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Abstract This study proposes a methodology for sizing and operating new flexibility options within a German carpentry, targeting to be operated as Net Zero Energy Factory (NZEF). A key element of this system is the maximization of the integration of the electric power locally generated by a photovoltaic plant and the electric demand for driving the manufacturing processes. This aim is achieved with a proper integration between design choices in terms flexibility options and optimal control of energy fluxes. In this work, benefits and criticalities arising from the integration of different flexibility options, such as stationary and mobile Energy Storage Systems, are identified and analyzed. A double step optimization process is implemented. First, a Model Predictive Control strategy is used to schedule the manufacturing machines and the energy storage systems (stationary and mobile). Then, a multi-objective optimization aiming at the minimization of annual energy grid exchange and the optimal exploitation of battery capacity is carried out with the Genetic Algorithm. Such a methodology allows the factory operators to optimally size the flexibility capacity (the battery energy storage in this application) needed to operate their industrial facility as a net-zero energy factory. Results show that an optimally controlled stationary energy storage system allows a reduction of energy exchange with the grid up to 53%. The further introduction of electric vehicles increases of about 5% and 67% the renewable energy self-consumption and carbon emissions savings, respectively, ensuring also a significant increase in the yearly annual savings (up to 406%).

Policies to reduce carbon emissions from electricity generation will be crucial for negotiations at the UN climate conference (COP21) in Paris. In 2012, we presented data in Nature Materials on the contribution that photovoltaic (PV) power plants installed in Germany, Italy and the UK are making to reducing greenhouse emissions. Here we update our analysis with three more years worth of data, extending our study not only to other countries but also to wind power and bio-electricity generation. This analysis focuses mainly on the technical feasibility of an electricity supply based on all-renewable sources; more detailed cost considerations will be discussed in a forthcoming work.

We report on the application of ZnO:Al as the transparent conductive oxide in high performance inverted polymer solar cells. We show that the optimized inverted architecture, which does not contain low work function metals or water-based transport layers, can be employed without sacrificing device efficiency. The widely studied P3HT:PCBM donor–acceptor system was chosen for the active layer. ZnO:Al layers were produced by dc-magnetron sputtering on glass substrates and used as the cathode. The thickness of ZnO:Al was optimized to achieve a low sheet resistance while maintaining high transmission. The resulting ZnO:Al layers were smoother than the reference ITO samples, and the active layers could be processed directly onto ZnO:Al without employing additional buffer layers. The structure of the top anodic contact was also optimized. Initial devices with an Au layer demonstrated poor results, and device performance improved when a MoO3/Ag anode was used. Control devices in the standard forward structure using commercial ITO coated glass substrates were compared to the ZnO:Al based cells. Higher photocurrents were obtained in the inverted structures than in the ITO-based solar cells due to the higher transmittance of ZnO:Al in the spectral range where the blend absorbs.

Abstract This case study of the Society of Environmental Toxicology and Chemistry (SETAC) workshop MODELINK demonstrates the potential use of mechanistic effects models for macrophytes to extrapolate from effects of a plant protection product observed in laboratory tests to effects resulting from dynamic exposure on macrophyte populations in edge-of-field water bodies. A standard European Union (EU) risk assessment for an example herbicide based on macrophyte laboratory tests indicated risks for several exposure scenarios. Three of these scenarios are further analyzed using effect models for 2 aquatic macrophytes, the free-floating standard test species Lemna sp., and the sediment-rooted submerged additional standard test species Myriophyllum spicatum. Both models include a toxicokinetic (TK) part, describing uptake and elimination of the toxicant, a toxicodynamic (TD) part, describing the internal concentration-response function for growth inhibition, and a description of biomass growth as a function of environmental factors to allow simulating seasonal dynamics. The TK–TD models are calibrated and tested using laboratory tests, whereas the growth models were assumed to be fit for purpose based on comparisons of predictions with typical growth patterns observed in the field. For the risk assessment, biomass dynamics are predicted for the control situation and for several exposure levels. Based on specific protection goals for macrophytes, preliminary example decision criteria are suggested for evaluating the model outputs. The models refined the risk indicated by lower tier testing for 2 exposure scenarios, while confirming the risk associated for the third. Uncertainties related to the experimental and the modeling approaches and their application in the risk assessment are discussed. Based on this case study and the assumption that the models prove suitable for risk assessment once fully evaluated, we recommend that 1) ecological scenarios be developed that are also linked to the exposure scenarios, and 2) quantitative protection goals be set to facilitate the interpretation of model results for risk assessment. Integr Environ Assess Manag 2016;12:82–95. ©2015 SETAC Key Points We use an herbicide case study to demonstrate how toxicodynamics-toxicokinetics models coupled with macrophyte population models can link dynamic exposure patterns to expected biomass dynamics in the field. We introduce models for 2 macrophyte species, Lemna sp. and Myriophyllum spicatum to refine a risk assessment based on laboratory experiments. Based on specific protection goals, we propose example criteria for duration and magnitude of effects and show how the modeling results could be used as risk refinement option. We recommend further refining and testing the models to develop ecological scenarios linked to the exposure scenarios and to set quantitative protection goals to facilitate the interpretation of model results for risk assessment.

