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Executive Summary: The EC Directive 2013/59/Euratom states in article 56 that exposures of target volumes in nuclear medicine treatments shall be individually planned and their delivery appropriately verified. The Directive also mentions that medical physics experts should always be appropriately involved in those treatments. Although it is obvious that, in nuclear medicine practice, every nuclear medicine physician and physicist should follow national rules and legislation, the EANM considered it necessary to provide guidance on how to interpret the Directive statements for nuclear medicine treatments. For this purpose, the EANM proposes to distinguish three levels in compliance to the optimization principle in the directive, inspired by the indication of levels in prescribing, recording and reporting of absorbed doses after radiotherapy defined by the International Commission on Radiation Units and Measurements (ICRU): Most nuclear medicine treatments currently applied in Europe are standardized. The minimum requirement for those treatments is ICRU level 1 ("activity-based prescription and patient-averaged dosimetry"), which is defined by administering the activity within 10% of the intended activity, typically according to the package insert or to the respective EANM guidelines, followed by verification of the therapy delivery, if applicable. Non-standardized treatments are essentially those in developmental phase or approved radiopharmaceuticals being used off-label with significantly (> 25% more than in the label) higher activities. These treatments should comply with ICRU level 2 ("activity-based prescription and patient-specific dosimetry"), which implies recording and reporting of the absorbed dose to organs at risk and optionally the absorbed dose to treatment regions. The EANM strongly encourages to foster research that eventually leads to treatment planning according to ICRU level 3 ("dosimetry-guided patient-specific prescription and verification"), whenever possible and relevant. Evidence for superiority of therapy prescription on basis of patient-specific dosimetry has not been obtained. However, the authors believe that a better understanding of therapy dosimetry, i.e. how much and where the energy is delivered, and radiobiology, i.e. radiation-related processes in tissues, are keys to the long-term improvement of our treatments. [ABSTRACT FROM AUTHOR]

Glued laminated timber made from hardwood is a sustainable structural product that is currently gaining momentum due to climatic changes and afforestation policy. Diversities in hardwood species have led to a lack of a complete standard for the production of glued laminated timber from hardwood in Europe. This paper addresses hardwood species available in Croatian forests, namely Carpinus Betulus L. (European hornbeam), Quercus Cerris L. (Turkey oak), and Acer Campestre L. (Maple), in terms of their suitability for the production of glued laminated timber. The suitability is assessed by a multi‐criteria analysis with seven criteria. Visual and physical properties include density, the occurrence of knots, and grain deviation in lamellas. Mechanical properties include the bending strength, modulus of elasticity, and shear strength of glue lines. In order to obtain physical and mechanical properties, corresponding experimental research has been carried out. Production costs have been evaluated in collaboration with the manufacturer. Results indicate a very high potential of European hornbeam and Turkey oak for the production of glued laminated timber. [ABSTRACT FROM AUTHOR]

The paper addresses a real-time optimization-based reference calculation integrated with a control structure for Modular Multilevel Converters (MMC) operating under normal and constrained situations (where it has reached current and/or voltage limitations, as it may occur during system faults). Firstly, a nonlinear optimization problem has been developed in which it prioritizes to satisfy the AC grid current set-points imposed by the transmission System Operator (TSO). The constrained nonlinear optimization problem is formulated based on the steady-state model of the MMC, whereby the prioritization is achieved through distinct weights defined in the Objective Function’s (OF) terms. The resultant optimization problem, however, is highly nonlinear requiring high computation burden to be solved in real-time. To cope with this issue, this paper applies a Linear Time-Varying (LTV) approximation, which permits to represent the nonlinear dynamics of the system as constant parameters, while a Linear Time-Invariant (LTI) system is used to formulate the optimization constraints. The converter’s current references are determined in real-time by solving a constrained linearized optimization problem at each control time step, which considers the TSO’s demands, the current MMC operating point and its physical limitations. Theoretical analyses comparing the responses of the linear and nonlinear optimization problems are performed to validate the accuracy of the LTV approximation. Finally, the linearized-optimization problem is integrated with the MMC controllers, evaluated under different AC and DC network conditions and compared with conventional control strategies, where it is shown that the presented method can be potentially employed to obtain the MMC current references for distinct network scenarios. [ABSTRACT FROM AUTHOR]

