Net Loads Research Articles

Flexible resource allocation optimization model considering global K-means load clustering and renewable-energy consumption

Abstract Vigorously developing flexible resources in power systems will be the key to building a new power system and realizing energy transformation. The investment construction cost and operation cost of various flexible resources are different, and the adjustment ability is different in different timescales. Therefore, the optimization of complementary allocation of various resources needs to take into account the economy and adjustment ability of different resources. In this paper, the global K-means load clustering model is proposed and the 365-day net load is reduced to eight typical daily net loads by clustering. Secondly, a two-level optimization model of flexible resource complementary allocation considering wind power and photovoltaic consumption is constructed. The flexible resources involved include the flexible transformation of thermal power, hydropower, pumped storage, energy storage, and demand response. The upper-layer model optimizes the capacity allocation of various flexible resources with the minimum investment and construction cost as the goal and the lower layer optimizes the operating output of various units with the minimum operating cost as the goal. The results of the example analysis show that the flexible capacity of thermal power units has nothing to do with the abandonment rate of renewable energy. As the abandonment rate of renewable energy decreases, the optimal capacity of pumped storage, electrochemical energy storage, and hydropower units increases. When the power-abandonment rate of renewable energy is 5%, the optimal allocation capacity of thermal power flexibility transformation, pumped storage, electrochemical energy storage, hydropower unit, and adjustable load in Province A is 5313, 17 090, 5830, 72 113, and 4250 MW, respectively. Under the condition that the renewable-energy abandonment rate is 0, 5%, and 10% respectively, the configured capacity of pumped storage is 20 000, 17 090, and 14 847 MW, respectively.

Assessment of structural mechanical effects related to torsional deformations of propellers

AbstractLifting propellers are of increasing interest for Advanced Air Mobility. All propellers and rotors are initially twisted beams, showing significant extension–twist coupling and centrifugal twisting. Torsional deformations severely impact aerodynamic performance. This paper presents a novel approach to assess different reasons for torsional deformations. A reduced-order model runs large parameter sweeps with algebraic formulations and numerical solution procedures. Generic beams represent three different propeller types for General Aviation, Commercial Aviation, and Advanced Air Mobility. Simulations include solid and hollow cross-sections made of aluminum, steel, and carbon fiber-reinforced polymer. The investigation shows that centrifugal twisting moments depend on both the elastic and initial twist. The determination of the centrifugal twisting moment solely based on the initial twist suffers from errors exceeding 5% in some cases. The nonlinear parts of the torsional rigidity do not significantly impact the overall torsional rigidity for the investigated propeller types. The extension–twist coupling related to the initial and elastic twist in combination with tension forces significantly impacts the net cross-sectional torsional loads. While the increase in torsional stiffness due to initial twist contributes to the overall stiffness for General and Commercial Aviation propellers, its contribution to the lift propeller’s stiffness is limited. The paper closes with the presentation of approximations for each effect identified as significant. Numerical evaluations are necessary to determine each effect for inhomogeneous cross-sections made of anisotropic material.

Practical Model for the Calculation of Lateral Electromagnetic Loads in Tokamaks at Asymmetric Vertical Displacement Events (AVDEs)

This paper describes a new practical numerical model for the calculation of lateral electromagnetic (EM) loads in tokamaks during asymmetric vertical displacement events (AVDEs). The model combines key features of two recently reported trial models while avoiding their drawbacks. Their common basic feature is the superposition of two patterns of halo current: one perfectly symmetric and another perfectly anti-symmetric. This model combines the following features that have not been combined before (a) a helically distorted halo layer wrapping around core plasma, and (b) halo-to-wall interception belts slipping along plasma-facing walls. This combination almost doubles the lateral net forces. An AVDE creates significant lateral net moments. Being relatively modest at VDEs, the lateral moments become a dominant component of EM loads at AVDEs. The model carefully tracks the balance of net EM loads (zero total for the tokamak), as a necessary condition for the consequent numerical simulation of the tokamak’s dynamic response. This balance is needed as well for the development of tokamak monitoring algorithms and simulators. In order to decouple from the current uncertainties in the interpretation and simulation of AVDE physics, the model does not simulate AVDE evolution but uses it as an input assumption based on the existing interpretation and simulation of AVDE physics. This means the model is to be used in a manner of parametric study, at widely varied input assumptions on AVDE evolution and severity. Parametric results will fill a library of ready-for-use waveforms of asymmetric EM loads (distributed and total) at tokamak structures and coils, so that the physics community may point to specific variants for subsequent engineering analysis. This article presents the first practical contribution to this AVDE library.

