Analysis of North Sea offshore wind power variability

This paper evaluates, for a 2030 scenario, the impact on onshore power systems in terms of the variability of the power generated by 81 GW of offshore wind farms installed in the North Sea. Meso-scale reanalysis data are used as input for computing the hourly power production for offshore wind farms, and this total production is analyzed to identify the largest aggregated hourly power variations. Based on publicly available information, a simplified representation of the coastal power grid is built for the countries bordering the North Sea. Wind farms less than 60 km from shore are connected radially to the mainland, while the rest are connected to a hypothetical offshore HVDC (High-Voltage Direct Current) power grid, designed such that wind curtailment does not exceed 1% of production. Loads and conventional power plants by technology and associated cost curves are computed for the various national power systems, based on 2030 projections. Using the MATLAB-based MATPOWER toolbox, the hourly optimal power flow for this regional hybrid AC/DC grid is computed for high, low and medium years from the meso-scale database. The largest net load variations are evaluated per market area and related to the extra load-following reserves that may be needed from conventional generators.Parts of this work were funded by Agentschap.NL, the Netherlands, now RVO.nl (Rijksdienst voor Ondernemend Nederland [25], under the project North Sea Transnational Grid (NSTG). The NSTG project is a cooperation between Delft University of Technology and the Energy Research Center of the Netherlands

Long-Term Load Forecasting Considering Volatility Using Multiplicative Error Model

Long-term load forecasting plays a vital role for utilities and planners in terms of grid development and expansion planning. An overestimate of long-term electricity load will result in substantial wasted investment in the construction of excess power facilities, while an underestimate of future load will result in insufficient generation and unmet demand. This paper presents first-of-its-kind approach to use multiplicative error model (MEM) in forecasting load for long-term horizon. MEM originates from the structure of autoregressive conditional heteroscedasticity (ARCH) model where conditional variance is dynamically parameterized and it multiplicatively interacts with an innovation term of time-series. Historical load data, accessed from a U.S. regional transmission operator, and recession data for years 1993-2016 is used in this study. The superiority of considering volatility is proven by out-of-sample forecast results as well as directional accuracy during the great economic recession of 2008. To incorporate future volatility, backtesting of MEM model is performed. Two performance indicators used to assess the proposed model are mean absolute percentage error (for both in-sample model fit and out-of-sample forecasts) and directional accuracy.Comment: 19 pages, 11 figures, 3 table

New Cycle-based Formulation, Cost Function, and Heuristics for DC OPF Based Controlled Islanding

This paper presents a new formulation for intentional controlled islanding (ICI) of power transmission grids based on mixed-integer linear programming (MILP) DC optimal power flow (OPF) model. We highlight several deficiencies of the most well-known formulation for this problem and propose new enhancements for their improvement. In particular, we propose a new alternative optimization objective that may be more suitable for ICI than the minimization of load shedding, a new set of island connectivity constraints, and a new set of constraints for DC OPF with switching, and a new MILP heuristic to find initial feasible solutions for ICI. It is shown that the proposed improvements help to reduce the final optimality gaps as compared to the benchmark model on several test instances.Comment: https://doi.org/10.1016/j.epsr.2022.10858

Stabilizing role of platelet P2Y(12) receptors in shear-dependent thrombus formation on ruptured plaques

Background: In most models of experimental thrombosis, healthy blood vessels are damaged. This results in the formation of a platelet thrombus that is stabilized by ADP signaling via P2Y(12) receptors. However, such models do not predict involvement of P2Y(12) in the clinically relevant situation of thrombosis upon rupture of atherosclerotic plaques. We investigated the role of P2Y(12) in thrombus formation on (collagen-containing) atherosclerotic plaques in vitro and in vivo, by using a novel mouse model of atherothrombosis. Methodology: Plaques in the carotid arteries from Apoe(-/-) mice were acutely ruptured by ultrasound treatment, and the thrombotic process was monitored via intravital fluorescence microscopy. Thrombus formation in vitro was assessed in mouse and human blood perfused over collagen or plaque material under variable conditions of shear rate and coagulation. Effects of two reversible P2Y(12) blockers, ticagrelor (AZD6140) and cangrelor (AR-C69931MX), were investigated. Principal Findings: Acute plaque rupture by ultrasound treatment provoked rapid formation of non-occlusive thrombi, which were smaller in size and unstable in the presence of P2Y(12) blockers. In vitro, when mouse or human blood was perfused over collagen or atherosclerotic plaque material, blockage or deficiency of P2Y(12) reduced the thrombi and increased embolization events. These P2Y(12) effects were present at shear rates >500 s(-1), and they persisted in the presence of coagulation. P2Y(12)-dependent thrombus stabilization was accompanied by increased fibrin(ogen) binding. Conclusions/Significance: Platelet P2Y(12) receptors play a crucial role in the stabilization of thrombi formed on atherosclerotic plaques. This P2Y(12) function is restricted to high shear flow conditions, and is preserved in the presence of coagulation