Determining contingency aware dispatch decisions by solving a security-constrained optimal power flow (SCOPF) is challenging for real-world power systems, as the high problem dimensionality often leads to impractical computational requirements. This problem becomes more severe when the SCOPF has to be solved not only for a single instance, but for multiple periods, e.g. in the context of electricity market analyses. This paper proposes an algorithm that identifies the minimal set of constraints that exactly define the space of feasible nodal injections for a given network and contingency scenarios. By internalizing the technical limits of the nodal injections and enforcing a minimal worst-case impact of contingencies to line flows, computational effort can be further improved. The case study applies and analyzes the methods on the IEEE 118 and A&M 2000 bus systems, as well as the German and European transmission systems. In all tested cases the proposed algorithm identifies at least 95% of the network and security constraints as redundant, leading to significant SCOPF solve time reductions. Scalability and practical implementation are explicitly discussed. The code and input data of the case study is published supplementary to the paper under an open-source license. [ABSTRACT FROM AUTHOR]

Moving towards regional Supergrids, an increasing number of interconnections are formed by High Voltage Direct Current (HVDC) lines. Currently, in most regions, HVDC losses are not considered in market operations, resulting in additional costs for Transmission System Operators (TSOs). Nordic TSOs have proposed the introduction of HVDC loss factors in the market clearing algorithm, to account for the cost of losses and avoid HVDC flows between zones with zero price difference. In this paper, we introduce a rigorous framework to assess the introduction of loss factors, in particular HVDC loss factors, in nodal and zonal pricing markets. First, we focus on the identification of an appropriate loss factor. We propose and compare three different models: constant, linear, and piecewise linear. Second, we introduce formulations to include losses in market clearing algorithms. Carrying numerical tests for a whole year, we find that accounting only for HVDC or AC losses may lead to lower social welfare for a non-negligible amount of time. To counter this, this paper introduces a framework for including both AC and HVDC losses in a zonal or nodal pricing environment. We show both theoretically and through simulations that such a framework is guaranteed to increase social welfare. [ABSTRACT FROM AUTHOR]

• A single IDF model valid for various return periods and durations is developed. • New scaling models of design rainfall curves are presented. • Adjusted rainfall event durations are considered in the context of scale invariance. • Parsimonious intensity–duration–frequency (IDF) structure is obtained. • Good fit to quantile predictions of extreme rainfall data for specified durations. This paper deals with intensity–duration–frequency (IDF) curves, which express the relationship between average rainfall intensity and event duration for various probabilities of non-exceedance (or return periods) for the design/analysis of hydraulic interventions and infrastructures in riverine and urban drainage contexts. New scaling models are proposed to develop a single IDF model valid for all durations, from below 1 h to 24 h. In these models, the scale invariance is applied to rainfall intensity to obtain a parsimonious IDF structure capable of defining a family of IDF curves at various return periods. The main novelty consists of the formulation of simple and multiple scale invariance based on adjusted design event durations. The parameterization is carried out in two phases: in the first phase, the adjustment size is searched for iteratively while the other parameters of the IDF structure are directly obtained in cascade; in the second phase, which enables considering different reliability levels for extreme rainfall data as a function of sample length at different durations, parameter refinement is carried out by means of a local optimization algorithm. The second step accommodates data samples of different extension as a function of available data at different durations. The application to four case studies at various latitudes in Europe, namely Helsinborg (Sweden), Frauenwald (Germany), Pavia and Erice (Italy), proves the IDF structure to fit well the quantile predictions of extreme rainfall data for specified durations below and above one hour. [ABSTRACT FROM AUTHOR]