Probabilistic net load forecasting based on transformer network and Gaussian process-enabled residual modeling learning method

Accurate net load forecasting plays an increasingly pivotal role in ensuring the reliable operation and scheduling of power systems. This paper introduces a novel probabilistic net load forecasting approach that combines the strengths of a Transformer network with Gaussian process regression. The state-of-the-art Transformer network is first employed to capture the net load pattern utilizing relatively abundant historical training samples. The remarkable temporal feature extraction ability allows it to discover the complex structure in net loads. Subsequently, the Gaussian Process is applied to capture the behavior of the Transformer network by modeling its forecasting residual utilizing a specific composite kernel. The modeling of the forecasting residual not only provides valuable uncertainty quantification of net load but also improves the forecasting performance based on the Transformer network. Comparative tests utilizing real-world data verify the superiority of the proposed method over other state-of-the-art net load forecasting algorithms.

Multi-time-scale capacity credit assessment of renewable and energy storage considering complex operational time series

Large-scale renewable integration presents an effective way to decarbonize power grids, but carries increased risk of supply shortfalls owing to its volatility and uncertainty. Storage is a promising option to improve the generation adequacy of renewable. Thus, capacity credit assessment of renewable and storage is crucial in ensuring adequate generation capacity to meet loads. However, efficiently and accurately assessing capacity credit of these resources is challenging due to temporal dependencies in the operational time series (net loads and conventional generation units) and the need for extensive operation simulations. This paper develops a comprehensive multi-time-scale assessment framework integrating analytical and simulation methods to calculate the capacity credit of renewable and storage, thus capturing temporal features of these time series. Then, an interval-based strategy is proposed to simulate system operations, incorporating demand response in key scenarios. Furthermore, partitioning around medoids clustering and parallel computing techniques are employed to greatly accelerate the numerous operations for capacity credit assessment. The proposed method is validated using the RTS-79 system and a provincial real-world power grid in China. The results indicate that the developed framework can achieve efficient and refined capacity credit assessment and thus evaluate the impact of storage on the capacity credit.

Wastewater treatment plant performance assessment using time-function-based effluent quality index and multiple regression models: the case of Bahir Dar textile factory

Extensive water and chemicals are used in the textile industry processes. Therefore, treatment of textile wastewater is vital to protect the environment, maintain the public health, and recover resources. However, due to poor operation and plant performance the partially treated textile wastewater was directly discharged to a nearby river. Thus, the aim of this study was to characterize the wastewater physicochemical properties and evaluate the performance of the textile factory-activated sludge process wastewater treatment plant (WWTP) in Bahir Dar, Ethiopia. In inlet and outlet of the WWTP, samples were collected for 6 months and analyzed on-site and in a laboratory for parameters including, dissolved oxygen, pH, temperature, total Kjeldhal nitrogen (TKN), chemical oxygen demand (COD), biochemical oxygen demand (BOD5), total suspended solids (TSS), total nitrogen (TN), total phosphorous (TP), nitrite, nitrate, and metallic compounds. The TSS, BOD5, COD, TP, nitrite, ammonia, and total chromium result were above the discharge limit with 73.2 mg/L, 48.45 mg/L, 144.08 mg/L, 7.9 mg/L, 1.36 mg/L, 1.96 mg/L, and 0.16 mg/L, respectively. Multiple regression models were developed for each overall, net moving average, and instantaneous effluent quality index (EQI). The predictor parameters BOD5, TN, COD, TSS, and TP (R2 = 0.995 to 1.000) estimated the net pollution loads of all predictors as 492.55 kg/day and 655.44 kg/day. Except TN, TKN, and NO3, the remaining six performance parameters were violating the permissible limit daily. Furthermore, the overall plant efficiency was predicted as 38 % and 42 % for the moving average and instantaneous EQI, respectively. Our study concluded that the integrated regression models and EQI can easily estimate the plant efficiency and daily possible pollution load.

