-37]; p < 0.001) when compared to patients with no hCAD. In a multivariable regression analysis hCAD was significantly associated with a shorter door-to-ECG time (- 3 min [p = 0.007; 95% confidence Interval [CI] - 5.16 to - 0.84 min]). Conclusion In this single center registry, hCAD was associated with shorter door-to-ECG time. In patients presenting in ED for cardiac evaluation, timely ECG diagnostic should be facilitated irrespective of hCAD

The Cdkn1a(SuPER) Mouse as a Tool to Study p53-Mediated Tumor Suppression

Cdkn1a, which encodes p21, functions as a major route for p53-mediated cell-cycle arrest. However, the consequence of Cdkn1a gene dosage on tumor suppression has not been systematically investigated. Here, we employed BAC transgenesis to generate a Cdkn1a(SUPER) mouse, which harbors an additional Cdkn1a allele within its natural genomic context. We show that these mice display enhanced cell-cycle arrest and reduced apoptosis in response to genotoxic stress. Furthermore, using a chemically induced skin cancer model and an autochthonous Krasdriven lung adenocarcinoma model, we show that Cdkn1a(SUPER) mice display a cancer protection phenotype that is indistinguishable from that observed in Tp53 suPER animals. Moreover, we demonstrate that Tp53 and Cdkn1a cooperate in mediating cancer resistance, using a chemically induced fibrosarcoma model. Overall, our Cdkn1a(SUPER )allele enabled us to assess the contribution of Cdkn1a to Tp53-mediated tumor suppression