With Europe dedicated to limiting climate change and greenhouse gas emissions, large shares of Renewable Energy Sources (RES) are being integrated in the national grids, phasing out conventional generation. The new challenges arising from the energy transition will require a better coordination between neighboring system operators to maintain system security. To this end, this paper studies the benefit of exchanging primary frequency reserves between asynchronous areas using the Supplementary Power Control (SPC) functionality of High-Voltage Direct-Current (HVDC) lines. First, we focus on the derivation of frequency metrics for asynchronous AC systems coupled by HVDC interconnectors. We compare two different control schemes for HVDC converters, which allow for unilateral or bilateral exchanges of reserves between neighboring systems. Second, we formulate frequency constraints and include them in a unit commitment problem to ensure the N-1 security criterion. A data-driven approach is proposed to better represent the frequency nadir constraint by means of cutting hyperplanes. Our results suggest that the exchange of primary reserves through HVDC can reduce up to 10% the cost of reserve procurement while maintaining the system N-1 secure. [ABSTRACT FROM AUTHOR]

Securing profits from energy, reserve capacity and balancing markets is critical to ensure the profitability of battery energy systems (BES). However, the intimate connection between offers on these trading floors combined with the limited energy storage capacity of BES renders its scheduling very complex. In this paper, we develop a bilevel optimization problem for strategic participation of a BES in the day-ahead energy-reserve and balancing markets, improving the state-of-the-art by (i) considering the conditional-value-at-risk; (ii) ensuring the real-time feasibility of the obtained day-ahead schedule; (iii) addressing the operational underperformance risk stemming from inaccurate battery modeling. In a case study, we illustrate how the proposed model allows risk-averse BES owners to hedge their day-ahead position without jeopardizing their expected profit, while ensuring the feasibility of their day-ahead schedule. [ABSTRACT FROM AUTHOR]

Štore Steel Ltd. is one of the major flat spring steel producers in Europe. Among several hundred steel grades, 70MnVS4 steel is also produced. In the paper optimization of steelmaking of 70MnVS4 steel is presented. 70MnVS4 is a high-strength microalloyed steel which is used for forging of connecting rods in the automotive industry. During 70MnVS4 ladle treatment, the sulfur addition in the melt should be conducted only once. For several reasons the sulfur is repeatedly added and therefore threatening clogging during continuous casting and as such influencing surface defects occurrence and steel cleanliness. Accordingly, the additional sulfur addition was predicted using linear regression and genetic programming. Following parameters were collected within the period from January 2018 to December 2018 (78 consequently cast batches): sulfur and carbon cored wire addition after chemical analysis after tapping, carbon, manganese and sulfur content after tapping, time between chemical analysis after tapping and starting of the casting, ferromanganese and ferrosilicon addition and additional sulfur cored wire addition. Based on modelling results it was found out that the ferromanganese is the most influential parameter. Accordingly, 12 consequently cast batches (from February 2019 to October 2019) were produced with as lower as possible addition of ferromanganese. The additional sulfur addition in all 12 cases was not needed. Also, the melt processing time, surface quality of rolled material and sulfur cored wire consumption did not change statistically significantly after reduction of ferromanganese addition. The steel cleanliness was statistically significantly better. [ABSTRACT FROM AUTHOR]

In this paper, we present a two-stage model of zonal electricity markets with day-ahead market clearing and real-time re-dispatch and balancing that accounts for transmission line switching at both stages. We show how the day-ahead problem with switching can be formulated as an adaptive robust optimization problem with mixed integer recourse and present a new algorithm for solving the adversarial max-min problem that obeys the structure of an interdiction game. We apply the model on a realistic instance of the Central Western European system and comment on the impacts of both proactive and reactive transmission switching on the operating costs of the system. Part I presents day-ahead models of a short-term zonal electricity market with switching, and describes our algorithmic approach for solving these models efficiently. Part II describes variants of the real-time model, and presents the results of our case study on the Central Western European market. [ABSTRACT FROM AUTHOR]

In this paper, we present a two-stage model of zonal electricity markets with day-ahead market clearing, and real-time re-dispatch and balancing that accounts for transmission line switching at both stages. We show how the day-ahead problem with switching can be formulated as an adaptive robust optimization problem with mixed integer recourse, and present a new algorithm for solving the adversarial max-min problem that obeys the structure of an interdiction game. We apply the model on a realistic instance of the Central Western European system, and comment on the impacts of both proactive, and reactive transmission switching on the operating costs of the system. Part I presents day-ahead models of a short-term zonal electricity market with switching, and describes our algorithmic approach for solving these models efficiently. Part II describes variants of the real-time model, and presents the results of our case study on the Central Western European market. [ABSTRACT FROM AUTHOR]