Parametric Evaluation of Different ANN Architectures: Forecasting Wind Power Across Different Time Horizons

The participation of volatile wind energy resources in the generation mix of power systems is increasing. It is therefore becoming more and more crucial for system operators to accurately predict the wind power generation across different short term horizons (5 to 60 minutes ahead) in order to adequately balance the system and maintain system security. This paper presents a comprehensive assessment of the influence of different parameters in artificial neural networks, such as the amount of historic data, batch size, number of hidden layers, number of neurons per hidden layer, and the amount of training data on the short term forecast accuracy. In order to identify the parameters which are most influential with respect to forecast accuracy, a sensitivity study isolating the various factors on a one-At-A-Time basis has been performed. To minimize the forecast error across the investigated forecast horizons, the developed neural networks use the feed forward back propagation algorithm. From the investigated cases it is concluded that a neural network with two hidden layers is most suitable for wind forecasting on the timeframes considered. Furthermore, with increasing forecast horizons (from 5 to 60 minutes ahead), better performance is achieved when neural networks contain increased neurons in the hidden layers and have enlarged training data sets.Intelligent Electrical Power Grid

Synthesis of a polymyxin derivative for photolabeling studies in the gram-negative bacterium Escherichia coli

The antimicrobial activity of polymyxins against Gram-negative bacteria has been known for several decades, but the mechanism of action leading to cell death has not been fully explored. A key step after binding of the antibiotic to lipopolysaccharide (LPS) exposed at the cell surface is 'self-promoted uptake' across the outer membrane (OM), in which the antibiotic traverses the asymmetric LPS-phospholipid bilayer before reaching the periplasm and finally targeting and disrupting the bacterial phospholipid inner membrane. The work described here was prompted by the hypothesis that polymyxins might interact with proteins in the OM, as part of their self-promoted uptake and permeabilizing effects. One way to test this is through photolabeling experiments. We describe the design and synthesis of a photoprobe based upon polymyxin B, containing photoleucine and an N-acyl group with a terminal alkyne suitable for coupling to a biotin tag using click chemistry. The resulting photoprobe retains potent antimicrobial activity, and in initial photolabeling experiments with Escherichia coli ATCC25922 is shown to photolabel several OM proteins. This photoprobe might be a valuable tool in more detailed studies on the mechanism of action of this family of antibiotics

Discovery and Differential Processing of HLA Class II-Restricted Minor Histocompatibility Antigen LB-PIP4K2A-1S and Its Allelic Variant by Asparagine Endopeptidase

Minor histocompatibility antigens are the main targets of donor-derived T-cells after allogeneic stem cell transplantation. Identification of these antigens and understanding their biology are a key requisite for more insight into how graft vs. leukemia effect and graft vs. host disease could be separated. We here identified four new HLA class II-restricted minor histocompatibility antigens using whole genome association scanning. For one of the new antigens, i.e., LB-PIP4K2A-1S, we measured strong T-cell recognition of the donor variant PIP4K2A-1N when pulsed as exogenous peptide, while the endogenously expressed variant in donor EBV-B cells was not recognized. We showed that lack of T-cell recognition was caused by intracellular cleavage by a protease named asparagine endopeptidase (AEP). Furthermore, microarray gene expression analysis showed that PIP4K2A and AEP are both ubiquitously expressed in a wide variety of healthy tissues, but that expression levels of AEP were lower in primary acute myeloid leukemia (AML). In line with that, we confirmed low activity of AEP in AML cells and demonstrated that HLA-DRB1*03:01 positive primary AML expressing LB-PIP4K2A-1S or its donor variant PIP4K2A-1N were both recognized by specific T-cells. In conclusion, LB-PIP4K2A-1S not only represents a novel minor histocompatibility antigen but also provides evidence that donor T-cells after allogeneic stem cell transplantation can target the autologous allelic variant as leukemia-associated antigen. Furthermore, it demonstrates that endopeptidases can play a role in cell type-specific intracellular processing and presentation of HLA class II-restricted antigens, which may be explored in future immunotherapy of AML