Abstract Hydrogen production systems supplied by photovoltaic solar energy have nonlinear dynamics and discontinuities which must be taken into account when a control system is applied. The main purpose of the control system is to maintain the electrolyzer current at the desired operating point and, at the same time, to optimize the grid energy consumption despite the solar energy variability. Classic controllers, like PID ones, are not able to obtain good performance over the whole operation range of these kinds of plants because of the aforementioned characteristics. To overcome these limitations, an optimal control strategy and a linear hybrid model predictive controller (HMPC) are applied to a hydrogen production system in this work. Regarding the optimal control design, a systematic framework is presented in order to obtain the optimal (in the sense of minimal grid energy consumption) trajectory of the states by converting the control problem into a boundary value problem by means of the Pontryagin’s Maximum Principle. Interestingly, the resulting control law is explicit and piecewise continuous. Regarding the linear HMPC strategy, a mixed logical dynamical description of the linearized equations of the system is considered in order to obtain the control law by solving an optimization problem in the form of a mixed integer quadratic programming. For this control strategy three cost functions associating the grid energy consumption and the electrolyzer efficiency are presented. The proposed controllers are tested through numerical simulations for both the nominal and uncertain cases and different performance indexes are considered. Finally, a discussion of the main advantages and disadvantages of each controller in real-life applications is presented.

AbstractThe transient expression of recombinant biopharmaceutical proteins in plants can suffer inter‐batch variation, which is considered a major drawback under the strict regulatory demands imposed by current good manufacturing practice (cGMP). However, we have achieved transient expression of the monoclonal antibody 2G12 and the fluorescent marker protein DsRed in tobacco leaves with ∼15% intra‐batch coefficients of variation, which is within the range reported for transgenic plants. We developed models for the transient expression of both proteins that predicted quantitative expression levels based on five parameters: The OD600nm of Agrobacterium tumefaciens (from 0.13 to 2.00), post‐inoculation incubation temperature (15–30°C), plant age (harvest at 40 or 47 days after seeding), leaf age, and position within the leaf. The expression models were combined with a model of plant biomass distribution and extraction, generating a yield model for each target protein that could predict the amount of protein in specific leaf parts, individual leaves, groups of leaves, and whole plants. When the yield model was combined with a cost function for the production process, we were able to perform calculations to optimize process time, yield, or downstream costs. We illustrate this procedure by transferring the cost function from a production process using transgenic plants to a hypothetical process for the transient expression of 2G12. Our models allow the economic evaluation of new plant‐based production processes and provide greater insight into the parameters that affect transient protein expression in plants. Biotechnol. Bioeng. 2012; 109: 2575–2588. © 2012 Wiley Periodicals, Inc.

AbstractMonolithic tandem cells involving a top cell with Si nanocrystals embedded in SiC (Si NC/SiC) and a c‐Si bottom cell have been prepared. Scanning electron microscopy shows that the intended cell architecture is achieved and that it survives the 1100 °C anneal required to form Si NCs. The cells exhibit mean open‐circuit voltages Voc of 900–950 mV, demonstrating tandem cell functionality, with ≤580 mV arising from the c‐Si bottom cell and ≥320 mV arising from the Si NC/SiC top cell. The cells are successfully connected using a SiC/Si tunnelling recombination junction that results in very little voltage loss. The short‐circuit current densities jsc are, at 0.8–0.9 mAcm−2, rather low and found to be limited by current collection in the top cell. However, equivalent circuit simulations demonstrate that in current‐mismatched tandem cells such as the ones studied here, higher jsc, when accompanied by decreased Voc, can arise from shunts or breakdown in the limiting cell rather than improved current collection from the limiting cell. This indicates that Voc is a better optimisation parameter than jsc for tandem cells where the limiting cell exhibits poor junction characteristics. The high‐temperature‐stable cell architecture developed in this work, coupled with simulations highlighting potential pitfalls in tandem cell analysis, provides a suitable route for optimisation of Si NC layers for photovoltaics on a tandem cell device level. Copyright © 2016 John Wiley & Sons, Ltd.

Our electrical world is changing. The journey we are on today parallels the era of Edison, Tesla, and Westinghouse in the early race for electrification. Change abounds: energy from nature, inverter-based technology, smart and smarter grids; decentralized power, and intercontinental interconnection. This new age of energy offers new choices and challenges, all heavily influenced by the practices that evolved over the past century and institutionalized in standards, interconnection requirements, grid codes, and technical regulatory policies. These standards drove the development of the electrical world, and now they play an important role in its transformation. We explore here the rapidly evolving standards world, one that is both the product of unprecedented technology and an environment for enabling even more technological advancements.