Cascade hydropower stations optimal dispatch considering flexible margin in renewable energy power system

Power system flexibility refers to the ability to respond to changing net loads within a predefined timeframe. The main causes of flexible demand are resource and load uncertainties. The joint interaction of resource and load uncertainty makes flexible demand more complex. Accurately assessing the power system flexibility and promoting flexible supply are important for maintaining grid safety and stability. In this study, a joint probability distribution for intermittent renewable energy sources (IRES) output and load forecast deviation is proposed. Subsequently, an optimal dispatch model that considers flexible demand and hydropower flexible supply is built to improve the operation scheme of flexible resources. A hydropower dispatch model that does not consider the probability of IRES output and load forecast deviation is used as the contrast model. A comparison of the results shows that the optimal dispatch model is more beneficial for maintaining grid safety and stability. The results show that the maximum upward adjustment flexible (UAF) margin of the optimal dispatch model of the Yalong River Downstream is 376 MW, whereas the maximum downward adjustment flexible (DAF) margin is 197 MW. This implies that a greater UAF supply is required in the case study to satisfy the power system flexible demand.

Propagation of conformity statements in compliance with the GUM and ISO 17025

According to ISO/IEC 17025:2017 statements of conformity must identify the decision rule applied, they must be risk-based and account for uncertainty. In legal metrology and often among testing and calibration laboratories, there is the need to reuse measurement-based conformity statements to disseminate acceptability of measurement results. In particular, decision rules are required that allow the statement of conformity for a linear combination of quantities for which, in turn, conformity statements are available. These decision rules should be simple and use information that is typically available, and they should comply with ISO/IEC 17025:2017, again by accounting for the level of risk and for uncertainty following the suite of documents of the GUM (the Guide to the Expression of Uncertainty in Measurement).Existing guidance requires the input and evaluation of standard uncertainties, or even of distributions, to derive statements of conformity, and as such may be inapplicable, or the required effort may deter practitioners. After reviewing the existing guidance, this research will identify typical settings which lead to particularly simple decision rules for stating conformity for linear combinations of quantities. These new decision rules are based on the specification limits and on information implicitly available in the decision rules of each input quantity. The rules will be proven, they are generalizable, intended to comply with ISO/IEC 17025:2017 and the GUM documents, and suitable to easily state the risk of not conforming to the weighted sum of the input specifications.For practitioners, a quick reference on feasible conformity statements for linear combinations of quantities is provided. The applicability of and need for the new decision rules are illustrated by two examples involving the legally regulated weighing of long vehicles and of net loads.

Quantifying space-time load shifting flexibility in electricity markets

The power grid is undergoing significant restructuring driven by the incorporation of renewable power and new flexible technologies that enable space–time load shifting, which is essential to mitigating space–time fluctuations associated with wind/solar power and other disruptions (e.g., extreme weather). The impact of load shifting is typically quantified via sensitivity analysis, which does not quantify operational flexibility (e.g., range or probability of feasible operation). In this work, we present a computational framework to quantify operational flexibility by assessing how much uncertainty in net loads can be tolerated by a power grid under varying levels of load shifting capacity. Our framework combines optimization formulations that quantify operational flexibility with power grid models that capture load shifting in the form of virtual links (pathways that transfer loads across space–time). Our case studies reveal that adding a single virtual link can lead to dramatic improvements in system-wide flexibility; this is because shifting helps relieve space–time congestion from transmission and generator ramping constraints.