In this paper, shaped continuous parallel plate waveguide delay lenses are proposed. The previous configurations introduced by the authors displayed a residual side lobe imbalance, showing the limitations of elliptical delay lens profiles, derived from a starting bifocal constrained lens. Polynomial profiles are proposed here as a way to enhance the scanning performance and the pattern shape. Optimized configurations demonstrate a reduction in the phase aberration levels over a large scanning range ([−30°, 30°]). The associated radiation patterns demonstrate lower and more balanced first side lobe levels (SLLs) ($\cong -18$ dB), as compared to the previous elliptical approach ($\cong -13.2$ dB). A validation has been proposed through the manufacturing and test of a prototype over the down-link Ka-band ([27.5–31] GHz). Excellent radiation performance [half-power beamwidth (HPBW), SLL] has been experimentally obtained over a wide angular range ([−31.5°, 31.5°]), including low scanning loss and high radiation stability over the entire frequency range. High radiation efficiencies are demonstrated with this fully metallic design, particularly suitable for space applications. The mechanical simplicity offered by the concept is also quite attractive for low-cost multi-beam platforms. [ABSTRACT FROM AUTHOR]

The market of batteries for electric mobility is expected to greatly expand in Europe during the next decades. The most sustainable batteries to be produced in the future depend on the primary and secondary resources available and on the capacity to produce and recycle battery cells. This paper proposes an optimization model based on Material Flow Analysis and prospective Life Cycle Assessment which allows us to suggest the types of batteries which should be produced and recycled, the primary and secondary resources to be used, and in which quantities. Several scenarios are proposed to address the uncertainty of the future batteries market. In the Reference Scenario, designed to reflect the European policies, the results show that Europe would achieve high self-sufficiency from external producers (72%), but this percentage could decrease drastically in the case of alternative scenarios (up to 35%). Furthermore, in the Reference Scenario, lithium-iron-phosphates (40%) and lithium-air (23%) batteries result to be the best options. To cut the consumption of lithium and cobalt, sodium-ion cells (3%) could also be considered for manufacturing or even nickel-cobalt-manganese (6%) type to exploit secondary cobalt. In alternative scenarios instead, the proposed algorithm would suggest different choices as a function of the boundary conditions. For instance, in case the demand and the re-use rate of the cells are higher than in the Reference Scenario, the environmental impact of batteries for mobility turns out to increase because of the lower self-sufficiency of the European industry. • Material flow analysis and prospective LCA are integrated into an optimization model. • Several scenarios are set to address the uncertainty of the future batteries industry. • The European batteries' production and recycling to cut GHG emissions are assessed. • The optimal management of primary and secondary resources is evaluated in time. • The model evaluates the batteries industry's relevant GHG mitigation (up to −45%). [ABSTRACT FROM AUTHOR]

A novel model for the clearing of European day-ahead electricity markets, with all associated types of orders, namely simple hourly orders, block orders, complex orders and PUN (“Prezzo Unico Nazionale”) orders is presented in this paper. An iterative algorithm is employed for the market clearing, bearing an inner iteration process for the handling of Paradoxically Accepted block and MIC orders, and an outer iteration process for the handling of PUN orders. During the iterative process a Master Problem and a PUN subproblem are sequentially solved and coordinated, for the efficient handling of all order clearing conditions and market and/or system constraints. The clearing conditions of each order type are explicitly incorporated in the PUN subproblem, formulating a Mixed Complementarity Problem bearing both primal and dual decision variables. The PUN subproblem concerns the sequential clearing of 24 hourly subproblems, employing a special technique for handling the possible inefficiencies due to the myopic nature of the hourly subproblem solutions, leading to enhanced behavior in terms of social surplus with respect to the state-of-the-art day-ahead market clearing solver. The model and the algorithmic process are evaluated in a west-European test case, demonstrating minimal computational requirements and proving its excellent escalation capabilities. [ABSTRACT FROM AUTHOR]