Beyond heat exposure — new methods to quantify and link personal heat exposure, stress, and strain in diverse populations and climates: The journal Temperature toolbox

ABSTRACT Fine-scale personal heat exposure (PHE) information can help prevent or minimize weather-related deaths, illnesses, and reduced work productivity. Common methods to estimate heat risk do not simultaneously account for the intensity, frequency, and duration of thermal exposures, nor do they include inter-individual factors that modify physiological response. This study demonstrates new whole-body net thermal load estimations to link PHE to heat stress and strain over time. We apply a human-environment heat exchange model to examine how time-varying net thermal loads differ across climate contexts, personal attributes, and spatiotemporal scales. First, we investigate summertime climatic PHE impacts for three US cities: Phoenix, Miami, and New York. Second, we model body morphology and acclimatization for three profiles (middle-aged male/female; female >65 years). Finally, we quantify model sensitivity using representative data at synoptic and micro-scales. For all cases, we compare required and potential evaporative heat losses that can lead to dangerous thermal exposures based on (un)compensable heat stress. Results reveal misclassifications in heat stress or strain due to incomplete environmental data and assumed equivalent physiology and activities between people. Heat strain is most poorly represented by PHE alone for the elderly, non-acclimatized, those engaged in strenuous activities, and when negating solar radiation. Moreover, humid versus dry heat across climates elicits distinct thermal responses from the body. We outline criteria for inclusive PHE evaluations connecting heat exposure, stress, and strain while using physiological-based methods to avoid misclassifications. This work underlines the value of moving from “one-size-fits-all” thermal indices to “fit-for-purpose” approaches using personalized information.

Peer-to-Peer Transactive Energy Trading of a Reconfigurable Multi-Energy Network

This paper proposes a bi-level peer-to-peer (P2P) multi-energy trading framework for a coupled distribution network (DN) and district heating network (DHN). At the lower level, each nodal agent represents its intra-nodal prosumers to optimize the local energy scheduling and P2P trading strategies based on the modified Nash bargaining theory, and a distributed algorithm is then adopted to enable individual agents to make their strategies autonomously only with the sharing of trading information. Once the lower-level P2P bargaining is settled, each agent is required to submit its nodal net loads and trading adjustment tolerances to the network operators. At the upper level, the network operators minimize the line power losses while satisfying network operation constraints by reconfiguring the DN and DHN as well as enforcing necessary trading adjustments from the lower-level agents when the network violations incurred by the P2P trading cannot be fully solved by network reconfiguration. Mathematically, the DN operation is modelled based on the linearized DistFlow with a set of new radiality constraints to sufficiently ensure the radial structure of the DN. The DHN operation is formulated as a quasi-linear thermal flow model independent of mass flow rate and water temperature, by which the computation complexity and limitations associated with traditional DHN formulations are addressed. Finally, a multi-energy network consisting of an IEEE 33-bus DN and a 23-node DHN is used to demonstrate the effectiveness of the proposed P2P trading framework and the efficiency of the solution algorithms.

Net joint moments versus internal joint loading: Can we trust correlations between joint moments and contact forces from generic-scaled models?

Net joint moments versus internal joint loading: Can we trust correlations between joint moments and contact forces from generic-scaled models?

Dietary Contributions to Metabolic Acidosis.

Eating a net acid-producing diet can produce an "acid stress" of severity proportional to the diet net acid load, as indexed by the steady-state renal net acid excretion rate. Depending on how much acid or base is ingested or produced from endogenous metabolic processes and how well our homeostatic mechanisms can buffer or eliminate the additional acids or bases, we can alter our systemic acid-base balance. With increasing age, the kidney's ability to excrete daily net acid loads declines (a condition similar to that of mild CKD), invoking increased utilization of potential base stores (eg, bone, skeletal muscle) on a daily basis to mitigate the acid accumulation, thereby contributing to development of osteoporosis, loss of muscle mass, and age-related renal insufficiency. Patients suffering from more advanced CKD often present with more severe acid stress or metabolic acidosis, as the kidney can no longer excrete the entire acid load. Alkaline diets based on fruits and vegetables may have a positive effect on long-term preservation of renal function while maintaining nutritional status. This chapter discusses the biochemistry of dietary precursors that affect acid or base production.

Can a digital twin of the residuum improve bionic solutions for individuals suffering from limb loss?

Introduction: Understanding the influence of whole-body activity (e.g., physical training) on the biophysics at organ-, tissue-, and sub-tissue-levels is important for designing optimal physical training/rehabilitation and effective control of assistive devices. The Griffith Centre of Biomedical and Rehabilitation Engineering (GCORE) has developed mature rehabilitation and assistive device technologies underpinned by the Personalized Digital Human (PDH). Method framework: The PDH is a physics-based digital twin of the human (and devices), which includes representation of an individual’s bones, articulations, muscles, and other soft tissues. Coupled with peripheral muscle excitation (e.g., electromyograms), PDH encodes muscle activations specific to the individual (e.g., sensitive to training and disease) and task (e.g. sensitive to control task)1. Examples: To analyze human performance, PDH quantifies mechanical parameters such as net loading to the body, organ (e.g., whole bone; Fig. 2), joint, tissue (e.g., ligament; Fig. 1)2, and sub-tissue (e.g., local strain in tendon; Fig. 1)1. Within a control system3, PDH predicts muscle activations that produce target mechanics (e.g., torque on rehabilitation ergometer), compliment an assistive device (e.g., torque above motor-driven assistance), sensory afferents that augment/simulate sensory experience (e.g., haptics), and safety margins (e.g., critical stresses) (Fig. 2).Fig. 2The PDH used within a control system to interpret sensor data, model the internal states of the human, provide augmented sensory afferents, and perform safety checks on the loading of musculoskeletal tissues3.View Large Image Figure ViewerDownload Hi-res image Download (PPT) Discussion/future directions: Currently, we are developing direct fusion of PDH with prosthesis design to optimize amputee residuum health4. Further, PDH could readily be extended to become the personalized digital soldier, with extensive scope for use in monitoring training loads, improving rehabilitation efficacy, and designing equipment to better interface with humans. Acknowledgements: The PDH is the result of numerous nationally-competitive and industry grants for over 2 decades. References 1Pizzolato C, Shim VB, Lloyd DG, et al. Targeted achilles tendon training and rehabilitation using personalized and real-time multi-scale models of the neuromusculoskeletal system. Front Bioeng Biotechnol 2020; 8:878. https://doi.org/10.3389/fbioe.2020.00878 2Nasseri A, Khataee H, Bryant AL, et al. Modelling the loading mechanics of anterior cruciate ligament. Comp Meth Prog Biomed 2020; 184:105098. https://doi.org/10.1016/j.cmpb.2019.105098 3Pizzolato C, Gunduz MA, Palipana D, et al. Non-invasive approaches to functional recovery after spinal cord injury: therapeutic targets and multimodal device interventions. Exp Neurol 2021; 330:113612. https://doi.org/10.1016/j.expneurol.2021.113612 4Frossard LA, Lloyd DG. The future of bionic limbs. Res Feat 2021; 134:74-77. https://doi.org/10.26904/RF-134-7477