The challenge in vehicle and crew scheduling is to arrange a given set of bus trips into running boards while minimizing certain objectives and complying with a given set of constraints. This scheduling was solved several tens years ago manually by a dispatcher who used his skill, experience, knowledge of history, and intuition. This attitude worked quite well in small instances but could not be applied in larger ones. Development of computers brought opportunities to build computerized vehicle and crew optimization systems. This paper describes a computer system KASTOR developed for vehicle and crew optimization, which complies with the special requirements of Czech and Slovak bus providers, and is significantly different from those in some west European countries. [ABSTRACT FROM AUTHOR]

Background Agri-food is one of the most important sectors of the industry in Europe and potentially a major contributor to the global warming. Sustainability issues in this context pose a huge challenge for several reasons: the variety of considered scales, the number of disciplines involved, the uncertainties, the out-of-equilibrium states, the complex quantitative and qualitative factors, the normative issues and the availability of data. Although important insight and breakthroughs have been attained in different scientific domains, an overarching and integrated analysis of these complex problems have yet to be realized. Scope and Approach This context creates huge opportunities for research in interaction with mathematical programming, integrative models and decision-support tools. The paper propose a computational viewpoint including questions of holistic approach, multiscale reconstruction and optimization. Some directions are discussed. Key Findings and Conclusions Several research questions based on a mathematical programming framework are emerging: how can such a framework manage uncertainty, cope with complex qualitative and quantitative information essential for social and environmental considerations, encompass diverse scales in space and time, cope with a multivariable dynamic environment and with scarcity of data. Moreover, how can it deal with different perspectives, types of models, research goals and data produced by conceptually disjoint scientific disciplines, ranging from physics and physiology to sociology and ethics? Building models is essential, but highly difficult; it will need a strong iterative interaction combining computational intensive methods, formal reasoning and the experts of the different fields. Some future research directions are proposed, involving all those dimensions: mathematical resilience, human-machine interactive learning and optimization techniques. [ABSTRACT FROM AUTHOR]

Numerous Life Cycle Analysis of bread pointed out that wheat production and transportation have important impacts on the environment. But wheat is grown all around the world and it is not always consumed where it is produced. In this paper an analysis of the wheat movements around Europe is done, taking special attention on the Spanish situation. An optimization of wheat exchanges is done eliminating the import–export overlapping. This optimization entails a reduction of the number of trips by 34% and the CO 2 emissions reduction due to transportation is calculated to be 121.175 tones. Consequently less trips, fewer trucks, less traffic and lower emissions that brings economic, social and environmental benefits. [ABSTRACT FROM AUTHOR]

A novel experimental approach of inter- and intramodel comparisons is conducted with five power market models to give recommendations for modelers working on decarbonization pathways of Europe until 2050. The experiments investigate the impact of model type (optimization vs. simulation), planning horizon (intertemporal vs. myopic), temporal resolution (8760 vs. 384 h), and spatial resolution (28 countries vs. 12 mega-regions). The model type fundamentally determines the evolution of capacity expansion. Planning horizon (assumed foresight of firms) plays a minor role for scenarios with high carbon prices. For low carbon prices in turn, results from myopic models deviate considerably from those of intertemporal models. Lower temporal and spatial resolutions foster wind power via storage and via neglected transmission boundaries, respectively. Using simulation instead of optimization frameworks, a shorter planning horizon of firms, or lower temporal and spatial resolutions might be necessary to reduce the computational complexity. This paper delivers recommendations on how to limit the discrepancies in such cases. • Comparison of five power market models with harmonized input data and model features. • Evaluating the role of model type, planning horizon, spatial and temporal resolution. • Model type decisive for investment decisions. • Myopic modeling hardly changes variable renewable energy expansion but might favor conventional power plants. • Spatial and temporal resolution crucial for ease of variable renewable energy integration. [ABSTRACT FROM AUTHOR]