A critical analysis of power conditions in sucker-rod pumping systems

The most decisive constituent of operating expenditures in sucker-rod pumping operations is related to the system's electric power use as most installations are driven by electric motors. Consequently, the reduction of operating costs can be translated to the reduction of energy losses both downhole and on the surface. Therefore, the energy efficiency of the surface and downhole components of the pumping system as well as the overall system efficiency play a big role in maximizing profits. The paper presents a critical analysis of the energy efficiency of the individual components of the sucker-rod pumping system and introduces novel models to find the system's total efficiency. The typical energy losses in the sucker-rod pumping system's main components (the downhole pump, the sucker-rod string, the surface pumping unit, the gearbox, the V-belt drive, and the prime mover) are discussed in detail. It is demonstrated that the level of the pumping unit's counterbalancing as well as any inertial effects do not impact on the net gearbox torques and on the required average mechanical output power of the motor. The energy consumption of the electric motor, however, is affected by the pumping unit's counterbalancing and the inertial effects because of the changes in motor efficiency due its variable loading within the pumping cycle. The system's useful output power is performed by the downhole pump when it lifts the produced liquid to the surface. The paper demonstrates that the so-called hydraulic power, calculated from the increase of the produced liquid's potential energy, is a reliable indicator of the system's useful power. Using the hydraulic power together with the electric power taken from the power supply permits an easy way to assess the over-all energy efficiency of the pumping system. The paper proposes several other variants of system efficiency calculations; they are based on the fact that all components of the pumping system are connected in series to each other. Sizing of electric motors for sucker-rod pumping installations is normally done with the use of a cyclic load factor (CLF) that accounts for the fluctuations in motor load during the pumping cycle. Originally, CLFs were found from the variation of motor current, but mechanical CLFs based on net gearbox torques are much more practical to use. This practice is fully justified in the paper by proving that the correlation between the motor's real current and its net torque loading is nearly linear. It is further shown that the safety of sucker-rod pumping installation design is improved if the electric motor is sized with the use of a mechanical CLF because that case gives the highest required nameplate motor power. • A critical analysis of the energy efficiency of the individual components of the sucker-rod pumping system is presented. • Novel models to calculate the over-all system efficiency of sucker-rod pumping systems are introduced and demonstrated. • The effects of counterbalancing on net gearbox torques and on the motor's mechanical power are evaluated. • Hydraulic power, representing the increase of the produced liquid's potential energy, is a reliable indicator of the system's useful power. • The use of mechanical instead of electrical CLFs to size electric motors is fully justified.

Time-Interval-Varying Optimal Power Dispatch Strategy Based on Net Load Time-Series Characteristics

In China, with the increasing permeability of wind power, the power supply capacity is enough overall, but has shortage in partial-time. During peak hours, the capability of wind power consumption is poor and the power balance becomes more difficult. In order to maximize the utilization of wind power, the net loads are chosen as the response objectives, which contain significant uncertainties and have no probabilistic distribution characteristics. Under the traditional day-ahead power dispatch mode with fixed length time intervals and in the regions with insufficient hydroelectricity, the thermal generators take charge of the peak-load shaving. The frequent adjustments of thermal power output affect the system operation safety, economic benefits, and environmental benefits. Thus, a time-interval-varying optimal power dispatch strategy based on net load time-series characteristics is proposed in this paper. The net loads respond differently to intervals. The length of each time interval is determined based on the net load time-series characteristics analyzed by random matrix theory. The dispatch mode in each time interval is determined according to the characteristic quantification index calculated by the empirical modal decomposition and sample entropy. The proposed strategy and method can extend the continuous and stable operation time of the thermal generators, reduce the coal consumption caused by the ramping operation, and improve the safety, stability, and economy of the system. Furthermore, the proposed dispatch mode is environmentally friendly with reduced environmental cost and increased carbon credits. An actual provincial power grid in northeast China is taken as the example to verify the rationality and effectiveness of the proposed method and strategy.

Day-ahead stochastic optimal dispatch of LCC-HVDC interconnected power system considering flexibility improvement measures of sending system

This paper proposes a day-ahead (DA) two-stage stochastic optimal dispatch strategy of line commutate converter-based HVDC (LCC-HVDC) interconnected power system, considering two flexibility regulation measures of sending system. First, the energy storage systems (ESSs) are used to suppress the real-time (RT) power fluctuations of sending system net loads decomposed by the Hodrick-Prescott filter under the two-stage stochastic programming structure, which can feedback to DA stage. Second, the flexible adjustment characteristics of LCC-HVDC power are modeled, and the actions of reactive power control equipment (RPCE) are limited for the operation safety. The static operation model of converter stations is linearized, and the linearization errors are analyzed by the probability statistics of multiple scenarios. The effectiveness of the proposed strategy is verified on the wind power LCC-HVDC transmission system.

Reserve Cost Allocation Mechanism in Renewable Portfolio Standard-Constrained Spot Market

Governments have been taking policy instruments to enhance green power (GP) development, while the renewable portfolio standard (RPS) has become one of the most prevalent choices. Although RPS can guarantee GP producers’ income and expansion from a medium to long term perspective, curtailments are still inevitable, as RPS is integrated to power system by financial contracts and cannot affect market clearing. To solve this problem, the paper modifies the clearing procedure with a physical contract-based RPS restriction. However, along with that, reserve cost allocation mechanisms (RCAMs) ignoring RPS obligations are no longer cooperative, since GP penetration and market reserve demands are partially determined by RPS obligations now. Thus, an innovative RCAM, dominated by both net loads and RPS obligations through reserve costs contribution rate (RCCR) is proposed. A tri-level model is formulated to evaluate modifications and the proposed RCAM. On the first level, RCCR is achieved by calculating the incremental ratio of system reserve costs from level-1 without RPS constraint to level-3 with RPS constraint. The lower two levels form a classic bi-level model, where energy users interact with the independent system operator by strategical investment in distributed energy resources. Case studies based on the IEEE 6- and 118-bus system demonstrate the effectiveness of the proposed RCAM.

A Semi-Analytical Model for Studying Hydroelastic Behaviour of a Cylindrical Net Cage under Wave Action

In the present study, a semi-analytical model based on the small-amplitude wave theory is developed to describe the wave fields around a single gravity-type cylindrical open fish net cage. The cage may be submerged to different depths below the free-water surface. The fish cage net is modelled as a flexible porous membrane, and the deflection of the net chamber is expressed by the transverse vibration equation of strings. The velocity potential is expanded in the form of the Fourier–Bessel series and the unknown coefficients in these series are determined from matching the boundary conditions and the least squares method. The number of terms for the series solution to be used is determined from convergence studies. The model results exhibit significant hydroelastic characteristics of the net cages, including the distribution properties of wave surface, pressure drop at the net interface, structural deflection, and wave loading along the cage height. In addition, the relationships between wave forces on the net cage with hydrodynamic and structural parameters are also revealed. The findings presented herein should be useful to engineers who are designing fish cage systems.

From local measures to regional impacts: Modelling changes in nutrient loads to the Baltic Sea

Study RegionOur study region is the Baltic Sea Drainage Basin (BSDB), which covers an area of 1.8 Mio km2 distributed over 14 countries in northern Europe. Study FocusWe use a large-scale hydrological and nutrient transport model (E-HYPE) to model basin-wide impacts of measure scenarios on the Baltic Sea, where eutrophication is a critical issue for the marine ecosystem. We constructed measure scenarios based on stakeholder acceptance, established in workshops in different regions around the Baltic. These measures include local stream reach to catchment scale measures aiming to reduce nutrient transport into the stream network (buffer strips, stormwater ponds) and measures aiming to reduce regional nutrient source releases (fertiliser leaching rates, rural household emissions). New Hydrological Insights for the RegionNutrient load reductions are often needed to reduce eutrophication and improve overall surface water quality in fresh-water and enclosed bays and seas, where dilution is limited and load emissions have long residence times. To reduce riverine nutrient loads, remediation measures are necessary, e.g. establishment of buffer strips or improved wastewater treatment. Such measures are, however, typically not designed to target nutrient load reductions at sea outlets, but rather focus on local improvements. Here, we show that measures, notwithstanding other meliorating ecosystem benefits, must include reductions in load emissions across large basin areas to impact integrated net loads into coastal sea basins, because reduction measures that only target nutrient delivery to the stream network typically cannot be implemented in a significant enough proportion of the total drainage area of large coastal river basins. Our impact scenarios show BSDB-wide nutrient reductions of up to 9 % for nitrogen and phosphorus compared to a reference scenario, if load emissions are reduced in the scenario assumptions.